At the spring edition of the Professional Pricing Society (yes there is such a thing) pricing thought leader Craig Zawada challenged the audience with some provocative claims. Craig has been disrupting pricing for a couple of decades now. In 2004 he was a co-author of The Price Advantage. This book introduced some of the key frameworks for pricing strategy, value mapping (see this article for more on value mapping) and the pocket price waterfall. The pocket price waterfall is the standard tool pricing experts use when looking for profit leaks.
In 2010, Craig surprised the pricing community by moving from McKinsey to the revenue management and pricing platform PROS where he is now the Chief Visionary Officer (you can read more about this transition here). In his recent talk, he justified the ‘visionary’ part of his title with some important predictions.
His key insight was that changes to the B2B buying process plus our experiences as consumers are forcing us to change how we approach pricing. This provides a powerful lens to bring pricing processes into focus and make sure they are aligned with the buying process.
The key changes to the B2B buying process
Most buyers are about 70% of the way through their buying process before they ever speak with a vendor, having done extensive research online.
Procurement has gotten more sophisticated and powerful, and is generally better equipped to negotiate price than the vendor’s sales force.
There has been a general acceleration in the speed of business, affecting everything from product development cycles to the speed of decision making, to willingness to change.
These three changes are having a big impact on how to price your products. Most B2B software is priced in one of two ways. The website provides some information on features and functions, maybe even a few case studies, and then potential buyers are asked to contact the vendor, sometimes after being asked to fill out a form.
The other option is a set of tiered pricing offers on the website, from which the buyer self provisions. Many companies use the second approach for smaller customers and the former for ‘enterprise’ customers. Both approaches have big problems in the new world.
Forcing people to contact you before providing critical price information, and then entering into a protracted sales process with lots of negotiation, slows down the customer buying process. As most salespeople have experienced, it can grind to a halt, and a slow decision often converts into no decision and no sale. Speed matters. Losing momentum kills deals.
The challenge with making your price public in a tiered pricing model is that you lose the opportunity to really understand your buyer and what is driving value. Web analytics will only get you so far. Even worse, a lot of value in modern ecosystems is driven by integrations and data sharing. In most cases, even with the help of applications like Zapier or Mulesoft, integrations require human intervention, generate costs and they should change your pricing (more on that in a future post).
Even the best-tiered pricing model is underpricing for some customers while scaring others away, who might have been won over with the chance of conversations. All of these challenges are getting worse.
Speed is the new currency
One of Craig’s key points at the Professional Pricing Society conference is that “speed is the new currency.”
One of PROS’ clients found that win rates went down 40% if a quote took more than 24 hours. Further analysis showed that price accounted for 67% of the time required to make a quote. The length of time it takes to generate a quote is emerging as a critical metric for pricing performance.
So how do we accelerate pricing? How do we get to a shared understanding of value quickly, without endless back and forth negotiations and pushback from procurement?
Craig’s answer to this question is that we have to make better use of pricing algorithms, that systematically connect price to value and demand. He went further than this to say that,
“People are beginning to trust algorithms more than they trust humans.”
This is a bold claim and as you can imagine many people in the audience pushed back. Media has been full of stories recently about the problems caused by content recommendation algorithms, the bias built into artificial intelligence and the impossibility of explaining how a deep neural network makes a prediction or recommendation. One of the hot trends in AI is XAI or eXplainable Artificial Intelligence. DARPA, the people who brought us the Internet, even have a project on this.
Before you dismiss Craig’s claim out of hand, think about the experience of buying a car. Some people like the negotiation process. But many of us, I am one, are a bit afraid of it. We know that the car salesman has a lot more experience with this than we do, is better trained and has more information (sort of like the procurement experts at a large company). Pricing transparency has become a value proposition in buying a new car.
There is an important lesson here. If the pricing algorithm is transparent (explainable) and makes sense, we are more likely to see it as fair than the outcomes of a high stakes negotiation. In many cases, a well-designed algorithm leads to a price that both parties see as being fair.
Ask yourself if there is an easy way to explain the algorithm behind your own pricing. The algorithm should have the following properties:
Be easy to explain
Connect price to value
Calculate using easily available data
If your pricing algorithm has these properties, your pricing will be seen as transparent, consistent and fair. This is what today’s buyers are looking for. And by meeting these criteria it will also be a lot easier to meet Craig’s first challenge, the need for speed.
Editor’s Note: This article first appeared on the DesiredPath blog here.
As healthy companies continue to grow it becomes harder to do so at the same rate through new logo acquisition.
At a certain company size in the SaaS model, revenue growth increasingly needs to come from the existing customer base.
This is well known to anyone in the customer success industry and the impetus for the birth of customer success in the first place.
Revenue expansion from the customer base is key for ongoing company growth. Yet customer expansion is still very much in its infancy.
Companies spend an inordinate amount of effort on labor-intensive adoption and reactive, renewal processes with little or no regard to creating a disciplined expansion strategy.
I call this approach Customer Success 1.0 and the practice needs to change if companies ever want to achieve expansion nirvana.
Customer Success 2.0
In Customer Success 2.0, companies consider the holistic potential that their products have on their customers’ business and practice customer success accordingly to cultivate the maturing use of the product.
That is, they set their sights on establishing ongoing benefit for customers through strategic partnering and achievement of business objectives that result in expanded product use.
The ultimate aim is to propel the customers’ businesses forward with the use of the product versus simply driving the use of the product.
Propelling Customer’s Business Forward – The True North
What does propelling the customers’ business forward look like operationally then?
At a high level, it means three things:
Adoption needs to be as automatic as possible: ongoing product improvements and increased automation or tech-touch approaches are required to make adoption as intuitive as possible requiring little to no outside assistance.
Retention needs to be focused on business outcomes: companies must understand their customers (why they buy, what they are trying to accomplish, how they incorporate technology into their environments) and what the successful customer journey is to allow for proactive and prescriptive customer management.
Expansion needs to focus on maturing customer product usage: when the first two elements are in place, Customer Success can focus its efforts on evolving the customer’s use of the product to further grow their business.
Customer Success 2.0 means that Customer Success Managers (CSMs) are ultimately focused on how the technology can support the maturity of their customer’s business so that expansion is a natural occurrence.
CSMs are partnering strategically with customers to add value to their business.
When Customer Success 2.0 focuses on expansion, we do not stop our sights on product adoption and renewals. Rather we consider the entire customer journey and plan to continue strategically partnering with customers to evolve their business use to facilitate growth. Expansion nirvana!
When they give out the Nobel Prize awards, they should seriously consider Elon Musk. No other person has achieved what he has: making electric cars cool.
When first displayed in the 1970s, electric cars were presented as green devices. They didn’t go very fast and you had to plug them in, but at least you weren’t burdening the atmosphere too much.
Flash forward to 2019. Elon Musk has made Telsa the electric car company. Meanwhile, at the New York auto show, every carmaker features an electric or hybrid. All are pale imitations of Tesla.
At the moment, it’s not clear in most people’s minds, so let me say it: Electric cars are the future. Just from a pure economic point of view, they are going to be the car that everyone has. Musk has done a great job of shining a bright light on it and all the car companies have moved in that direction because he’s made it a status symbol.
Taking a step back, what he’s done is amazing. Tesla isn’t the nerdy little car that tree huggers use. It’s an upscale, beautiful car and it happens to have unbelievable performance.
For that reason, I think Tesla and electric cars are going to take off over time.
Tesla vs. Model T
Tesla’s rise comes about 100 years after the introduction of the first affordable car, the Ford Model T. Though there are some differences, the similarities are striking. The Model T was voted the Car of the Century because it was bold and created a huge societal movement.
Thanks to assembly-line production, Ford was able to produce millions and keep the price low enough to service the emerging middle class. Henry Ford made the car so that it was “so low in price that no man making a good salary will be unable to own one.” Though Ransom E. Olds created the first mass-produced car in 1901, Ford and his engineers were able to improve upon Olds’ methods.
Like Henry Ford, Elon Musk is a gadfly and his persona creates a powerful narrative for anyone looking for one. Like many visionaries before him, he’s dabbled in a few businesses. He founded PayPal then SpaceX and Tesla all within four years. Smart, connected to Silicon Valley and known for taking “moonshots,” Musk recently excited the South by Southwest audience by telling them that he planned to build a factory in Los Angeles this year that will offer commercial space flights in 2020 and aim for Mars in 2022.
Given all this, for Musk, Tesla might seem like an afterthought. But in 2017, Tesla became the world’s most valuable carmaker, lapping General Motors.
The electric car market in the 21st Century
One can see why investors are excited about Tesla. Investors look into the future to see potential opportunities, and Tesla has nailed a big one. On the one hand, you have a growing sense, even among non-green people, that the millions of tons we’re pumping into the atmosphere isn’t doing us any good.
On a numbers basis, the world is getting warmer and it’s projected to stay on that trajectory. For years, those who noticed this thought we might have to revert back to the horse-and-buggy days, but now it appears we can have our hot rods and drive them without fear that we’re ruining the earth.
Even if you think that climate change is bunk, there’s simple economics. Electric cars don’t need gas. The average American spends about $2,400 a year on gas. That’s about $46 a week. Based on a University of Michigan study, electric cars cost about half of what gas cars do to drive, which means about $23 a week to get around.
Although there are downsides to owning an electric car, like having to charge it every night, there are lots of upsides including the ability to drive without stopping for gas.
That’s reason enough for everyone to consider moving to e-cars. Now that their performance is equal or better than regular cars, what’s holding you back?
We’re bringing OV Partner Liz Cain back to the podcast for the third time. On this episode, she and Kyle dive into their experiences with pricing and product led growth. Learn about some of the most common pricing mistakes they see and why they were both hesitant about PLG initially, but came around in a big way.
The advent of the SaaS model fundamentally changed how software companies approach customer service. When each piece of software was sold as a high-priced package, the emphasis was on traditional sales tactics: stress the positives, gloss over the negatives, make the sale and move on — make it past your refund period, and you’re safe.
But the move to a subscription-based strategy made that approach untenable because assent could no longer be won and forgotten about. Instead, it suddenly needed to be continually earned, with each fresh month presenting an opportunity to keep a customer around or lose them to a more appealing competitor.
This naturally had an impact upon how companies presented themselves. Instead of products, they started to sell services, and brand reputation became essential for more than just determining initial expectations of quality. Given that ongoing SaaS marketing now demands great priority, it’s only sensible to ask one important question: what sets the top brands apart?
Well, one of the core ingredients to excellent SaaS marketing today is using community content. What does this content involve, why is it effective, and how can you use it? Let’s take a look.
What counts as community content?
Put simply, community content is content produced by your community — the complexity arises from what your community actually involves. You’ll hear talk of UGC, or user-generated content, which encompasses all types of content created by your users or followers (including reviews, testimonials, photos, videos, guides, even poems if you prove sufficiently inspirational), but not every piece of UGC is going to count as community content.
For instance, if you ran a UGC contest (quite common as a marketing tactic), you might get a host of social media users to take photos in line with your stated parameters — but how many of those people would actually be users of your service? It’s likely that some (perhaps most) of them would have followed you idly, and simply taken the chance to get the offered incentive.
On the other hand, time-tracking tool Toggl does something interesting: it allows its users to take a test to see how well they understand the tool, then encourages the experts to join its Toggl Master program and get paid to help new Toggl users get the most out of it (it even provides case studies). This is a clever way to turn leading users into influential advocates.
Community content, then, is content produced by people who actually use your service, and ideally those who are quite invested in it: your long-term customers and/or your biggest clients. Their content is more significant, more telling and consequently more powerful.
The added value of peer support
Signing up to a SaaS solution isn’t like a conventional B2C exchange — it has a lot more in common with a B2B arrangement, particularly when the cost veers towards the enterprise level. This is because it’s typically intended to be a long-term investment. You can relate it to buying an iOS or Android smartphone: if you get an iPhone, then you’ll want to eventually replace it with another iPhone, because moving data between mobile operating systems is a huge pain.
Company support is massive, obviously — a great SaaS company will offer 24/7 support through multiple channels, and perhaps dedicated account managers for high-end clients — but peer support is also a great selling point. Case in point: Shopify attracts a lot of merchants for not only its well-regarded support system but also its strong and helpful community (which runs to over 580k members) — the company even features its customers’ stories very heavily as part of its blogging strategy.
Why wouldn’t any SaaS business with a good community want to emphasize it? Customers aren’t always going to want to go directly to the software providers for assistance, and there will invariably be issues that those providers can’t really help with (for instance, creative roadblocks or other matters that indirectly involve the software). Knowing that there’s somewhere to go for peer support is a huge reason to choose one solution over its alternatives.
Hyper-relevant social proof
Peer support isn’t the only reason to prefer a Saas business with a strong community, naturally. It’s also about getting the kind of social proof that you can’t get from a simple review. Reviews can be taken out of context, or selectively edited, or cajoled through general incentives and/or special treatment — someone can say, “This is the best software solution I’ve ever used! 10/10,” and then never use it again. Community content is different.
Community content is produced steadily over time. It’s long-form and complex, tracking ups, downs and everything in the middle. By following a SaaS company’s community, you can get a great idea of not only how good the service is, but also how well the company listens and responds to feedback from its biggest customers.
It’s a little like choosing between job offers, and seeing that one of your prospective employers has numerous staff members who’ve been with their company for decades. That tells you something about what it’s actually like to work there. Community members might get frustrated and complain about various things, but if they continue to subscribe, that shows you that they still consider that service to be the best of its kind.
Knowing this, SaaS businesses that do manage to keep their customers subscribed for a long time should absolutely make that fact abundantly clear to prospective customers. The message is simple and powerful: subscribe to this service, and you won’t regret it.
How to turn it to your advantage
Now that we’ve looked at how community content is informing SaaS marketing by raising and demonstrating the value of a service, we can think about how you can use it to better market your SaaS business. Well, it isn’t too complicated. Let’s run through a few basic tips:
Actively work to build a community. Even if your service is excellent, you can’t rely on a community forming — and no community means no community content. Provide an official forum, and encourage your in-house support team to provide updates there on occasion to incentivize customers to join up and get involved. (Here’s some general advice on building a network — much of it is applicable here.)
Highlight notable posts/guides. Once you have some community content being produced, be sure to highlight any posts or guides that you think are particularly insightful. For instance, you could get permission from a customer to mention their guide as a valuable resource in your marketing pitch.
Document user communication. Whenever you get involved with your community to acknowledge the varying perspectives and learn from them, you should document the results. Having one of your marketing points as “We listen to your customers” is one thing, but if you can actually demonstrate that you listened to customer feedback and made a significant change as a result, it will prove it to be the case.
Wrapping up, community content is driving SaaS marketing through fundamentally reflecting the overall health of SaaS businesses. Any company with a thriving community will want to boast about it, while any company getting a lot of flack from its users will want to keep quiet and stick to conventional talking points. The former will win the customers, of course — so make every effort to strengthen your community.
All businesses are becoming software businesses. It doesn’t matter what industry you’re in or what size company you are, software is a critical component—a foundational element. Couple that with the emerging trend of applying Agile software development principles to business development, and it’s easy to understand why CIOs who aspire to be CEOs—a career path that’s more common than you might think—are able to make that leap successfully.
There are actually quite a few points of commonality between the CIO and CEO roles. There are also some very distinct differences. I have personal insight into how and where they overlap and diverge because I’ve made this transition myself. From CIO at New Relic, Inc., I took on the CEO role at Airware. Today, I am CEO at Puppet, a company that provides infrastructure automation and delivery solutions that enable teams to more securely scale the software that powers everything around us.
It has been an interesting journey with its share of challenges and many rewards. Through the process, I’ve come to understand a great deal more about why the CIO-to-CEO path makes sense and what someone attempting to walk it can expect along the way.
With technology becoming a more and more central part of any business, it’s not all that surprising that the right CIO can become an excellent CEO. And, if you dig beneath the surface, you’ll quickly realize that there are many core CIO skills and areas of expertise that are directly transferable to the CEO role.
CIOs get the big picture.
To perform their job well, CIOs need to have an inherent understanding of how all the functions within a business work. While CEOs aren’t expected to be experts in everything, they are expected to understand at least the basics of how things work across different business functions—where things intersect, and how workflows operate across a company. Having the CIO’s bird’s eye view allows you to think more critically and effectively about how to drive efficiency, agility and speed within your organization.
CIOs know how to leverage technology effectively.
And, because CIOs are technologists, once they have identified how to drive efficiency, agility and speed, they also understand how to leverage technology to facilitate the processes that will achieve their vision. The combination of insight into what needs to be done and the know-how to make it happen is very powerful for driving change and growth.
CIOs are used to doing more with less.
CIOs are always working to get rid of tech debt, and keeping a close eye on how much is going into tech debt versus how much is going into other functions. They are responsible for reviewing many more business cases than the budget can possibly accommodate, so they are used to having to do the hard job of picking priorities and dealing with disappointed parties.
CIOs are able to apply Agile concepts to business development.
Finally, a CEO who used to be a CIO is well positioned to take full advantage of applying Agile concepts to build and grow a business. The Agile approach has been thoroughly proven in the software development sphere, and now many companies are successfully using the same concepts to create a whole new and very modern approach to business development. A leader with CIO experience can maximize the benefits of this opportunity in a big way.
As you can see, from financial budgeting to operational processes to big-picture company vision, there is a lot of crossover and opportunities for cross pollination between the CIO and CEO roles.
All that said, there are some things that are very different between these two roles. Primarily, they have to do with a greater depth of responsibility.
Maybe the biggest CEO-specific responsibility is defining and holding the company culture. While vision and fundraising are obviously important, I believe that establishing and nurturing the culture of your organization is the number one thing a CEO can influence. And the smaller the company, the truer this is. As the CEO, you own the culture—who you hire, who you fire, which behaviors you reward and which you discourage. And as the CEO, everything you do is a reflection—intentional or unintentional—of the values underlying your company culture. Everything you do and say, everything you don’t do or say, every word you write, who you meet with and who you don’t meet with. All those choices affect how people perceive the culture and values of the company. So, it’s critically important to be very thoughtful about those choices. Know what kind of culture you want to create and be aware of how your actions help build that or detract from it. This responsibility is ultimately so much bigger and more important than any other function in the company. It is the company.
As a CIO, you partner with different people to help develop and cultivate their vision based on their specific goals and objectives. As a CEO, you are the person who is driving all of that for the entire company. You’re looking not only at what you’re doing this year, but for the next three to five years and you are doing this in an ever-changing market where predicting what the future will look like more broadly is part of your day job. Internally you’re not just looking at one functional area; you’re looking at the entire organization and how all the pieces will fit together. This can be a pretty big shift in perspective.
On the money side, the CEO is doing more than simply allocating money on tech investments, which is typically the primary financial responsibility of the CIO. At the CEO level, you are responsible for everything from ensuring you have the right business model to scale the company to fundraising to managing earnings calls. It’s a broader and longer game when you’re the CEO. And, obviously, there’s more at stake.
And that’s kind of what all the differences between the CIO and CEO roles boil down to: bigger stakes and the overwhelming sense of responsibility that comes with them. It’s an honor that comes at a cost. While it’s great to be able to make all the big decisions, the consequences of those decisions are ultimately your responsibility and can weigh heavy on you. At my current company where I am CEO, I am responsible for the livelihoods of 500 people, many of whom had been with the company for many, many years. I know them personally. They are trying to put kids through college, buy a house, buy a car. And their dreams depended on the performance of the company. But, no pressure.
And, for better or worse, the CEO’s responsibility is largely something that must be borne alone. CEO is an intense job that will teach you the meaning of the saying, “It’s lonely at the top.” As CEO, you’re not a peer of the executive team (they all work for you), and you’re not a peer of the board (they advise you and can fire you). You’re in a unique position of power, which can be very rewarding, but also very taxing.
The last factor to consider in a transition from CIO to CEO is what I call the “Hotel California” factor. When times get tough (and they will) you realize there’s no easy out. You have to go in with a high level of commitment because—unless you’re fired—there’s no simple exit plan for a CEO. So, you need to be all in on believing in and delivering on the company vision. It’s not that leaving is impossible, but it’s definitely complicated. If you take a CEO position, you need to be in it for the long haul.
The CIO Advantage
We’ve covered the crossover points and the points of differentiation between the CIO and CEO roles. But what about the things that give a CIO a specific advantage as a CEO? For a software company, there is a tremendous amount of value having been a CIO working in a technology company that sells into the CIO function, or even the VP of Infrastructure or DevOps team. That experience is really helpful when it comes to understanding the fundamentals of how companies buy technology, information that can come in very handy for a CEO.
Relevant messaging can make or break the sale. As your company grows and scales, your product becomes a bigger-ticket item for your customers. As your offer evolves, you need to make sure your messaging evolves as well. Whether you’re selling directly to the CIO, into their department, or to a broader base of users within the company, as the average size of your deals increase, you need to be able to articulate your product’s value from the ground level all the way up. This can be especially challenging for startups that are still focused on feature/function messaging. That approach works fine for the end user, but as you take your pitch up the food chain, you need to be able to demonstrate broader, company-wide value and help people who are not “hands-on keyboards” using the technology understand and appreciate its power as well.
A CEO who understands the pressures of the CIO role first hand will have a solid understanding of a company’s absorption capacity. So much is changing in corporate environments these days, and the reality is that you can’t change everything at once. This means that sometimes, there’s just too much going on for a customer to get a deal done. They may not have enough resources, or they may not have enough time in their own schedule to pull off a new implementation or integration, no matter how much they love your product. In cases like this, the CEO who has been in the CIO’s shoes will know to respect that situation and won’t try to pressure a customer into a deal when the timing just isn’t right. Reality is that you can push a sale, but you can’t as easily push implementation and adoption. If they don’t use the technology, they won’t renew the technology so in the long run, it will be a loss. Hence, while it can be hard, that restraint can be crucial to salvaging the relationship for another day.
You’re never going to “own it all.” If you try to control everything with a product that is too closed and too proprietary, you’re going to get rejected from the system. Any CIO knows the importance of being open, connected and able to integrate into other solutions. This is particularly true in complex enterprise environments where a company has already made substantial investments in infrastructure and other technology. They want something that is complementary—that plays well with others. This is why API-based architectures are so popular. They make life easy by being open and connected. This is a big core value of ours at Puppet. Our products leverage open-source projects, and we’re continually cultivating those projects as we strengthen the open-source componentry our commercial products are built on. It’s important to us to deliver value on both sides so that we can provide a solution that works for as many people and organizations as possible.
Distinct Roles with Valuable Crossover
In today’s technology-driven markets, it’s not surprising that these two roles are converging. Based on my personal experience and what I’ve seen throughout the industry, it’s clear that if we were to create a Venn diagram of the CIO and CEO roles, there would be plenty of middle ground between the two. Both roles are critical to any organization’s success, and while they are not interchangeable, there is certainly a clear path to transition from CIO to CEO in a way that can deliver tangible competitive advantages. So, if you’re a CIO looking to move up into the top position, don’t sell yourself short. And if you’re a member of a board looking to hire a new CEO, don’t overlook the opportunity to harness the transferrable skills and strategic strengths of a world class CIO.
A dramatic shift is underway. Product-led go-to-market practices across the SaaS spectrum, and the need to deliver stellar customer experiences, are becoming all the more important. Organizations are forced to re‐examine how they drive revenue by using the product as the main growth lever. Companies who adapt to those changes will emerge as winners, while those faithful to the old ways will cease to exist.
Being the lifeblood of new business, sales follows their quota and goals to close as many deals as possible. Before product-led spread like wildfire, sales wasn’t held accountable for any process beyond sealing a deal. The lack of a unified agenda across and within teams, in conjunction with ignorance of in-product behavior, limited the sales organization’s prevalence to top of the funnel activities.
The direct association we made about sales practices until recently was in this order:
Sales outreach → Series of Demos → POC/Controlled trial
Eventually, that buy before you try approach caught up with the SaaS industry. The expectation that seamless product experiences need to be delivered in the B2B space flips the script on every traditional sales process adopted thus far. This could not be truer for sales teams, which now have to nurture and convert product qualified leads (PQLs).
This guide will discuss emerging B2B sales processes, uncovered via a comprehensive research conducted by ReinventGrowth on 40 SaaS organizations, and examine how they can be incentivized with PLG practices and product onboarding.
Step 1: The product-data imperative
For a while now, marketing data has defined SaaS growth, mostly by monitoring a prospect’s online behavior. Organizations rely on enrichment and lead scoring tools, which recognize prospects by industry and size. So, when somebody signs up from a Fortune 500 company, sales teams are alerted and follow up with a personalized approach. The rising importance of product experience however, supports that even when a tailored experience is provided, the work is not done. A viable monitoring process following users’ in-app progression needs to be established to map adoption and engagement levels far beyond subscription.
Product-led organizations already drive stellar experiences by capitalizing on product data and taking advantage of the customer experience gap humans leave behind. A gap that has nothing to do with the lack of exceptional strategic skills. On the contrary, it relates to the undeniable fact that meaningful interactions are driven by product features (in conjunction with product guidance) that leverage the context of usage. The organization’s competitive advantage derives from allowing product data to dictate “where” product engagements should exist and “when” human-assisted activations should be eliminated.
In order to achieve that, sales teams need to claim ownership of trial data and observe user behavior to pinpoint where product experience may be broken or drop-offs occur. While this association may resonate for companies serving high trajectory customers, the increased involvement of sales in self-serve onboarding (40%) suggests otherwise. Setting aside the preferred distribution model, a product-led sales team harmonizes the high tech-touch activations by giving a concerted focus on a prospect’s needs and in-product behavior.
By adopting in-app segmentation criteria and acknowledging where your product experience needs to be refined, sales teams can become proactive when approaching prospects by capitalizing on historic usage patterns and not rely solely on their hypothesis in regards to barriers to entry.
The acknowledgment of product usage patterns in regards to breadth, depth and efficiency of use (indicating team activation, adoption and users’ proficiency levels, respectively) are a good foundation sales teams can adopt when striving to streamline PQL criteria.
In addition, sales teams should consider emerging product metrics in their evaluations. As much as those metrics directly concern product management, their adoption across teams help into the development of a common language and optimization of internal procedures at the same time.
Tracking trialists and freemium accounts’ behavior, to realize if they employ PQL characteristics, whether or not they have signed under a corporate domain. This enables sales teams to not to waste their manpower on leads that don’t meet PQL criteria while discovering sales opportunities in disguise.
Monitoring trialists’ PQL characteristics to determine if they can benefit from the product offering without forcing their way into closing a new deal. To give you an example, Gainsight PX will send a welcome email presenting sales availability, but will not actually force a demo onto a prospect. After the 28-day trial period, and if the prospect has shown signs of significant usage, sales will follow up to schedule the first sales session. This is the point where a completely no-touch approach is merging with a product-assisted sales process, but only after the prospect has turned out to be a product qualified lead. Please note that this is not a golden rule. Gainsight PX has been a product-led organization since its infancy. If an organization is adopting a purely traditional sales model, the shift should be progressive. Sudden changes will most probably cause friction and confusion.
Step 2: Create a consultative sales team
Trying a new product always feels a little like magic. The rise of the customer and hyper-competition have come to put an end on the latter effect. Products have to stay competitive and the sales team needs to embrace customer needs to the very end. Product-led sales teams follow this mentality by acting as consultants based around customer centricity and avoiding aggressive sales tactics when striving to hit their quota.
The research’s results demonstrate that this notion already exists in the market. Take the case of Receptive, where sales acts like an extension of customer success and advises prospects in case there is not a fit. Following the same mindset, Close holds sales accountable for evaluating a prospect use case and, if they are after a different subset of features, advises accordingly. It’s one of the organization’s core values to be against selling the product just for the sake of the sale itself.
Step 3: Make sales part of the onboarding process
The third characteristic of a product-led sales team is that it breaks the shackles of product demos and is actively implicated within the onboarding process. Under that spectrum, the business offers a standard trial or freemium and sales is only involved when strategic guidance is applicable.
There are several advantages that come along with including sales in your customer’s onboarding process:
Accelerated onboarding. Onboarding is accelerated and customers realize initial value early in the customer lifecycle.
Eliminate airtime. When sales onboarding includes delivery of targeted data-driven engagements, airtime conversation for product capabilities is eliminated and both parties focus more on fit.
Insightful customer data. The sales organization offers a useful string of (product) data to customer success which further streamlines its part in the onboarding by:
Suggesting additional professional services programs and being able to explain the reason why.
Being aware of the strategic insights they should focus on before syncing with buyers.
By relying on usage behavior, sales identifies PQLs and compares engagement levels with the expected ROI results.
Passing feedback to product management. Sales teams are able to streamline the onboarding process by passing the necessary feedback to product management. If for example, prospects are engaging with key features but the steps to initial value are complex, it won’t be long until customers churn. Sales should find those bottlenecks and establish a feedback loop with product management to optimize onboarding touchpoints.
Product evangelists. The onboarded team(s) can later act later as a product evangelist across the customer’s organization. This helps customer-facing teams deal with the human hurdle, one of the main barriers towards successful adoption, and get the internal buy-in sooner.
The research uncovered multiple occasions where sales might be involved in the onboarding process.
The popular project management S/W, created an in-house sales methodology that’s based around customer centricity and divides its strategy into two parts: Trial Onboarding run by sales and Post-Sale Onboarding run by customer success. The business created this methodology because, when a buyer signs up, she needs to trust in the product offering before showing it off to team members.
During trial onboarding, sales proactively sends automated drip campaigns and, only if there is a fit, a personalized invitation will be sent to move the process forward. In the Post-Sale Onboarding, customer success concludes the process within the first week post-purchase, to offer onboarding services for the entire team.
The leading digital asset management solution, serving mostly the enterprise sector, offers a trial where the customer can use all the features under the guidance of a sales engineer. The sales organization has a customer-centric approach and helps customers get the most out of the product, in order to embrace adoption sooner than later. At the same time, product management tracks users’ first login by the specific FAQ they clicked on or which tutorials are the most popular to further optimize the educational material.
While in a traditional sales strategy, the sales organization barely scratches the surface of product capabilities. With a product-led strategy, customers realize the initial value early on. Despite the fact that we may not be able to say how much sales’ costs are reduced or to what percent the sales cycle is optimized, it is certain that teaming with customer success on the onboarding process will reduce a lot of friction.
Step 4: Merge the lessons learned
The last step revolves around injecting the lessons learned from a self-serve strategy into a human-assisted sales process. In this instance, sales teams can adopt practices arising from self-serve and experiment with scalable targeted in-app activations, which can accelerate the sales process without compromising customer experience.
The popular email management solution, when dealing with high trajectory, had historically used sales to create and maintain the relationship. The hypothesis was that the product was fitting those customers’ needs and, as long as internal teams could provide a decent service, churn would never prevail. Eventually, customer-facing teams discovered that these customers were not the most profitable and many times didn’t align with a mass market mainstream product. Fast forward to now, where the onboarding team has established an ongoing feedback loop with sales to capitalize on the learnings derived from the trial and insert them into its processes.
Yesware is only a successful use case, further considerations can be:
How sales can lead prospects to initial value faster.
Where scalable practices have higher impact and when the human factor needs to be involved
If we could make a direct comparison between the activations of a traditional and a product-led sales organization we would arrive at the following conclusions:
Sales teams adopt a product-led model by capitalizing on product analytics, owning the reins of early adoption and sharing active feedback in regards to product experience optimization.
Sales takes advantage of sales opportunities (product qualified leads) that may first appear “in disguise” and segments prospects based on usage.
Sales reps act as consultants based around customer centricity.
The sales organization actively becomes part of the onboarding process by enabling customers to realize initial value early on and offering a useful string of data to customer success.
The internal teams exchange insights and best practices to ease the acquisition & onboarding process.
Adopting a product-led strategy fundamentally changes how individual teams function within an organization. Knowing how a product-led GTM approach affects sales is key. As much as the sales organization may be concerned with top funnel activations, the effects of a wrongly sealed deal will negatively affect any organization’s ROI afterward. Successful product-led organizations change that by prioritizing internal alignment across teams and putting the product in the middle of every process. In a world where an organization’s revenue is highly dependent on new customer acquisition, improving customer experience by leveraging the product itself is key to achieving this outcome.
Being a data-driven sales manager means, at a high level, understanding how metrics impact one another, how to approach setting goals against key performance indicators (KPIs), and how to coach to the achievement of those goals. Where the rubber really meets the road, though, is how a manager incorporates data into her ongoing managerial cadences. The most impactful place to do this is in weekly 1:1 meetings.
What Data Do You Need?
Incorporating data into your 1:1 meetings with your reps starts with determining what information you need in order to have a productive conversation.
Here’s an approach to help you determine what you most need to know:
Document the key topics you want to cover on your agenda.
Define what questions you are trying to answer within each topic.
Identify the pieces of data most important to be able to answer those questions.
The data points identified in the third step, which appear in the far right column in the example above, are the ones that need to be accessible on an ongoing basis and reviewed in preparation for each 1:1 meeting. The most common method of making data like this available is by building a dashboard in Salesforce or in the sales analytics or reporting software used in your organization (like we make here at Atrium).
That dashboard can then be shared with reps and linked in recurring meeting invites for the 1:1 itself and for the preparation time that you have scheduled on your own calendar in advance of the meeting, so that it’s always available and easy to find. Similarly, if you keep a Google Doc or other 1:1 template somewhere that is completed for each meeting, you can link the dashboard at the top of that document as well.
Preparing for the Meeting
Once you have a clear agenda, and a dashboard set up so that you have the data to inform that agenda, making the meeting as productive as possible then comes down to preparation, each and every week. First, you should assign ownership to specific agenda items. As the manager, you are ultimately responsible for making sure this meeting is productive, but many organizations have the sales reps own key areas of preparation for the meeting, including being responsible for bringing data about their own performance to the meeting, or having a portion of the agenda solely dedicated to concerns the rep has or topic areas they want to discuss. It’s important to make sure that it’s clear who is responsible for what pieces of preparation in advance of the meeting and who will be driving different pieces of the agenda.
With that structure in place, the remaining hurdle is time. The best way I’ve found to ensure time is available to prep for 1:1s is to make that preparation time its own block on my calendar, so that time can’t be eaten up by other priorities – often you can prep for multiple 1:1s that will be held in a given day in a single time block at the beginning of the day. That preparation time can be used to go through a metrics inspection using those saved reports and dashboards, or items that the rep has brought to the agenda, so that you can walk into the meeting already having a clear sense of what areas you need to discuss and what specific coaching points you need to cover.
Repeat the Cycle
Points covered in the 1:1 meeting will often have associated follow-up and next steps. Be specific about what those are, including the timing to complete, who is owning that next step and when you’ll check in on it again. With that clarity, you can then add the follow-up to the agenda for future meetings and ensure that the reinforcement cycle of data-driven coaching and proactive follow-up continues.
In future meetings, you can check in on those metrics you identified as wanting to impact in previous meetings, watch for new indicators of success that can offer learning opportunities across the team, and monitor for the next area of coaching and development.
I’m an unusual messenger for the idea that there are limitations to what you can do with marketing analytics. I am, after all, a highly data-driven CMO with a background in data science, analytics and other quantitative disciplines. But changes in today’s marketing environment are shifting the way we work with data and our expectations of what it can do.
Over the last ten to fifteen years, marketing has become much more reliant on data. I saw the transition as it happened. At the time, I was running strategy and analytics departments—everything from simple marketing analysis and dashboarding to financial analysis, FP&A and big data. Slowly, marketers started coming into my quant departments for guidance on how to divvy up their budgets or develop analytically-derived audience segments.
The line between marketing and analytics blurred fairly quickly, and I became something of an “accidental” CMO, currently heading up marketing at Shopify. Still, I’ve always thought of myself first and foremost as an analyst. This is why it feels a little strange to be the one calling out the fact that we have, in some instances, reached a point of diminishing returns when it comes to viewing marketing and sales through a purely data-defined lens. We’re starting to realize that you can’t completely manage human decision making with an algorithm.
How We Got Here – Discovering PLG Roots in Direct Response
Let’s take a quick step back and look at how we got here. The current product led growth (PLG) trend didn’t come out of nowhere, and neither did the more general direct-to-consumer business model. If we time travel back about ten years, we can see the roots of both of these movements, which harness data to power marketing and drive growth.
At that time, about 2010, I joined an incredible Santa Monica-based company called Beachbody, which was transforming the health and wellness space selling exercise DVDs and meal replacement shakes via direct response TV and multi-level marketing. I’m not ashamed to say that being part of that organization at that time remains one of the best professional experiences of my life. From 2010 and 2016, Beachbody exploded, growing their revenue from about $400 million to more than $1.3 billion. They accomplished this Herculean feat by being very disciplined about running the numbers and striving to be the gold standard for analytics-driven direct response marketing.
And if we go back a little further into the history of direct response marketing, we can see how pioneers in the space laid the groundwork for contemporary direct-to-consumer brands like Bonobos and Dollar Shave Club. Back in the late 1990s and early 2000s, a company called Guthy Renker forged new marketing territory with products like Proactiv, cutting out the middleman and building their business on an in-depth understanding of unit economics, customer acquisition cost (CAC) and lifetime value (LTV).
Today’s product-led companies are building on those ideas, creating a hybrid entity that combines direct response analytics with a superior customer experience. This is the revolution Shopify powers. Our customers are the companies that are carrying the direct response torch into the future. Shopify provides them with everything they need to start, sell, market and manage their businesses in a single platform. Our own company has evolved alongside our customers, broadening our services and products to meet the growing needs of an expanded range of entrepreneurs.
Mostly, we believe we’ve succeeded because we take something very complex and make it simple. That’s a big advantage these days because marketing seems to get more complicated every day.
The State of Marketing Today – Adapting to a Different Landscape
It wasn’t that long ago that we mostly thought about marketing as existing in two discrete categories: brand and direct response. But now, it’s more accurate to describe marketing as a spectrum.
There are several factors driving this shift. For one thing, the evolution of the direct-to-consumer brand, which combines the best of both worlds—the math of direct response and the experience of a brand marketing operation. Then, there’s the rise of growth marketing, a trend that embraces the concept of creating something that’s more than the sum of its parts. It used to be enough to spend $1 on marketing and get $2 in return, but that kind of linear growth doesn’t cut it anymore. Growth marketers have hacked the system using viral marketing mechanics and gaming techniques to create viral loops and other growth drivers so that we’re no longer talking about one plus one. Now the equation is more like one plus one squared and becomes four.
On top of all these changes, marketers are also realizing that there are limitations to what we can do with measurement and attribution. For a while, we were thinking that if we just did enough math, eventually we’d be able to reduce everything to a perfect direct response model. But now marketers are coming to terms with the fact that there’s no silver bullet modeling solution for attribution or the effect of brand marketing on direct response metrics. All of which leads to more blurred lines as companies attempt to achieve some level of quantification in their marketing, but are also happy to settle for general improvement in place of a global solution for how to spend marketing dollars most effectively.
The convergence of brand and direct response marketing is also removing the traditional division of channels. Once, brand marketing was almost exclusively associated with radio, TV, and out of home while the direct response space usually occupied by B2B companies was primarily focused on digital channels. Now, however, there’s a lot more channel crossover, which is in part a natural correction to what was an overswing of the pendulum toward digital spending.
Shopify is getting more aggressive about looking at ways to use non-digital channels. While I’m still a strong advocate for precise and consistent use of data and analytics to inform marketing decisions, it’s possible to reach a point at which companies are willing to pay more than advertising is worth simply because it can be measured. Paying a premium just so you can measure something is counterproductive. I’d much rather achieve a better return in an uncertain and imperfectly measurable world.
Take word of mouth, for instance. That is a powerful marketing tool that can’t be boiled down to a formula. It’s something of a black box, which makes it very difficult to create intentionally. There is, obviously, not only a human element to word of mouth, there’s also a community element. One of the first steps to encourage users to share your product with their peers is to participate in the conversation. I’m often shocked by the extent to which brands avoid participating in the conversation people are having about their product. People will talk with or without you; why not join in?
Another approach to influencing word of mouth is to create viral mechanics that produce a reliable incentive for people to pass on information about your product. This taps into social gaming strategies and can work well when done right. The most effective method we’ve found, however, is simply to build a product that’s so good people can’t help talking about it. That’s the path Shopify took, and it has been very successful. As one set of entrepreneurs used Shopify to bring their business dreams to life, they told other entrepreneurs. All we had to do was build a better product for an under-addressed, but large, market segment.
The Internal Marketing Organization – Building around Real-life Sales Funnels
In addition to adapting to the changes in the external marketing landscape, organizations also need to adjust their internal operational structure and flow so that it aligns more closely with how customers actually buy. Lesson one: the funnel is never a straight line. Any attempt to take a complex process like convincing someone to adopt and use your product is never going to be as simple as MQL, SQL, SAL. You might be able to build a perfect data model in the world of analytics, but in the real world, things are a whole lot messier than that.
So, how do we succeed in this messier world?
The first step is to segment your customer base effectively. Instead of treating your customer base as a monolithic entity, segment it in terms of, for example, LTV or conversion propensity. Defining LTV will help you determine if a customer deal is lucrative enough to justify the expense of sales rep time and labor. Being able to score customers based on how likely they are to convert can help you refine your marketing efforts, though perhaps not in the way you would assume. Rather than focusing on the people who are most likely to convert, you might do better to work on the second or third decile of conversion propensity—people who are sort of open to buying your product, but not already sold on it. The people most likely to buy will probably convert on their own—without needing sales support—but that 20th or 30th percentile could use some sales support.
Whichever scenario you’re dealing with, you need to be pretty rigorous about understanding—in real time—who your customer or lead is so that you can put them in the right funnel.
Speaking of the funnel, who owns the funnel in a product-led organization?
In my experience, the best way to address any ambiguity is through a well-defined organizational structure and—so far—the one that I’ve seen work most effectively for product-led companies is a matrixed environment in which you have product lines or business units on one axis and services that support those product lines on the other axis. In this scenario, marketing is typically treated as a service because it takes on a supporting role in a product-led environment.
For Shopify, I embed a product marketer in each product line. These product marketers become the hinge that connects the product and services axes on the organizational matrix. In this position, they maintain important connections with both sides. On the product side, they are connected at the hip to their respective product manager, and on the services side, they all report to a centralized head of product marketing.
The partnership between the product marketer and product manager is key because they have joint ownership over a set of numbers that they agree to hit together. While some people will push back on this, saying that it’s critical to have only one person be accountable, our teams have done well with this model.
Having all product marketers report into one head of product marketing is also crucial because it helps to maintain consistency across multiple products. Without this throughline, you risk accidentally shipping your org chart, meaning you go to market as multiple products instead of a single, cohesive platform which is how the customer experiences your product.
The marketing landscape continues to evolve, sometimes in anticipated ways, and sometimes in unexpected ways. And while data will always be the backbone of a lot of marketing strategy, people are starting to embrace the fact that you can’t measure everything or attribute every single dollar and every single action. Over several years, we’ve learned that attribution is something you improve, not something you solve.
That said, we’re definitely doing better on a lot of fronts. We may need to update John Wanamaker’s famous quote, “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” With access to data and the technology to analyze it, we have been able to reduce wasted ad dollars.
Still, we know enough now to realize we’ll never be able to perfectly model exactly where a sale came from. We have to get comfortable with the messiness of the real-life marketplace and get brave enough to try out different attribution schemes. We have to stop making the mistake of sticking with faulty attribution models that we know are wrong just because they deliver neat and tidy results—like the last-click models that fail to accurately address a purchase journey that has an average of six touch points.
Eventually, you’ll do something like use last-click attribution to give social media credit for a sale that actually came from search, and then increase your spend on social and fail to get the incremental sales you expected. That’s not a winning strategy.
So, don’t expect data to solve all your problems. Don’t deny the messiness that is modern-day marketing. But do test what you’re doing to see what works for your business. The more comfortable you are operating in a dynamic environment, the more successful you’ll be.