Occam's Razor by Avinash Kaushik | Digital Marketing and Analytics Blog
Occam’s Razor by Avinash Kaushik contains a whole host of blog posts on every aspect of Google Analytics. You’ll find in-depth how-to guides and information on a wide range of topics, including qualitative analysis, competitive intelligence analysis, analytics tips, web metrics and Digital Marketing.
Some moments in time are perfect to reflect on where you are, what your priorities are, and then consider what you should start-stop-continue. In those moments, you are not thinking of delivering incremental change… You are driven by a desire to deliver a step change (a large or sudden discontinuous change, especially one that makes things better – I’m borrowing the concept from mathematics and technology, from “step function”).
In those moments – common around new years or new annual planning cycles – the difference between delivering an incremental change vs. a step change is the quality of ideas you are considering. In this post, my hope is to both enrich your consideration set and encourage the breadth of your goals.
My professional areas of interest cover Customer Service, User Experience and Finance, though here on Occam’s Razor my focus is on influencing incredible Marketing through the use of innovative Analytics. To help kick-start your 2019 step change, I’ve written two “Top 10” lists, one for Marketing and one for Analytics – consisting of things I recommend you obsess about.
Each chosen obsession is very much in the spirit of my beloved principle of the aggregation of marginal gains. My recommendation is that you deeply reflect on the impact of the 10 x 2 obsessions in your unique circumstance, and then distill the ten you’ll focus on in the next twelve months. Regardless of the then you choose, I’m confident you’ll end up working on challenging things that will push your professional growth forward and bring new joy from the work you do for your employer.
First… The Analytics top ten things to focus on to elevate your game this year…
The Step Change Analytics Obsessions List.
A1. Improve the Bounce Rate of your top 10 landing pages by 50%.
(Improving Bounce Rate results in reducing it. :))
You'll be surprised by the steep drop in Cost per Acquisition.
Google Optimize will be one of your BFFs in this quest. You’ll know you’ve moved beyond basic improvements when you start setting Custom Objectives – they require deeper thinking, which is a good sign.
A2. Eliminate 40% of the numbers from your dashboard.
Take the newly-created white space to explain what to do based on performance of 60% of the numbers that remain.
What your boss wants most this year, more than love, is to be told what the data wants her to do. Don't leave her guessing.
A3. Take your first steps towards unlocking smart algorithms.
Learn what Session Quality is in Google Analytics, then learn how to use it in your campaigns to improve conversions. In the Audiences section, go to the Behavior folder.
Learn what Smart Bidding is in Google Ads, then learn how to use it in your campaigns to improve outcomes.
Machine Learning algorithms will make our data smarter in unparalleled ways; Session Quality and Smart Bidding offer early clues about the scale and type of intellect. In both instances, it is immensely valuable to really understand how a smart algorithm uses billions of data signals to calculate likelihood of a conversion.
Across all your analytics data, algorithms will take you places humans simply can't. This should be the year you invest in an expansion in skills and practice to take advantage of these possibilities.
A4. Take a class in data visualization. It will save your life.
Anyone can make a complicated visual, it takes someone very special (you!) to draw out the essence of the story data is trying to tell.
Through all these courses remember the most important thing about data visualization: It’s not the ink, it’s the think. Obsess about improving the think, just as much as I’m encouraging you to improve the ink.
A5. Obsess about what happens after campaigns end.
In our analytics practice we tend to celebrate victory too early (at the end of the campaign) or with insufficient breadth (the full scope of impact).
Did you get customers with high lifetime value? How long did the brand lift – say Awareness – last? What was the average order value of the second purchase by people you acquire via Search, compared to those via Retail?
Is there a difference in behavior between people who signed up for email over the last year vs those who did not? What the cost of getting a retail customer to make subsequent purchases over mobile apps lower?
A6. Understand your personal impact, obsess about improving it.
Grab the revenue number for the company. Now work out how much of it is influenced by you directly. Make a note of what it is (likely to be a couple percentage max).
Double that number this year.
What are the first five things on your list?
None of them will be easy, but converting insights into action via influence rarely is. But, you don't have to stretch too far to see how amazing it would be for you (and data too!) if you double your impact.
A7. Run one super-large controlled experiment.
To prove what your Executives believe purely from their gut. Or, to disprove it.
Does Facebook advertising really work better than TV? Can you create premiumness for your brand using digital? Is a 15% coupon now better than 20% off the next purchase? Does swapping out male model posters for cute animals triple sales?
Does sponsoring a fashion show lead to an increase in brand equity? Does free pickup in store result in higher attach rates?
A8. Identify four relevant micro-outcomes to focus on in 2019
(In addition to the macro-outcome of revenue).
Businesses win when you optimize for a portfolio, because at any given time only a tiny fraction of people want to buy. Solving for micro and macro-outcomes is directly connected to the holy grail of solving for short-term AND long-term success.
Employees also become smarter when they have to optimize for more than one thing. :)
A9. Throw away your custom attribution model. Embrace data-driven attribution.
For some things, humans are already less smart than machines. Trying to guess what might be happening across millions of touchpoints on and off site, on and offline, is one of those things.
Skip the first five steps of attribution’s ladder of awesomeness, jump to DDA. From the tens of hours saved per week, figure out how to feed offline data into your data driven attribution model.
With an obsession with data-driven attribution, you are also solving for a portfolio rather than a silo. Super cool, super profitable.
A10. Hire an experienced statistician to be a part of your analytics team.
There is too much goodness in modeling that you are not taking advantage of. From segmentation models to identifying incrementality to predictive modeling to survival analysis to clustering to time series to… I could keep going on and on.
2019's the year you get serious about serious analytics.
Outsource or eliminate half of your data capture and data reporting responsibilities, and allocate it to data analysis and driving action.
You'll be surprised at the increase in your salary and bonus (oh, and the company will benefit too!).
In context of Analytics are you aiming for something special in 2019 that I've not covered above? Will you please share that with me by adding a comment? Thank you.
Switching gears, here are ten things to obsess about to collectively deliver a step change via your Marketing game this year…
The Step Change Marketing Obsessions List.
M1. Improve the Bounce Rate of your top 10 landing pages by 50%.
(Improving Bounce Rate results in reducing it. :))
Same as the #1 on the Analytics list. :) Far too many Marketers ignore this simple strategy to make lots more money. You work so very hard to earn attention, why then let your ads write checks your website can’t cash?
An additional delightful benefit: I find that getting Marketers to obsess about landing pages forces them to audit the user experience, something worth its weight in gold.
M2. Put up or shut up time for your social media strategy.
99.999% of corporate social media participation yields nothing.
Your CMO wants people to love your brand and organically amplify its goodness. It genuinely is a good thought. Except, a cursory glance at your social contributions show nothing of that sort over the last three years.
So, why are you spending all that money?
I recommend using that money to buying your team iPhones every Friday, I assure you that'll have a positive ROI.
Or. Focus on social media primarily as a paid media strategy. Bring the same discipline to the application of accountability to social media ads that you bring to your Display or Video ads anywhere on the web.
Aim to shift 25% of your marketing budgets in 2019 to opportunities that are powered by ML algorithms and rejoice at the boost in profits that results.
M4. TV works, solve for each factor that drives success.
Most TV campaigns are sold and bought based on reach (GRPs FTW!).
In my experience you should optimize for reach AND one overarching story AND creative consistency AND ensure each successfully tested creative has enough frequency to wear-in.
And, if you can't solve for three ANDs… Shift money to max out the Performance Digital opportunity, then with the left over money buy every person in your team – and at your agency – a new car. Your TV budget is big enough , and trust me when I say that giving out a new car will have very high motivational and bottom-line ROI.
M5. Seek to understand the customer journey.
What drives the first purchase? What drives the second? What drives the support calls in between? What does using the product really, really feel like? What drives advocacy?
All advertising that fails does so because the Marketer behind it understands only one sliver of the experience, then solves for that sliver with heart-breaking short-term focus.
When the Marketer understands the answers to the above questions, it influences the creative, it influences targeting, it influences retail store displays, it influences frequency, it influences product design, it influences…. it changes everything. Including profits.
Journeys are better than tinder dates.
6. Solve for intent. It is more possible and more critical with every passing day.
See-Think-Do-Care is a great intent-centric business framework, if I may say so myself, for challenging your current marketing strategy.
What intent is your current marketing content (tv, digital, ads, emails) targeting? What happens once your ads meet that intent? What meaningful content are you publishing, on and offline, to engage audiences before and after the BUY NOW (!) moment? Is your measurement aligned with the intent your marketing is targeting, or are you judging a fish by its ability to climb a tree? How do you know?
Shifting to See-Think-Do-Care is the single biggest force multiplier when it comes to your marketing. Help shift your organizational thinking to the current century in 2019.
M7. Your marketing budget allocation can be improved anywhere from 50% to 50,000%.
Allocating budgets is the hardest decision a Senior Marketer will make. Most will use strategies like Digital had 27% of budget last year, this year we should do between 28 and 30%. History, gut-feel, inter-company-politics, etc. are primary reasons why this silly mindset is pervasive across companies.
A better way? Profitable opportunity size.
I don't think you can argue with the first part: Invest where you make more profit. The second part takes a bit more work. It comes from plotting diminishing margin curves with confidence intervals. In English: How high can the investment goes before every $1 you invest returns less?
You are a Marketer, so it's unlikely that you'll plot these curves. Make it a priority for your Analytics team to do so; without them massive chunks of your budget is being flushed.
(Also, see obsession #10 on the Analytics list.)
M8. A grandmother's Marketing strategy for grandmothers only.
A bit provocative, but I want to challenge how most Marketers just make little tweaks to their strategy. The bigger the company, the more that this pernicious problem exists. Don't let that be you, and allow me to share two views that'll challenge your reality.
Here's the average time spent per day by US adults with media devices…
My humble description of a "grandmother's marketing strategy" is the bar on the right (65+).
It is eminently sensible for our marketing for our fellow 65+ aged Earthlings to be reflective of the implications of that right-most bar.
The problem arises when our entire marketing strategy is an extension of that right-most bar. For our entire marketing strategy to be structured on that 6:55 you see above, when our products and services are not 65+ centric is… A bit silly. Perhaps even reflective of failing our fiduciary duty.
Note the difference in total media consumption (time, place, device, more). Note the products and services your company currently offers. Reflect on this: How misaligned is your current marketing strategy?
The difference between leaning-back and letting content wash over us vs. leaning-in and pulling content you desire is huge. It dramatically changes what your marketing should be solving for (beyond the obvious investment alignment by platforms issue).
One more reality-check for your 2019 Marketing strategy: Here's a helpful deep drive into the shifts in consumption of TV across US adults – in just six years (!!)…
This possibly explains why Toyota's entire Marketing strategy seems to be TV-centric (with the incredible frequency of 48 per day per person here in the bay area!). It seems Toyota is only trying to sell cars to 65+ (whose TV watching has actually increased).
In 2019, resolve to align your marketing strategy with your 1. products 2. goals 3. audience, and 4. amount of expressed intent on the platform.
Credits: Originally created by Sara Fischer of Axios, the first graph is via my buddy Thomas Baekdal's newsletter. 100% of you need to sign up for it. The second chart is from the lovely team at The Economist.
M9. Suck less more.
Every campaign you are currently executing can be made to suck less – especially if you think end-to-end experience.
Ex: Expedia's emails are so long they always trigger "[Message clipped] View entire message." Suck less and maybe use my past behavior to send shorter emails so I know you care about me?
Ex: Nordstrom sends me one email a day with exclusive deals – how many clothes do they think I need? Suck less and maybe send me one a month? Or, base it on shopping patterns in store to deliver delight and not just a deal?
Ex: Macy's email I just received (titled "Resolution #1: get an extra 20% off before it ends") has promotions for Women, Men, Shoes, Bed & Bath, Kids, Juniors, Jewelry, Plus Sizes, Handbags, Home, Kitchen, Beauty. All above the fold. Below the fold: Large pictures with promotions for White Bedding, Biggest Underwear, Biggest Mattress (yes again), Best Face Forward, 25% off Adidas, Macy's presents the Edit, Fresh Pastels (the image does not make clear what this is), Free, Fast Pickup. PHEW! This can be unsucked at so many levels, with just a little bit of love and focus.
Ex: Even really good programs can use sucking less. Companies like Google and Microsoft have so many divisions. Each team/department optimizes for itself, emails are pretty good, hence each thinks they are doing really well. But, if you flip the lens to me – the recipient – I get a lot of email from each company. I wish someone at G/M would track Emails Sent/Humans Sent To, and reflect on the sad reality. It would create a culture of Marketing with me at the center instead of a company department – you can imagine the benefits.
I'm using email marketing as an example of activating the power of suck less because I love email marketing. It is an effective and profitable strategy. It has loads of behavioral data available. It needs a comparatively small team to execute well. Yet see how much opportunity there is to suck less at even the largest companies.
Substantially bigger opportunities to suck less exist in all other Marketing you are doing. TV. Print. Radio. Display (omg, sooooo much opportunity!). Video. Website. Mobile app. Everything else.
All you need to do is take a quick peek under the covers.
Your 10x goal for 2019: For every $1 invested in chasing a shiny object (VR ads! Influencer marketing!!!), invest $10 in sucking less in existing large clusters of your Marketing.
Profits that follow will also be that lopsided.
One last bit, culture eats strategy for breakfast. Create a quarterly Most Unsucked Team award, and celebrate this dimension of success. Incentives matter.
M10. Bring your great taste and expectations to work.
You can easily recognize when something is mediocre – even when others put lipstick on the pig and run it around the organization as the greatest success of the month.
You know what exceptional looks and feels like – you are not just a Marketer, you are an intelligent customer.
Yet, my experience is that most Marketers stay in their lane. Often, company cultures encourage that non-beneficial behavior.
In 2019, speak up.
You have great taste. Don't leave it at home when you leave for work.
When you see low quality work being pushed out by your Marketing organization… Create alternative mocks. Push for your version of the brand's tag line (not the generic MBA buzzword puke-fest). Ask for a better balance between Earned-Owned-Paid marketing. Politely challenge your Leader's assertion that creative x is better because he feels like it will be. Recommend experimenting with reckless ideas, instead of directly putting 30% of the budget on them. If you see lipsticked pigs being paraded around as exceptional examples, humbly, privately, flag the corrosive implication on culture to the most senior leader who'll listen to you.
You deserve to be heard.
When you speak, it'll give others around you the courage to speak up as well. Smart people tend to run in packs.
That’s it. :)
A slight repetition: Reflect deeply on the impact of the 10 x 2 obsessions in your unique business environment. Then, distill down to a total of ten you’ll focus on in the next twelve months. Finally, put a start and expected end date for each item. If you get through the list, you would have contributed a step change to your company’s bottom-line, and discovered unexpected personal joy.
The universe of digital analytics is massive and can seem as complex as the cosmic universe.
With such big, complicated subjects, we can get lost in the vast wilderness or become trapped in a silo. We can wander aimlessly, or feel a false sense of either accomplishment or frustration. Consequently, we lose sight of where we are, how we are doing and which direction is true north.
I have experienced these challenges on numerous occasions myself. Even simple questions like “How effective is our analytics strategy?” elicit a complicated set of answers, instead of a simple picture the CxO can internalize. That’s because we have to talk about tools (so many!), work (collection, processing, reporting, analysis), processes, org structure, governance models, last-mile gaps, metrics ladders of awesomeness, and… so… much… more.
Soon, your digital analytics strategic framework that you hoped would provide a true north to the analytics strategy question looks like this…
The frameworks above cover just one dimension of the assessment (!). There is another critical framework to figure out how you can take your analytics sophistication from wherever it is at the moment to nirvanaland.
It is important to stress that none of these frameworks/answers exist in a vacuum.
Both pictures above are frighteningly complex because the analytics world we occupy is complex. Remember, tools, work, processes, org structure, governance models, last-mile gaps, metrics ladders of awesomeness, and… so… much… more.
The Implications of Complexity.
There are two deeply painful outcomes of the approaches you see in the pictures above (in which you’ll also see my work represented as well).
No CxO understands the story we are trying to tell – or, even the fundamentals of what we do in the world of analytics. Therefore, they are inclined to remain committed to faith-based decision-making and continue to starve analytics of the attention and investment it deserves.
Leaders of analytics organizations do not truly appreciate the wonderful effectiveness, or gross ineffectiveness, of their analytics practice (people, process, tools). You see… None of the currently recommended frameworks and maturity models aids analytics leaders in truly understanding the bottom line impact of their work. The result is analytical strategies that are uninformed by reality, and driven new tool features, random expert recommendations and shiny objects (OMG we have to get offline attribution!).
When one grasps these two outcomes – blind business leaders, blind analytics leaders – it is simply heartbreaking.
The dilemma of how to simplify this complexity, to create sighted business and analytics leaders, has lingered with me for quite some time. I’ve intended to create a simple visual that absorbs the scale, complexity and many moving parts.
I wanted to create a visual that would function as a diagnostic tool to determine if you are lost, trapped in a silo or wandering aimlessly. It would help you realize the extent to which analytics impacted the business bottom line today, and what your future analytics plans should accomplish.
Then one day, a magic moment.
During a discussion around planning for measurement, a peer was struggling with a unique collection of challenges. He asked me a couple of questions, and that sparked an idea.
I walked up to the whiteboard, and excitedly sketched something simple that abstracted away the complexity – and yet preserved the power of smarter thinking at the same time.
Here’s the sketch I drew in response:
Yes, it was an ugly birth. But, to me, the proud parent, it was beautiful.
It took a sixteen hour direct flight to Singapore for the squiggly sketch to come to life – where else, in PowerPoint!
The end result was just five slides. As the saying goes: It's not the ink, it's the think.
I want to share the fully fleshed out, put into practice and refined, version of those four slides with you today. Together, they’ll help you fundamentally rethink your analytics practice by, 1. understanding data’s actual impact on your company today and, 2. picking very precise and specific things that should be in your near and long-term analytics plans.
The Impact Matrix.
To paint a simple picture of the big, complicated world of analytics, the whiteboard above shows a 2×2 matrix.
Each cell contains a metric (online, offline, nonline).
The business impact is on the y-axis, illustrated from Super Tactical to Super Strategic.
The time-to-useful is on the x-axis, illustrated from Real-Time to 6-Monthly.
Before we go on… Yes, breaking the x-axis into multiple time segments creates a 2×5 matrix, and not a 2×2. Consider that to be the price I’ve paid in order to make this more actionable for you. :)
Diving a bit deeper into the y-axis… Super Tactical is the smallest possible impact on the business (fractions of pennies). Super Strategic represents the largest possible impact on the business (tens of millions of dollars).
The scale on the y-axis is exponential. You’ll notice the numbers in light font between Super Tactical and Super Strategic go from 4 to 10 to 24 to 68 and onward. This demonstrates that impact is not a step-change – every step up delivers a massively higher impact.
Diving a bit deeper into the x-axis… While most data can be collected in real-time now, not all metrics are useful in real-time.
As an example, Impressions can be collected in real-time and they can also become useful in real-time (if actioned, they can have a super tactical impact – fractions of pennies). Customer Lifetime Value on the other hand takes a long time to become useful, over months and months (if actioned, it can have a super strategic impact on the business – tens of millions of dollars).
Here is a representation of these ideas on the Impact Matrix:
[You can download an Excel version of the Impact Matrix at the end of this post.]
Impressions can be used in real-time for decision-making by your display, video and search platforms (e.g., via automation). You can report Gross Profit in real-time, of course, but doing so is almost entirely useless. It should be deeply analyzed monthly to yield valuable, higher impact actionable insights. Finally, Lifetime Value will require perhaps the toughest strategic analysis, from data accumulated over months, and the action takes time to yield results – but they are magnificent.
Pause. Reflect on the above picture.
If you understand why each metric is where it is, the rest of this post will fill you with euphoric joy rarely experienced without physical contact.
The Impact Matrix: A Joyous Deep Dive.
In all, the Impact Matrix contains 46 of the most commonly used business metrics – with an emphasis on sales and marketing. The metrics span digital, television, retail stores, billboards, and any other presence of a brand you can think of. You see more digital metrics because digital is more measurable.
Some metrics apply across all channels, like Awareness, Consideration and Purchase Intent. You’ll note the most critical bottom line metrics, which might come from your ERP and CRM systems, are also included.
Every metric occupies a place based on business impact and time of course, but also in context of other metrics around it.
Here’s a magnified view that includes the bottom left portion of the matrix:
Let’s continue to internalize impact and time-to-useful by looking at a specific example: Bounce Rate. It’s in the row indicating an impact of four and in the time-to-useful column weekly. While Bounce Rate is available in real-time, it is only useful after you’ve collected a critical amount of data (say, over a week).
On the surface, it might seem odd that a simple metric like Bounce Rate has an impact of four and TV GRPs and % New Visits are lower. My reason for that is the broader influence of Bounce Rates.
Effectively analyzing and acting on Bounce Rates requires the following:
* A deep understanding of owned, earned and paid media strategies.
* The ability to identify any empty promises made to the users who are bouncing.
* Knowing the content, including its emotional and functional value.
* The ability to optimize landing pages.
Imagine the impact of those insights; it is well beyond Bounce Rates. That is why Bounce Rate garners more weight than Impressions, Awareness and other common metrics.
When designating a metric as a KPI, this is your foremost consideration: depth of influence.
With a better understanding of the Impact Matrix, here’s the full version:
[You can download an Excel version of the Impact Matrix at the end of this post.]
As you reflect on the filled out matrix, you’ll note that I’ve layered in subtle incentives.
For example, if you were to compute anything Per Human, you would need to completely revamp your identity platforms (a strategy I’ve always favored: Implications Of Identity Systems On Incentives). Why should you make this extra effort? Notice how high those metrics sits on the business impact scale!
Other hidden features.
The value of voice of customer metrics is evident by their high placement in context of the y-axis. Take a look at where Task Completion Rate by Primary Purpose and Likelihood to Recommend are, as an example. They are high in the hierarchy due to their positive impact on both the business and the company culture – thus delivering a soft and hard advantage.
You’ll also note that most pure digital metrics – Adobe, Google Analytics – sit in the tactical bottom line impact. If all you do day and night is just those metrics, this is a wake-up call to you in context of your actual impact on the company and the impact of that on your career.
At the top-right, you’ll discover my obsession with Profit and Incrementality, which form the basis of competitive advantage in 2018 (and beyond). Analyzing these metrics not only fundamentally changes marketing strategy (think tens of millions of dollars for large companies); their insights can change your company’s product portfolio, your customer engagement strategies and much more.
The matrix also includes what is likely the world’s first widely available machine learning-powered metric: Session Quality, which you’ll find roughly in the middle. For every session on your desktop or mobile site, Session Quality provides a score between 1 and 100 as an indication of how close the visitor is to converting. The number is computed based on a ML algorithm that has learned from deep analysis of your user behavior and conversion data.
Pause. Download the full resolution version of the picture. Reflect.
It is my hope that the placement of each of the 46 metrics will help you add metrics that might be unique to your work. (Share them in comments below, add to our collective knowledge.)
With a better understanding of the matrix, you are ready to overcome the two problems that broke our hearts at the start of the post – and do something super-cool that you did not think we might.
Action #1: Analytics Program Maturity Diagnostic.
Enough theory, time to some real, sexy, work.
The core driver behind creation of the Impact Matrix was the non-obvious problem #2: How much does your analytics practice matter from a bottom line perspective?
YOU matter if you have a business impact. You’ll have a business impact if your analytics practice is sophisticated enough to produce metrics that matter. See the nice circular reference?
In our case we measure maturity not by evaluating people, process, and layers upon layers of tools, rather we measure maturity by evaluating the output of that entire song and dance.
Answer this simple question: What metrics are most commonly used to make decisions that drive actual actions every week/month/more?
Ignore the metrics produced as an experimental exercise nine months ago. Ignore the metrics whose only purpose is to float along the river of data pukes. Ignore the metrics you wish you were analyzing, but don’t currently.
Reality. Assess, reality. No point in fooling yourself.
Take the subset of metrics that actively drive action, and change the font color for them to green in the Impact Matrix.
For a large European client with a multi-channel existence, here’s what the Impact Matrix looked like after this honest self-reflection:
More of the digital metrics are green, because there are more digital metrics period. You can see the company’s marketing strategy spans television and other offline advertising, including retail.
You’ll likely recognize many of these metrics as the one that your analytics practice outputs every day. They represent the result of a lot of hard work by the company employees, and external analytics partners.
We are trying to answer the how much does the analytics practice matter question. You can see that more sharply now.
For this company most green metrics cluster in the bottom-left quadrant, with most having an impact of ten or under (on a y-axis scale of 1 to a ). There is one clear outlier (Nonline Direct Revenue – a very difficult metric to compute, so hurray!)
As every good consultant know, if you have a 2×2 you can create four thematic quadrants. In our case the four quadrants are called Solid Foundation, Intermediate, and Advanced:
For our company, the maturity of the analytics practice fit mostly in the Solid Foundation quadrant.
Is this a good thing?
It depends on how long the analytics practice has been around, how many Analysts the company has, how much money it has invested in analytics tools, the size of their agency analytics team, so on and so forth.
If they have a team of 50 people spending $18 mil on analytics investment each year, over the last decade, with 12 tools and 25 research studies each year… You can now infer that this is not a good thing.
Regardless, the Impact Matrix now illuminates clearly that highly influential metrics are underutilized. These are the metrics that facilitate deeper thought, patience and analysis to deliver big bottom line impact.
Conduct this exercise for your own company. Identify the metrics actively being used for decision-making. Which quadrant reflects the maturity of your analytics program? With the investment in people, process, tools, and consultants, are you in a quadrant where your bottom line impact is super strategic?
Identify your target quadrant. In this instance the company could move bottom-right and then up. They could also move top-left and then top-right. The choice depends on business strategy and current people, process, tools reality. This should be obvious; you always want the Advanced quadrant lit up. But, you can’t go from Beginner to Advanced directly – evolution works smarter than revolution. (If your Solid Foundation quadrant is not lit up, do that first.)
Create a specific plan for the initiatives you need to undertake to get to your next desired quadrant. You’ll certainly need new talent, you’ll need a stronger strategic leader (less ink, more think), you’ll need to identify specific analytics projects to deliver those metrics, and you’ll most definitely need funding. Divide the plan into six-month segments with milestones for accountability.
The good news is that it is now, finally, clear where you are going AND why you are going there. Congratulations!
Start a cultural shift. Share the results of your assessment, the green and black reflection of the current reality, with the entire company. Inspire each Marketer, Finance Analyst, Logistics Support Staff, Call Center Manager, and every VP to move one step up or one step to the right. If they currently measure AVOC, challenge them to move to Unique Page Views or Click-thru Rate. It will be a small challenge, but it will improve sophistication and, as you can see in the matrix, the impact on the bottom line.
Most companies wait for some Jesus-Krishna hybrid to descend from heaven and deliver a glorious massive revolution project (overnight!). These never happen. Sorry, Jesus-Krishna. Instead, what it takes is each employee moving a little bit up and a little bit to the right while the Analytics team facilitates those shifts. Small changes accumulate big bottom line impact over time.
So. What’s your quadrant? And, what’s your next right or next up move?
People commonly believe that more data means better results. Or, that if an Agency is providing a 40 tab, font size 8, spreadsheet full of numbers that they must have done a lot of work – hence better value for money. Or, a VP wants two more histograms that represent seven dimensions squeezed into her one page dashboard.
If more data equaled smarter decisions, they would be peace on earth.
A core part of our job, as owners of the analytics practice, is to ensure that the right data (metric) reaches the right person at the right time.
To do so, we must consider altitude (aka the y-axis).
Altitude dictates the scope and significance of decisions. It also dictates the frequency at which data is received, along with the depth of insights that need to accompany the data (IABI FTW!). Finally, altitude determines the amount of time allotted to discuss findings.
Managers have a lower altitude, they are required to make tactical decisions – impacting say tens of thousands of dollars. VPs have a higher altitude, they are paid a ton more in salary, bonus and stock, because they carry the responsibility for making super strategic decisions – impacting tens of millions of dollars.
This problem has a beautifully elegant solution if you use the Impact Matrix.
Slice the matrix horizontally to ensure that the metrics delivered to each leader are aligned with their altitude.
By every indicator available, ecommerce is continuing to grow at an insane speed. Although it may seem impossible to imagine with ecommerce already totaling up to 5% of overall commerce, there’s astronomical growth still to come.
Still, I’m heartbroken that some the simplest elements of ecommerce stink so much.
It is 2018—why are there still light gray below-the-fold add to cart buttons?
There are numerous subtle issues as well. One strategic issue is illustrated by Timbuk2.
Timbuk2 pays a huge margin to its resellers to sell their messenger bags. These resellers, in turn, give a bigger cut to Amazon, who then sells the Timbuk2 bag for 30% off. Yet, when I want to pay full price on www.timbuk2.com, I have to buy a minimum of $99 to get free shipping!
I understand channel conflict, Timbuk2, but this is just plain not being hungry. You could win bigger by cultivating higher more profitable direct relationships, especially when the old world order of commerce is collapsing all around you.
And I’m ignoring the extremely light gray font reviews…on a shade grayer background!
(I really want to buy the Closer Laptop bag. The small one in Jet Black looks cool. I refused to buy it because I don’t want to reward a lack of ecommerce imagination. I am one person, I know it is not going to really hurt them, but I don’t know how else to protest a brand I love.)
Pause. Deep breath.
I do get excited about this stuff. My heart bleeds digital.
There is an ocean of opportunities when it comes to elevating ecommerce. In this post, I want to focus my passion and zero in on something that is difficult to solve for, yet immensely profitable: Inserting a sense of urgency into the shopping process.
I don’t mean: BUY IT NOW OR ELSE!
I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount.
Sizing the Opportunity.
In order to have the same passion to take advantage of this magical opportunity (nudge, nudge) you’ll first want to understand how inefficient your current shopping process is.
Do two things, they’ll bring you to your knees:
1. Go look at your ecommerce conversion rate. It shows you how often you win. :) Your overall conversion rate is likely to be around 2%. You don’t need an advanced degree in math to compute that 2% winning is 98% not winning!
Do something simple. Increase current conversion rate by 25%, quantify how much increased revenue there will be. Yes, that additional $6 mil is not as hard to accomplished for an imaginative focused team – in fact you can get that from implementing half of the recommendations in this blog post.
2. Go to the Multi-Channel Funnels folder in Google analytics and look at two other yummy reports: Time Lag and Path Length.
They report two dimensions of speed: How long does it take for a human to convert?How many visits does it take for a human to convert?
My preferred choice is Path Length; it is rich and actionable.
This data you’ll see, the analysis you’ll do, will scare you. It will also create a sense of urgency to do something about it!
These two recommendations will help you compute the opportunity size for your management team.
Aim for quintupling revenue, obviously, but calculating just 25% improvement will give you all the budget you need from your management to insert urgency into the shopping process. Present a yummy spreadsheet that quantifies the cost of inaction, how much money you’ll lose by not delivering a 25% improvement every week. It will be heartbreaking, and now you are ready for progress!
My goal with these recommendations is to have a big impact on your ecommerce existence, and to spark your creativity as you go out and change the world.
Let’s go have some fun nudging people.
1. In-stock status.
It mildly irritates me when sites don’t use this nudge.
How many hotel rooms, cameras, seats in a theater, are left?
Only 15 left in stock. Have that right under the price.
How about: Last run! Be one of the last 9 people to own this credenza design.
OMG! Click, click, click!
Or, 1 in-stock in the REI store next to your office.
I’ll admit that you need to have a well-integrated logistics platform to make these ideas work. But given the decade we are in, if you have not already done that, you are facing an existential crisis. Please stop reading this post, pull in your agency and internal teams urgently to figure out how to dig your company out of this deep hole.
If you have a well-integrated logistics platform already, then all I’m asking for is this: lock your online and offline IT folks in a nice Four Seasons suite for 72 hours with your User Researchers, and BAM! Money will start falling from the sky.
Speaking of the Four Seasons, consider how sad their nudging strategy is vs. the one that booking.com has on display:
All the data you need for this nudge… You already have. That’s what makes the Four Seasons strategy, and that of most sites, so heartbreaking.
Convert the inventory status into a conversion boosting nudge.
2. Life of current price.
It physically pains me how rarely this nudge is used.
Dynamic pricing is everywhere. Why not share that information with the shopper?
This price is guaranteed for the next 18 hours.
This price reflects the highest discount in the past 24 weeks.
Limited-time offer applied to the price you see.
Seasonal promotion! Expires Friday.
Reflects special pricing for our highest-tier Frequent Flyers.
Price has reduced by 14% since your last visit.
I’m sure you’ll find language and phrasing that works perfectly for you (see PS at the end of this post). There is a nugget tied to a unique dimension for your dynamic pricing strategy. Please find it, please use it.
Here’s an example from The Golf Warehouse:
Here’s another one from Overstock that shows two time based nudges…
You can take advantage of other dimensions related to pricing that are unique to your digital strategy.
This one comes from YouTube TV: Lock-in this monthly rate for life.
YouTube TV’s price just went up from $35 to $40 (they added more channels). Everyone who’d signed up at $35 was grandfathered at that price – until they cancel!
Yet, this incredible benefit was not a part of YouTube TV’s merchandizing strategy from day one. You can imagine that a whole bunch of additional people (me!) would have jumped on board. Instead not only do I not have YouTube TV, I am sad/upset. Double loss.
You have an entire staff of economists, financial analysts, directors and VPs spending so much time on finding the perfect price to charge an individual. Why not convert that immense hard work into a nudge that creates a sense of urgency?
3. Direct competitor comparisons.
38% cheaper than Nordstrom.
Sometimes, by using one of the multitude of price aggregators, you can have an understanding of where your pricing is at an item level. Where the match is in your favor, why not use that as a nudge?
You can have the comparison for as long as it is valid. You don’t even need to specify a time—people are familiar with FOMO.
Only at B&H, this item comes with a free LG Watch!
First, who does not like free stuff?
Second, who does not like believing they are getting a special deal?
Three, who does not freak out that if they don’t buy it right away, this “insane deal” will disappear?
Me. I did that. At B&H. :)
Again, your merchandizing team is working hard to procure these amazing bundles for your customers, so why are they not a core part of your nudge strategy?
Costco Special: Get an extra year of warranty!
Our average delivery times to California are 50% faster than Amazon.
Save $150 on installation compared to Best Buy!
Our return rates are 40% lower than Wayfair.
You catch my drift.
Here’s just one example from SugarCRM:
Here’s a comparison on Honda’s site…
No, actually it is from Toyota’s site.
They know that if their car is more expensive, with worse mileage etc., better to be upfront as the customers are looking for that information…
You can also go deeper when it comes to implementing the spirit of this nudge. Kendrick Astro Instruments has the normal table based competitor comparison, additionally they also have a detailed comparison with images to give you more detail…
This shows hunger and desire to win… Their text:
This image displays the quality of Kendrick's cabling that we use on all Premier and FireFly heaters. Our cabling remains flexible in cold weather (down to -40° C), are all labeled for easy identification and all have metal RCA connectors..
This is the text next to their competitor's image (which you can view in higher resolution):
This image displays a competitor's cabling. It is a PVC coated RCA patch cord. PVC gets very stiff in the cold and as a result, makes it an awkward component to use at the telescope. As well, due to the lack of flexibility and give in the cold, it can defocus camera lenses.
Not all that hard to see how this nudge drives higher conversion rates.
Your employees stand up at 11:00 AM each day and sing the company song. There is a line in there about your company’s unique value proposition. Something so special, it stands out against everyone you compete with.
Why let that be your little secret? Why don’t you convert that into a nudge?
Consider how much louder your 11:00 AM company sing-a-long will be when your employees see you laying it out there and going head to head with your competitors.
4. Delivery times based on geo/IP/mobile phone location.
Amazon does this really well.
Each item’s estimated delivery time to you depends on the closest warehouse to your home address. So that Timbuk2 bag might be delivered to me the next day, but it would take two days to get toCarissa in Alabama.
Amazon shows this best delivery time for me right next to the price.
More often than not, I see that Prime One-Day or Prime Same-Day and, as if by magic, I find my mouse glide toward the Order Now button!
The closeness of the customer to your delivery environments remains an infrequently used strategy in creating an urgency nudge.
Another dimension of the delivery time nudge is order in the next 4 hours and get it tomorrow with fast shipping!
In our instant gratification culture, who can resist that?
You are $39 away from overnight shipping has been done to death. (If you are in this category, know that the last “secret” of ecommerce is that figuring out how to weaponize shipping – and free returns – is a powerful conversion increasing engine. Not easy, but your business model has to change to survive.)
But. If you are still in that world—don’t worry, I still love you—know that a behavioral shift from an emphasis on cost to an emphasis on the benefit will make a huge difference.
Add another $39 to your order and get your order 48 hours faster!
This takes advantage of the person’s location, your warehouse location, and your shipping policy, and frames it all as a positive nudge.
A couple more examples to inspire you.
Love these delicious sandals on Express. My wife thinks I’ll look prettier in the red, I think the Mustard really looks like my color. :)
I love the nudge they have built-in showing how many in my size are in stock (only one!)…
Not wanting to risk it, I click on the Find in Store link you see at the bottom of the page.
I get a interstitial that shows me availability of the sandal by geographic location…
Here’s the lovely part… I did not have to do anything. Express did a reverse lookup based on my IP Address, matched that with their stores, then checked their ERP system for inventory and got me the answer. All inside one second.
Dominos will now deliver a pizza to you wherever you are. Literally wherever. In a park, in the dark woods, under a bridge. They look up your mobile location (with your permission), and they’ll come find you.
Assuming you want pizza that bad.
There are still websites that ask you to choose your country when you land. In this day and age, for the sake of Zeus, I hope that is not you. But, how inventively are you using the location nudge?
Significantly higher revenue awaits.
5. Social cues to the rescue.
The last couple of months have not been great for social networks. I’m sure something beneficial will come to the entire digital ecosystem from all this.
A minority might believe that the whole social media thing is going to die. It is not. Community and sharing are core to who we are as humans. It is not going to change. (And, you still need a place for guilty pleasures: indulging in the latest Kardashian-West clan developments!)
Stretch your imagination and it is not hard to come up with some super-clever nudges that incorporate aggregate non-PII information that is public.
People have shared this blouse 18 times in the last hour on Instagram.
80 people in California have booked this destination in the last 30 days.
1,846 Pins for this closet on Pinterest.
Our most tweeted style of underwear!
800 plusses on Google+.
Ok, so maybe not Google+ (I was genuinely excited about it, I am sad it died). But you get the idea.
Social cues (/proof) can help create a sense of urgency for a whole host of companies. Yet, I bet you’ve rarely seen the use of this aggregated information to deliver nudges.
Here’s a simple example of aggregated non-PII based social cue, from, a site you’ve seen me express adoration for in the past, ModCloth. Every product has a little heart sign, visitors to the site vote their love which helps me make more confident decisions…
ModCloth also allows their customers to contribute something you might consider PII, their photos. These make perhaps the ultimate social proof as I can see the skirt I want (mustard again FTW!) on different body sizes…
ModCloth has a whole lot of social proof strategies. They have a Style Gallery, #ModClothSquad, #MarriedinModCloth etc.
Think expansively about social proof.
Naked Wines has a lovely widget next to each of their wines that shows the would buy again rate…
And, they show you historical sales and would buy it again rates.
Checkout the Kimbao Sauvignon Blanc you can see sales and would buy it again rates since 2011. At 91%, the rate is highest this year. Sweet. Add to Basket!
Another team thinking expansively about leveraging social proof are the excellent folks at Basecamp. If you scroll to the bottom of their web pages you’ll see…
Completely non-PII based social proof, a simple cumulative trend of the number of customers. What better way to convince you to use them than this lovely up and to the right trend?
One final, massively underutilized, social proof nudge for you to consider.
Every smart ecommerce strategy has an individual-level referral program bolted on from the very start. Your current customers refer your products and services to their friends, family, and complete strangers—in exchange for a little benefit for themselves.
It is rare, however, to see the use of that referral information as a nudge.
Your friend Alex will receive $5 if you order in the next 24 hours.
The site is keeping track of the referral (to pay your friend Alex his bounty). They have all the information they need to create the above line of text. Why not use it?
Read Diana’s review of this product.
Diana, of course, referred the product to you, and that insight is in the URL you used to get to the site. The site is simply going the extra mile to surface Diana’s review, as it will likely be more meaningful to you than the other 29.
I love Patagonia; I value the brand’s ethos so deeply. And, when I say love, I mean LOVE. Two of the three pieces of clothing I’m wearing right now are from Patagonia. Yet there does not seem to be any strategy at Patagonia to help me (and you and other brand lovers) to create social cue nudges.
Humans inherently want to share, they want to show off, and they want to pass on recommendations/deals to their community. Got social nudges?
6. Personalization. Yes, from 1995!
Do you remember what I did during the last visit to your website?
No PII, just off the anonymous first-party permission-based cookie. Did you use that to change the site’s home page?
And, if you have a GDPR compliant login mechanism…Does your machine learning-powered ecommerce platform leverage the lifetime of my site experience, complaints, purchases, etc., to anticipate my activity?
Do the pages on your site wrap around my objectives, rather than your static and pimpy ones?
Is your entire sales strategy obsessed with the Do, or does it also obsess about the See, Think and Care bits of the complete human experience?
Personalization is the ultimate nudge—to create ecommerce-related urgency and to bring your brand closer to the customer over the lifetime of their experience with you.
That’s because personalization means truly caring. Personalization requires a huge investment in understanding. Personalization is translating that individual human-level understanding into anticipation. Personalization means helping. And when you do it right, personalization means you pimp with relevance—the best kind.
The desire to personalize across the complete human experiences kicks off the processes that fundamentally alter how you treat every human. The reason it works, when done right, is that deep down, we want people to care about us. And yes, we will end up doing more business with people who show that they care for us. Really care. The ultimate nudge.
Today something complex, advanced, that is most applicable to those who are at the edges of spending money, and thus have an intricate web of internal and external teams to deliver customer engagement and business success.
The Marketing Industrial Empire is made up of number of components.
If you consider the largest pieces, there is the internal (you, the company) and the external (agencies, consultants).
If you consider entities, you’ve got your media agency, your creative agency, your various advertising agencies, your website and retail store teams, your analysts, marketers, advertising experts, the UX teams, campaign analysts, fulfillment folks, the data analysts who are scattered throughout the aforementioned entities, the CMO, CFO, and hopefully your CEO. And I'm only talking about the small portion of your existence that is your marketing and analytics.
Whether you consider the large, simplistic perspective (internal – external) or the more complex entity view, it’s really easy to see how things can become siloed very quickly.
It’s so easy for each little piece (you!) to solve for your little piece and optimize for a local maxima. You win (bonus/promotion/award). It is rare that your company wins in these siloed existence.
That’s simply because silos don’t promote consideration of all the variables at play for the business. They don’t result in taking the entire business strategy or the complete customer journey. Mining a cubic zirconia is celebrated as if it is a diamond.
Heartbreakingly, this is very common at large and extra-large sized companies. (This happens a lot less at small companies because of how easily death comes with a local maxima focus.)
So how can you avoid this? How do you encourage broader, more out-of-the-box thinking?
This might seem simplistic, but sometimes it helps to give things names. Naming things clarifies, frames, and when done well it exposes the gaps in our thinking.
Today, I want to name two of the most common silos in large and extra-large companies, in the hope that it’ll force you to see them and subsequently abandon siloed thinking and solve for a global maxima.
Name abstract ideas, draw pictures, deepen appreciation, take action.
Could not be simpler, right? :)
The Advertising Ecosystem: Passive Consumption.
I'm randomly going to use Geico as an illustrative example because the frequency at which they are buying ads means that every human, animal, and potted plant in the United States has seen a Geico commercial at least once in the last 6 hours (contributing to Geico’s business success).
Typically the ads we see are the result of the external creative and media agencies, and their partners in the internal company team/s.
Geico purchases every kind of ad: TV spots, radio ads, billboards (OOH), digital displays (video, online,– social media), print (magazines, newspaper, your cousin's Christmas letter), and so much more.
The teams naturally gravitate towards optimization and measurement that spans their individual mini-universes.
Was that a great ad? Can we test different spending levels in that market? What is the best way to get people to remember the delightful gecko? Can we automate the placement of display ads based on desired psychographics?
Did we get the TRPs that we were shooting for? What was the change in awareness and consideration? What was the reach/frequency for the Washington Post? How many impressions did our Twitter ads get, and how many people were exposed to our billboards?
These are important questions facets of, and delivery optimization of, the advertising. Questions like these, and adjacent others, tend to drive the entire lives of creative and media agencies/teams. For entirely understandable reasons. Siloed incentives delivering siloed local maxima results.
I cannot stress enough that these results can be positive (for the ad business and, in this case, the sales of insurance products). And yet, as a global maxima person it does not take a whole lot of effort to see a whole lot of opportunity if both the siloed incentives can siloed execution implied by the above questions can be changed.
Here’s an incredible simple way that every human seeking global maxima can look beyond the silo: “So, what happens after?”
As in, what happens after the finite confines that are the scope of my responsibility/view?
To see that, the first step is to paint a picture that illustrates the current purpose (your silo), and then give it a name.
Here’s that picture for the example we are using, and the name I gave it is “passive consumption.”
Over 90% of advertising is passive consumption. This means that the ad is in front of the human and they may see it or not see it.
Even on the platforms where interactivity is at its very core (Instagram, Facebook, YouTube, etc.), almost all of the advertising does not elicit any sort of interactivity. If you look at the percentages, almost no one clicks on banner ads, a small percentage on search ads, and you need only speak with a few people around you to see how many people actively engage with TV ads vs. run to the bathroom or pull out their mobile phone the moment forced-watch TV ads come on.
Keep in mind, this is not a ding against passive consumption or the hard work done by Geico's agency and internal teams. Blasting ads on TV does cause a teeny tiny micro percentage to buy insurance – a fact provable via Matched Market Tests, Media Mix Models. The teeny tiny micro infinitesimally small number of views of brand display ads will cause outcomes. (Hold this thought, we’ll come back to that in a moment.)
So, what is the passive consumption challenge?
First, how far the vision of the creative and media agencies/teams will see (thus limiting success – global maxima). Second, trapped in the silo the vision for what will be measured and deemed as success.
The first is heartbreaking. The second ensures the death of any long-term impact.
Let me explain.
With over 90% passive consumption…. Well, passive… Smart media and advertising agencies/teams will primarily use post-exposure surveys to measure awareness (what companies provide car insurance) and consideration (which brands you would consider).
The brilliant agencies will also measure elements such as purchase intent (how likely it is that you'll consider Geico as your next car insurance provider) and likelihood to recommend (how likely is it that you'll recommend Geico to your family and friends).
All of these metrics will cause surveys to be sent via various mediums to people who've seen the TV ads, the banners on Facebook, and the video ads on YouTube. And a subset of users who were not exposed to the ads. Usually, there is anywhere between a few hundred to a thousand survey responses that will end up providing a statistically significant sample.
The scores from these responses are presented in weekly, monthly, or quarterly meetings. Segmented by marketing activity, they are the end-all be-all justification for media spending. Snapchat increased aided awareness by +23%, let us spend more there. Or, billboards in Georgetown and Austin shifted purchase intent by +2%, we should triple our spend in Chicago.
Every measurement and optimization initiative is based on this cocktail of metrics. Thus delivering a positive, but local, maxima.
Even the next best innovation in media will be based on results from the same metrics cocktail. Thus delivering a little more positive, but still local, maxima.
Why not global maxima?
Because success is determined by, innovation is driven by, measurement that is self-reported feelings.
That name captures the actual thing that is being measured (feelings) by the metrics above, and where the data comes from (self-reported) after being exposed to our advertising.
This will help your company, your agencies, understand limits. Limits in terms of what’s happening (mostly, passive consumption) and what data we are looking at (all post-exposure and self-reported).
Limits in measurement that incentivize solving for a local maxima.
Let me repeat one more time. Passive consumption measured by self-reported feelings does drive some success – else Geico would not be the financial success it is. In the short-term some campaigns are trying to drive long-term brand influence or causing a shift in public opinion or simply to remind people your brand still exists as a choice. All good. Self-reported feelings are wonderful. Appreciate that even in those cases where you are not trying to drive short-term sales, if all you have are feelings converted into metrics… You are limiting imagination.
An obsession with just passive consumption by your agencies and internal teams delivers 18 points of success. I’m saying if you think global maxima, remove limits, you can do 88 points!
The Business Ecosystem: Active Engagement.
Getting those additional 70 points success requires breaking the self-imposed creative/media/advertising silo and caring about the human behavior if people lean-in instead of passive consumption – when they take an action (a click, a phone call, a store visit).
Time to draw another picture, and give this behavior a name.
I call it… drum roll please… Active Engagement!
Some people, between 0.01% to 10% (so rare!), who see Geico’s online ads will visit a Geico retail store or Geico's website.
People are actually doing something. They are walking into your store, talking to an agent, picking up the literature, calling you on the phone, clicking on to your site, watching videos, comparison shopping, and more. This is all human behavior that your tools can report for you.
A small percentage will end up buying insurance – mazel tov! –, providing perhaps the most valuable data.
The lucky thing about active engagement is that, in addition to self-reported feelings, you also get tons of highly-useful quantitative data representing human behavior.
I call this type of data: Observed Human Behavior.
If you are a part of an creative, media, or an internal company team, you have two powerful issues you can solve for: passive consumption (happens most of the time) AND active engagement (happens some of the time).
Likewise, you can seek to understand performance using self-reported data where the people reflect on how they feel, along with behavior data that represents what they actually do.
The combination of these two factors deliver the much needed Global Maxima perspective.
That is how you shatter silos. The creative agency has to care about how ads perform in their labs, in the real world, and what kind of online and offline behavior the creative is driving (end-to-end baby!). The media agency has to care about the creative and where it needs to get delivered (recency, frequency FTW!), and the bounce rate (70% ouch, 30% hurray!) and profit from each campaign. The retail experience team, the call center delight team, and the site experience team will break their silo and reach back into understanding the self-reported feelings data from the media agencies and the ideas that lead to the creative that delivered a human to them.
Everyone cares about the before and after, solving for the overall business rather than their little silo. Passive consumption plus active engagement equals global maxima. Or, self-reported feelings plus observed human behavior equals global maxima.
Here’s a massively underappreciated benefit: It also encourages every employee – internal and external – to take full credit for their impact on the short and long-term effects of their effort.
It is rare to see this happen in real life, even at top American and European companies.
What’s usual is to see the three silos between creative agencies, media agencies, and company internal team. There is usually further sub-segmentation into passive consumption teams (also lovingly referred as brand agencies/advertisers) and active engagement teams (performance agencies/advertisers). The further sub-sub-segmentation into products and services (depending on the company).
They then quickly fall into their respective measurement silos, solving for the local maxima.
Change starts with naming things and drawing pictures. Gather the key leaders at your company and agency partners. Show them passive consumption and self-reported feelings along with active engagement and observed human behavior. Talk through the implications of each picture. Ask this influential audience: What can you contribute to when it comes to breaking silos?
I have yet to meet a single company where simply drawing the picture did not result in a dramatic rethinking of focus areas, responsibilities, and ultimately priorities.
Accelerating Success: Five Quick Changes.
Once you have that discussion, what should you do to truly cause a significant change in behavior?
Five Es form the core of the strategies that I end up using (please share your's via comments below). They are:
1. Expand the scope of data your employees use.
For the people who buy your television ads, include both store and website traffic data. Break the shackles of GRPs and Frequency.
For people buying your display ads on Facebook, include page depth, bounce rate, as well as micro-conversion rates for those campaigns. Break the shackles Awareness and Views.
For people buying your videos ads on Hulu, complement Hulu's self-reported feelings metrics with user behavior and conversion rates.
And continue going in this fashion.
2. Expand the incentives structures for your employees.
Most marketing employees, both internal and external, undertaking passive consumption initiatives are rewarded for cost per TRP, effective reach, awareness and consideration increases, etc. Whatever this bucket as an employee incentive, it can stay.
Consider adding one or two KPIs from active engagement. For example: Store visits, phone calls (as a result of that increase in consideration). Website visits, loyalty, micro-outcomes, and 25 other easily-available observed human behavior metrics are available to you pretty much in real-time.
For people who own responsibility for your stores, call center and website, take a metric or two from passive consumption and make it a small part of their incentive structure.
People respond to what they are compensated with, or promoted for. Use it to solve for a global maxima in the company and its customers.
3. Expand the time horizon for success.
This is really hard.
You buy 100 TRPs, it’s expensive, and the executives tend to start badgering you for immediate results.
The problem is that self-reported feelings data takes time, and since at least 90% of passive consumption leads to no immediate active engagement, all this does is incentivize bad behavior by your agencies and employees. Long-term objectives are thrown onto the chopping block and long-term strategies are judged on short-term success – which immediately ruins the campaign’s measurement. Oh and the audience being bombarded by your ads that are trying to deliver short-term outcomes from long-term creative and campaigns… They despise you because you are sucking, they can see that, and they instantly realize your are wasting their time.
No matter how much your wish, a Chicken won’t birth a Lion’s cub.
If you want short-term success, define the clearly as a goal, pick the right short-term self-reported feelings metric and observed behavior metric, now unleash your creative agency and their ideas (on that short-term horizon), then plead with your media agency to buy optimal placements, and ensure the retail/phone/web experience is not some soft and fuzzy experience, rather it is tied to that clear goal and success metrics. Sit back. Win.
If you want long-term success… Same as above, replace short with long. How amazing is that?
4. Expand the datasets that teach your smart algorithms.
If you’ve only visited this blog once in the last 12 months, or read just one edition of my truly amazing newsletter :), Marketing <> Analytics Intersect, it is quite likely I have infected you with the passion to start investing in machine learning in order to bring smart automation to your marketing and user-experience initiatives.
If you are following my advice, make absolutely sure that you are not training your algorithms based solely on passive consumption, self-reported feelings data. It is necessary, but not sufficient.
Rich observed behavior data will provide your algorithm the same broad view of success as we are trying to provide the humans in #2 above. In fact, the algorithms can ingest way more data and complexity. Thus allowing them to solve for a super-global maxima compared to our humble abilities.
Every algorithm is only as smart as the data you use to educate it. Don't short-change the algorithm.
5. Expand leadership comfort level with ambiguity.
For your TV efforts, there are limits to what you can measure. You have self-reported feelings data, and usually that’s about it. If you have a sophisticated world-class measurement team, you may be running some controlled experiments to measure one or two elements of active engagement observed human behavior data.
For YouTube or Hulu on the other hand, you’ll have additional self-reported feelings data, and if you follow my advice today, plenty of directly-causal observed human behavior data at your disposal.
Get very comfortable with this reality, and execute accordingly.
When some executives are not comfortable with this reality, they typically end up gravitating towards the lowest common denominator. Even in regards to strategies where more is possible (digital), they just end up using self-reported feelings data for everything.
I do understand why this is; executives are pressed for time, so the executive dashboard needs only one metric they can compare across initiatives. This instantly dumbs-down the intelligence that could help contribute to smarter decisions.
Kindly explain this to your executives, share with them the value of being comfortable with a little ambiguity that comes from using the best metric for each initiative type.
We can achieve smarter global maxima decisions if we just use different metrics in some instances.
The larger the company, the harder it is to solve for a global maxima. Companies need command and control. Companies worry that people are going to run wild in 15 different directions. Companies need to reward an individual, that means creating a finite role that can be defined and measured at a small level. Companies add layers upon layers to manage. Companies create org clusters (divisions). And, more.
Every one of these actions forces a local maxima. Every human can see their few pixels and have no idea what the image looks like.
Even if then the company progresses little by little, they’ll run out of luck one day. Worse some nimble small company – that does not yet have to worry about all of the above – will come eat your breakfast first, then dinner and then lunch.
The lesson in this post applies across the entire business, even if in this instance it is applied to marketing and advertising.
Paint a picture of what the local maxima execution looks like in your division – or better still company. Give these pieces a name. Then, figure out, like I’ve done above, what the connective tissue is that’ll incentivize global maxima thinking and execution.
As always, it is your turn now.
In your specific role, are you solving for the global maxima or a local maxima? How about your creative and media agencies? Your internal marketing or product teams? Has your company done something special to ensure that teams are considering both self-reported feelings and observed human behavior? Is there a magic metric you feel that’ll encourage each piece of the business success puzzle to solve for a global maxima?
Please share your wisdom, tips and secrets to success via comments below.
I worry about data’s last-mile gap a lot. As a lover of data-influenced decision making, perhaps you worry as well.
A lot of hard work has gone into collecting the requirements and implementation. An additional massive investment was made in the effort to perform ninja like analysis. The end result was a collection trends and insights.
The last-mile gap is the distance between your trends and getting an influential company leader to take action.
Your biggest asset in closing that last-mile gap is the way you present the data.
On a slide. On a dashboard in Google Data Studio. Or simply something you plan to sketch on a whiteboard. This presentation of the data will decide if your trends and insights are understood, accepted and inferences drawn as to what action should be taken.
If your data presentation is good, you reduce the last-mile gap. If your data presentation is confusing/complex/wild, all the hard work that went into collecting the data, analyzing it, digging for context will all be for naught.
With the benefits so obvious, you might imagine that the last-mile gap is not a widely prevalent issue. I’m afraid that is not true. I see reports, dashboards, presentations with wide gaps. It breaks my heart, because I can truly appreciate all that hard work that went into creating work that resulted in no data-influence.
Hence today, one more look at this pernicious problem and a collection of principles you can apply to close the last-mile gap that exists at your work.
For our lessons today, I’m using an example that comes from analysis delivered by the collective efforts of a top American university, a top 5 global consulting company, and a major industry association. The analysis is publicly available.
I’ve chosen to block out the name of entities involved. Last-mile gaps exist at all our companies. It is not important where this 2018 analysis came from. In the tiny chance that you recognize the source, I request you to keep it out of your comments as well.
For each of the 17 examples we review, I’ll share an alternative version I created. I invite you to play along and share your version of any of the examples. I’ll add them to the post, and credit you.
In this case the goal was to create handouts, perhaps to make it easier for audiences to consume the data by themselves. I would humbly still advocate for simplicity when it comes to data presentation.
Some of the fixes to solve for simplicity could be to use fewer sprinkles, a simpler header – graphics and text –, and we can be very selective about what’s on he slide. As you look at the slide, I’m sure you’ll come up with other ways in which we can liberate the white space for the tyranny of text/colors.
Solving for simplicity contributes to communication effectiveness. It of course reflects on your brand, and, most of all, helps you have better control over the story you are trying to tell.
For the rest of this post I’ll ignore the simplicity and storytelling elements and focus exclusively on the data itself. How, what, why and instead of.
Look at the graph above, and the little table… Ponder for a moment what you would do to close the last-mile gap and help the essential message shine through.
Here are some things that stood out for me:
1. Graphing choices can exaggerate or undersell reality.
One way to exaggerate is to start your y-axis at 40, as it the case above. The resulting line exaggerates the trend and ends up implying something that might not quite be there.
Start at zero. Please.
2. False precision can cause clutter, and undercut the Analyst’s brilliance.
This is very subtle.
You’ll notice that the numbers on the graph are expressed with one decimal point. As in 47.7, 56.5, etc. If you pause and consider how this data is collected, via a small triple digit sample self-reported survey results, you’ll quickly realize that the error range in this data is likely a few points. If that’s true, showing the .6, .5 is implying a precision that simply does not exist.
Besides, this false precision also clutters the graph.
3. Remove the distractions, ruthlessly.
In an 11-year span, each data point is a lot less important than the trend. Do you need the dots on the graph? Do you even need the numbers for the individual months?
When it comes to closing the last-mile gap it is helpful to have a ruthless streak. It is helpful because in service of our ultimate objective, you’ll have to kill some of your favorite things, you’ll have push back against your boss/peers who might love clutter, and you might have to help change an entire culture. Hard, painful, work. But, immensely worth it.
Here’s an alternative way to present the data, using nothing more than the standard settings in good old Excel:
It shows the trend, simply. You can see it is up broadly over eleven years. That it was under 50 and is now close to 70.
Did you notice the trend is not as exaggerated as the original? And, still effective!
You might use a different font, perhaps have the graph be smaller, or maybe twist the month-year in the other direction. No problem. I’m confident if you apply the first three filters, whatever you create will close the last-mile gap better.
Here’s an example of doing exactly the opposite of principle #1. The y-axis is artificially set at 100%, as a result the trend is understated.
You don’t need to go this far.
Just let your favorite graphing tool auto-set the major and minor-axis, which will result in the graph looking like this…
Simple. No funny business.
The trend stands by itself waiting your words as to why it is meaningful.
This next one is pretty interesting. My request to you is to not scroll beyond the slide. Pause. Absorb the graph. Try to understand what the author is really trying to say.
For bonus points, consider the perspective of the person reading this graph rather than the person who created it.
Read. Don’t scroll. Absorb.
How well did you understand the trend and the insight being communicated? What would you have done differently if you’d created the graph?
Here are some things that stood out for me:
4. Show as much data as is required, and no more.
The goal in the original seems to be to show top priorities for 12 months. If so, is the data for August 2017 really adding value?
Often we want to show all the data we have (after all we spent time collecting it!). In this case, it get’s in the way of understanding the 12 month shift.
5. Experiment with visualization options, even in Excel!
We have five dimensions of data, and two data points each (if you apply principle #4). We want the audience to be able to compare two data points for each dimension, and look across all five dimensions.
The bar chart is a sub-optimal way to let the audience see this. Consider experimenting with different visuals in Excel (or D3js).
I applied the radar chart to this data, and got this lovely end result…
It is ten million times easier to see the two data points for five dimensions, and realize that only two have changed.
Likewise, the overall trend also pops out at you so much easier in this case.
It would have taken ten minutes for us to explain the data and trend in the original. We can do that in five seconds now. You can use the time remaining discussing why this trend is material and what to do about it (if anything). Actually allowing data to play its natural role: Influence decisions.
This is a really nice example of a lesson that we tend to forget all the time (myself included).
You know the exercise by now. Pause, reflect on this slide, then scroll.
Here’s what stood out for me:
6. Don’t send a graphic to do a table’s job.
In this case, we are comparing two simple data points, on two dimensions (past, present). Why do we need a graph taking up all the space?
Why not just have a table that shows previous 12 months as 7.1% and a row under it with next 12 months as 8.9%?
Even better, why not just have one line of text:
Percent change in marketing budgets = +1.8 PP
Why have two fat bars?
Once you arrive at that conclusion, you’ll apply principle #4 and realize that the most interesting data on this slide is not the visual… Rather, it is the table on the top right corner of the slide.
Bada, bing, bada, boom, ten seconds later here’s your slide:
A simple table with a touch of colors that draws out the core message simply, directly and quickly.
The lighter shade for the core numbers will result in them being pushed a bit into the background. This simple choice guides the reader’s eyes gently to the delta (the most important bit).
I like playing with the borders a bit, as you see above. You might have other things you are picky about. And, that is ok. :)
To illustrate principle #6, here’s another slide where the graphic is completely unnecessary:
A tiny table with two data points will do just fine.
Here’s a bonus lesson for the analysis ninjas out there. Please don’t imply a linear trend between “current levels” and “next three years.” There is no indication that data from 2017 to 2020 is available, and it is highly unlikely that it will follow a linear trend. This is another example of breaking principle #1.
(Let’s not lose sight of the big picture: I am delighted that spending on analytics is going to increase that much! As our leaders spend this largesse, I hope that they’ll remember the 10/90 rule to ensure optimal returns. The money needs to go to you!)
This one flummoxed me.
Let’s see if you can internalize what is going on. Stare at the graph intently, seriously, and see if you get the points…
Bold items naturally catch the eye, in this case the blue bars. Most people in the western world look from left to right, that is how you’ll likely try and understand what’s going on.
Your first impression will likely be that the blue bars are showing a random trend in marketing spending.
If you are the curious type you’ll realize that is the wrong conclusion, and you’ll want to understand what’s really going on. Soon enough you’ll get to the x-axis and a carefully review will illuminate that the reason for the weirdness is the choice to show the industry names alphabetically!
7. Please, please, please keep the end-user in mind.
In this case the end-users (our senior leaders) would be primarily be interested in understanding where marketing spending is highest and lowest. This is very difficult to accomplish above.
Secondarily, they’ll want to know where they fall in context of all other industries, this is almost impossible to accomplish above.
The reason the x-axis is organized alphabetically is to allow you to look up your specific industry easily. This thought is good. My hypothesis is that it likely forms a small percent of the use cases, primarily because just knowing your spend is not that valuable. What’s valuable are the above two use cases.
Here’s what I recommend keeping front of mind: If a non-analyst is looking at the data, what uses cases form the basis of the value they’ll extract. Then, ensure the info viz is solving for that.
In this case the bars with the data seem to be randomly sorted. The visualization is getting in the way, creating a wider last-mile gap.
Luckily this is a quick fix in good old Excel. Two minutes later, you’ll have a little waterfall…
It is easy to see the outliers and the pack of eight that are close to each other (something you can’t even see in the original).
It will certainly take an extra couple of seconds to find your industry, but in service of the two bigger use cases, it is a small price to pay.
You can play with the layout to your heart’s content. If you dislike waterfalls for some reason and prefer towers…
I like the waterfall, but this is not bad. :)
Play with the colors, drop shadows, fonts, and more. Make the graph your own. Just don’t forget to look at it through the eyes of the end user and solve for their use cases.
(Speaking of colors… I’m partial to chart styles 17 through 24 in Excel. In my work you’ll see a particular affection for style 18.)
Comparison by angle is significantly more difficult than by length.
That is well on display below…
The colors in the pie will catch your eye. Yet, from the sizes of the slices it is difficult to internalizes the differences between each dimension.
8. Eat Pies, Don't Share Them!
Since humans find comparing lengths much easier, it should only take a few minutes to take the data and convert the slide above into something that closes the last-mile gap efficiently.
The above slide is a good example how to apply all the principles you’ve learned thus far. The question and the data are the hero, almost all by themselves. Allowing you to focus sharply on your story.
Scroll up and down and compare the two slides. You’ll see many more differences.
I’ve extoled the virtue of using a table, instead of trying to be extra sexy and throwing in a graphic.
The challenge with tables is that they can become overwhelming very quickly.
Here’s an example that illuminates that clearly.
It feels like there is a lot. It also breaks principle #2, false precision, which makes things worse.
Considering the core message the analysis is trying to send, I believe that it is also breaking rule #4, extra perhaps unnecessary data.
9. Make your tables pop, guide the reader’s eye.
There are numerous tools available to you inside Excel to make your tables pop. I usually start by playing with the options at my disposal under Conditional Formatting.
One straight-forward option is to use Color Scales, green to yellow, to produce a simpler table that pops…
The elimination of the overall average makes the table tighter.
It is easier to look at the trend in each column. What’s even more delightful is the second use case of comparing the highs and lows across the four dimensions. So much easier.
While all the data is still there, most senior leaders want to understand trends and the contrasts. They want relative positioning, the above table does not require expending too many brain cells to get that. And, if your boss does not trust you… She still has the numbers there.
Notice the combination of fonts, colors, style treatments, in the table above. Bunch of subtle points there.
If your personal tastes are different, no problem. There are other styles you can use.
Here’s the data rendered using solid fill Data Bars…
In this case I feel data bars add clutter, but they make internalizing the trend across individual dimensions easier.
If, like me, you are biased towards radical simplicity via white space, you can keep the table. Consider applying some subtle font color treatment to create something that’s still a step change over the original…
I’ve shown the highs and lows in a way that you’ll see them quickly.
Red was chosen on purpose to emphasize that it was the most important thing from the customer’s perspective. Blue fades into the background a bit because it is the least important.
One final touch.
I felt it might be of value to see the product and services dimensions together, comparing them across B2B and B2C.
Here’s that version…
There’s a little air gap in the table to emphasize the two comparisons are different. You can usually use visual cues like these to help the consumers of your analysis.
We disagree on a whole lot of subjects in our country these days, but the one thing we can all agree on is that the human attention span is probably ten micro-seconds.
Add to that short attention span the fact that each executive has 18 other urgent things taking up their brain cells. As if all that was not hard enough, while you are presenting they are also likely on their phone or laptop.
Persuading anyone in these circumstances is a herculean task.
With that context in mind, how many leaders do you think will understand what’s going on here…
4 dimensions x 5 time periods x crazy swings = Ouch!
For bonus points, notice the randomness in the x-axis. It jumps from 2014 to 2017 without any visible explanation. To make things worse, look at the trend lines – they connect the two data points to imply a trend between 2015, 2016 that may or may not exist.
For even more bonus points, notice that there are four Februaries and as if it is no big deal an August is thrown in randomly.
These might seem like small issues, but I assure you that you’ll instantly lose credibility with any intelligent leader in the room. They won’t raise their hand and start to berate you...
If you bring sharp focus, you increase chances of attention being diverted to the right places. That in turn will drive smarter questions, which will elicit thoughtful answers from available data. The result will be data-influenced actions that result in a long-term strategic advantage.
It all starts with sharp focus.
Consider these three scenarios…
Your boss is waiting for you to present results on quarterly marketing performance, and you have 75 dense slides. In your heart you know this is crazy; she won’t understand a fraction of it. What do you do?
Your recent audit of the output of your analytics organization found that 160 analytics reports are delivered every month. You know this is way too many, way too often. How do you cull?
Your digital performance dashboard has 16 metrics along 9 dimensions, and you know that the font-size 6 text and sparkline sized charts make them incomprehensible. What's the way forward?
If you find yourself in any of these scenarios, and your inner analysis ninja feels more like a reporting squirrel, it is ok. The first step is realizing that data is being used only to resolve the fear that not enough data is available. It’s not being selected strategically for the most meaningful and actionable insights.
As you accumulate more experience in your career, you’ll discover there are a cluster of simple strategies you can follow to pretty ruthlessly eliminate the riffraff and focus on the critical view. Here are are five that I tend to use a lot, they are easy to internalize, take sustained passion to execute, but always yield delightful results…
1. Focus only on KPIs, eliminate metrics.
Here are the definitions you'll find in my books:
Metric: A metric is a number.
KPI: A key performance indicator (KPI) is a metric most closely tied to overall business success.
Time on Page is a metric. As is Impressions. So are Followers and Footsteps, Reach and Awareness, and Clicks and Gross Ratings Points.
Each hits the bar of being “interesting,” in a tactical oh that’s what’s happening in that silo soft of way. None, passes the simple closely tied to overall business success standard. In fact, hold on to your hats, a movement up or down 25% in any of those metrics may or may not have any impact on your core business outcomes.
Profit is obviously a KPI, as is Likelihood to Recommend. So too are Installs and Monthly Active Users, Orders and Loyalty, Assisted Conversions and Call Center Revenue.
Each KPI is of value in a strategic oh so that is why we are not making money or oh so that is why we had a fabulous quarter sort of way. A 25% movement in any of those KPIs could be the difference between everyone up and down getting a bonus or a part of the company facing layoffs. Often, even a 5% movement might be immensely material. What metric can say that?
When you find yourself experiencing data overload, don an assassin's garb, identify the metrics and kill them. They are not tied to business success, and no senior leader will miss them. On the ground, people will use metrics as micro diagnostic instruments, but they already do that.
A sharp focus on KPIs requires concentrating on what matters most. Every business will have approximately six KPIs for a CEO. Those six will tie to another six supplied to the CMO.
After you go through the assassin’s garb process above, if it turns out that you have 28 KPIs… You need help. Hire a super-smart consultant immediately!
2. Focus only on KPIs that have pre-assigned targets.
This is a clever strategy, I think you are going to love it.
Targets are numerical values you have pre-determined as indicators success or failure.
Turns out, creating targets is insanely hard.
You have to be great at forecasting, competitive intelligence, investment planning, understanding past performance, organization changes and magic pixie dust (trust me on that one).
Hence, most companies will establish targets only for the KPIs deemed worthy of that hard work.
Guess what you should do with your time? Focus on analysis that is worth your hard work!
Start by looking at your slides/report/dashboard and identify the KPIs with established targets. Kill the rest.
Sure, there will be howls of protest. It'll be John. Tell him that without targets you can’t identify if the performance is good or bad, a view every CEO deserves.
John will go away and do one of two things:
1. He will agree with you and focus on the KPIs that matter.
2. He will figure out how to get targets for all 32 metrics along all 18 dimensions.
You win either way. :)
An added benefit will be that with this sharp focus on targets, your company will get better at forecasting, competitive intelligence, investment planning, org changes, magic pixie dust and all the other things that over time become key assets. Oh, your Finance team will love you!
Special caution: Don't ever forget your common sense, and strive for the Global Maxima. It is not uncommon for people to sandbag targets to ensure they earn a higher bonus. If your common sense suggests that the targets are far too low, show industry benchmarks. For example, the quarterly target may be 400,000 units sold. Common sense (and company love) tell you this seems low, so you check actuals to find that in the second month, units sold are already 380,000. Suspicion confirmed. You then check industry benchmarks: It is 1,800,000. WTH! In your CMO dashboard, report Actuals, Target and Benchmark. Let him or her reach an independent, more informed, conclusion about the company’s performance.
3. Focus on the outliers.
Turns out, you are the analyst for a multi-billion dollar corporation, with 98 truly justifiable KPIs (you are right: I'm struggling to breathe on hearing that justification, but let's keep going). How do you focus on what matters most?
Focus your dashboards only on the KPIs where performance for that time period is three standard deviations away from the mean.
A small statistics detour.
If a data distribution is approximately normal then about 68 percent of the data values are within one standard deviation of the mean, about 95 percent are within two standard deviations, and about 99.7 percent lie within three standard deviations. [Wikipedia]
By saying focus on only reporting on KPIs whose performance is three standard deviations from the mean, I’m saying ignore the normal and the expected. Instead, focus on the non-normal and the unexpected.
If your performance does not vary much, consider two standard deviations away from the mean. If the variation is quite significant, use six (only partly kidding!).
The point is, if performance is in the territory you expect, how important is it to tell our leaders: The performance is as it always is.
Look for the outliers, deeply analyze the causal factors that lead to them, and take that to the executives. They will give you a giant hug (and more importantly, a raise).
Having an upper control limit and a lower control limit makes it easy to identify when performance is worth digger deeper into. When you should freak out, and when you should chill.
Look for outliers. If you find them, dig deeper. If not, move on permanently, or at least for the current reporting cycle.
Use whichever statistical strategies you prefer to find your outliers. Focus sharply.
4. Cascade the analysis and responsibility for data.
In some instances you won't be able to convince the senior leader to allow you to narrow your focus. He or she will still want tons of data, perhaps because you are new or you are still earning credibility. Maybe it is just who they are. Or they lack trust in their own organization. No problem.
Take the 32 metrics and KPIs that are going to the CMO. Pick six critical KPIs for the senior leader.
Cluster the remaining 26 metrics.
You'll ask this question:
Which of these remaining 26 metrics have a direct line of sight to the CMO’s six, and might be KPIs for the VPs who report to the CMO?
You might end up with eight for the VPs. Great.
Now ask this question:
Which of these remaining 18 metrics have a direct line of sight to the eight being reported to the VPs, and might be KPIs for the directors who report to the VPs?
You might end up with 14 for the directors.
Repeat it for managers, then marketers.
Typically, you'll have none remaining for the Marketers.
Here's your accomplishment: You've taken the 32 metrics that were being puked on the CMO and distributed them across the organization by level of responsibility. Furthermore, you've ensured everyone's rowing in the same direction by creating a direct line of sight to the CMO’s six KPIs.
Pat yourself on the back. This is hard to do. Mom is proud!
Print the cascading map (CMO: 6 > VPs: 8 > Directors: 14 > Managers: 4), show it to the CMO to earn her or his confidence that you are not throwing away any data. You've simply ensured that each layer reporting to the CMO is focused on its most appropriate best sub-set, thus facilitating optimal accountability (and data snacking).
I’ll admit, this is hard to do.
You have to be deeply analytically savvy. You have to have acquired a rich understanding of the layers of the organization and what makes them tick. You have to be a persuasive communicator. And, be able to execute this in a way that demonstrates to the company that there’s real value in this cascade, that you are freeing up strategic thinking time.
You’ll recognize the overlap between the qualities I mention above and skills that drive fantastic data careers. That’s not a coincidence.
5. Get them hooked on text (out-of-sights).
If everything else fails, try this one. It is the hardest one because it'll demand that you are truly an analysis ninja.
No senior executive wants data. It hurts me to write that, but it is true.
Every senior executive wants to be influenced by data and focus on solving problems that advance the business forward. The latter also happens to be their core competence, not the former.
Therefore, in the next iteration of the dashboard, add two more pieces of text for each metric:
1. Why did the metric perform this way?
Explain causal factors that influenced shifts. Basically, the out-of-sights (see TMAI #66 if you are a subscriber to my newsletter). Identifying the four attributes of an out-of-sight will require you to be an analysis ninja.
2. What actions should be taken?
Explain, based on causal factors, the recommended next step (or steps). This will require you to have deep relationships with the organization, and a solid understanding of its business strategy.
When you do this, you'll begin to showcase multiple factors.
For the pointless metrics, neither the Why nor the What will have impact. The CMO will kill these in the first meeting.
For the decent metrics, it might take a meeting or three, but she'll eventually acknowledge their lack of value and ask you to cascade them or kill them.
From those remaining, a handful will come to dominate the discussion, causing loads of arguments, and resulting in productive action. You'll have known these are your KPIs, but it might take the CMO and her team a little while to get there.
After a few months, you'll see that the data pukes have vanished. If you've done a really good job with the out-of-sights and actions, you'll notice notice that the focus has shifted from the numbers to the text.
Massive. Yuge. Victory.
If more examples will be of value, I have two posts with illuminating examples that dive deeper into this strategy…
You don't want to be a reporting squirrel, because over time, that job will sap your soul.
If you find yourself in that spot, try one of the strategies above. If you are desperate, try them all. Some will be easier in your situation, while others might be a bit harder. Regardless, if you give them a shot, you'll turn the tide slowly. Even one month in, you’ll feel the warm glow in your heart that analysis ninjas feel all the time.
Oh, and your company will be data-influenced — and a lot more successful. Let's consider that a nice side effect. :)
Knock 'em dead!
As always, it is your turn now.
Have you used any of the above mentioned strategies in your analytics practice? What other strategies have been effective in your company? What is the hardest metric to get rid of, and the hardest KPI to compute for your clients? Why do you think companies keep hanging on to 28 metric dashboards?
Please share your ideas, wild theories, practical tips and examples via comments.
Like me, I'm sure you are working on complex challenges when it comes to data.
Multi-petabyte data warehouses. Multi-touch, cross-channel attribution analysis. Media mix modeling. Predictive analytics. Human-centric analysis. Oh, and let's not forget the application of machine learning to every facet of your work.
It is genuinely fun to work on these opportunities. They’re difficult, and every step forward offers a renewed sense of excitement and inspiration.
Despite the joy in these high-level, forward-thinking initiatives, I've disciplined myself not to let the unsexy fundamentals go overlooked. I’m particularly vigilant about avoiding friction in the core systems that facilitate the flow of money into the company and beloved products out of it.
So today, that valuable reminder for you kicked off via a case study inspired by Condé Nast. To inspire, and jump-start, a change in your focus, we’ll also look at Heal, Facebook and prAna.
Before we proceed with the stories… The unsexy fundamentals in this post focus on user experience. If you are a reader of my newsletter, The Marketing < > Analytics Intersect, you’ve seen me apply it to metrics (last TMAI was on Bounce Rate), reports, frameworks and more. The concept touches all facets of our professional universe.
Condé Nast | A Story of Unrequited Love.
Condé Nast is in a world of hurt, along with everyone else in the print business. In 2017, they've twice replaced the company's Chief Revenue Officer. They are pursuing a variety of digital experiments, and it remains unclear whether any of them will stick (unlike the New York Times, where new initiative such as "The Daily" podcast and T Brand Studio have proven overwhelmingly successful).
You might assume that Condé Nast, through these changes and new initiatives, would have solved the fundamental issue of subscriber retention.
Join me on that journey.
I love The New Yorker.
"Love" is an understatement. I ADORE The New Yorker magazine. I love David Remnick. And Amy Davidson and Sheelah Kolhatkar and John Cassidy and Jia Tolentino and… all of 'em. Hence, I'm proud to be a paying subscriber. The nourishment that your soul craves is in The New Yorker, and I encourage you to consider your own subscription.
As I almost exclusively read the articles online, I visited the website to switch to digital-only (from digital + print) when my subscription expired in October.
I recall this simple task posing a surprising challenge. I was busy, and ultimately, I gave up. Last week, in my guilt for reading articles online for free, I decided to try again.
The first step was to log into my New Yorker account.
I was already logged into the site and thus found this to be a bit of a nuisance. But, no biggie.
Post-login, I was taken to my profile page, where under the Edit button I received a lovely reminder of my tardiness.
[Full disclosure: The New Yorker, starting May 2017 had sent me at least 14 reminder letters via postal mail with a form to complete fill out and return with a check. I don't know who does this anymore, certainly not us. I want to add that I did not get a single reminder via email – with a direct link to renew. This despite the fact that The New Yorker has my email address, and it would be cheaper to send me 14 emails than printed letters. Clearly, the Department of Postal Mail is vigorous at Condé Nast.]
I clicked on Customer Care (but not before taking a tangent to explore what "Amazon Digital Subscriptions Manager" is, turns out to be the most expensive way to get a subscription to the magazine!).
Amazingly, I was asked to log in again, this time on a completely new domain.
It was a bit odd to see the captcha. I wonder just how many hackers are dying to access the Condé Nast subscription website to help process renewals!
Mildly irritated, I did as I was asked.
Once again, I was presented with a summary of my account, and I began scanning for my next action.
I simply wanted to change my subscription from digital + print to just digital, and to know what it will cost.
I scanned my options on the left navigation, with few promising options.
I give "Renew" a try.
My only choice was to up the game to two years.
I wondered what the Wired cross-sell says about New Yorker subscribers. Had it been tested?
Next, I tried "Digital Access." It seemed to smell right.
Wrong choice again.
This just told me how to access the magazine anytime, anywhere! :)
Back to exploration mode.
(At this point, I was not irritated. I realized there was a lesson to be learned. So I began taking screenshots of this unnecessarily painful journey, wondering if any Condé Nast employee had ever tried to change their personal subscription.)
I revisited "Manage Your Subscription," to make the next best choice: "Adjust auto-renewal."
Right choice? No. Wrong again.
I didn't want to update my credit card.
This, I was forced to resort to the last bastion of the frustrated: "Subscription FAQs."
I hate FAQs; they are almost always useless. Will Condé Nast prove to be the one exception to the rule?
"How can I renew my New Yorker subscription," seemed somewhat promising. I dutifully choose "clicking here."
I was right back to where I started, amazed that this company is in so much trouble financially but won't offer someone desperate to pay them a seamless way to do so.
Left to the footer, I clicked "Subscribe." At that point, what did I have to lose?
This took me to a third site, where, finally I was able to choose a digital-only subscription!
No. Not really.
This is a "12 Weeks for $12" offer that only applied to new subscribers. This offered no path for an existing subscribers.
What was even more frustrating — massively so — is that there was also no answer to my other question: How much would a digital-only subscription cost?
In fact, on this subscription page (the one I linked to when recommending The New Yorker above), there is no way to determine how much The New Yorker costs per year.
Let me say that again. If you are trying to subscribe — new or returning — Condé Nast does not tell you the annual subscription cost!
What kind of con are these people running?
This put me at my wit's end. I'd failed to give them my money.
I revisited the second site to select "Chat Now."
Having logged in three times, as indicated in the top-right corner, I am asked once again to supply my credentials.
I waited an eternity for the chat session to start, completely absent of any status indication (x minutes remaining, or you are 10th in the queue).
Bored, I jumped back to the other window to tinker.
That's where I noticed the suddenly appealing "Cancel" link. Click!
I found the three choices intriguing.
How many of those who visit the page to cancel their subscription would like to improve the experience? (It was also not clear what "experience" meant.)
I opted to "Reconsider and save $10," simply because I love The New Yorker, and I wasn't going to give up on them. I am going to subscribe no matter how inept Condé Nast is.
A friendly message informed me that I was to wait for an email containing my $10 discount.
Why do I have to wait, I wondered.
Did Condé Nast have so many employees that someone was going to review my "case history" and validate my worthiness for the $10 discount, which, let me remind you, they offered proactively?
My chat window came alive. Hurrah!
No. Not really.
"Leah" seemed unfamiliar with the Condé Nast platform. She directed me to pages I couldn't see, and asked me to go sign up for an intro offer which I knew I wasn't allowed to get (that was clear in the legal terms on the page).
After not helping at all, I admired her chutzpah in asking if she can help me with anything else.
Frustrated, I choose "End Chat."
I decided to wait for my $10. I felt I'd earned it by now.
Now, it has been a couple weeks. Crickets from Condé Nast.
Since I still love The New Yorker, I'm considering a digital subscription under my wife's name. She'll get 12 weeks for $12, which is sad as I want to pay full price.
12 weeks into that subscription, perhaps I'll finally come to find the full annual fee.
Ensuring loyal customers are able to renew and modify their subscription is the most fundamental of functions. It is not revolutionary to say that you really don’t want friction there.
Condé Nast has analysts upon analysts upon analysts. They have a world of user experience experts. I am genuinely and absolutely confident that these 400 people are executing large complex projects to save Condé Nast from financial trouble. None of them though thinks that that starts with something simple and fundamental: Fixing renewals. Or, telling people what a subscription actually costs.
To say that this breaks my heart is an understatement of galactic proportions.
Up next, you.
Condé Nast is hardly alone. I highly recommend a close self-evaluation to ensure that this isn't true for you as well.
To inspire prompt action by you, let me share a few more UX examples that are super-close to the company making money (the thing they/you should positively nail).
Heal | A Story Unfulfilled Forms.
Heal has an irresistible value proposition: They’ll send a doctor to your house!
I’m blessed to have health insurance. Still going to a doctor is such a pain, and even with an appointment the doctor makes me wait. Heal it is.
I install the mobile app, and proceed to making my first appointment.
The very first thing I have to enter is my date of birth. Seems reasonable.
Here’s the screen I get…
What is the reasonable number of times the Heal UX team thinks a human should be expected to click the little < button to get to their date of birth?
I won’t tell you how old I am (very!), it is a lot of back clicks for me. A lot.
I just gave up.
For this article I opened the app again. There has to be a (hidden) better way.
I tried to click on “January 2018” hoping it pops up a calendar. No dice. I then clicked on “Sun, Jan 7.” Nope. Nothing else seems clickable. Looking… Scanning… Then, I clicked on the little “2018” on the top left. I get a list of years, score! I scroll, scroll, scroll, I’m old, scroll, and find my year of birth.
Consider this: You are a startup trying to upend the existing insane healthcare system. Should you have a simpler way to fill out the date of birth? Unsexy fundamental.
In the month of December, when I needed an annual exam, I could not get the address field in the Heal app to get my home address in there. (Unsexy fundamental.) I had to make an appointment and drive to the doctor. Oh, the humanity!
Facebook | A Story of Unsent $100s.
The only way now to get to your followers on Facebook is to buy ads.
No problem. After I would post something I want my Facebook followers to see, I would click the blue Boost button and pay Facebook $100. That seemed to solve the Reach problem.
Then one day a little while back I’m greeted with a new button: Boost Unavailable.
I have 45k followers on Facebook, without boost I get just 4k.
So I want this problem fixed. I want to give Facebook my $100. Except. Boost Unavailable.
When I click on that button, I get this, to me, confusing message.
A long time ago I had a personal page on Facebook. A couple years ago they informed me that I was not a person, I was a brand and forced me to change that page to “brand page.” I lost all my connections, and got followers instead.
Now, I don’t know what to do with this message. This account is all I have.
I click on Manage Page Roles, to see what my choices are…
I have to admit I am lost.
I am confident someone at Facebook understands what is going on, they even understand every option in the 19 choices in the left nav. Sadly, I don’t. The end result is that I can’t give Facebook my $100 and get my posts boosted.
As you might have heard, Facebook is just fine without my $100 every other week. They are clearing $10 bil a quarter. Still, an example of an unsexy fundamental that their user experience team could consider solving for.
prAna | A Story of Unfiltered Sadness.
I appreciate the opportunity to support businesses that solve for fair trade, green and sustainable business practices. If their products last forever, even better as I have to buy a lot less over time.
prAna is a good example of such a company. I also admire their brand building efforts – from the logo to the shipping envelopes.
I can’t afford their clothes at full price, but can’t resist looking at the men’s sale section when I need something.
Filters are your BFF when you are in environments with lots of choice. You can quickly go from being overwhelmed to narrow focus.
prAna’s site has loads of filtering choices: Gender, size, activity (yoga, hiking…), fit (slim, fitted), inseam, color, fabric (fair trade, HeiQ…), performance (PFC Free DWR, quick dry…), rating, silhouette (button down shirt, flannel, that’s it, really!), country of origin.
Guess what’s missing?
Imagine you have go trawl through hundreds of items on sale for clothing you need. What is the first thing you want to filter by?
Yes! Type of clothing.
Pants. T-Shirts. Jackets. Shorts.
That is the one filter prAna does not provide. Unsexy fundamental.
Even with the other 9 filters, it is hard to quickly find what I’m looking for.
I have received 7 emails in the last handful of weeks from them with this subject line: “40% Off: End of Season Sale – Your Favorite Looks are Going Fast – Don’t Miss Out.” I wonder how long it will take the User Experience experts at prAna to figure out why the conversion rate is zero percent.
If the UX experts shop on the site, they’ll find these unsexy fundamental issues everywhere.
The most common reason I return pants are that they are not long enough. Pants with 34” inseam fit me.
I was looking for new pair of travel pants. The Calculus Pants look like they could do the job.
Two weird things.
No waist size. I can take a gamble on M, but length is not a gamble I’m willing to take. I scroll around a bit. Nothing.
I click on “Size & Fit Guide,” in case it specifies something for these pants.
I get the generic guide. It is helpful in that it confirms that I need “Long Inseam.”
Except. That information is not on the Calculus pants page.
Scroll up. Scroll down. Scroll around. Switch to mobile site, because why not. Nope. Nothing.
Perhaps these pants don’t come in the three choices (Short, Regular and Long). But at least tell me what the inseam size the Calculus pants are! Unsexy fundamental.
prAna charges $8 for returns, for any reason. That is a lot. Hence… No pants for me.
Unsexy fundamentals are very sexy. I recommend two actions on your part:
1. Create a dedicated (small) team to obsess continuously about the most fundamental functions. Ensure that you have a special rewards mechanism in place for them (like every other company out there you currently only reward people who work on shiny object projects).
The team’s work will start with the fundamentals closest to your core transactions. Cart and checkout for digital; cashier experience in your store. Build from there.
2. Create incentives for your employees to be secret shoppers. In fact, ask your CEO to try and do business with your company. The frustration she/he/they feel will drive amazing impact (on User happiness and company profit).
Sure, it will delay your multi-channel attribution predictive analytics powered single source of the truth initiative, but it'll be worth it.
2018: the year of doing the unsexy fundamentals well!
As always, it is your turn now.
Do you have a program/team in place to focus on unsexy fundamentals? What currently stands in the way of your company obsessing about ensuring all pathways to making money have been smoothed over? What is the primary mechanism in helping you figure out what unsexy fundamentals are broken? Do you have an example of a user experience, any mobile app or site, that is persistently frustrating?
Please add your insights, stories, frustrations, and wonderful accomplishments via comments below.
Today, a simple lesson that so many of us miss at great peril. In fact in your role, at this very moment, your company is making a mistake in terms of how it values your impact on the business.
The lesson is about the limitation of optimizing for a local maxima, usually in a silo.
We are going to internalize this lesson by learning from Microsoft. It is a company I love (am typing this on my beloved ThinkPad X1 Carbon Gen 5, using Windows Live Writer blogging software!). I bumped into the lesson thanks to their NFL sponsorship.
If you were watching the Oakland Raiders beating the hapless New York Giants (so sad about Eli) this past Sunday, you surely saw a scene like this one:
Quarterback Geno Smith using his Microsoft Surface tablet to figure out how he added two more fumbles to this career total of 43. Or, maybe it was him replaying the 360 degrees view of the three times he was sacked during the game.
For all this expense, you'll see players and coaches using them during the game (as above). The Surface branding also gets prominent placement on the sidelines – on benches, on movable trollies and more. It is all quite prominent.
I adore Mr. Lynch’s passion. Oh, and did you notice the Surface branding?
Now, let’s talk analytics and accountability.
NFL ratings are down, but an average game still gets between 15 m – 20 m viewers. That is a lot of pretty locked-in attention, very hard to get anywhere these days.
The question for us, Occam’s Razor readers, is… What does the Surface Marketing team get for all this money?
If the Surface Marketing team is like every other team at every other company engaged in sponsorships and television advertising, it’ll measure the same collection of smart metrics like everyone else.
First one will be Reach. The Surface team is likely measuring it with deep granularity (by individual games, geo, days, times of days, and a lot more). I’m confident that their analysis will show they are getting great Reach.
The team will rightly be congratulating itself on this success.
Next on the list, having spent enough of my life with TV buyers, I can comfortably say that the Surface team is also expending copious amounts of effort measuring one or more dimensions of Brand Lift metric. Ad Recall, Brand Interest, Favorability, Consideration etc.
Brand Lift is most frequently measured using surveys.
Given the number of times Microsoft Surface, or its branded presence, shows up in a game (52 times in my count in the OAK – NYC game), I believe the Surface team is getting very positive reads from its post NFL ad-exposure surveys.
After 52 times most people would recall the ad, surely answer the survey with some interest in the brand, and everyone (except Coach Belichick) seems to like using the tablets, a favorability that will surely transfer to a whole lot of viewers.
This would, indeed should, result in more congratulations in the Surface team.
The two-step approach above reflects the most common approach Marketers, and their Agencies, use to measure success. Did we reach a large audience? Do they remember anything?
The answers to these two questions power job promotions, bonuses and agency contract renewals with higher fees.
I believe this is necessary, but not sufficient.
I believe this approach optimizes for a local maxima (the media buying bubble) and does not create the necessary incentives to solve for the global maxima (short or long-term business success).
Let me illuminate this gap.
Here’s the global maxima question: How many Surface tablets have been sold due to this near-blanket coverage in NFL games via precious undivided attention?
That was the question that crossed my mind during Sunday’s game.
I had one data point handy.
According to TripIt I’ve visited 156 cities across 32 countries in the last few years. During these trips, meetings and meetups, I've never seen a Microsoft Surface tablet in the wild. Not one.
That’s not completely true. I have seen one frequently. The one I bought for my dad four years ago.
One data point does not a story make.
To assess a more complete answer, we turn to our trusty search engine Bing…
The picture above starts 12 months after Surface inked the $400 million NFL contract. The Surface's share of shipments is so small, it does not even show up in a graph.
Not being content with just one view of success, I tried other sources.
This is a bit hyperbolic, but in the grand scheme of things… No one is buying a Surface.
Local maxima view of success: The Surface team’s NFL contract is a smashing success. The team is getting great Reach and great Brand Lift. Contract with NFL renewed for another 12 months.
Global maxima view of success: Microsoft is losing.
[Key caveat: The data Statista and IDC provide capture shipments. It is possible that the Surface is being sold directly in a way that neither of these two sources would capture those sales. Perhaps some kind of B2B sales. To overcome this possible issue I’ve used the Statcounter data to capture usage. Still, there is a possible scenario where none, or not enough, of the Surfaces sold visit those two million sites.]
Sadly, Microsoft is not alone in this local maxima focus. Most companies function in a similar manner. Yours. Mine. Other people’s. Our collective mistake is that we don’t think critically enough about what we really are solving for. Our company’s mistake is the incentive structure they put in place (which almost always rewards the local maxima).
Let me give you two examples of this sad local maxima obsession that crossed my desk just this morning. All in the space of one hour.
Local – Global Maxima Example 2: Gap Inc..
A report has been published on The Age of Social Influence. Its goal is to aggressively recommend the strategy of marketing via Social Influencers. Here’s the publishing company’s intro of themselves: “We are a powerful data intelligence tool that combines the knowledge and insights you need to deliver a successful celebrity and social influencer marketing strategy.”
Their claims of this wonderful Social Influencer strategy is based on a survey of 270 respondents. 270. It seems like an oddly tiny choice by a powerful data intelligence tool company (PDITC).
They have all kinds of numbers from the 270 survey sample showing glory.
The very first example in the report of a brand winning hugely with a Social Influencer strategy is Gap.
Here’s a screenshot from the report…
While we all love Cher, seriously she is special, this is a classic local maxima let’s only look at what will make us look good to pimp stuff we want to strategy.
What would be a global maxima if you are going to use a company as a poster child?
Here’s Gap’s financial performance over the last five years…
Gap Inc. has been struggling for years, flirting with financial disaster recently in every facet of its business.
I invite you to explore other financial data on the eMarketer Retail website. Look at Revenue, Earnings, Margins, Employment… Everything is super sad. For an additional valuable lesson, click on Digital as well. It shows the social performance of Gap (illustrating even the local maxima is quite suspect).
I dearly wish the Gap survives, they make good quality clothes.
I also wish that the powerful data intelligence tool company would have chosen to focus on looking at the global maxima success before using Gap, and the other examples in their 40 page report. That would have made their drum banging for Social Influencers more persuasive. It would also have resulted in fewer clients of powerful data intelligence tool company shuttled in the direction of spending money on something that mostly likely will not produce any business results.
Local – Global Maxima Example 3: Amazon
A celebration was shared with me for 31 custom gifs created by Giphy for the up and coming retailer Amazon.
Here’s a non constantly looped, to ensure you’re not annoyed, sample…
The celebration was based on the fact that the total view count for these 31 custom gifs was 31 million.
[Sidebar: Always, always, always be suspicious of numbers that are that clean. 31 gifs being viewed a clean 31 million times is cosmically impossible. Seek the faq page to understand how views are measured. Identify that there is no clarity. Now, be even more suspicious.]
I’m afraid in my book views don’t even count as a local maxima. Even if they are in yours, I hope you’ll agree they are a million miles away from a global maxima.
I wanted to share this example from Amazon because you can’t use the global maxima of overall business success I’ve used above. Even if Jeff Bezos goes around hitting people with feather dusters, Amazon will keep selling more and more products. They have already reached perpetual motion.
What do you do when it is difficult to identify the global maxima from a super-tactical animated 31 gifs with 31 million views effort?
Try to move four steps up from wherever you are. Global maxima lite.
In this case, here’s a great start: % of Users who shared the gif who are not current Amazon customers.
So much more insightful than Views, right?
We are shooting for a deeper brand connection, by an audience that holds business value for us. Sure these people are annoying their friends, but hey at least as Amazon we can remarket to them – and friends (!) – and convert them to Prime customers!
I’m sure you can think of others that are five, six and eight steps above Views. (Share them in comments, and earn admiration.)
It does not always have to be revenue or profit. But, please don’t pop the champagne on views, impressions and other such primitive signals of nothingness.
On the topic of measurement, let’s go back to Microsoft and brainstorm some strategies for their unique use case.
What should Microsoft have measured?
Purely as an academic exercise I’m leaving aside the possibility that the Surface is simply not a good tablet. That would certainly impact sales – marketing or no marketing. But, since Microsoft went back for year five, it is safe to assume at least they believe it is a good tablet.
Ok? It is a good tablet.
Again as an academic exercise I’m going to ignore the four year horizon. There is no question that at the end of year two Microsoft had overwhelming proof from a multitude of data points that the NFL contract was not selling any Surfaces. They did not need Big Data or Artificial Intelligence to come to that conclusion. If they could not get out of the contract, at the end of year two a better use of $100 mil spend per year would have been to change the covers on the Surfaces to Xbox green, and change the numerous printed brand opportunities on the sidelines to Xbox as well. A great selling product, with a much bigger overlap with the NFL audience than the Surface.
Ok? We are not looking after year two.
During the first and second year, what could we have measured as Microsoft if we wanted to do better than the local maxima? Better than Reach and Brand Lift metrics?
Let me plant three ideas (please add yours via comments).
An enhanced survey would be a good start. Along with measuring ad recall etc., they could also ask how likely are you to choose the Surface over the iPad as your next tablet?
It is a tougher question than do you remember the ad or what tablets can you name. It is going head to head with the thing people usually say when they mean tablet. And, you are looking for switching. A strong behavior shift, a harder yes to get when I’ve done surveys. All this brand exposure, if its working, should shift that key intent signal.
Really easy to do. And, you can easily get thousands upon thousands of responses – you don’t have to settle for 270. It would have given the Marketing team a leading indicator that no one is going to buy the Surface as a result of the NFL partnership. The signal could have been received even a couple months in, and certainly by the end of year one.
Time series correlations would have been a great start right after the first week of the contract. How many people are visiting the Surface website on Sundays? Is that materially significant compared to weeks prior or weeks where there were not as many games? Was there an improvement on Sundays in digital sales? How about retail sales on Mondays?
This is simple stuff. Even visits to the site would have been a nice low level signal.
As the season went on, we could look for test and control opportunities. The NFL always has blackouts in cities/states where the stadiums don’t have enough attendance. This past weekend it was in two states, complete blackout of free broadcast games. Is there a difference in site visits, online conversion rates, offline sales, between states that had one game broadcast on Sunday, two games broadcast on Sunday and no games broadcast on Sunday?
A little more complicated. The site stuff is easy to segment. For store sales Microsoft could easily get data from its stores in malls, and likely also from retailers like Best Buy with a little arm twisting. This data would have shows Microsoft, a few months in, that the global maxima might not be reached.
If you don’t have this type of ubiquity, Matched Market tests are also fabulous in these cases to discern if a specific marketing strategy is having a business impact.
Three ideas that I hope will spark many more in your mind when you shoot to measure the global maxima.
I want to briefly touch on one refrain I often hear about these long term efforts, or short term efforts that are not working but are looking at a longer horizon: So what if the results are not there. This is a long term brand building play, Apple did not become a beloved brand in one year.
There is a kernel of truth there, brand building take time. There is a kernel of BS there as well, Apple is Apple primary because of its innovative products.
Let’s not talk about Microsoft in context of the above statement as even if we assume there was some long term brand building happening, it did not translate into business success.
When you hear a statement like that, after you launch a new underwear, cooking range, VR headset or whatever… Obsessively measure more than the local maxima to discern signals in the short term that illustrate that the long term brand building play is not just an excuse to flush a lot of money. Both the Gap and Amazon examples have ideas to inspire you.
Or consider that even your long term brand building play, in the short term should cause you to take noticeable amounts of market share. It won’t be 80% in the short term, but neither is that statement a reason to spend more money if all you got is 5% in year one and 10% in year two.
Don’t settle for opinion.
You have data.
Bonus: The real winner of the Microsoft NFL contract?
The NFL of course.
Microsoft makes great hardware. To make it work for the NFL, Microsoft surely wrote lots of custom software for the NFL’s specific use cases. Microsoft likely invested in tens of millions of dollars of camera equipment, wifi/networking upgrades in every stadium, deployed a small army of Microsoft employees to do on-site tech support before, during and after the games in every single stadium. And, more and more and more.
The NFL should be paying Microsoft $110 million a year to upgrade the ability of its coaches, players and teams to have access to this state of the art technology to compete more effectively every Thursday, Sunday and Monday!
The NFL is slated to make $14 billion in 2017, they can surely afford to give $110 mil a year to Microsoft.
Back to the real world… Even when you measure short term success, please do not be satisfied with a local maxima. Even in the short term you can measure something better. On the long term, you have all the elements you need… Definitely measure the global maxima!
Do this because it is the right and smart thing to do for your company. But, a tiny bit, do it because in my experience (across the world) global maxima solvers progress exponentially faster in their career. Turns out, delivering business results matters. :)
As always, it is your turn now.
Do you have a suggestion for what Microsoft or Gap or Amazon should measure as their global maxima? If you’ve been successful getting your CEO to focus on the global maxima, what approach really worked? If you were the role of the Chief Scientist of powerful data intelligence tool company, how would you measure the impact of Social Influencers in a more intelligent manner?
Please add your powerful ideas, brilliant critique and innovative strategies in comments below. I look forward to hearing from you.
It is time to point out an ugly truth, and to be the brave person that you are, the intelligent rational assessor of reality that you are, and kill all the organic social media activity by your company.
All of it.
Seems radical, but let’s take it one step at a time.
To give you a sense of the depth and breadth of ideas I’ll cover today, here are the sections in this post:
I urge you to have an open mind. My plan is to challenge your critical thinking skills, and share lessons that will apply broadly across the professional effort you put day in and day out. Most of all, I’m excited to frame an important problem, and present solutions that will transform an important part of your marketing strategy.
The Promise of Marketing Utopia.
I hate pimping (what marketing has come to be). I adore building meaningful relationships – the kind of long-term connections where a brand truly gives a f about their customers, and gives something of value in exchange for their attention. I LOVE brands that can pull this off, and support them with my un-asked-for evangelism and precious $$$s.
Hence, you can imagine how gosh darn excited I was at the advent of Facebook and Twitter (first real social networks). There were a billion people there, spending a meaningful amount of time on these wonderful platforms. Excitedly, brands could have a presence (a "page") where they could contribute meaningful updates (info-snacks) in order to be a part of the organic conversations people were already having by the tens of millions.
Daily meaningful brand connections would be converted into brand familiarity, shifts in brand perception, feeding brand loyalty. #orgasmic
If you were a travel company, meaningful would now translate into helping feed wanderlust. The company could contribute info-snacks about where people should go, exposing the coolest places in the world, helping people travel better via tips, pictures, videos… you know… communicating travel love. The one thing a travel company would have in common with travel customers. The most imaginative travel marketers could even extend this opportunity to helping connect the purpose of their existence, selling tickets and hotel rooms, to helping people create moments of happy by crafting day/s of escape from the rough and tumble of life.
Glorious, right? If you work at Expedia or Cathay Pacific, does that not make you want to come to work and, for at least a part of your employment, create meaning? How rare is that!
If you were Cisco, meaningful would mean sharing info-snacks whose entire purpose could be to get Engineers promoted. Share tips, ideas, schematics, usage shortcuts, creative implementations, solutions to top problems that hold Engineers back… you know… understanding your audience deeply and give them something of value in exchange for their attention. The most imaginative B2B marketers could even figure out how to be a part of solving some of the deepest entrenched problems in the industry (STEM education, equal opportunity, + +) and in turn add an entire value-system to their brands.
Marketing based on something real, rather than a coupon or company brochure.
The Broken Promise of Marketing Utopia, Implications.
None of the above transpired on Social platforms.
Businesses of all types, including Google (SMB, Main), got on amazing platforms like Facebook (and Weibo, Instagram, Pintrest etc.) and started pimping. All that their collective imagination could manifest in a Utopia-possible environment was: LOOK ME I AM SO PRETTY!! BUY NOW!!!
Stuff that is a turn off.
Consider the Google’s first FB page above, it is a complete disaster with not a single post in the last six months being of even five seconds of value to any small business. That page, or the main one, is not an overt Buy Now, but if you think critically like the tough Marketer I want you to be you’ll have a hard time finding a single post that’s solving for Google’s human customers. Almost every single one is pimping Google (or pimping random research Google has commissioned – to pimp Google!). The non-value is so transparent, yet they post every single day something that basically is solving for Google (although only God knows what that is). If someone bothers to interact with the post, the posted comment is a spam or totally useless. Yet. They keep posting. Polluting utopia.
Google is not unique in not understanding the promise, checkout your company’s FB page.
This strategy by businesses lead to what I now call the Zuck Death Spiral. ZDS.
Real humans on Social platforms quickly got turned off by these low-grade Social contributions/posts by companies. That meant humans (us!) refused to engage with them. This was noticed by Team Zuck, who started to slowly turn down the presence of company posts in User feeds. This lead to less Reach for brands. Which in turn lead to even fewer customer interactions for content posted by brands. Which was duly noted once more by Team Zuck. Which… you know where this is going, tightened the screws on organic Reach even more. And, here we are in a barren desert for brands on FB.
Most brands get less than 1% Reach via their organic contributions on social platforms. And, less than 1% engagement of any kind from that less than 1% reached (identified using the best social media metrics: Conversation Rate, Amplification Rate, Applause Rate).
ZDS is solving for FB, as FB should, and it is an attempt to solve for FB’s users.
So… If all you can do is overtly or covertly pimp… And, pimping is not cheap (that Google page, and your company’s page, has pictures, videos, an agency deployed, internal company employees with a “social media execution checklist”, senior leadership time committed, and more)… And, all it does is get you 1% Reach, max, with almost no engagement… Why do you still have an active (organic) social media effort?
Why is this reality not smacking some sense into your marketing strategy?
The Broken Promise of Marketing Utopia: Examples.
Is it difficult to check if your brand is caught up in the Zuck Death Spiral? No.
Do you have access to any data to measure how deeply non-impactful your organic Social Media efforts are? OMG, yes.
Everything you need, data and information, to do an audit is public.
All you have to do is visit your company’s Facebook page (or Instagram, LinkedIn, Pinterest, etc. presence).
Let me show you what to look for. Let’s start with Expedia. They have 6.4 million Likes as of today. Go look at any post on the page if you are an Expedia employee.
First thing you’ll look at is the Applause Rate (likes, other emotions, you’ll see it right under the photo). That number is 75. Divide that by 6,462,977 (potential audience size today).
0.00113%. That’s a painful stab in your heart.
Next Conversation Rate (comments, you’ll see a total at the end of your posts). 7. Divide that by 6,462,977. A sad 0.00011%.
Finally, my favorite sign that you truly added value to a human rather than pimp, Amplification Rate (shares). 3/6,462,977. At this point you are weeping with me: 0.00005%.
To give you some context as to how insanely lame these numbers are, Expedia.com received 59,400,000 Visits in May 2017. This post accomplished 75+7+3. More people walk into the Expedia lobby in Bellevue, WA, every second of every minute.
You might be screaming that is not fair Avinash, the Zuck Death Spiral ensures that a tiny fraction of 6,462,977 are seeing Expedia’s posts! Very fair point. But, is the Social Media Budget at Expedia not justified based on the potential from 6,462,977? Would Expedia commit it’s multi-million-dollar budget to Social Media based on the potential to engage 75+7+3 people on Planet Earth?
One final point. Brand destruction.
Pretty much every single comment on pretty much every single Expedia post is a complaint about how horrible Expedia is (from personal experience I know this is not true). If your Facebook presence is solely to inspire people (see Trish Sayler above) to create clever rhymes about how bad you are… Why are you on Social Media?
Ignore the active smearing of the Expedia brand, let’s go back to data: Is it worth have 75 | 7 | 3 as the value delivered from an organic Social Media strategy for a company with 54,900,000 Visits?
My answer is an emphatic no. Expedia should immediately cease 100% of its organic Social activity.
1/100th of the Social Media budget could be spent on any other random digital strategy to get 75+7+3, and have zero brand destruction!
Oh. And while I’m focusing on Facebook for the sake of simplicity, everything in this post applies to all other Social Media channels. The Utopia failures. The lack of imagination. The small numbers. The uselessness.
Here for example is a post on Twitter by Expedia:
The numbers: 9 | 2 | 2. Divided by 391,000 (followers).
You can do the math and assess dent in the universe this content contribution from Expedia is making.
Almost nothing. Technically, perhaps less than nothing.
I hate making recommendations based on outliers, please know that Expedia is the norm. Hence, the title of this blog post.
Here’s a B2B example, a company I think well of… Cisco.
Go through the same analysis.
Your numbers are 31 | 1 | 3. Divided by 845,921.
Would you spend a single hard-earned Cisco router and switches dollar to get this as the return from a multi-million dollar Social Media budget?
Like my company, your company, and Expedia, Cisco gets no value from their organic Social Media efforts. Technically, Cisco is getting negative returns once you account for the people, process, tools, agency, leadership investments.
Let’s switch gears and look at a B2C company with a massively positive opportunity to leverage the word Social in every way on these platforms… Chick-fil-A.
Better numbers, as you might expect.
1k | 89 | 73. Divided by 7,775,155.
Consider it. Chick-fil-A could buy the most remnant TV inventory on a channel least watched by humans during the middle of the night and get better Reach. And they can also measure how many of them walked into a Chick-fil-A in the next 12 hours.
Does the above number justify custom videos, images, active posting by Click-fil-A on Facebook?
One final example to bring this home.
ProjectManager.com is a lovely tool. It is wonderful that they use folks like Jennifer Bridges, Susanne Madsen and others to create very helpful Project Management videos on YouTube. It seems they are a medium-sized business.
Here’s their Facebook page:
69 | 0 | 25. Divided by 62,951.
Pound for pound, better performance than all three (four including Google) companies above. Shame on them.
Still. Are the resulting Applause Rate, Conversation Rate and Amplification Rate enough for a smaller business to use it’s precious marketing dollars on this Social Media strategy/impact?
Consider this as well for all brands… There is no native discovery model on these Social channels. Your content will live for 20 minutes and then it is dead. Not just because of ZDS, but also because there is no Search behavior by users or a method that would deliver Serendipitous Discovery of content you post.
Unlike say on YouTube, or your Blog, where your Subscribers will see the content right away, and then through Bing and Yandex and YouTube itself people will find your content when relevant and keep viewing it. Your content there has a live beyond 20 minutes.
Win Big: Stop Posting Content for Organic Reach On Social Channels.
Given the numbers above, and be sure to check any other Social Media channel your company is actively investing in, I hope you have the input you need to apply your critical thinking skills.
Let me give you one final push: You have better alternatives to drive short and long-term Profitability for your company (rather than investing in organic Social Media).
Here’s an example.
I write an insightful newsletter with the singular aim of improving your salary. The Marketing < > Analytics Intersect. You should sign up. It is a companion to this blog, I write once a week there and once a month here.
One year into it’s existence, TMAI has 21,246 Subscribers.
Measuring Open Rates for email is difficult (the tiny pixel ESPs use to track opens are not executed by default for most email programs). Even with that flaw in reporting, TMAI has Open Rates of around 9,000 (9,895 precisely for the last one). Around 1,000 people (912 for the last one) take an action that is of value to me.
A random person, me, can get 9,000 opens of my content, at least a thousand active engagements with my brand whenever I want. I have over 1,000,000 Social Media followers across the five platforms (Twitter, Facebook, LinkedIn, Google+, Instagram). I can’t even get 1/100th the impact.
My simple unsexy email newsletter strategy crushes the on paper potential of one million Social Media followers.
And, beyond the impact… I also directly own the relationships with my 21,246 Subscribers, I own the data, the relationship exists on my platform, and I can use it as creatively I want to use it with no limitation on type of content (text or video or dancing penguin gifs).
Why should your company be on Social Media 5x per day to get a lousy 20 interactions with your brand? How is that acceptable ROI from your investment in a 5 person Social Media team, a Social Media Agency, a Social Media analytics tool, a Social Media auto-posting tool and more?
Could you not get 100x ROI from the 0.25 person that's running your email newsletter?
Could you not just take all that Team, Agency, Tool, money, throw it into AdWords or AOL Display Ads and not get massively higher ROI, of any kind, in 10 minutes?
Could you not get better ROI taking all that money and buying remnant inventory on your local Television channel?
Could you not get better ROI if you just took that money and bought free lunch for the employees in your building every other day?
OMG, you most definitely can.
So. Why are you on Social Media?
Is it fun to shout in a vacuum?
Why does it not feel dirty to go waste your shareholder's money?
Stop it then.
Welcome to the world of higher standards for impact delivered. Feel cleaner and prouder coming to work every day as a Marketer/CMO.
Is the Huge Audience on Social Media Platforms Completely Useless?
There are a couple of billion people on Facebook (and billions or hundreds of millions on other Social channels). From an advertising perspective, that’s still an audience that might be of value to your business.
Kill your organic Social strategy completely, switch to a paid Social Media strategy.
This simple switch from the fuzzy Organic goals to concrete Paid goals will give the one thing your Social Media Marketing strategy was missing: Purpose.
It is now easy to define why the heck are you spending money on Social Media? To drive short and medium-term brand and performance outcomes.
Set aside the useless metrics like Impressions and 3-second Video Views. Set aside hard to judge and equally useless Like and Follow counts. Measure the hard stuff that you can show a direct line to company profit.
Define a purpose for the money you are spending.
For the clients I’ve worked with across the world, expressed behavior of the users suggests that the largest cluster of intent is See. There is a little bit of Think and a little bit of Care. (This is why Social marketing strategies that target Do intent yield extremely poor results.)
If the purpose is to execute See and Care intent marketing strategies (in the old world sometimes incompletely referred to as brand marketing), you can use the following amongst my favorite metrics to deliver accountability:
1. Unaided Brand Recall 2. Likelihood to Recommend 3. Lift in Purchase Intent 4. Shift in Brand Perception (negative to neutral, neutral to positive, positive to proactive evangelism) 5. Lifetime Value
Humans have measured these using primary and secondary research methods for 3,500 years. Quite easy to do the same for your newly focused paid Social advertising efforts.
If on the other hand the purpose of your paid Social advertising is to target Think and/or Do intent, you should measure the impact using the following across your digital – and pan-digital presence:
1. Recency & Frequency 2. Loyalty 3. Task Completion Rate 4. Assisted Conversions 5. Macro-Outcomes Rate 6. Economic Value
We have measured these for a long time on the web. You can use your quantitative tools to measure most of these (Google Analytics, Adobe, True Social Metrics). And. You can measure these for your ecommerce, non-ecommerce, B2B, B2C, pure content, non-profit, or whatever else kind of delicious business you are running.
Now, you’ll hold your agency and employees accountable for delivering business profitability for your Social efforts just as you do for any other advertising effort – Search or TV or Email.
Just as you would do in all those other cases, do more paid Social advertising if the metrics show a business impact and improve/eliminate your paid Social efforts if they don’t.
It will mean a different Social content strategy, different targeting strategy (leveraging rich Social signals), and a different landing page/app strategy. Proper end-to-end user and business optimization. Nirvana, delivered by that magical word… Purpose.
The path to your salary and job promotion is also now crystal-clear. Right?
Is the Idea of Marketing Utopia Permanently Dead?
I’ve seen the near-future, and I believe we’ll get to Utopia Marketing.
The fact that companies don’t know how to be human, how to take even 20% of their people plus budget and invest optimally in understanding humans and deliver something of value to those humans is deeply heartbreaking.
Yes, I can blame the short-term quarterly focus of the CMOs and the SELL, SELL, SELL MORE incentives they create for you to earn your bonus. But still, how heartbreaking is it that not even 1% of us could convince our CMOs to allow us to do what Social was actually good at? How sad is it that we have such little influence? I blame us.
Still. I am optimistic that Marketing Utopia, as I’ve imagined it at the top of this post, is not dead. I think the solution will be to get rid of the humans from the process!
What? Human marketing by getting rid of humans?
Yes. Hear me out.
I think AI/Machine Learning will solve this problem.
Today, humans and their limited ability to process data, and the finite incentives in place, are the reason we burned Utopia to the ground. We simply can’t process billions of signals across tens of millions of touch points across millions of people, and figure out the best message at every moment and its short, medium, and long-term business value.
Current advances in ML already give me hope that algorithms will understand intent a billion trillion times better than your current employees AND these algorithms will have the inherent capabilities to process billions of data points to truly understand complex patterns of user behavior and..