To increase momentum and gain headspace, they hire people for specific roles, such as head of product or customer success.

Then, several weeks later, they realise that the headspace didn’t free up. On the contrary, it shrank.

Why? Because they are outsourcing tasks instead of problems.

Outsourcing tasks takes time and headspace. You need to detail what needs to be done, which is exactly the thing that takes some time to formalise. And then, you check back if execution went accordingly, step by step.

As a result, some things don’t even get outsourced to your team. They get stuck inside your mind as you are stuck detailing everything. This kills momentum. I call this:

Delegation Stagnation

Founders may suffer from it for a variety of reasons

• They feel like they are burdening others when giving vague problems

• They feel like they should know everything before handing over things

• They want to be/feel in control of everything (neurotic tendencies)

• They have perfectionist tendencies, so all details should match their ideal vision

• They are insecure that if they don’t own the problem themselves, they might fail, and handing it over is a risk

All reasons are very human, yet you can’t let this stop your startup from growing. Luckily, there’s a way to approach this.

You should shift from handing out task/solution ownership to handing out problem ownership. And in doing so, you should onboard your team into your learning process. Really, they will get it.

Your team is a group of people that is eager to learn. If you listen to any podcast or read any book by a seasoned CEO, they often say that they needed to learn how to delegate.

You can just say this to your involved team members:

“Hey, I want to improve on giving you more ownership of problems, so in the coming weeks, I will be giving you problems instead of concrete tasks. I want to check in with you on how that is going, and evaluate and think of the best way for us to work together”

In this way, you create a feedback loop with the people you are learning with. Everyone knows they should talk to customers to learn what they need; your team members are no different.

Additionally, because people now own the problems they are solving, they will likely work with more drive towards the goals. Win-win!

So, do you suffer from delegation stagnation at times? Do you have any other tips for fellow founders to overcome it?

• PMFit: How well does your solution align with your target market?

• GTM (Go-To-Market): your strategy to get the show on the road

• GTMFit: How well does your GTM and target market align?

The building blocks are up for debate. This is my synthesis of going through dozens of frameworks on product, product-market fit, and GTM.

For nailing your product-market fit, check out this

• Free Market Fit Canvas + Feedback Tool

• Product-Market Fit Scale (infographic to ‘measure’ PMFit)

For nailing your GTM, check out these legends

• Alexander Estner’s GTM Foundation + Checklist

• Maja Voje’s ICP Sanity check + 14 GTM Miro Templates

• FletchPMM’s Robert and Anthony have great content on GTM.

To understand why product-market fit is elusive, thinking about completing a business model canvas is helpful.

Answering each of the nine building blocks is easy.

However, startups never have just one idea for any building block. They easily have four.

So, they end up with over thirty answers across the canvas.

Generating options is the easy part. Selecting the right ideas is the hard part, as my research

Common dilemmas

• Which segment is our beachhead, because each has certain benefits?

• Which JTBD is their main goal after talking to five different managers?

• What is the key problem, among the three you identified?

• What is the dominant competitor, among the five you’ve heard in interviews?

The solution to identifying the right answer is fit.

All these answers should fit together cohesively. You can imagine that among those nine building blocks of a successful business, there’s more than one fit.

In theory, for nine nodes, there are 36 connections possible. That would be very complex. I’ve made it simpler by identifying the key building blocks and linkages for product-market fit.

The 9 building blocks of product-market fit

When it comes to product-market fit, I’ve broken it down into nine building blocks.

Your task is to map out all your options for each segment and find the best set of 9 answers that are cohesive.

In the diagram below, you can see the 11 most important fits for your product-market fit. You can use these to identify the right set of answers.

Evaluating fit using your gut

Luckily, humans come with an intuitive fit assessment tool: our gut. Consider you are launching a taxi company, and are completing the canvas for the business segment.

• Customer: Bob, the business traveller

• JTBD: Needs to be at the airport at 05:00 AM

• Problem: However, he lives 100 km away from the airport

You get an idea of why that might be problematic. Bob needs to travel to the airport to catch the flight, so need to find a solution—hopefully your taxi company.

Do you have a blue car problem?

But now check out this one.

• Customer: Bob, the business traveller

• JTBD: Needs to be at the airport at 05:00 AM

• Problem: However, his car is blue.

You just feel it doesn’t make any sense. If you don’t, go see a doctor (me). You don’t want a blue car problem in your startup. Here’s another one, to test your gut feel.

• Customer: Bob, the business traveller

• JTBD: Needs to be at the airport at 05:00 AM

• Problem: However, he has skipped breakfast.

I still feel it doesn’t make a lot of sense, but a little more than his car being blue. You may feel that fit is a spectrum.

Evaluate your fit with this tool

For your startup, you should answer these nine building blocks to get a sense of your product-market fit. To help you with evaluating fit, I’ve made this tool, free to use for everyone.

The importance of fit is a fledgling insight of my scientific research on early-stage startups, part of my PhD that I’m finishing now.

Additional readings on fit

• The updated Market Fit Canvas (used with over 200 startups)

• A free AI tool to get feedback on your market fit

• Free Google Sheet + A4 Printable Template

• Instructions on how to use the framework

The rationale

Founders should be able to answer three questions:

1. Why is the customer in the market for a solution in the first place?

2. Why are the current alternatives on the market not good enough?

3. How is your solution better?

This gives three focal areas, which the above framework addresses.

• Customer

• Competitors

• Your solution

Market Fit Feedback Tool

To use the framework, I’ve made a web app that gives feedback and a 0/100 score. Some screenshots below.

Take me to the tool

Explanatory tooltips that help with your input

Get overarching score

Feedback per building block

Optimised for desktop, but works on mobile

Free Templates

Digital

If you want to save your work to share with yur team, you can use this template.

Get the free Google Sheet Template

Printable worksheet for workshops

A post-it optimised worksheet! Print on A4, regular post-its fit in the box. Grab those post-its and run a Market Fit Workshop yourself.

Market Fit Canvas Worksheet

3.17MB ∙ PDF file

Download

Download

How to use

Likely, you will have multiple answers per building block. The goal is to make single narratives that fit together well. This might mean you can make 4 different stories for each customer segment.

For instance, for the ‘hasty family’, these could be the answers.

1. Customer Archetype: Hasty Family

2. Job to be Done: Get to the airport complete (with everyone and everything).

3. Root Problem: However, they have three young kids, six suitcases, and are leaving during the morning chaos.

4. Dominant Competitor: Therefore, they could drive their own large SUV and park it in long-term storage.

5. Competitor Flaws: However, loading the car is a “Tetris” nightmare; the parking shuttle is slow and hard to manage with strollers/heavy bags.

6. Consequence: As a result, they arrive at the gate exhausted, sweaty, and realise they forgot the toddler’s favourite toy in the trunk of their car 5 miles away.

7. Solution: Luckily, there’s a “Full-Service Family Van” transport.

8. Feature @ Problem: They provide an extra-large vehicle with pre-installed car kid seats; the driver assists with a “final check” list.

9. Feature @ Competitor: Curbside drop-off that handles luggage directly to a porter, skipping the parking shuttle entirely.

Customer (1-2-3)

In steps 1, 2, and 3 you need to lay out the situation of the customer.

1. Customer Segment: Who is this, specifically?

   1. Which beachhead customer segment are you talking about?

   2. Make it a real person, so ‘Head of HR’ instead of ‘HR Department’

2. Job to be done: What is this person trying to achieve?

   1. What is their Job to be Done?

   2. This is not your or your startup’s job to be done!

3. Problem: What obstacle stands in the way of achieving that Job to be Done?

   1. Understand that a problem and a job is not the same thing.

Competitors (4-5-6)

Here you identify that it’s not a blue ocean, and if your customer doesn’t buy you he does something else.

4. Dominant Competitor: What is the most dominant solution they use if they are not buying you?

   1. Base this on customer interviews

5. Competitor Flaw: What are the shortcomings of this solution?

   1. Why does it suck?

6. Consequence: What happens as a result of the current best option and not fixing the underlying problem?

   1. This must be something people really want to prevent from happening. It should be painful, such as ‘wasting €10k a day’ or ‘employees get fired’

Your solution (7-8-9)

Only now can you start yapping about yourself. But, if you crafted step 1-6 well, your solution should fit like a glove to the problem you just sketched.

7. Solution: Pitch your solution in 1 sentence.

   1. Explain the product category. What is it that you make

8. Benefit A: Explain how your solution fixes the problem

   1. Make sure your benefit actually tackles the problem of step 3

9. Benefit B: Explain how your solution addresses the shortcomings of alternatives

   1. Make sure that the problem you framed around the shortcomings of the alternatives (step 5) fits really well with this benefit

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In my experience, founders spend time most time on competition and their solution, rather than understanding why they are buying in the first place.

1. Why is your potential customer on the market for a solution in the first place?

Understanding why people are on a market to buy is incredibly important. This reveals a hidden mechanism.

• AirBnB: Because most people don’t have a bed and home in cities they travel to

• Uber: Because they need to get from point A to point B

• Notion: Because our brains are too limited to capture everything, especially in teams

• The wired telephone: Because people are not in the same place

• The steam engine: Because mines were flooding with water

It might feel stupid, but formulating your problem and job to be done without talking about competition is incredibly hard. Can you do it for yours?

2. Why are the current solutions not good enough for the customer?

This is where founders spend some time. They look into the market and flag features of competition. But features in itself is not enough. People should complain and bitch about.

• AirBnB: Hotel rooms are often small and don’t have a nice experience of being at a home

• Uber: Waiting for a cab without knowing when it comes sucks

• Notion: 76 scattered Google Docs are hard to navigate

• The wired telephone: Because sending letters takes 2 weeks

• The steam engine: Because horses die and can’t work 24/7

Now, these complaints will differ per segment. The nature of the competition and shortcoming can be a way to segment your market.

Notion can target people that use Google Docs than teams that do everythig over Slack without proper documentation. This requires a different marketing message and perhaps channel.

3. How do you do it better?

This is what founders usually bite down on. They list how they are better, which features or benefits they have compared to competition. Applies to both hardware, medtech, and deep tech.

• AirBnB: Local homes with a bed that make you feel like home

• Uber: Application to order and track a cab to take you home

• Notion: Interconnected and dynamic wiki for your team to keep good overview of documentation

• The wired telephone: Hardware to speak to people across country

• The steam engine: Machine that converts coal into energy to pump water out of mines

So, these three questions explain a short story on why these innovations might have gotten traction.

If you write down great answers to these three questions, you are building a cohesive narrative of why your startup will succeed. At some point, it should feel logical that they will buy you. That is what product-market fit is all about: the arguments should fit each other like a glove.

Workshops for accelerators

Stress test your product-market fit

By building such a narrative, you can stress test your product-market fit easily. Based on many workshops I’ve done, this is harder than it seems. Try out this free template, the Product-Marekt Fit Logic.

Get free Google Sheet template

Get free Google Sheet template

🔥 Patron Content 🔥

Premium subscribers have access to a custom GPT that has been fed all my writings on product-market fit. It scores your input on all building blocks:

Get the GPT below:

Doctor Market Fit

Get your product-market fit score (0/100)

💡 Sorry Jesus, lord of AI, for I have sinned, but I’m tapping into the AI hype now. Yes, you read that correctly. I’ve made an AI tool that helps to get a sense of product-market fit…

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9 months ago · 17 likes · 1 comment · Jeroen Coelen

1. Goal: Build a customer theory

2. Structuring and starting the interview: Keep your baby in your bag

3. Framing the interview

4. Don’t just ask for problems

5. Identifying the right JTBD ⬅️ Today

6. Understand the value in your value proposition

7. Using the film reel technique to get detailed explanations

8. Six techniques on how to wiggle out extra information

9. Getting your baby out of the bag

10. Crafting your customer theory

In constructing our theory of the customer (Chapter 1), we should understand why this customer is in the market for a solution in the first place.

The previous chapter laid out the basics of problems and jobs to be done. Consider this chapter an advanced deep dive into how to apply these ideas in your interviews.

The tactics will help you isolate the right Jobs to be Done for your startup. That’s quite important. Why?

Because if you know why customers hire your solution, the rest of your entrepreneurial journey becomes much easier, both on your problem-solution fit and GTM strategy.

To name a few, knowing your JTBD can give you:

• Easier solution scoping: you know what is essential and what is nice to have

• Precise segmentation: higher conversion rates when targeting

• Tailored messaging: potential customers respond more

• Improved positioning: customers understand you better

Sounds neat, right? Therefore, this chapter still focuses on building blocks 1-2-3 of the PMFit Logic (image below), which answers: why is this customer on the market for a solution to begin with? The JTBD is a key answer to nail.

5.1 Focus on emotional jobs to be done

JTBD-focused questions reveal the customer’s end goal. Such questions can get two types of answers: functional and emotional. Let’s see what the functional answer looks like (reiterating examples of the previous chapter).

Q (you): “What do you use Substack for?”

A (me): “To send a weekly newsletter”

That’s boring; it doesn’t provide a rich explanation of the ‘why’ behind my behaviour. Why do I do that? The other question might evoke something more.

Q (you): “If I may ask, what are you trying to achieve with your Substack?”

A (me): “To build a decent following of founders and build my personal brand”

It’s slightly more aspirational, but still, both answers are very functional jobs to be done. It’s fine to understand these, but this isn't always what primarily drives people.

It echoes what we did in the previous chapter, but we didn’t fully unpack it yet. For that, we need to focus on the emotional jobs to be done.

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• Talk to customers

• Find your specific niche beachhead market

• Build something small (MVP) instead of a big vision

• Try to sell instead of fishing for compliments

• Move fast and iterate

But then I realise and get frustrated:

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The advice isn’t untrue. The general idea works.

The tips are not unknown. Most struggling founders have heard these ideas.

(This ‘Not X, But Y’ is not AI-generated, pinky promise)

The problem is elsewhere: the tips are bullshit because they exclude the nitpicky details of the execution.

As a result, the tips become empty mantras that founders repeat in front of the mirror, without giving them the tools to evaluate if they are doing it well.

Consequently, founders get lost. Here’s what to ask yourself instead:

1️⃣ How are you talking to customers?

Are you having fun chats with your demo on screenshare or digging deep to truly understand them? Are you proposing follow-up calls? Are you tracking who says yes and who says no to understand who is your ICP? More on this.

2️⃣ How have you identified and validated your beachhead market?

Have you defined ‘SMEs’ as your beachhead or have you sent 500 manually crafted LinkedIn DMs/emails over 8 weeks to find out which message resonates with which target group? 6 emails sent, you say? Wow, impressive. More on this.

3️⃣ Is your MVP really an MVP?

Do you have a prototype that works, or are customers actually shouting ‘OMG, YES THIS IS HELPING ME SO MUCH?’ Is it the minimum thing you could’ve built? Or did you just slap the label ‘minimum’ on your Notion Page? More on this.

4️⃣ Are you trying to sell or just fishing for compliments?

Listing all your features with a sales deck open is not a sales call. It is a push call. You want to learn how to organise your sales calls. Read books on this (e.g. Demand Side Sales, Gap Selling, or Rob Snyder)

5️⃣ Are you adding features as a proxy for progress?

Iterating fast is not about imagining and building as many features as possible. Iterations happen beyond your product. You should iterate on your marketing, channels, copy, messaging, and positioning. More on this.

Do you need help with applying the ideas correctly and getting your product to market? I’ve got room to take on two startups for mentoring the coming months. Link in comments to check out my way of work and pricing.

🔥Jeroen’s Hot Take🔥

Five additional reflections and frameworks. First one is on the house:

1. Not all evidence is equal

Many of their experiments referred only to interviews. For solution validation, that can be risky, because ‘bitchin’ ain’t switchin’. For instance, their pricing interviews were an airball. There are many frameworks to assess evidence, but they are probes, not truths. Take them as thinking tools to sharpen your mind.

Below is the non-linear confidence meter by Itamar Gilad. See how surveys are still ranked at 1-3, whereas actual results get to 7-10? That’s a huge gap. Thread lightly.

2. You can’t really validate a startup idea

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AI seems like a simple value unlock

However, when AI came along, attention for value unlock shifted towards AI. People were never really interested in PMFit; they were attracted to the potential money behind it.

That explains the superficial understanding of most people, and the lack of desire to go deeper, just like most AI evangelists don't understand neural networks or cognition, yet they rave on about AGI.

If it’s your first tech bubble, you can be easily persuaded

I guess this is the circle of news and hype, which for some reason keeps repeating itself. Still, my thesis is that it's mostly new gunslingers that jump on the hype train.

If you haven't been part of or invested in any tech hype, everything seems new and filtering out false promises can be challenging. After doing two or three, you get the drill.

It's like a 16-year-old girl falling for the wrong guy time after time, believing the promises of the next one that says 'he's really different'. After some breakups, she learns to avoid such guys.

We are really bad at predicting technology

Basically, tech bubbles, including AI, are like predatory bad boyfriends you learn to avoid in your teens and twenties. After big data, blockchain, NFTs, the metaverse, AR, AI is the true one that 'really matters'. Do you believe him?

We generally suck at predicting when technology will come about. See this graph with predictions of AGI. It’s always 10-20 years away or something. Sounds familiar?

“Fusion power has been one of those things that's been "only 20 years away" for about 50 years now.” - Source

In research reviewing tech forecasts, up to 80% of the predictions are off (Source + Source). Why, all of a sudden, did we get better at predicting AI’s future?

Technological innovation is non-linear, and a sudden jump in performance we’ve seen in the past years doesn’t mean anything for the future. It might plateau for 25 years, who knows? Nobody.

But Jeroehoeen, people do demand the iPhone.

Well, do they?

The masses demanded communication at a distance. The growing adoption of laptops and smartphones shows that.

Before that, we had telephones.

Before that, we had electrical telegraphs.

Before that, we had postcards.

Before that, we had smoke signals (kinda).

The iPhone, at launch, was an Mp3 player with phone functionality and a web browser. Much of the web wasn’t optimised for mobile yet, like it is today.

The App Store launched a full year after the first iPhone was released. Spotify was non-existent, iTunes was pay-per-song. The camera just had 2 Megapixels (Nokia N95 had 5MP).

All things considered, the first iPhones were relatively limited compared to the mini PCs we carry today.

Despite those ‘setbacks’, they sold over 6 million units in the first year.

So, yes, the introduction of the iPhone resulted in demand, but it didn’t create it. Why? It was always there.

Demand is like gravity working on a mug on a table

An interesting analogy I borrow from Ramoglou & Tsang (2016). They equate markets and demand to a mug on a table that doesn’t fall despite the gravity.

The force of gravity surely pulls the mug towards the centre of the Earth. However, the table blocks it. The moment the table is removed, or the mug slides off the table, the gravity starts moving the mug. The force is enacted.

Similarly, in markets, the market pull/need is the force. There are customer desires which can be met. However, sometimes, there’s not the right product for that, so no demand as a result. But the need remains.

When the right product gets introduced, i.e. the table is removed, all of a sudden, those forces turn into visible demand: people buying iPhones.

Why should you care?

That is why demand can only be fully demonstrated the moment actual sales are happening.

Everything before that is a proxy. All prototypes, problem interviews and other experiments that don’t involve transactions are insufficient to validate demand.

🔥 Jeroen’s Hot Take 🔥

There will be many people disagreeing with me on this post. I’ve held this argument many times, and there are always people who go against it. Here are the common complaints:

1. “But people demanded iPhones. They were camping outside”

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How to use

• The position on the x-axis says something about how strong a signal is related to product-market fit.

• 1000 followers on Instagram in itself are not a strong sign of product-market fit, whereas 10 customers happy in a full price pilot are.

• Indeed, those 1000 followers might convert to paid pilots, but we don’t know what the conversion rates are, and if they will be happy. Therefore, it’s a weaker proxy.

Free PDF version

Pmfit Scale By Dr Market Fit

1.17MB ∙ PDF file

Download

Download

🔥 Jeroen’s Hot Take 🔥

This is version 4 of my product-market fit scale. I feel this might not be the final version. Here’s why, and what options I considered.

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How can I shorten my time to market?

That means, how can I get to sales or paid pilots as soon as possible? Often, people build an MVP for this. That is a great move in itself. However, the M in MVP often is not honoured: many MVPs have way too many features.

I see two reasons for this:

• Too many features are considered the core

• The beachhead segment is so broad that you need many features to satisfy all of them

I’ve written many posts (here, here, here, or this one) on defining your true beachhead segment. Still, a narrow beachhead doesn’t solve all problems. How do you go from a narrow beachhead to an MVP?

Identify true key features with MoSCoW framework

The MoSCoW framework, developed in 1994 by Dai Clegg, asks four questions:

1. What features MUST my first version have?

2. What features SHOULD my first version have?

3. What features COULD my first version have?

4. What features WON’T my first version have?

Are your founders’ beachhead markets too vague or broad? Are they building instead of talking to potential customers? I run two hands-on workshops for accelerator programs that fix these issues.

Check out my workshops

In answering these questions, you need to go through your mental or actual database of insights from sales calls and problem interviews.

1. Must Have:

   1. Features that 90% of your beachhead needs

   2. Essential to addressing the main Job to be Done

   3. Hair on fire problem stuff

   4. Won’t buy you without this

   5. Conclusion:

      1. Don’t skip this

      2. Make sure you have the data to support it—‘5 people said they were interested’ is not strong data

2. Should Have

   1. Features that generate value but don’t serve the main Job to be Done

   2. 60% of customers would seriously benefit from this, but can still generate enough value without it

   3. Conclusion:

      1. Include these in the later releases

      2. But don’t add before your Must-Haves work greatly

3. Could Have

   1. Cool ideas that do not add to the main job to be done

   2. About 25% of customers could seriously benefit from it, and future features built on this might unlock a new segment.

   3. Conclusion

      1. Postpone for now, unless you are ready to double down on that new segment.

4. Won’t Have

   1. Feature ideas that will never help more than 5% of your target market

   2. Features aimed at completely unrelated jobs to be done

   3. Often are the result of creative brainstorm sessions or strong opinions expressed by 1 potential customer

   4. Conclusion

      1. To hell with it

      2. Kill it with fire

Common challenges with this framework

• Problem: “Just 2 features feel too small to generate value”

  • Solution: That’s an assumption; make sure it’s true: pitch these two features before building anything with a brochure test. 10 pitches, and you know if you are on the right path.

• Problem: Some founders have limited market input; therefore, they are reasoning about which features might help their customers, rather than basing it on actual expressed interest/sales.

  • Solution: go out on the market, do 20-50 sales calls (even pre-launch) to see which aspects resonate the most.

• Problem: The beachhead market is too broad (all SMEs with $10M+ revenue). Your beachhead should be rooted in behaviour, not firmographics.

  • Solution: If you can’t answer the first 6 out of 9 questions (use this tool to verify), you need to talk to more people.

• Problem: I’ve got three features that 3 different groups of people like, not one that covers 90%

  • Solution: Your beachhead is too broad; you are targeting too many people. Unless you are launching in an inherently multi-stakeholder environment that needs all three from the start, you might want to pick one of the three to start out with.

Do you want a 1-1 session with me? I’ve got three mentoring slots available

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🔥 Extra Practical Examples 🔥

Whenever I run this with a startup, the above issues pop up. 95% of founders that can’t answer these questions with evidence just need to go to the market more often.

I mentored this construction startup that was very early stage. It was a new material technology that performed higher on sustainability aspects. However,

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The problem: limitations of the BMC

You probably know the Business Model Canvas (BMC). The canvas is likely the most used startup framework in the world. I don’t use it in my workshops. Why?

• The value proposition building block is confusing to most people

  • Nobody intuitively understands what it is.

• It overcomplicates the early stage: it maps a future business model, which is different from what most startups need.

  • Therefore, I prefer the Lean Canvas because it focuses more on the key challenges of a startups

  • And highlights the problem and solution as distinct building blocks

• Most important: It doesn’t show how things are connected. It suggests that coming up with 9 answers is designing your startup.

  • My research shows otherwise

Solution: The Business Model Toolkit

If you want to focus on how your building blocks connect, be sure to check out The Business Model Toolkit by Board of Innovation.

It gives you a set of cards to connect and visualise your business model. There’s a Miro-template ready to use!

Swapfiets bike lease example

The Toolkit allows you to simply visualise the exchange of values between parties, as per the above Swapfiets example: A monthly fee gets consumers a bicycle and on-demand repairs. It’s a fairly simple business model.

Whoop example with multiple stakeholders

Get the free Miro template

Whoop’s business model below is little more advanced as you can see. Making a business model visual like this is a great way to align your team on what the hell you are doing.

More examples:

There’s a PDF you can download with 50 examples over here. You just need to leave your email. Some examples here:

🔥Premium Guide: How to get more focus in a startup

Find your Minimum Viable Startup in five steps

1. Open the Miro-template

Get the free Miro template

2. Map your 5-year business model from your current business model

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The popularity doesn’t reflect its rigour, though. It’s not based on academic research meeting scientific criteria, and to be frank, it shows. The majority of the categories by CB Insights are self-reported by founders. Perhaps, therefore, the categories on this list are quite ambiguous.

How is ‘no market need’ different from ‘poor product’? How is ‘Ran out of cash’ on top? Is startup failure not, by definition, running out of money? That’s a tautology. It’s like answering the question ‘Why did the ship sink?’ with ‘Because it didn’t float anymore’.

The problem: timing

Among all these vague failure reasons, one stood out to me: the mistiming of the product. I’ve heard founders talk about ‘timing’ on podcasts when listing the reason they failed.

And I always feel a little uneasy. What do you mean, timing? In this article, I’ll do a deep dive in the mythical failure reason: Timing.

It’s everywhere

I see timing everywhere. On podcasts, blogs, it’s a dominant explanation. A brief survey among my followers on LinkedIn showed that 16% of founders attributed their first startup failure to timing:

Clearly, the idea of timing is prevalent among our community. But what does it mean?

How does CB Insights define timing?

So what is timing? Well, first, with timing, people don’t mean seasonal timing, like trying to sell snowboards in May. CB Insights defines timing in this report:

#10 – Release product at the wrong time

If you release your product too early, users may write it off as not good enough and getting them back may be difficult if their first impression of you was negative. And if you release your product too late, you may have missed your window of opportunity in the market. As a Calxeda employee said, “In [Calxeda’s] case, we moved faster than our customers could move. We moved with tech that wasn’t really ready for them – ie, with 32-bit when they wanted 64-bit. We moved when the operating-system environment was still being fleshed out - [Ubuntu Linux maker] Canonical is all right, but where is Red Hat? We were too early.”

Here, you can already see the sloppy definitions: “users may write it off as not good enough”. Does that mean the product was not good enough? Because that’s another distinct failure reason: “Poor product”

But the second part perhaps is clearer: “We were too early”. That echoes other quotes from founders CB Insights collected:

A drone company
”History has taught us how hard it can be to call the timing of a market transition. We have seen this play out first hand in the commercial drone marketplace. We were the pioneers in this market and one of the first to see the power drones could have in the commercial sector. Unfortunately, the market took longer to mature than we expected.”

A cancer diagnostic company
”Getting the technology right, but the market-timing wrong, is still wrong, confirming cliche about the challenge of innovating… We may have been right that [a specific cancer aspect] is “hot” and will be important in the future, but we certainly didn’t have enough capital around the table to fund the story until the market caught up.”

It’s psychological: externalisation

To me, this seems to be the founders’ claim that they knew it all and had the right idea and right product ready. It’s just that they were too visionary to get traction: the world wasn’t ready for them.

To them, timing seems a strategic issue, nothing else. If only they had launched their product about 5 to 10 years later, they would have been successful. This is where I smell bullshit. I hope I’m not strawmanning here, but I think timing is an umbrella excuse.

Timing can be a way to externalise your failure, away from yourself, so your ego doesn’t take a hit. To paint an extreme caricature, ‘we didn’t make any mistakes, it’s that the market wasn’t ready’.

However, it could be that sometimes timing indeed is the answer. To combat my pessimism, I will explore whether timing is indeed a valid explanation for innovation failure.

The investigation

To refute my cynical theory, I just need to find one case where it is clear that, indeed, timing is the best explanation for startup failure. If I succeed in my falsification (Popperian) inquiry, I can drop my grudge.

However, to investigate this, I can’t use recent examples of CB Insights. If you say the market wasn’t ready in 2024, likely it isn’t ready in 2026.

Therefore, I’m going through my mental rolodex of innovations that struggled with adoption, much longer ago, with one case stemming from the early 1900s. Because then, we have the power of hindsight to reflect: what did go down, really?

Through these cases, I’ll build a definition of what ‘timing’ means to me, and in the end, after digging through, I found one example that might fit the category. You be the judge. Let’s go.

First suspect: General Magic

The 1990 ‘smartphone’ that flopped

The first product that comes to mind is General Magic, the startup that made (one of the) first smartphones. The team had serious talent.

To name a few: Pierre Omidyar, who later founded Ebay. Tony Fadell worked on the iPod and iPhone and later founded Nest. Andy Rubin, who later founded and created Android. Kevin Lynch, who later became CTO of Adobe.

In 1994, the team launched an equivalent of the modern smartphone. They made the software and had initial deals with Sony and Motorola. The device had apps, internet, could make phone calls, and even had emojis. But chances are you never heard about it. Why? Because it flopped, hard.

Why did it fail? For numerous reasons, I’ll list a few.

• It was quite slow

• The battery was bad.

• For the internet on your Sony Magic Link device, you needed to plug in a cable. Yes, very mobile.

• The Motorola variant had a wireless modem with a data rate of 4800 bps (0.6 Kb per second); an MP3 song would take approximately 2 hours to download. The MP3 codec was released in 1994, so I guess not many MP3s were downloaded on the Motorola.

• The ‘internet’ you could use was not ‘the internet’, but some AT&T private network, as Blackberry did with their Ping messaging.

• Initial versions didn’t ship with a web browser.

• The screen sucked in most lighting conditions (no backlight), touchscreen was not very responsive.

• Furthermore, it was much more expensive than smartphones today: the retail price $800 in 1994 is equivalent to almost $2000 today. In 2026, only a fully maxed-out iPhone Pro Max with 2TB hits that spot, in a very mature market. Breaking the bank for a device that doesn’t work well? Not so surprisingly, it flopped.

Did General Magic fail because of timing?

Tony Fadell, one of the founding members, wrote a book on startups and talks about his experience. In his book ‘Build’ he mentions the timing was wrong. He often states that timing needs to be right. Also, he reflects that having a vision is different from shipping a product. But do they relate to ‘timing’?

Indeed, they had a vision that vaguely resembles a modern smartphone, but you can also see that they have chosen a lot of technologies that weren’t mature enough yet.

Is picking immature technologies a timing issue? You could also argue it’s a design failure. The designers and engineers imagined a device that the technology of that era simply couldn’t support.

Let’s take the touch screen. That technology sucked back then. Apple’s Newton (early iPad) flopped partially because the touchscreen notoriously sucked so badly that it was impossible to use.

Relying on that immature technology was a mistake. That’s perhaps one reason why Blackberry, for a brief time, took off as a smartphone: buttons were a more reliable user interface. And that is just one of General Magic’s many technological shortcomings.

Actual failure reason: betting on immature technologies

So when people say timing was the issue, sometimes it’s masking another failure reason: building on immature technologies. Which is a more nuanced take. I argue, if this is the case, don’t label it timing, because it doesn’t represent the situation well.

However, there’s an anachronistic aspect to it. We can only say this in hindsight for some technologies. Let’s unpack another example to see what I mean by this.

Second Suspect: Hydrogen Cars

It has been promised for years and years.

Around the year 2000, hydrogen as a fuel (for mobility) experienced hype. As more people realised there’s a limited resource of fossil fuels, hydrogen became the saviour.

Hydrogen packs 3 times the energy of petrol, and over 100 times the energy of an EV car battery. Sounds promising, doesn’t it?

One car manufacturer announced a project to make a hydrogen fuel cell car for the masses, ready in a couple of years. What happened next was a bubble. Car manufacturer after car manufacturer made a similar promise, as visualised below.

In 2003, amidst a post 9/11 Iraq invasion, cynically, the Bush administration invested over a billion dollars with the famous slogan, “the first car driven by a child born today could be powered by hydrogen.” Perhaps this investment was at the political peak of inflated expectations of the technology.

Between all the optimistic statements, researchers found increasingly pessimistic claims emerging (image below). You can see, for instance, how Ford went from ‘Full launch in 2010’ in 2002, to ‘Commercial in 2020’ one year later, followed by ‘If ever’ in 2004. That’s how bubbles implode.

Why did they adjust their prognoses? Simple: The technology was not ready yet. Common critiques: Expensive, lack of infrastructure, and storage issues.

Fast forward to today, despite the potential of the fuel, it’s still not ready in 2025. Hydrogen projects are being cancelled across industries. Airbus cancelled its hydrogen plane as the aviation industry doesn’t believe in it. EVs have made a bigger dent in petrol car sales than hydrogen.

Did hydrogen fail because of timing?

Were all those hydrogen projects ‘timed’ wrongly? Well, that is not the most accurate way of explaining what is going on. You can find ideas and prototypes for hydrogen cars dating back to 1806; that’s two centuries ago. That means that it has taken over two centuries, and we still haven’t figured it out.

Such a trajectory sounds more like a technological challenge, rather than a (strategic) timing issue. You can’t say ‘timing’ is the issue, because the technology hasn’t arrived today. That’s like saying people trying to build teleport or time travel machines failed due to timing.

Actual failure reason: hitting a technological ceiling

Hydrogen failed because it hit a technological ceiling. It’s just not feasible today, or extremely unviable. Sure there are some pilot projects, but you don’t see the mass adoption that was once anticipated.

Still, timing is sometimes used as an argument for the deep tech startups that hit these technology ceilings. For example, this innovative material, graphene, was expected to revolutionise storage and batteries. Despite the Nobel prize awarded for the discovery involving the manufacturing of graphene, it hasn’t lived up to expectations.

So far, it seems that timing is just a lazy way of explaining the lack of technological success. But what happens if we set the technology aside?

Third Suspect: Google Glass

When AR didn’t take off.

Let’s assume people figure out the technology. It mostly works. Then surely, we can find a product that is too visionary for people. There’s this saying that goes ‘Most Advanced, Yet Acceptable’ (MAYA).

Remember Google Glass, which was launched in 2012 and killed in 2015. Was Google Glass too early?

This is me in 2013, a designer friend who interned at Google—I remember being quite jealous—took it to the design school I was doing my Master’s. I remember putting it on, posting a Facebook picture, and you can see the comment that got more likes than my original picture.

The product hasn’t left a rich impression on me, but I remember it kinda worked. But, others have listed it—it was a prototype after all—as buggy, slow, overheating issues, clunky voice and gesture UI, and bad battery life. However, Google Glass had an interesting aspect that is not technological.

Today, bodycams and wearables with cameras are more common, like RayBan’s Meta Glasses. Back then, society didn’t like the idea of being recorded all the time. Even the term ‘glasshole’ was coined for people who wore it anyway. This illustrates the social aspect of innovation.

Was Google Glass mistimed?

Beyond the tech failure, this is an example where there is some societal backlash to new products. Did that stop adoption? Not really. Innovators often ignore the social backlash. For instance, mobile phones were not deemed necessary by the masses at the start.

This video—be sure to turn on English subs—shows the responses of people in 1998, explaining why they don’t need a smartphone: ‘I’m not that important’, or ‘Sounds annoying, being called when cycling’. Indeed, a very Dutch video.

In books, social acceptance is listed as a factor in innovation adoption. But that’s also because you can always find naysayers for any new technology. Was it really blocking? I doubt it was in this case. The product just sucked with a two-hour battery life.

Remember this Rabbit AI pin? It faced a similar backlash. But it didn’t kill the product. The fact that it barely worked, and was just expensive hardware running Android with a simple voice-based LLM that didn’t work well, killed it.

Actual failure reason: no killer feature

Similarly, Google Glass lacked some core killer features that make it highly desirable. Meta-glasses indeed are a thing now, but I barely see them in the wild (adoption seems niche), and I assume it’s mostly being used by TikTokkers to record easily in public, which is a killer feature for them. Google Glass just didn’t create enough value.

So far, the ‘timing’ failure seems to come down to two things:

1. The technology didn’t work or barely worked, and didn’t provide enough value

2. The technology was way too expensive for the little value it provided

Okay, it still is quite technological. But what if we find a technology that was ready, and only a social aspect was blocking. For that, you need to hop on my time machine to 1900—A machine I built for the sake of this article.

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Fourth Suspect: Elevator Buttons

A technology we take for granted, perhaps don’t really see as an innovation anymore are elevators. The vertical people movers originated in the 19th century. Back then, controlling a lift carriage was a skill, almost like operating a tram.

The liftboys needed to stop the elevator manually by operating a lever. The best liftboys could smoothly stop the lift carriage perfectly aligned with the floor it was heading to. Liftboys would sometimes, if the riders were rude or didn’t expect a tip, on purpose leave a gap to annoy the passenger. In my research, I even found a story of a German liftboy who was so elegant in his skill that he even successfully seduced a woman with it—he worked in a hotel anyway, so the next step was closeby.

The liftboy was quite technically apt and could do simple repairs without the need of a mechanic to come. It was quite a different profession as we see it today in most luxury hotels. Why did they disappear? In the first decade of the previous century, elevator buttons were invented.

The competitor of the liftboy: buttons

Elevator buttons enter the market in early 1900s. Indeed some of the new elevators are equipped with the buttons. But, not all. Actually, even though it’s economic, the elevator buttons didn’t take off as expected. That took half a century, only in 1950. What happened?

When the elevator was introduced, people were scared they would drop. Even though the mechanism that would stop a sudden plummet to death worked, the general public really wanted someone professional in the cabin. It made them feel safe. Even the few elevators with buttons still had a liftboy.

It was not only for safety: the liftboy was a host. He would do some unforced small talk, like somebody working behind a bar. That surely fixes the awkward floor staring we often do today. So why did liftboys stay for so long? It was a little bit like ‘this is how we do it’.

Why did it shift?

Most historians point to a strike of 15.000 liftboys (and other lift-related workers) in New York on a day in 1945. Estimated economic damages: $100M. That triggered a lot of building owners to equip elevators with buttons now and get rid of the liftboys: they prefer reliability over luxury.

That was the start of the demise of the liftboy. In the next decades, the carriage operators would make place for push buttons that the peasants control. We now only see liftboys in luxurious hotels or countries where wages are low enough to pay for it.

It’s important to note that in 1950, the Otis Elevator Company launched ‘Autotronic’, which allowed the coordination of multiple elevators of the same building efficiently. This contributed to the adoption. It’s never one thing, but the social backlash has never been so clear for an innovation, requiring a strike to push people over.

Actual failure reason: cultural resistance

I would argue that the dominant ‘failure’ reason for early push buttons for a long time was cultural resistance. The technology worked, but they were just too early to market. So by those lines, we might say, they mistimed their product. But that brings me to another issue I want to unpack last.

Timing hints at strategic deliberation

When you say, “We mistimed our product”, you are also saying you have considered postponing it. Based on my experience working with over 350 startups, I’ve never heard that line of reasoning.

“Maybe we should stop our startup and try it in five to ten years”.

Founders don’t say this, or at least not very often. Sometimes founders ‘shelve’ their product to pick it up later, but that’s just a way to deal with a breakup. I’ve never really seen founders pick it up again after five years.

It’s a verb, too

You might hear people say how they underestimated how long a market took to mature, or for supporting infrastructure to arise, or for technologies to develop, sure. But those are hindsight explanations that don’t have much to do with strategic intentions.

When you say timing, it’s a verb, like segmenting your market. And there you could say: we missegmented our market and therefore failed. But I’ve never seen a founder who wants to postpone the attempt to introduce his product.

Next, most founders don’t have an array of products to choose from. Startups mostly work on trying to get this one thing to work. Timing is not really a strategic consideration.

Debunking the timing myth

Based on my deep dive, I would argue that timing is often an inaccurate explanation of startup failure. It’s an umbrella term that shields the founder’s ego, but doesn’t really show what happened in reality.

Often, there are more accurate explanations for startup failure, like building on immature tech, hitting technological ceilings, getting social backlash, or meeting cultural resistance.

Calling it timing suggests that there is something temporal you can control as a founder, whereas most founders just focus on getting that one idea to market. If you encounter ‘timing’ as a failure reason, from now on, you should ask questions and dig deeper if you really want to learn something.

Verdict: The failure reason ‘mistiming products’ is a myth.

Stop telling yourself you are failing because of timing.

YOU MADE IT TILL HERE. Tell me:

Did you like this deep dive? Let me know by liking the post or dropping your thoughts in the comments. If you have something to nuance or disagree with, that’s even more fun 🔥

In this post, I will break down the specific traits that set the best founders apart—and the ones that will get you far in 2026.

Which trait are you best at? Let me know in the poll below.

Real focus

• They focus on getting their startup to the next level: identifying the next plateau to reach (rather than rushing to world domination from 0 sales).

• They know you can’t easily test 6 things at the same time; instead, they test them in three waves of 2.

• They are not easily distracted by shiny new objects (new tech, new channels, etc.). If something new pops up, they keep working on the thing they strategically committed to.

“People think focus means saying yes to the thing you’ve got to focus on. But that’s not what it means at all. It means saying no to the hundred other good ideas that there are” - Steve Jobs

Great at balancing short-term and long-term

• The best founders I worked with last year understood that their grand vision is 5 to 10 years away.

• They actively separate what they will do this year from where they want to be in 10 years. This helps them avoid working on things that are not relevant right now.

• Very often, these founders automatically prioritise sales, because they know exactly where they want to be number-wise.

True customer obsession

• The best founders know that in the end, it’s about the customer, not their startup. Obsessing over your customer rarely goes too far.

• They are in contact with many of their customers in informal ways, such as phone calls, and often have a group of “ambassador customers” who preach to their circles.

• For these founders, the customer is an endlessly interesting phenomenon to understand. Each time they find a new variant or discover a new aspect of their customer, they are excited to report: “You know what’s funny? This group does Y instead of X.”

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Systems thinking understanding of their business

• These founders think of their startup as a system they are building, and understand that changing one thing has consequences elsewhere.

• They can easily create a model or project numbers to get a sense of how the system works, but they don’t treat this as reality: they see this exercise as a way to uncover interdependencies.

• They understand that customers are a key node in their system, and easily steer the conversation back to how it links to the value they create for those customers.

Sales and an opportunistic mindset

• Their lead list is already populated, and they are doing 20 hours of sales per week.

• Some founders just see opportunities everywhere. Whoever they speak to, they can think of ways to generate value.

• They think in sales processes, such as defining the next step, making proposals, finding ways to help the customer, and making money.

“Jeroen, I’ve got three potential market segments to target, how do I select the right one?”

Here are three questions to ask yourself that often speed up your process.

1️⃣ Can we eliminate some markets just by reasoning?

A fitness startup I was mentoring sold over 100 hardware products across five segments. One of the segments was professional athlete trainers. Should they target those, as they had some very positive feedback?

My Advice

We could reason, by simple calculation, that the market was not big enough given their product revenue. Even though, for PR reasons, saying your tool is used by the national sports team is cool, as a beachhead segment its not great. The startup eliminated that segment for now.

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2️⃣ Is there a segment you already have decent traction in?

A travel startup began selling its immersive history walks to boutique hotels. Talks are going great, and outreach converts almost 40%. But what about other segments, like museums and other tourist organisations?

My Advice

Well, there’s a reason you’ve got early traction, and you need a good reason to abandon it. Keep 80% focused on your current segment while it grows revenue, but use 10%-20% to do explorative outreach/sales on new segments to see if you get traction more easily—and more lucrative. If the data doesn’t convince you that the new market is better, just stay in your initial lane for now.

3️⃣ Do you have any outreach or sales feedback yet?

This SaaS tool for innovators who want to validate ideas had three segments in mind. They built a full product and had a few paying customers from one segment. The other two segments were still promising. What to do?

My Advice

Manually do outreach for all three segments—no time to automate yet. Aim for 20 sales calls per segment. The data will tell you which segment has the most pull. You will feel it.

⚠️ Warning

Don’t focus too much on shiny validation methods. A/B testing and landing pages sound cool, but generating traffic is harder than you think. Creating good ad campaigns often takes much longer than you think—likely, this is your first time.

Just doing manual outreach to land 10 calls is way faster. You are doing this to learn about market demands, not to validate if you can build a scalable sales funnel. Don’t try to achieve too many things at once.

Top reads on beachhead marketing

• What makes a great beachhead? (Beachhead 101)

• Five expansion strategies from your beachhead

• What most people miss when making their beachhead

• How to identify people for your beachhead

• Why beachhead segmentation boosts momentum

The idea: There are many active-looking people on the job market who go to job boards. But some people are latent, as he told me: not looking, but maybe open. Isn’t that an opportunity?

Before building anything big, he’s concierge-testing this (some call it handcrafting). Do things that don’t scale!

When he approaches potential customers via LinkedIn, he talks with them about their job. Aiming to surface their frustration, with for instance, their boss, or their long commute.

Even though they weren’t actively applying to jobs, all of a sudden, they are open to a new job. That is a latent problem, then, right?

The recruitment founder thought we were onto something, that there is a vast group of people that you can activate in this way: a latent problem beachhead market. What if you can unlock that? Shift the industry? Well.

However, the more outreach he did, the fewer conversions he made. Was this latent problem really a latent problem? It prompted me to reflect.

Problems in general

I see problems like this more often. Sustainability startups that work on the latent problem of “People want to be more sustainable, but don’t act on it” — dime in a dozen of those. Is my idea of latent problems perhaps wrong?

Below is one of my favourite frameworks, which helps to recognise high-urgency problems.

On the lower levels of problem urgency, 1 & 2, you find people who can’t or don’t experience the problem you are aiming to solve. You can’t sell to them.

On the higher levels, 4 & 5, we find people who are open and on the market for a solution. Sales potential grows. At level 6, you missed the window to sell.

At level 3, I put the latent problem, based on a suggestion of a mentor to whom I showed the initial version of this framework.

“How could I’ve missed latent problems, I thought?”

I thanked him for the tip and published it, including latent problems.

But in this experience, I’ve learned something new that adds additional nuance.

Do you need a sanity check on your go-to-market strategy and your product-market fit? Work with me 1-on-1. First call is always free. More info here.

Latent problems don’t exist to the customer

The idea of latent problems, according to the textbook, are problems that are not yet recognised by the main stakeholder.

In the case of startups, that stakeholder is the potential customer. I add ‘potential’ on purpose, because customers are people who actually give you money.

However, there’s a paradox: you can’t talk about latent problems.

The moment you talk about an unrecognised problem, it stops being latent. You made someone aware, hence it loses the status of being under the radar, by definition.

The experience and act of observing the problem changes the problem exists. To make this clear, let’s make an analogy to quantum physics.

Schrödingers cat

Remember Schrödingers cat, a thought experiment on the concept of superposition of quantum mechanics?

When I asked the recruitment founder this question, he started laughing: “Why do you think I know anything about quantum physics, Jeroen?”. Okay, fair.

You put a cat in a closed box with poison that is triggered by a single radioactive atom. If the atom decays, the poison is released, and the cat dies. Poor kitty.

According to quantum mechanics, until the atom is measured, it is in a state of being both decayed and not decayed. Therefore, before you look in the box, the cat is entangled with the atom and must be considered both dead and alive (superposition).

The moment you look, the superposition collapses into one reality. You either see a dead or a live cat. Cats can’t be dead and alive at the same time.

Schrödinger created this scenario to demonstrate how absurd it creates situations when quantum rules are applied to everyday objects.

Schrödingers problem

Now, the sudden collapse of the cat’s vitality into alive or unalive upon inspection sounded familiar. For unrecognised problems, it seems that observation collapses the latent position of a problem.

When potential customers are made aware of a problem, they can either recognise it as a problem or not.

If they don’t see it as a problem, they ignore it, so you can’t make a sale.

And even if they see it as problematic, they have two options. They can still see it as not urgent, i.e. the potential of chewing gum under your shoe is not something we proactively try to avoid.

In some cases, the potential customer will say: ‘Wait, was I being inefficient? I didn’t know! Is this a thing I can do faster?’ Then they might buy.

What did the founder do with his latent problem?

After I showed the founder the draft of this article, he added an interesting challenge:

“How do you test if somebody is actually in 4 or 5, and not a 3? They often don’t know themselves.”

Sometimes, you start with somebody being a 3. But then, in the conversation, they flip to a 4 or 5: yes, now that you say it, please help me.

But sometimes, he reflects, there’s doubt. He finds that if he pushes them (a thing he doesn’t like to do), you can get a fraction of them in your sales funnel. It takes a lot of effort, but you can do it.

He goes that, of that small fraction that you can get into your funnel, an even smaller fraction converts to a sale. So the majority of those hard to convert ones actually is just a 2 disguised as a 4. Real 3s don’t exist.

He reflects that the best way to find out if you have a 4 or a 5, or a hidden 2, is:

“Just ask very directly if they want to buy you. Make your proposition, and see if they want to buy”

That usually filters itself. Don’t convince people who are not ‘desperate’ to buy you. You need high problem urgency.

Don’t chase latent problems

Therefore, if you recognise your startup is built on a latent problem, you are in a risky territory. It’s not just a weak problem; in many cases, it turns out not to be a problem at all. Schedule a call with me for a sanity check.

Related reading

The difference between problems and jobs to be done (article)

How to spot the right job to be done for your problem (video)

1. Goal: Build a customer theory

2. Structuring and starting the interview: Keep your baby in your bag

3. Framing the interview

4. Don’t just ask for problems ⬅️ This post

5. Identifying the right JTBD for your startup

6. Understand the criteria of success via competition

7. Using the film reel technique to get detailed explanations

8. Six techniques on how to wiggle out extra information

9. Getting your baby out of the bag

10. Crafting your customer theory

Chapter 4 - Don’t just ask for problems

Based on the previous chapters, the interview should be underway, and we’ve framed it correctly. Now we can start to dig deep.

In the current chapter, I cover the following:

• Example questions to get deep and rich answers

• Why you should not focus on problems (right away), and what to do instead

• How to assess the relevance of discovered problems in interviews

• A very, very brief philosophy of problems and jobs to be done

• How to get people to start talking about their jobs to be done

4.1 Don’t open with problems

Everyone says, “Love the problem”. Yes, problems are extremely important for startups.

But asking for problems is a terrible strategy. Let me show why jumping to problems at the start of an interview can lead to unreliable answers.

Q (you): “What problems do you have, Jeroen, with using Substack?”

A (Me): “Well, I’m not growing fast enough. I wish I had more statistics to understand my readers better. I want more people to have a paid subscription”

or

A (Me): “I don’t understand why some posts perform well and others don’t. It’s a bit hit and miss sometimes.”

While valid, these points hide two critical traps every founder needs to see.

Read more