6 Steps to Finding Product Market Fit
By: Product Dave
Tags: Growth Hacking, Product Management, Product Market Fit, Software Development, Technology

Step #1 Line up Your Product Goals

To find Product-Market Fit (PMF)— you need to define what the PMF condition looks like. Is it exponential user signups? Or high revenue growth? Or is it having the largest market share?

The PMF goals need to align with your company's financial milestones. The CPO (or whoever the “Manager of Product Managers” is) will need to work with the CEO to agree on a strategy to achieve the financial milestones.

The financial milestones are broken down into Product Team Goals. The Product Team Goals will guide the Product Hypotheses that will be developed by the product team.

If you’re the only PM in your company, take the initiative to align your Product Team goals with your Product Leader. Ask for your team's goals for the current and next quarter. Skipping this step will cause a misalignment in company priorities.

Once the Product Team Goals are clear, it’s time to come up with Product Hypotheses.

Step #2 Coming up with Product Hypotheses

Product hypotheses are sometimes called product initiatives or product ideas. I prefer to call them hypotheses because I can detach my biases from the product idea.

To come up with product hypotheses, look at your internal and external data channels. Speak with customers, look at your product analytics, check out your competitors and speak with internal teams.

Generating product hypotheses is a blog on its own. Here is a blog from Hackernoon with a more in-depth explanation.

Once you have a few Product Hypotheses, centralise them in one place. Having ideas in one place allows for higher-level thinking. You can read more on how to centralise and manage ideas here.

Now that everything is in one place, it’s time to prioritise the most valuable hypotheses to make small bets with.

Step #3 Prioritising the Product Hypotheses

At this point, there will be a few assumptions and unknowns. That’s okay. You’ll validate the assumptions in Step #4 & 5.

Set up a prioritisation meeting with the core members of your product team — Tech Lead, a Designer, a Decision-Maker and a Subject Matter Expert. Keep the prioritisation meeting small. 4 to 5 team members is a good size.

Go through the list of Product Hypotheses and label each item with an expected Impact, Confidence and Effort.

Impact means how likely you’ll be able to achieve your quarterly product goals

means how likely you’ll be able to achieve your quarterly product goals Confidence means how much you understand the hypotheses and how risky the idea is

means how much you understand the hypotheses and how risky the idea is Effort is an estimated effort based on a high-level tech solution

Once you’ve gone through the list of Product Hypotheses, you should see something like this:

Here is a template you can use to do this yourself

Once you’ve decided on a few hypotheses to test, it’s time to speak with 5 customers to see what customers think.

Step #4 Get Feedback from Five Customers

Before you start building, seek feedback from five customers on the product hypotheses. Five customers should give you a good indication on whether if the idea is worth pursuing or not.

Use a mix of customer insights (qualitative data) and customer behaviours (quantitative data), so you can get a full picture of what people say vs what they do. Here is a guide on how to ask the right questions.

This process can take a few days to a few weeks. There are three scenarios you should expect:

More than four customers are interested in the product hypothesis — this is the best-case scenario. Getting to 80% confidence is enough for you to move to the next step. Three out of five are interested — this is a tiebreaker and you might want to find more customers to speak with. Two out of five customers are interested in the product hypothesis — ask why and use the new insights to come up with new hypotheses. Add the new hypotheses into the backlog and reprioritise.

Assuming you’re getting good feedback from customers, it’s time to move onto the next step.

Step #5 Make Small Bets with Product Experiments

Product experiments are sometimes called “MVP’s” or “Prototypes”, or “Small Bets”. Regardless of the semantics, the purpose is to validate the hypotheses further by collecting proprietary data.

Your proprietary data is your secret sauce to finding Product-Market fit

Proprietary data is the secret sauce to find Product-Market Fit. It generally includes the following insights:

Your customer’s unique behaviour and the customer journey

and the The pricing sensitivity of your target market

of your target market Feature ideas for your next product iteration

for your next product iteration Insider knowledge about your product category

There are usually two types of experiments you can build:

A Proof of Concept experiment that demonstrates the product but doesn’t fulfil the actual need of the customer. (e.g. smoke and mirror tests)

that the product but the actual need of the customer. (e.g. smoke and mirror tests) A functional experiment that works, but it’s usually created with an unscalable solution or with minimal features. (e.g. “plain-donut” product)

Here are some ideas for MVP experiments

You can also employ A/B tests to launch these experiments. The extend of your product experiment depends on the company risk and the resources you have.

You can read more about different experiments here and don’t forget to create a tracking plan for your product.

Step #6 — Evaluate Market Traction

Once you’ve launched your product experiment, keep a close eye for early signs of customer traction mentioned above. Stay close to the signs of traction below:

Exponential organic growth in revenue, conversion, and engagement High user retention at a minimum of 40% of new customers At least a 3 to 1 return on customer acquisition cost over your customer lifecycle At least 40% of customers tell you they are “very disappointed” if the product is removed from the market

If the product is not showing any signs of traction, use tools like Fullstory or Amplitude to see why customers dropped off in your product. Use this as an opportunity to create new sets of insights and start the process again.