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Marketing organization haven’t changed much in the last 40 years or so. But that’s about to change.

We live in a world of exponential change. As we have moved from the industrial age, to the information age, to the mobile age, we now are entering the age of artificial intelligence and automation.

Advancements in computing is making computers to reach human brain capacity by 2025. By 2050 the projected power of computing will reach the capacity of all humans on earth. Already today it is projected that soon, algorithms, automation and robots, will impact 1 billion human jobs in 2020.

It is safe to say that marketing organization are affected too.

But what will be the impact, and how can we prepare? That’s exactly the subjects of this blog post. In this blog post, I want to try to answer the following questions that relate to modern digital marketing organizations:

  • What mega-trends are forcing modern digital marketing organizations to change?
  • What will become the new reality for CMO’s?
  • What is the impact of this on the tasks of people within a modern digital marketing organization?
  • What should you do as a marketer to embrace this change?

Mega-trends influencing your marketing job

If we want to understand how to adapt to change, we first need to understand the environment where our future marketing organization will need to thrive.

And a lot is happening around us:

Ever and ever more informed customers

Already today our customers are very informed, nothing new here. But the continued introduction of new technologies like visual search, VR and AR are making customers smarter. Think of recent Android versions from Google that now have visuals object recognition on board. Users will point their smart device to your product, and get “augmented”.

Large digital players take more control of customer journey

Voice interfaces powered by, first niche artificial intelligence, and later by wider general artificial intelligence and smart home devices. Think of Amazon Echo entering the living room, informing customers through this new channel, and allowing the order process to happen instantly. Amazon in this case controls the entire customer journey.

Faster (digital) product cycles, newbie for ever and ever

Physical and digital products are going through faster cycles. In the future this will be a series of endless upgrades, where products are morphing continuously, and users will be in a continuous newbie mode. Professional, but also consumers, won’t have time to master anything before it is displaced. Endless newbie is the new default for everyone, not matter your age or experience. Think of a Tesla cars, that gets updated over-the-air to have new features on board.

Marketing technology innovation cycles shorter and shorter

As I demonstrated in an earlier post, the speed in which marketing organization need to introduce new innovations is increasing. As we have just mastered the new basics, suddenly we need to deal with new innovations like chatbots and augmented reality within our marketing strategy. Think of chatbots that didn’t exist 2 years ago.

Technology explosion, everything becomes smart

Everything is about technology. Increasingly our products and our services are connected, smart and interfacing to an open ecosystem and the large digital platforms. Think of smart cars, smart cities, smart flower pots, smart everything…. yes I’m talking the Internet-Of-Things here.

New consumption patterns

Consumers, especially the younger generation, are moving away from buying and owning products. They massively opt-in to renting or lending products, wanting to experience products rather than own them. Think of AirBnB.


In the industrial age, companies did their utmost to save themselves time by increasing their efficiency and productivity. That is not enough today. Now organizations need to save their customers and citizens time. They need to do their utmost to interact in real-time. Real time is human time. Think of ever reducing delivery times, or 3D printing.

Self learning machines & automation

It is hard to believe, but before the end of this century, 70 percent of today’s occupations will likewise be replaced by automation— including the job you hold. But people will embrace this change. Those who best optimized the process of working with machines will create the best opportunities in the future. This is not a race against the machines. If we race against them, we lose. This is a race with the machines.

Brands evolve to open platforms

Smart products allow to build more digital connectivity with customers. These smart products add to the experiences brought by open eco-systems. Think of Nike who has opened their Nike+ platform to an eco-system of developers & hardware developers.

The New Reality for CMO’s

Within the context of these mega-trends, being a CMO is not without its challenges….

Increased responsibilities

In the last decade, CMO’s and marketing managers have seen a drastically increased field of responsibility.

CMO’s are responsible for the classic marketing mix. You know, the 4C’s or 4P’s. That has changed. Today they must take charge of much more: digital transformation, customer experience, marketing technology and social business. To name a few.

And all of this with budgets under pressure, and still struggling to proof ROI to the C-level.

Ever faster change

Do you also have the feeling that marketing has changed more in the past 2 years than the past 50 years? A couple of blog posts ago I wrote how the speed of change in the field of marketing is increasing.

As an effect, most marketers today feel overwhelmed with the speed of change happening in the job we are passionate about.

Everything seems to be new, always. It’s never easy, it’s always complicated. And by the time we started understanding something, it’s already outdated as a tactic.

Organizational struggles

As CMO’s try to cope with their increased responsibilities, they are nothing without the right organization. The problem is that great talent is really hard to find.

Numerous times I have had conversations with CMO’s complaining about the knowledge gap within their organization.

Next to the knowledge gap, and outdated decision making structure (governance) is making change a slow and cumbersome process.

And some change seems impossible: CMO’s are responsible for customer experience, but have no span of control over the organization to make the necessary changes.

How likely is AI and automation going to impact marketing jobs?

A couple of years ago, the University of Oxford published an influential paper on the future of employment, trying to answer the question :

How susceptible are jobs to computerization?

They’ve gone through the effort of estimating the chance of computerization for 702 (!) detailed occupations.

The model predicts, not surprisingly, that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations, are at risk.

But the questions that I want to try to answers are:

How is automation and AI going to impact the job of marketers?

And when is this going to happen?

How should marketers embrace the change?

Within the long list of occupations, the paper learns us that some marketing occupations will be affected, while others are not going to be impacted for the foreseeable future. The chart even seems to show that a lot of marketing occupations are in the ‘green zone’.

But… nothing less is further from the truth. Also these green occupations are going to be affected by digitization, automation and AI….

Software will eat the bottom of the marketing ladder, so get ready to climb.

Detailed impact of AI on Marketing Jobs

Let’s have a look at the job of “marketing managers”. That’s a very generic title which covers a lot.

Marketing managers deal with strategy, developing marketing campaigns, marketing communication and event marketing, to name a few things.

Within this wide range of marketing manager tasks, let’s have a look at how automation and AI will have an impact in the foreseeable future. 

How is is automation and artificial intelligence impacting these occupations of marketing profiles:

  • Market research:  Lucy by Equal3, in the back powered by IBM Watson is capable of going through massive amounts of internal and external content and data. The output is details on customer segmentation, persona insight, ideal media mix and even message suggestions. Today Lucy is still reserved for the Fortune 1000 and requires a lot of training of the AI engine to get it working, but the technology advances quickly.
  • Creating customer journey’s: by being able to continually process huge amounts of customer data, Deep Learning systems can create way more granular, more accurate personas, allowing real-time adjustments to each customer’s journey. Every interaction and new set of options can be customized to the actual individual’s behaviors, context and timing, heightening the quality of their brand experience.
  • Content creation: news media such as the LA Times, Forbes and the Associated Press have already been using AI tools to produce fact-based articles, summaries and reports on a basic level. However, companies like like Articoolo and Quill have developed AI platforms for writing content on a more advanced level. As Quill’s website puts it, organizations are increasingly using “advanced natural language generation (Advanced NLG) to transform their data into narratives.” Content writers may dread this development, but the upside is that whatever a machine writes can’t be any worse than most of the crappy content already glutting the web. You can’t pin that on AI. Other companies into robot-writing are Wordsmith and Narrative Science.
  • Tagging content for personalization: Alfred from Boomtrain is capable of analyzing massive amounts of content, and then tag the content accordingly. This content can then be used in newsletters, dynamic websites, and marketing automation environments. Another example is IBM Watson content hub, in which content assets like photo’s and images are automatically tagged with relevant meta-data.
  • Account based marketing strategy building: there are many shortcomings with present-day lead generation and marketing automation models that prevent ABM actualization, starting with the problem of identifying quality leads. Yet the B2B prospecting adage that 95% of leads are misses needn’t hold true anymore, thanks to AI. A Deep Learning platform (like the products developed by MarianaIQ) can analyze thousands of inputs about demography, psychography, social media behaviors and a raft of other data to create hyper-accurate personas, constantly updated in real time. That enables marketers to find and engage only the best prospects within the accounts they want to target, achieving 1:1 personalization with each of them. Since AI cost-effectively automates much of the lead generation and engagement process, tomorrow’s ABM programs are implemented at scale, across all of a marketer’s accounts, by more and more companies. (source: MarianaIQ white paper)
  • Persona building: Can computers understand an individual human’s personality (and then, presumably, use that understanding to better target marketing messages)? It turns out that’s no longer even a question: if you haven’t yet played with CrystalKnows, be prepared for some weirdly accurate insights into yourself and those you know well, based on public Internet information. And, yes, Crystal advises you how to interact with others based on those insights, going so far as to suggest changes to your emails to better fit the style of the recipient. If there’s a gap between this and letting a computer just manage the whole relationship without any human involvement, it’s almost too small to worry about. This is where Mariana comes in. The whiz-bang part of its pitch is using artificial intelligence (“deep learning” as in the Mariana Trench – get it?) to build personas by analyzing a sample of your existing customers. Users see attributes for each persona such as interests, titles, functions, tenure, and average deal size. Pretty cool, I must say. (source: customerexperiencematrix)
  • Building marketing automation campaigns: up until now, the complexity of such campaigns was constrained by our limitations as humans. We could only keep track of so many rules, for so many segments, at so many trigger points before it became an unmanageable tangled mess. But AI-powered marketing automation will have no such constraints. Machines will calculate thousands of microsegments and microtriggers, dynamically adjusting their own internal “rules” for optimizing engagement. Check out the AI-powered marketing optimization product Amplero, which boasts continuous testing of 1,000’s of marketing permutations through multi-armed bandit experiments. (source: Chiefmartec)
  • Writing short copy for email, Adwords, or Facebook: AI is able to understand huge amounts of data faster than humans. By testing and proposing the best email subject lines, Facebook Ad headlines, and photos the AI will help marketers to achieve faster and more accurate results. AI computers will test different combinations of words, phrases and images to check which one works best to meet your goals. The AI is able to analyze millions of headlines and photos on the whole internet. It can check and analyze the click-through rates of the Facebook ads of your competitors. The result will be more effective and moneymaking advertising than today. (source: Marius Schober on Medium)

Main body backgrounds, mainimages, overlaytext, andsoon — are dynamically assembled when they are served, according to the particular needs of the impression.

  • Programmatic advertising with AI: using AI marketers can build campaigns that become smarter over time. The output is that now marketers can predict what combination of creative and audience segmentation will perform best. Using what is called “Dynamic Creative Optimization” or DCO, hyper personalization at scale can  generate e.a. 80 quintillion creative ads on a weekly basis. Main body backgrounds, main images, overlay text and other elements are dynamically assembled when they are served, according to the particular needs of the impression. To get an idea about that number: that’s 80000000000000000000 unique ads or 80000000000 billion ads. Companies that are innovating in this space are Adacao, Admotion, Adobe, Appnexus, Skylads or IntelliAds, to name a few.
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What is the future of marketing? Not far away, but only 5 years from now. Not the future according to futurists and dreamers, but realistic: what can we expect with great likelihood?

And what is the impact on marketing organizations, the job of marketers and the skills we need within 5 years?

I have been researching this subject for a while now, and it’s impressive to see how marketing will change in just 5 years. Everyone in marketing should prepare and “buckle-up” as things are going to go fast !

If you are short in time, scroll down and quickly access the Slideshare on the Future of Marketing, at the bottom of this post….

Exponential technological change ahead

Exponential change is something very strange. You won’t notice anything for a while, and then suddenly everything happens at the same time. That’s what’s called exponential change, and 2017 seems to be the pivotal moment where everything is getting into an accelerated pace.

Think of a couple of years ago, where self-driving cars where just a dream. Today they are reality. The same goes with chat-bots, augmented reality or artificial intelligence.

Virtuality VR arcade pods of the 80’s (Ben Delaney)

I still remember myself as a student experiencing virtual reality back in 1996, through virtual reality arcade machines.

But the history of VR is much longer, going back to stereoscopic photo’s and viewers in 1838, early flight simulators in 1929, and the first VR head mounted display in 1960.

So VR has a long history. But then, suddenly, technology catches up and things get into an accelerated pace.

Technology that seemed “sleeping” as technology, such as artificial intelligence, and chat bots, now suddenly are coming to the market in an accelerated pace. Similarly, suddenly, VR headsets are available everywhere, at affordable prices.

The rapid pace of these innovations and technological advances also had a major impact on marketing strategies. Think about these marketing domains have evolved the last decade:

  • customer touch points (moving from letters, to phone, email, websites, social media, chat, voice recognition, beacons, artificial intelligence, …)
  • customer behavior (purchase, recency/frequency/monetary, loyalty, online behavior, omni-channel, personalized, predictive, …)
  • advertising (catalog, personalization, automatic, …)
  • logistic innovation (store, delivery, 1 hour delivery, drones, 3D printing,…)

The biggest challenge for most companies is  how to introduce these innovations in a fast way, so technology doesn’t catch up by the time you finish your implementation.

9 mega-trends and 2017 as a turning point in history

Mankind will change more in the next 20 years than in the last 300 years. A statement by futurist Gerd Leonhard that makes you think about the impact of what is to come.

But what exactly is to come? Without going too futuristic, there are some very clear trends that will very quickly have a big impact on the future of marketing and on humanity in general.

1. Computing power goes exponential

D-Wave, a computer developed by the Canadian company D-Wave Systems, uses quantum computing power. By 2025, this kind of computer will have the computing power of an entire human brain. That might not sound like a lot, but it actually is a big thing. By 2050, these types of computers will have the computing power of all people on earth.

Today, these types of computers are not so practical at all: D-Wave consumes the electricity of a whole city the size of Brussels in Belgium. For the time being we won’t be able to have this kind of computing power into our pocket ;-)

2. Algorithms affect 1 billion jobs by 2020

Source: Above and Below the API, Forbes, 2015

In an article by Peter Reinhard the progress of automation and the impact on future jobs is projected. He divides the job market into two types of jobs: “Above the API” jobs and “Below the API” jobs.

In principle, most jobs run by a programming interface (API) will be replaced by an automated process.

As examples of APIs, Peter Reinhard names Uber and 99designs as companies that allow people to perform tasks, while ultimately can also be done by robots. Think about autonomous vehicles, software-generated designs, etc.

While the jobs under the API will become smaller, this will secure the jobs above the API. And who are the people above the APIs? Software engineers of course.

Either way, software engineering / computer programming is the absolute ‘over the API’ job of the future.

3. Everything becomes SMART

Everything becomes SMART. Smart seems to be the new green. Just about everything is smart today.

Take a word, put the “smart” in front of it, and you have what you see today: smart cars, smart refrigerators, smart printers, smart cities and even smart flower pots.

This is about the Internet of Things (IOT) here: smart and cheap sensors make that everything can be connected to the Internet.

This connectivity adds value and smart brands are already busy in the to build an open platform and eco-system around their smart products.

4. From belongings to Experiences and Trust

We often don’t notice it,  but books, movies, music, mobility, content on the internet and much more things are more and more abundantly available and almost free or inexpensive. Distribution of these goods have gone down dramatically, or have become entirely free. That has created totally new business models like the ones of Uber and AirBNB.

And because everything has become so abundant, you get the effect that possessing tangible things is no longer what people want.

Personally I notice this trend with younger people. They are looking for things that are unique, and often they turn to experiences as the new way of owning things. Just look at the rise of the various types of mobility services offered by the major car manufacturers. They do not sell cars anymore, but they sell mobility as an experience.

Another element that cannot be brought in abundance is: trust. Trust must be earned over time. As we prefer to do business with brands we trust, we are also willing to pay a premium. Since long time in marketing we call that branding. Brands may request higher prices for similar products and services than companies without brand because we trust them for what they promise.

Trust is not tangible and has an even greater value in a world of abundance.

5. Self-learning machines have become better than people

In only 5 years, from 2012 to 2017, machines have succeeded in getting extremely good in recognizing speech and images. Google Speech Recognition is already today able to reach an accuracy of 96.1% even in noisy environments.

Speech recognition also evolves to voice recognition: computers know who speaks and can respond differently based on the recognized voice.

6. Ask anything to “smart agents”

We can ask questions to smart speakers like Google Home and Amazon Echo. What will the weather be like today in Belgium? What does my calendar look like? What is the traffic this morning to work?

Soon we will not even have to ask for things. Artificial intelligence will know what we want, in advance.

The first examples of this are found in Google Now and also a bit on the iPhone with Siri. Amazon is also experimenting extensively: they are trying to predict and send you products before you indicate that you want to buy them.

7. Visual Search – Your smartphone camera will be your new Google

Look through your smartphone to a billboard and you can instantly start a chat conversation with a store and proceed to a purchase.

Blippar, VIV.AI and Google Lens are some of the first examples of this “visual search” future.

8. Live 360° video broadcast

Live 360 ° video broadcasting on Twitter, Google or Facebook is possible today. Today you still need special hardware on your smartphone, but give it another 5 years and the hardware might be integrated into your smartphone or smart glasses.

9. Precise location detection

Based on accurate tracking and spatial computing, smartphones can provide an accurate picture of their environment. This allows to add images through augmented reality. Google has been working with Google Tango for a number of years to optimize this and also brings more and more devices on the market that have deep and space views. Apple with their Apple ARKit are going to amaze us from september 2017 onward.

With this exact location, you can for example exactly pinpoint, guide and find the location of something in a store.

Retailers of stores are increasingly forced to bring digital, virtual and physical together. They need to become hybrid retailers: virtual store, e-commerce webshop and interactive store. And all of that connected to each other.

What will the future of marketing look like in 2021?

With all these mega-trends in mind, how will marketing as a discipline look in just a few years?

Everything will be about technology

As has been evident for a number of years, marketing is increasingly becoming a technical discipline. IBM with IBM Watson brings the domain of artificial intelligence closer to marketers under the form of an API. Feel free to think in terms of “apps” that we can start using in our marketing environment.

It’s the “appification” of Artificial Intelligence.

Also Google is working on an open source platform (Tensorflow) that brings machine learning and artificial intelligence possibilities towards an ever-growing community of developers.

From products to experiences

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Despite a huge surge in adoption of content marketing, measuring the business impact or calculating the ROI of content marketing is complicated.

“How do I calculate content marketing ROI” is one of the questions I get the most from people wanting to start with content marketing. Often, when it comes to content marketing, marketers are struggling to build their own business case internally.

With this post I want to demystify the field of content marketing ROI, and provide some practical help on how marketers can measure things that have a quantifiable impact on the results of the brand.

In this post I cover the following subjects:

  • what is important to measure?
  • how do I select the right metrics and KPI’s?
  • how can I setup a dashboard? how do you calculate ROI?

Are you ready? Here we go !

What’s your content marketing objective?

Before you do anything, you need to clearly define the goals of your content initiatives.

Depending on the size of your company, your content marketing initiative, the structure of your company, etc. you will most probably have multiple objectives.

I have found that the best way to structure your objectives is to split your content marketing initiatives into what I call content programs. Usually the business objectives for these programs boil down to any of these objectives:

  • brand awareness,
  • lead generation,
  • customer acquisition
  • thought leadership,
  • engagement,
  • customer retention / loyalty,
  • website traffic
  • lead management or lead nurturing
  • sales
What is important to measure?

Once you’ve decided your business goals, the next question is how you’ll measure success.

Where metrics go wrong

Measuring marketing success can be difficult because marketers have literally hundreds of marketing metrics to choose from, and almost of them measure something of value. The problem is that most of them relate very little to the metrics that concern a CFO, CEO or business manager:

  • Certain success metrics look great on paper, but still offer little added value in making decisions. These metrics are sometimes called “Vanity Metrics” (link to blog post in Dutch on Vanity Metrics). Vanity metrics give marketers or entrepreneurs a false feel of success. Or to put it the words of Eric Ries “Vanity Metrics are dangerous.
  • Another thing often found when marketers report results is, they are  reporting on quantity and not quality. A typical example is that the number of leads are reported, but we have no clue on wether these leads are any good.
  • One of the worst metrics you can report on is cost metrics, because they frame marketing as a cost center. You might be able to reduce marketing cost, but that doesn’t mean anything to leadership.
  • And a last pitfall metric is where marketers report on activity, and not on results. Marketing departments are always extremely busy, and it feels good to report about 20 emails that have been sent, and 5 new marketing collateral materials that have been created. But when only reporting on activity, business sees marketing as a cost center rather than a profit center.

What is important to measure?

If activity, cost, and quantity aren’t the right metrics to use, what are? Anything that speaks to the CFO’s areas of primary concern:

  • revenue,
  • margin,
  • profit,
  • cash flow,
  • ROI,
  • shareholder value

In other words, your company’s ability to generate more profits and faster growth than your competitors.

In the end CEO’s prefer to see clear results. Hard business results. They want to see the ROI of Content Marketing.

In a previous blog post article I show you those hard business results using 22 examples of companies that used content marketing, and which had clear business results.

What is important to measure in Content Marketing?

To get a better understanding of the ROI of our content marketing programs, we’ll need to surface a number of metrics. Depending on the objectives of your content marketing initiative you will need to use other metrics.

For example, if your content marketing initiative has the objective of driving traffic to your e-commerce website, in that case you must choose the metrics that track down everything that contributes to that goals. If your objective is thought leadership, you will need other metrics. I think you get the idea…

Understand the difference between Performance & Operational metrics

If you want to understand the effect of your actions, you will also need to track how much effort you are putting into it, to reach the result you are seeing. That’s why I often distinguish between performance metrics and operational metrics:

  • Performance metrics:  metrics on consumption, retention, sharing, engagement, leads or sales.
  • Operational metrics: metrics track production (number of assets, velocity, speed of steps in the process), cost & ROI .

Here’s how Marketo aligns high-level goals to related metrics.

Measuring operational performance

For example, in larger operations you want to understand how much time people spend on writing, editing, researching, etc.

By setting an arbitrary cost on the time spent to create each type of content asset, you can get a better understanding of the total efficiency of your production resources. Initially you can simply use a time tracking tool like Harvest or Teamwork.

Example of an excel sheet tracking down operational team performance per content asset type.

Alternatively you might want to check out specific content marketing tooling like Kapost, Compendium or Percolate. There are many, many more tools available, so it’s important evaluate these tools in a formal tool selection process.

A selection of content marketing tools. (Image Source: Altimeter)

Measuring per channel

In any content marketing initiative you will use communication channels to distribute and promote your content.

When building your dashboard, you want to use a couple of metrics that directly relate to the performance of your channels.

Usually these metrics are interesting to people dealing with those communication channels, but they are likely less interesting to managers or C-level.

Examples of possible metrics, sorted per channel and objective.

Picking the right KPI’s

Along with metrics that give insight into the performance of your content or communication channels, you want to select a number of KPI’s. By choosing a number of KPI’s you can monitor the performance of your content marketing initiative through time.

When picking KPI’s, here are some tips to take into account:

  1. Choose no more than five key metrics. It’s hard to put organizational focus on more than that, so choose wisely.
  2. Measure success versus goals for those metrics for every campaign, every channel, every sales rep/region, every product, etc.
  3. Show trends for those metrics over time – that way you can immediately see where you are improving and where you are not.
  4. Put on a dashboard for everyone to see so there is always a succinct view of what marketing is trying to achieve, and where you stand.
  5. Have employee recognition systems in place. Make sure top contributors get recognition – give them badges they can put on the desks or cube.
  6. Rinse and repeat. The best performing companies track results weekly, monthly, and quarterly – so they can improve.
Create your content marketing dashboard

Once you have selected all your metrics and KPI’s, the next step is to bring them together into a dashboard. In case you have multiple content marketing programs, the best thing to do is to track them down in separate dashboards. To get an easy overview of everything you are doing, you might want to bring an aggregate of the most important metrics of all these programs togethers in a single view.

For each of these programs you also want to create a governance system that governs the performance of each of these programs.

In case you are unfamiliar with such governance system, let me quickly fill you in: governance is basically reporting, and deciding on your plans, the execution status, and the possible optimizations of your content marketing initiatives. Often, in these governance reports and during the governance meetings you also report on organizational issues, possible solutions, next steps, and report on budget and ROI.

Measuring Content Marketing ROI

Calculating the monetary ROI can be really difficult, especially when you have intangible objectives like thought leadership or brand awareness.

But with all the ideas and insights in this blog post you should be able to select the right metrics and KPI’s that provide insight into the gain and cost of your investment into content marketing.

Calculation the ROI of your content marketing initiative can be as simple or as complex as you want it to be.

But if you are just starting with content marketing, here are some tips that come straight from my personal experience running small to large content marketing operations:

  • don’t overcomplicate your dashboard, instead spend most of your time on content quality. You really don’t need that many metrics to know if things get moving or not.
  • start with one single program, and resist the urge to launch multiple programs in the beginning.
  • wait 6 months to 9 months before you start setting up a formal governance system, but meanwhile track the necessary metrics. Your management might not have the patience to wait until content marketing ROI kicks-in after the usual 6 to 9 months.
  • In the beginning focus on communicating internally, about the little successes your are having with your content marketing initiative (ea. first workshop, first 10 pieces of content, first downloads, etc).

That’s it for this one. If you liked this post, why not subscribe to my blog?

Warm regards,

Tom De Baere

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As marketing becomes more and more advanced, personalized marketing is critical.

Personalization in marketing is real, needed and possible. It re-enforces your brand, and can mean the difference between being competitive or disappearing into oblivion.

But how do you that ?

In this blog post I want to discuss a methodology and a personalization model that helps you to:

  • segment your audience, beyond demographics and geographic
  • link your business objectives with 1-1 personalization campaigns
  • understand how personalization actually works

Let’s get started!

Why Data Needs Strategy

The big overarching business benefit of personalized marketing experiences is the following:

People tend to respond better and be of greater value to your business when they feel their needs and interests are being specifically addressed in personalized communication.

On a deeper level, the business benefits of personalization are:

  • Likelihood of buying: When your marketing messages are relevant to the situation of customers and their interests, they are more likely to buy.
  • Increasing customer lifetime value: Focusing on increasing the lifetime value of each customer as much as possible by making your marketing contextual is a key driver of long-term profitability.
  • Better insight into customer base: Examining the performance of certain customer segments provides important insight into the health of your customer base, enables you to spot trends and patterns in what’s working and what isn’t, and can help inform your strategy going forwards.

But collecting data for the sake of collecting is stupid without having a strategy to monetize that data. Good examples of strategies that can be developed are the following:

  • Discover the right new customers: using behavior and customer look-alike analytics your can inform your targeting strategy.
  • Nurturing of new and existing customers: insight into online or offline behavior can drive nurture campaigns to drive customers into making a first purchase
  • Cross-sell, upsell and affinity models:  customers build a history of interactions through service requests, product use, and other communications. You can use this insight to fuel product recommendation to customers, or products recommendations for account managers if that makes sense for your business. Lead analytics and lead scoring can prioritize incoming leads, help you acquire high quality leads and grow existing customers.
  • Churn models: predict customer churn, and counter churn with churn campaigns Loyalty models: using customer data, specific strategies can be developed towards most profitable customers, or strategies to retain customers.
New segmentation criteria needed

The absolute first step in personalization is having a segmentation model . It sounds boring, and it probably is. But it is critical to have your segmentation model mapped out.

As marketers, we sit on piles of CRM data, transactional data, web-analytics and email addresses. But when we need to communicate with customers, we still take the widest possible segment because we have do not have the time, or the tools, or the insight to personalize our messages.

That’s the typical situation. Sorry to put you on the spot, but I think in the majority of marketing organizations there is little room for personalization beyond addressing someone with his/her first name. Hey, I’ve been there myself. When you go into your CRM system, it turns out your segmentation model is not entirely what you need, and you widen your segment because the list seems too small.

Do you recognize the situation? You want to personalize, but the segmentation criteria you use in your systems are not adapted. Let’s fix that by adding segmentation criteria to the model that allow us to personalize the marketing experiences of our customers.

If you would review the segmentation criteria often found in most organizations to most likely would find something like this:

  • demographic segmentation: this is the most basic segmentation. This can be gender, age, income, and more.
  • geographic segmentation: this is all about where the customers is located.

The segmentation that is key to making your marketing more personalized and customers centric is what I call “ customer centric segmentation criteria ”:

  • psychographic criteria: this is all about who the customer really is.
  • behavioral criteria: this is all about what the customer does when he is seeking the value you bring with your products or services.
Psychographic and Behavioral Segmentation Criteria

Cluster your segmentation criteria into product, category, marketing application, … and work your way towards more customer centric segmentation criteria you have or should have.

Most segmentation models contain elements on market segmentation, application and product segmentation. That’s most commonly found. Most of us also have access to CRM segmentation which gives us some contact and account segmentation, but that’s it. And transactional systems like ERP or invoicing systems give us monetary data.

The problem is that we don’t have the interests of customers in the model, nor do we have the behavior in the model…  In essence,  most segmentation models are built around brands , and not around customers.

That’s not really “customer centric”, is it? So let’s add a couple of customer centric segmentation criteria to make personalized marketing experiences possible…

But which segmentation criteria do we need to add? To answer that question, the easiest thing to do is to map out your current segmentation model.

  1. Start by making an inventory of the segmentation criteria you have today
  2. Cluster these segmentation criteria into product, category, marketing application, … and work your way towards more customer centric segmentation criteria you have or should have.
  3. Map these clusters along the customer journey.

Once you have done this exercise, it becomes clear what you are missing in your systems.  You can now start implementing or updating the segmentation criteria in your different marketing systems:

  • Your CRM system
  • Your website content tagging
  • Your marketing automation system
  • Your analytics software
  • Your e-commerce platform …
Linking Strategy with Data

Data is nothing without strategy to monetize the data. You might have the segmentation model ready. And you might have the data. But without a strategy to monetize this all, you won’t get zip.

Let’s take the example of a marketing organization in the retail industry.

  • The business objective: the marketing managers wants to re-active lapsing customers. Lapsing customers are customers that have bought in the past, but for some reason they are buying less today.
  • Micro-segmentation: to reactivate these lapsing customers, we want to address them with a contextual relevant message, because that is what is needed to win-back these lapsing customers. Using transactional data, lifestyle or interest data, and behavioral insight we build a micro-segment of these lapsing customers.
  • Personalized communication: a demand generation program that runs automatically to this micro-segment will run on weekends, offering a 30% discount in the favorite category of our segment.

This is just a small example how strategy can fuel a marketing program, through data and micro-segmentation.

Usage of the segmentation model

Using the example of our marketing manager in the retail industry, we can further dive into the details of how the segmentation model can is used in the different stages of customer acquisition or retention:

  1. Traffic building: first drive traffic through different channels and tactics
  2. Engagement capturing: capture and segment the engagement behavior
  3. Demand generation: run personalized marketing and sales campaigns
  4. Experience delivery: and in the case of existing customers, run programs that bring personalized experiences

The “SUSHI” example

Each of these different stages contain different tactics. In the case of traffic building you have lot’s of possibilities, same thing goes for creating and capturing engagement. And the same goes for the other stages.

To explain what this means, let’s dive into some details by pouring the model into a real-life “sushi” example: we want to bring personalized marketing experiences to prospects that are interested in everything related to “sushi”. Our objective in this example is selling equipment like rice cookers, sushi knives, etc…

  1. prospects are targeted with content marketing topics about sushi, using Facebook ads, emails and pages on a website
  2. engagement is then captured, segmented and interpreted by ea. a marketing automation system.
  3. based on this engagement, personalized campaigns or “demand generation programs” are executed on one-to-one basis.

That’s it for this one. A very practical post this time, on how you can introduce more personalized marketing. Let me know what you think, and feel free to comment.

Thank you for reading. If you like this post, why not subscribe to this blog?

Warm regards,

Tom De Baere

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We are now at the dawn of the Fourth Digital Transformation. The disruption brought by digital is impacting existing business models like never before. And it is not likely to stabilize any time soon. The next wave of digital transformation is just around the corner…

In this blog post I want to cover the following subjects:

  • the fading of classic interfaces and the rise of new customer touchpoints
  • the new-middle-man platforms, introducing new middle-man functions
  • how to build a platform strategy that embraces this change.
Drivers of the Fourth Digital Transformation

To understand the fourth digital transformation, we first need to understand what is happening today. And a lot is happening today!

  • Chat-bots, voice control, and smart digital agents, are bringing new ways of communicating with brands.
  • Virtual reality, enhanced reality and mixed reality are entering our lives, impacting the way we consume information, the way we work, and the way we buy products.
  • The fin-tech world is introducing convenience in payment methods. Examples are Apple Mobile Wallet or new fin-tech entrants like Stripe, 21INC, Square, or even Kickstarter. They are disrupting the way we think about money and banking in general.
  • Packet delivery by drones, location based logistics from Parcify, and 3D printing are changing the way we think about logistics and manufacturing.
  • Personalization and customization is entering the world of consumers, making them accustomed to hyper-personalized communication, products and services.
  • Subscription based business models from Walmart, Stitchfix, Birchbox, Ordergroove and others are bringing products as a service.
  • And the sharing and borrowing economy, in which we want to own little, consume more, and experience more, are brought by Uber, AirBNB, and all its copies.

This is what we know and see today.

In all this chaos, with new start-ups entering the market literally every day, what is really happening?

As we have moved from mainframes, to graphical interfaces, to smartphones today, we are now moving into vision and sensing.

Interfaces are fading, and soon it becomes all about the experience.  

Welcome to the 4th digital transformation…

Fading interfaces

25 years ago my dad bought our first family computer, an IBM XT. It was a big machine with a heavy clunky computer screen on top of the computer, hooked up to a black-and-white mechanical matrix printer with a big fat cable. Do you still remember the sound? trrrrrrt…trrrrt…trrrrt.

Flash-forward 25 years and I’m talking to my smart watch. I tell my Amazon Echo to play music from Spotify. My Nest is quietly doing its work in the background, until I tell Alexa to slightly turn up the heater.

On the other hand, I am still typing this blog post on my laptop. And I still often use my smart-phone when I am on the road.

But I believe the way we work and interact with systems around us will drastically change….

From reactive to active systems

Today we still need to command systems, before they do something for us. “Siri, what’s on my agenda” is a working gimmick on my smartphone, although it has little added value to me. So I don’t use it a lot.

But what if Siri starts doing things automatically, like booking your favorite restaurant, communicate with my contacts to resolve a conflicting agenda appointing, and recommending holiday destinations. The device recognizes a pattern, and then acts upon it.

We can already see it happening on our smartphone with Waze, the popular GPS-navigation app from Google. Waze is trying to predict where you are going next. LinkedIn is already making suggestions on how to prepare for your next meeting. It can do that because it has access to your calendar and who you are meeting. Facebook is warning you it will be raining soon at your location, and that you better get your umbrella ready. And if Tesla cars can’t find anything in your agenda, it will automatically plot the route to your home and start driving you home.

More and more systems, algorithms and software will make autonomous decisions for us. Soon these systems will be buying stuff for us, because they predict we need them.

How will autonomous decision making by artificial intelligent platforms impact your marketing?

From Carrying to Experiencing Technology 

Google Home, Amazon Dash, Dot and Echo, but also Microsoft Hololens. All examples of large players building new types of interfaces. These voice controlled, gesture and vision controlled smart assistants, also sometimes called smart agents, make use of artificial intelligence platforms.

You might have not seen them in real life, they are entering our personal and professional life in the coming 5 years.

It’s going to be big. The examples of Amazon, Google and Microsoft are only the beginning. It’s the rumble before the storm, so to speak.

Apple and Google have been been acquiring technology companies the last few years.

  • Google bought Eyefluence in october 2016. Eyefluence has developed a very advanced eye-tracking interface. Eye-tracking is a very important technology to future virtual reality headsets.
  • And investors like Alibaba, Google and others have been poring billions (!) into a secret company called Magic Leap , of which a first prototype leaked to the public recently.
  • Back in 2013 Apple bought Primesense, the company that developed the original Xbox Kinect. In 2015 Apple also bought Metaio , a well-known company powering many of the popular augmented reality (AR) applications used today (like the IKEA virtual catalog, and Ferarri’s AR showroom app), and in 2016 they bought Flyby Media.

Robert Scoble, American blogger, technical evangelist, and author , thinks that Apple will be  releasing an AR headset in 2017.

A teaser from Magic Leap, the secret company backed by billions of dollars from Alibaba and Google.

Location Aware Devices – Spatial computing

And, surprise surprise, Google and Apple have been working together, to develop the image-recognition capabilities found in Google’s Project Tango.

Project Tango is Google’s Augmented Reality Computing Platform.

Combined with the right hardware, it brings indoor navigation, 3D mapping, physical space measurement, environmental recognition, augmented reality and more, into a virtual world.

As an example, Aisle411 demonstrates what’s possible today in terms of indoor navigation for retail purposes. Other examples include Lowe and iStaging, which demonstrated what it can do for them for interior design.

Project Tango is the first platform that shows the power of spatial computing. Spatial computing is the concept that computers can learn where certain objects are located in the physical world, and overlay virtual objects.

In the beginning the interfaces will still require some form of command and control, and most probably will be somewhat clunky, as my first XT computer back in the 80’s.

But in only a couple of years from now, these devices and the smart digital assistants behind them, will become more and more invisible and less intrusive, acting as a natural and fluid part of our daily and professional lives.

How will you react to these fading interfaces? How will you react to a world without interfaces where it is all about the experience?

Software “eating” marketing and sales

Companies today are implementing new ways to bring added value to customers in new ways. They introduce marketing innovations such as content marketing, personalized and predictive product recommendations, and near-real-time customer service.

By 2020, most customers will manage 85% of their relationship with a business without talking to a human being, according to Gartner.

But although the majority of the conversation will be digital, when they do want to talk to a business, they want it faster and faster.

They expect near-real time communication. This is driving early adopters to experiment with new types of customer touchpoint such as chat-bots, video-calls, but also instant logistics in ever decreasing delivery times using drones and 3D printing.

Marc Andreessen penned his famous “Why Software Is Eating the Worldessay in The Wall Street Journal five years ago. Today it is, more than ever, very relevant.

This also brings us with the disruption that digital is bringing to the world of sales. Customers no longer buy from sales-people. Where classic salesmen used to have the task of informing, educating and convincing customers, the role of sales is under pressure. Today it is being replaced by software, algorithms and dominant-player-platforms from Google, Facebook, Amazon, Alibaba and Apple.

If you control the platform, you also control the supply chain.

As an example of a potential future way of buying is brought by Blippar.

Today Blippar is just a an app on smartphones, capable of recognizing objects. I’ve tried it and it works surprisingly well, although it doesn’t recognize all objects, and it still make a lot of mistakes.

But the potential of Blippar is massive: imagine you are seeing an object you like, let’s say a pair of cool sneakers that someone is wearing. Next thing you do is walking up to the person and asking ‘Can I “blipp” your shoes?”. You point your smartphone to the shoes, and you “blipp” them. By “blipping” the shoes, you buy the shoes, in the right size…

If you control the platform behind Blippar, you will also control the supply chain…

How will you react to the change in buying behavior of customers? Is your future customer a robot? Will marketers of the future need to market to robots and algorithms?

The NEW “Middle-Men” Digital Platforms

Uber and AirBnB are the stereotype examples of “digital disruption”. They’ve shaken up many industries, and many start-up’s are claiming to be the next Uber, iTunes or AirBnB of a random industry that needs disrupting.

The disruption they bring is that they cut out the so-called “middle-man” players.

In the music industry iTunes has cut out physical music shops, and in transport they Uber has cut-out intermediate taxi-companies and brought taxi drivers straight into contact with customers. Numerous examples are available, and as time moves, more and more industries are being disrupted by combining existing technologies in a smart way.

My claim is that we now are seeing a fight among the large digital platforms to claim a whole new middle-man position.  IBM, Facebook, Google, Apple and Amazon are best placed to take that position of new middle-man. They are pouring billions of euros or dollars into artificial intelligence, machine learning and new gesture-, vision- or speech-driven interfaces.

Why are they doing this? Why are they driving people to use these new smart digital agents?

By having people using these smart agents, they also control the interface that decides who will be sourcing the products you buy through the interface. They also have control of the platform that controls the lighting in your smart house, or the platform that decides that milk needs to be ordered for your smart fridge.

If you control the platform, you control the customer.

Is this all bad? Of course not. Many consumers and businesses absolutely don’t care. As long as they can enjoy the benefits of these smart agents for free, or for a low price, they are right to use these platforms.

But the impact on marketing is certainly an important one:

  • No access to end-customers:  you no longer have direct access to your end-customer, because the platforms serve as an intermediate. This means that any moment in time they can change the rules in which are using their platform to interface, advertise or use their platform in general.
  • They control the access to products and services: using these new interface, new types of App Stores, search algorithms and advertising solutions will be implemented by these platform players. If you want customers to buy your products through these new interfaces, you will have to pass through the platform. The problem is that  you do not own nor control this platform. That means that you will have to pay to play.

Again, it’s not all bad news.

I don’t believe we are into a doom scenario where these big players crush everything around them. That would be counterproductive, also for them…

How to Embrace the Fourth Digital Transformation?

The amount of change coming to marketing managers and business leaders is certainly overwhelming.

It’s a complex problem that requires strategic thinking.  Smart brands can stay ahead of the curve by embracing the change ahead. They work with the dynamics of the market, riding the waves created by the giants of the internet.

Some of the strategic questions that need answers in this context:

  • How will you market to customers in a world where customers no longer visit websites?
  • How will you sell to customers in a world where customers buy products using buying agents or algorithms?
  • And how should you work with these internet platforms that you do not control?
Building your platform strategy

There are 2 elements to building your platform strategy.

Building a platform strategy, requires understanding of your current customer journey. You will also need to start understanding how these new technologies will be impacting the customers journey. That’s the first dynamic to take into account.

The second element that will inform your strategy is the type of business you are in:

  • If you are in a niche market, it remains a sound strategy to continue to build your “owned” platforms...
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