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Build data to validate customer insight and build confidence in your offer

Customer discovery is messy; it never follows a simple linear path from ignorance to enlightenment. Part of the reason is the lack of data to really guide us as business owners. We rely on a lot of intuition, feeling our way to traction.

But this can be slow - and take us down many wrong paths before we find the right ones.

Data beats intuition every time.

But in the early days we just don’t have enough. Contrast this with someone, like Tesco or Apple, who have so much data they can practically rely on algorithms to do the customer discovery, spot pain paints, validate them with experiments of which we’re blissfully unaware and kill their ideas dispassionately if they don’t meet their hurdle rates.

Good business owners, however, find ways to build data, because that’s how they build confidence before they invest their time, money and passion.

And unlike those big data monsters, we can move faster, have lower thresholds to invest and much less reputation to lose if it all goes wrong.

Here are two simple ways to bring a bit more quant into your customer discovery:

1. Score the pain

It’s relative of course, but there’s frankly no point getting out of bed if you’re not solving an acute and ideally urgent pain for someone. What I call “mild interest” can always be deferred to next week or next year. You’re looking for an emotional intensity that screams “HELP ME NOW!”

When I work with business owners I always start by asking them about the emotional state of their customer. They nearly always say “They’re frustrated”. I should play one of those Family Fortunes buzzers when they do because frustration isn’t intense enough. We’re all frustrated. Hell, I spend my life frustrated – but I only act on a small fraction of those frustrations.

So I help them look deeper – “…and why’s that?” is a good prompt to get to “Defeated”, “Despair”, “Resentful”, “Exposed” etc. These are pains worth overcoming, because you know life would be better without them – and that’s worth fighting for – or paying for.

I built a simple excel tool with a bit of objective scoring for these emotional states, 1 for frustration, 3 for Disgusted, 5 for Ashamed etc.

Then I look at how intense that emotional state is – Mild, Moderate, Severe, Excruciating, again I apply some scoring.

And lastly, I look at how frequently the pain is experienced – all day, every day, every few days, once a week etc. Again with some scoring.

Obviously the higher the score the stronger the case for a solution – and the likelihood that there’s a business opportunity. If you’re fixing things that people don’t care about that much or that enough, well, good luck.

It’s a pretty quick exercise, great to do as a team to prompt discussion and alignment. DM me if you want me to send you the excel, it’s not pretty but it can help.

2. Build hypotheses you can test yes/no

Part of the reason customer discovery can be messy is because we think we’re just looking for insight. All that active listening produces hundreds of pages of notes, thousands of post-its – and in my experience at least, a whole load of confusion.

We need a system to help us make sense of the insight – and that’s where the scientific method comes in:

  1. Define hypothesis (what you believe – it could come from some great customer discovery sessions).

  2. Test hypothesis (in an objective, and ideally quick experiment or two).

  3. Build data (for analysis and decision-making).

The key to this is to make your hypothesis something you can get a binary response from – yes or no – and make it pretty narrow, so there’s less room for subjective biases to creep in.

So, for example, if during customer interviews I keep hearing business owners talk about reading startup books but struggling to put them into practice, I could build a hypothesis like this:

I believe my customer has read ‘The Lean Startup’ by Eric Ries

This is better than “I believe my customer is interested in starting their own business”, or even “I believe my customer reads books on starting their own business”, because it’s really specific, and it will generate a fact rather than an opinion or a hypothetical “I want to read 'The Lean Startup'”.

I could then test a second hypothesis about the emotional state after reading The Lean Startup and now sitting at your desk – “ignorance”, “intimidated”, “panic”, “confused”. Pick one and listen out for it unprompted – or shift to test another if you keep hearing others.

So, whilst you don’t want to behave like a robotic survey monkey firing hypotheses during customer interviews, having a list of 7-10 beliefs you’re looking to validate can be a really helpful way of building data as well as new insights in an interview or even an observation experiment – and definitely a survey.

And this builds data.

Imagine how much more confident you would feel if you could look at a table of data that had 20 customers all answering yes to beliefs that supported the idea for your business. Versus say a slide with a load of quotes.

For customer discovery, make your write up in excel rather than powerpoint.

Business is based on zeros and ones. Especially ones.


By the way, this is what the Familiarize product I’ve built does – check it out at It’s precisely there to help founders know what to do the day after they’ve finished The Lean Startup, so they avoid the emotional states above! The first workshop on your customer’s struggle is free, so you have nothing to lose.

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