maximize learning

In growing any business we experience constant internal and external change that pushes us to respond and adapt.  Maybe a threatening competitor enters the market, one of our customer acquisition channels changes abruptly, or a new platform like mobile enters the market, changing how our users behave. 

There is one common thread through all of these changes. We can’t control any of them. We can’t control what our competitors do, how Google and Facebook update their algorithms, or what TechCrunch writes about our company. Yet teams spend endless energy worrying and complaining about these types of things that they are completely powerless to affect. Top performing teams, in contrast, focus on what they can control. 

The most powerful thing we can control is how much we learn and how fast we apply our learnings to adapt to change. This brings me to an important question and the first principle of top performing growth teams, maximize learning.

Where Should We Spend Time Learning? 

There are three areas upon which growth teams should focus. Each is a goldmine of information:

1. Users - What motivates our users? Where do they live? How do they think about and explain the problem we are trying to solve? What fears do they have? What do they associate our product with?  
2. Product - How do users flow through our product? How do they change states? Or in other words, how do they go from being an activated user, to a user who’s built a habit with our product, to a long-term engaged user? Why do they change states? What are the triggers that push them along? What are the hurdles they face as they move through the product?  
3. Channels - How do our growth channels work? What are the rules of engagement? How does Facebook’s feed algorithm operate?  How does Google decide which content to rank first? How do we get our emails out of the promotions box in Gmail? Note: We’ll never know the answers to these platform-specific questions with 100% assurance because the platforms keep them a secret and change them constantly. Since we can’t ask the platforms directly, like we can ask our users, we need to reverse engineer the rules of the game for each platform, the same way a chef reverse engineers a recipe.

For all three areas, we could ask endless questions, but the point is, the more we learn, the more we can influence growth. If we are better at learning and applying, we can outgrow competitors by using our learnings to inform which tactics we pursue and how we implement them. 

Maximize Learning Video

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Maximizing Learning = Winning In The Long Run

Every time you learn something and apply that learning you'll improve your growth rate.  So for companies that are able to consistently outlearn and apply over the long term, should also out grow others. 

There are 3 main reasons teams that learn and apply their learnings the quickest win in the long run:

They Have Higher Hit Rates
Companies that know more about their customers, product and channels, give themselves an edge in the growth experiment process. They prioritize collecting and analyzing information in a systematic way and this empowers them to more accurately choose the highest impact experiments more often. 

For instance, if I know Facebook’s ad algorithm better than my competitors, I can outgrow them by creating better ads and achieving lower CPC’s and CPA’s. If I know what type of messaging my audience responds to I can create better conversion points across the board.  If I know how and why some users get stuck in my product and some users sail through, and the difference between those users, I can design better experiments.  

The bottom line here is, if we deploy more successful experiments than our competitors, we will learn more, better hone our growth process and grow faster.

They Capitalize On New Opportunities Faster
“When one door closes, another opens” applies here. The environment in which a company operates is always shifting, and while these shifts may make one growth tactic ineffective, they also create new opportunities for growth. These shifts are going to happen whether we like it or not so if we focus on spotting these changes quickly and maximizing learning around them, we will adapt better than anyone else. In doing so, we will capitalize on the new opportunities faster than our competitors who haven’t made maximizing learning a core competency. 

They Focus Inward
It’s easy to get caught up in what competitor XYZ is saying or doing, what TechCrunch wrote about us, or in announcing a big round of funding. But focusing on these things never drives success the way building products users love, cracking the nut on growth and building strong teams does.

Maximizing learning about users, product and channels focuses teams inward on what really matters, and filters the outward noise from competitors, press, pundits, and other distractions that take teams off task. What really matters is how well we’re executing and that comes down to learning the most about product, users, and channels and executing against those learnings.

Learn Fast, Don't Fail Fast

“Fail Fast” is a cliche that many companies live by. In my opinion this places focus on the wrong goal. We should focus on learning as fast as we can, not failing as fast as we can. While failing is a key part of learning, this mantra leads to a few dangerous habits, the two worst of which are:

1. Skipping analysis in the name of moving fast - I would estimate that over 50% of experiments at most tech companies I’ve seen go unanalyzed. Teams that do this are on a mindless pursuit, zig-zagging back and forth rather than strategically narrowing in on their destination. In skipping the analysis, they’re not learning from what they’re doing. When experiments fail, they quickly move on to the next experiment. They end up doing more of anything, rather than doing more of the “right” things. The point isn’t to fail fast, the point is to increase our probability of success. But we can’t do this unless we learn from our experiments, and we can’t learn from our experiments unless we analyze them.
2. Choosing the least resource intensive experiments to “fail faster” - Another example of how teams become desperate to “save time” at the expense of increasing their probability of success, is by choosing experiments based on minimizing resource requirements rather than maximizing learning. This manifests is when teams push to ship something as fast as possible so that they can “fail fast.” If we need something to be more complete or different in order to learn, then yes, we should invest more resources to ensure we can learn from our efforts. Sometimes to learn the most meaningful thing we have to take on a more resource intensive experiment, and that’s ok.

The point of this whole process is to start with a roster of ideas, in the form of hypotheses, test a few, learn from those tests, apply those learnings back to the prioritization process and go through the loop over and over, learning more each time through. In the beginning, the ideas and hypotheses will be informed by gut because we don’t have much data yet. But then as we test, learn from those tests, and apply them back to the idea prioritization process, we begin making decisions informed by data, rather than gut alone. In this way, we can bubble up more of the most impactful experiments and hypotheses over time, drive growth faster, and improve our probability of success. 

Four Things To Implement This Principle

Run Hypothesis Driven Experiments
There’s a reason the scientific method has been around for hundreds of years. The structure and the process yields the greatest learnings and insights, which is why the best growth teams have adopted it to structure their efforts. 

I often see people make a change to their product or try a new acquisition tactic and call it an experiment. The idea is on the right track but the implementation misses the point. What they’re doing is not actually an experiment unless they establish a clear hypothesis and walk through the method from start to finish. 

A hypothesis clearly states what we expect to observe and should always be written down. A good hypothesis will be quantifiable, set the foundation for the design of the experiment, and help us ask the right questions during the analysis phase so that we can extract the most impactful learnings. Without a hypothesis in place, our questions are undirected and don’t necessarily leading us to the critical learnings. In a later lesson, we will dive deeper into how to structure and test growth hypotheses.

Capture and Share Learnings, Not Activities
Many teams do two things that undermine this principle of maximizing learning:

1. They fail to capture learnings in a systematic way. They spend endless resources building a foundation of invaluable learnings and just let them sit in people’s heads. Over time these learnings are either lost as team members leave or forget or they become warped through a game of telephone. It’s shocking how many teams do this. Instead, capture learnings in experiment tracking documents that are shared team-wide (I will share templates for these experiment docs in a later lesson). 
2. They focus on sharing activities, “this is what I did,” rather than learnings. In How to Run a Weekly Growth Meeting That Gets Results I explain how many teams tend to focus on their activities, what they did, rather than on their learnings. Activities are easy for another team member to understand by checking out a spreadsheet or meeting deck, but the learnings resulting from an experiment are much more nuanced and harder to understand without discussion. Sharing learnings leads to much more interesting and productive team conversations and creates a distribution channel for the most important information to be disseminated across the team. 

The bottom line is this: These learnings are least useful when they’re stuck in one person's head, they’re more useful when recorded in a document somewhere that someone might stumble across and they are most useful when captured and pushed across the team in a repeatable and systematic way.
 
Ask the Uncomfortable Questions
One of the hardest things about maximizing learning is that sometimes the thing that is most important for us to learn for the health of our business is something we we really don’t want to hear. But running from reality always catches up with us sooner or later. It’s always better to face into and ask the questions prompted by what the data is tellings us, no matter how uncomfortable they may be. 

When I was building the growth team at Hubspot, we positioned Sidekick as a freemium product. For freemium models virality must be built into the product to sustain a free growth engine, a la Dropbox and Evernote. With Sidekick (now HubSpot Sales) we struggled to find this organic viral growth engine. We kept saying we were going to build organic virality into the product, but waited too long to face the hard question of whether this would be possible for us. By the time we faced the question the ship had sailed without us. We pulled back on the freemium model and shifted towards more of a traditional SaaS model. Face the questions that make you feel uncomfortable. In doing so, you’ll reveal the biggest insights and make the most progress. 

Apply This Principle To The Team, Not Just The Business
The team is one of the most important assets at any any company, and is often as critical to success as the business itself. To maximize learning effectively we must develop the individuals within the team, as well as the team as a whole, by setting up systems for constant team development. Doing this infuses the habit of learning into the culture and reinforces a learning-first mindset. 

This is the main reason I started Reforge and run programs such as the Growth Series - to help experienced professionals accelerate their learning from top practitioners.  Despite making this a focus at HubSpot and having amazing support from the broader company, there was never enough time in the day to fulfill all of the development opportunities for my team. 

At Hubspot we invested in constant learning for our team in a number of ways - we offered a $5,000 tuition reimbursement for continuing education, we sponsored a company book club, and brought in experts on a regular basis to give tech talks on specific topics. 

For the growth team, we each set personal OKRs (objectives and key results) to measure our progress against our personal growth goals. Quarterly, each team member set their own OKRs, shared them with the rest of the team, and met regularly with other team members to discuss their progress. Whether you choose to model your company’s team development process off of HubSpot’s example or not, invest resources in developing your people and create and document a process around their personal growth.

If I Stepped Into Your Company Today As VP Of Growth…

I would want to understand whether your team operates by this principle of maximizing learning, and if so, across which areas it’s strong and which ones need work. To assess this I would ask a number of questions to get insight on whether your team has a learning-first mindset, how it learns about its users, product and channels, and whether there are effective processes in place to disseminate those learnings with everyone on the team. Below is the checklist of questions I would walk through - go ahead and give them a try with your team.

Learning About Users, Product, And Channels

• How are we learning about users, product and channels? 
• Do we collect and analyze information in a systematic way?
• Do we have specific systems in place to learn about all three areas?
• What was the last major change in an our acquisition channel?  How quickly did we discover it and adapt to it?

Learn Fast, Don’t Fail Fast

• Are all experiments being analyzed?
• Are we choosing experiments based on estimated impact or resource requirements?

Running Hypothesis Driven Experiments

• Are we establishing a clear hypothesis for each experiment and writing it down?
• Are we using the hypotheses to design the experiments and direct our analyses?

Capturing and Sharing Learnings

• Do we have a process in place to capture our learnings? Or are they stuck in people’s heads? 
• Are they captured in a way that’s easily accessible to the entire team?
• Does the team discuss learnings or activity?
• How are learnings shared with the team? 
• Are some people hoarding learnings, rather than making them accessible to the wider team?

Asking Uncomfortable Questions

• Do we face into and ask all of the questions prompted by what the data is tellings us, even the uncomfortable ones? 
• Are there any questions that people are avoiding? If so, what are they and how can we tackle them?

Creating And Developing A Learning-First Team

• Do we hire voracious learners?
• Do we have systems in place to help each member develop?
• What else can we do to prioritize individual growth of our team members?

Thanks to Lauren Bass for helping me produce this content.