Cheat Codes: Early idea validation part II: uncovering insights

This blog is part IV of a series. See part I here.

Armed with core hypothesis in your opportunity space - the known unknowns - every founder needs to learn from customers, and learn quickly. But quick shouldn’t sacrifice depth. We need to dig deep with customers to understand their true behavior and motivations, and get to 2nd order insights.

Uncovering Insights

Now it’s time to talk with customers. Go where they are! I mean that both physically (e.g. if your customer is a sales rep, go to a sales conference. If your customer is a pet parent, go to dog parks) and virtually. My favorite virtual, scrappy places to start understanding my customers better and sourcing people to have 1-on-1 conversations with are LinkedIn, Facebook groups, and Reddit forums.
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While ultimately you’ll want to narrow down to a focused ICP, right now the key is going broad and talking to many types of people in the broader customer bucket. Benefits of starting broad are:

• It will help you observe trends or differences across them which in turn, will help you be more precise with your ICP later (e.g. size of company, specific industries, 
• When you inevitably pivot later, you’ll have an understanding of other customer segments, tangential pains and behaviors. It also helps identify and differentiate between economic buyers (who controls the budget), stakeholders, and users.
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You may be armed with the outline of the must-be-true statements that need customer validation, but keep in mind that people struggle to articulate their needs accurately. If tech companies had asked users what they needed, they might have said bigger hard drives. But what they truly needed was a way to access their files anywhere, anytime, without worrying about physical storage limitations - and now we have cloud storage. This illustrates that people often don't fully grasp what they need and are constrained by what they currently know. The key is digging deeper to understand the underlying behaviors and motivations.

Measurable Impact Insights

If you talk to an SDR, they may share that they can’t make enough cold calls in a day and that dialing takes too long.They want to make more calls. Solution - build a robo dialer for them that can dial many prospects at once, giving the SDR what they “want” (more calls) and better odds for a connect (this exists!). But if we ask an SDR what they’re held accountable for, they’d tell you it’s building pipeline. The number of calls they make is just a method for getting enough prospects on the phone to convert some to a lead. If they could make no calls and still generate pipeline, they would be even happier!

Start by asking your customer what their priorities are for the year. And then keep asking why until you both know what specific metrics they’re focused on and why they think that matters to them and the company. Once you understand what they care about, what is the specific goal? How much improvement would a new solution need to have to that metric to be meaningful (e.g. better enough)? 

Second Order Insights

While we’re having the many conversations with founders, customers, and experts in a domain, we share and listen to insights. Oftentimes, we all have the exact same insight about a customer. This makes us pause. Do we know anything that others don’t? 
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At MVL, we continuously push ourselves and founders to get to second order insights - the insights below the surface that ladder up to the insight we all know. Getting to these second order insights is how you build a company that can disrupt and win.

Tips & Tricks

• Focus on Discrete Experiences: Guide discussions toward understanding the customer’s real-world scenarios rather than theoretical examples. What’s the last time they did ‘x’? What exactly do they do? If you can get a customer to actually show you, even better! Not only does this help understand underlying needs but the current behavior is also your competition, even if it’s not a real product.
• Frequency and Severity: It’s much easier to sell something that a customer needs to use a lot. Particularly if you’re trying to change someone’s behavior. How often does the customer think about this metric or do this workflow?
• Show Something to React To: While early validation is still focused on understanding the opportunity, and not trying to gain conviction in a particular solution, it can be helpful to introduce wireframes to gauge reactions. Most people are better critics than they are visionaries. Coming with a solution can allow you to ask things like - what would you do if you had this solution? Instead of asking a customer if they like a solution, try to understand what they would do with it and what it would allow them to do outside of the solution.
• Keep Asking Why: Use the 5-whys technique to keep digging deeper to understand underlying motivations. Each response you get from a customer becomes the basis for your next ‘why’ question, allowing you to peel away layers of symptoms to get to the root cause. While it’s called “5-whys”, the number of times you should ask ‘why’ really depends on the responses you get and the depth of the root cause.
• Seek Patterns, Not Anecdotes: Finding an instance that validates a hypothesis feels good, but we want to identify themes across customers. On the flipside, human brains naturally seek out patterns, even when they don’t exist - called patternicity - and can lead us to false conclusions. Ensure you’re talking with a diverse set of customers and continually aggregate and synthesize.
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Mini Case Study: Magnify

Magnify learned a second order insight that drove their product vision. Churn is a growing problem for B2B SaaS companies. The current solution is building out customer success teams to monitor and reduce churn. This is expensive and not scalable.

Through customer discovery, it was clear that organizations don’t have visibility into the customer 360. At first glance, organizations need visibility into indicators of churn, who might churn, and how to stop them from churning. This insight was true across many customer interviews and had the team stopped there, Magnify would have built an analytics solution that surfaced these insights.

But the team kept digging to understand why organizations don’t build this in-house today and what a solution to the problem would allow them to do. Customer success or AEs then had to do something with these insights - they had to manually perform actions to stop the churn. And, typically once they had these reactive data points, it was too late to save the accounts.

Those second order insights led to Magnify as we know it today, a way to proactively manage the customer lifecycle with AI-driven automated workflows.

Common Pitfalls

We’ve talked about what to do. Watch for these “gotchas” as you go.

• Not Validating Core Hypothesis: If you’ve outlined known knowns and must-be-true statements that need validation, then you know what you need to answer in early customer research. It’s important to make sure you learn enough in these areas to move them into “known knowns” and de-risk the idea. You can do this by outlining a general research script that will help you validate those hypotheses.
• Recency Bias: Avoid making decisions based solely on the most recent interview or information. It can lead to impulsive decisions that disregard prior learnings. You can avoid recency bias by continually aggregating and synthesizing feedback across all conversations.
• Lack of Data: Back to the discussion on pattern vs anecdote. Make sure that you talk to enough people so that you have insights across many types of customers, across any necessary dimensions - size of company, role, types of customers they sell to, vertical, etc.
• Lack of Focus: Control the urge to solve everything for the customer. Leverage the early validation to understand the breadth of opportunity, hone in on the patterns, and gain conviction in a starting point. (Note: It may be helpful to paint the picture of the future ‘solve everything’ in a pitch deck but be clear where you are starting and why. Stay focused other than the one ‘future vision’ slide.)
• Asking if They’ll Buy: The inclination is often to ask a customer if they would buy your product. But this is the time for validation, not selling. And, the answer to this question is not very predictive of whether they will actually buy when you launch your company. Listen for positive indicators like them asking you to let them know when they can buy it.
• Happy Ears: Seeking and hearing only positive affirmation in customer views is detrimental and a waste of time. Actively leaning into objections and why someone might not want the product is actually helpful to understand objections clearly and build conviction that you can overcome them. Similarly, if you never listen for objections, you delay the inevitable, and waste time building something that is not the right solution or a big enough opportunity.
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Summary

The basics of opportunity validation are straightforward but continuing to push ourselves to dig deeper and uncover 2nd order insights is where the challenge and fun begins! Doing so will set you up to move faster and build compelling products. 

As we build conviction around an opportunity space, we want to start developing more conviction in a solution. While we may have used initial concepts with customers for them to react to something, we also want to approach solution validation in a more rigorous way. This deserves its own deep dive, so stay tuned for Part 3 - Solution Ideation & Validation.

To learn more about MVL, read our manifesto and let’s build a company together.