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Chapter 7: Keeping the dynamic process of product market fit in mind as your company grows

Product market fit is not reached at a defined point. Brian Balfour suggests thinking of it as a "series of tests and checkpoints that increase in difficulty, but also decisiveness." It's important to know where you are on this path before switching to a focus on growth.

Net Promoter Score is a method to measure customer happiness that has been used by many companies as an indicator of growth. NPS is calculated based on responses to a single question:
How likely is it that you would recommend our company/product/service to a friend or colleague?
The scoring for this answer is most often based on a 0 to 10 scale.

Scores of 9 to 10 are called Promoters, and are likely to exhibit value-creating behaviors

0 to 6 are labeled Detractors, and they are likely to exhibit the value-detracting behaviors.

7 and 8 are labeled Passives, and their behavior falls in the middle of Promoters and Detractors.

NPS is calculated by subtracting the percentage of customers who are Detractors from the percentage of customers who are Promoters.

The Product Market Fit Survey

Sean Ellis' of Survey.io, developed the Product Market Fit Survey, also known as the "Must-Have" score, in collaboration with KISSmetrics. It gives you an objective metric that removes emotion from the scaling decision while also giving you other important qualitative information. The key question on the survey is:

How would you feel if you could no longer use [product]?

1. Very disappointed

2. Somewhat disappointed

3. Not disappointed (it isn't really that useful)

4. N/A - I no longer use [product]

If you find that over 40 percent of your users would be "very disappointed" without your product, there is a great chance you can build sustainable, scalable customer acquisition growth. This 40 percent benchmark was determined by comparing results across hundreds of startups. Those that were above 40 percent are generally able to sustainably scale their businesses; those significantly below 40 percent always seem to struggle.

Read How to Measure Product Market Fit with Survey.io, by VentureHacks

7.4 Leading indicator engagement data

The "must-have" score tells you what people say they would do (i.e., be very disappointed if the product disappeared). Now you need data about what they are actually doing. Leading indicator engagement data (typically at a small scale) tells you whether the user is getting meaningful value out of the product. This data must reflect events or actions, not views or downloads, aligned the core purpose of the product.

At this stage you are no longer examining individual interactions but looking at statistical results from a large group.

Metrics to consider

Retained engagement - does a high proportion of new customers start using your product and then never stop? Does your retention curve flatten to a solid percent of users?

Percent of users driving revenue - Of your total users, what percent are converting to provide you with revenue? If you're solving a worthwhile problem, people will pay.

Organic growth - Are you seeing growth happen organically by happy users telling everyone who will listen about it? Is the value proposition so strong that people convert with little to no effort, and are your target customers so in need of a solution that they seek you out in droves?

7.5 Engagement - customer research tips

Are you tailoring to the right market segments? Do different customer groups/segments behave differently?

Can customers find out about your offering? What about the time and effort required to find and use your product?

Are you aware of specific language, ethnic, status, age, gender, or religious nuances that may pose barriers to enrollment?

Are there hidden costs or stressors to gather the required documentation to sign up? Are there ways you could incentivize first use? Is your enrollment process too time-consuming?

Who are your new customers? Through which channels did they come to purchase your products?

What is your cost to acquire new customers?

How can you improve the acquisition process?

What are preferred transaction and servicing channels for customers?

Do customers read or respond to various communications?

Which customers use multiple products and features?

How well do you understand the context in which customers use your products and services?

What incentives do you have in place to increase use? How may the context be changing?

Are there key pain points customers face that you may not be aware of?

What incentives do you have in place to increase uptake?

Who has the most influence on decision-making behaviors of your customers?

Do you know why this could be happening?

Read more

1. Make your pirate metrics actionable, by Amplitude
2. The Ultimate Guide to Customer Acquisition (Kissmetrics)

Retention is a key metric for PMF, and is measured through a retention rates and tracked with a retention curve. A retention curve plots the percentage of returning users on the Y axis and time since first use on the X axis.

1. The curve shows the percentage of customers active over time for each cohort, a group of customers that share a common characteristic, such month of purchase

2. You can expect to see an "initial drop off" of customers who try it and don't come back

3. If the curve becomes flat at a certain value, that is the percentage of customers retained from that cohort

4. The stronger the product-market-fit, the lower the initial drop and the higher the percentage of customers who try the product and continue to use it in the long run

5. Consider what/who is the retained market, and how big the percentage is? Identify key characteristics of those retained vs those who left.

How do I compare curves across cohorts?

First, plot the raw data for cohorts in a matrix with the cohorts as columns and time as rows.

Next, calculate the retention rate for each cell, the number of active users (for that cohort and timeframe) divided by the initial number of customers in the cohort.

Finally, plot the data points on a line graph as in the example below. If PMF is improving, the cohort retention curves should move up and become flatter over time.

What if I experience problems with retention?

Answer the questions below to determine where you might retain customers and where they churn.

What are the biggest technical barriers to ongoing use? Does the customer understand the product value ? Where can you respond to customers' changing needs through better, more consistent dialogue?

Trust and loyalty - Are you giving them sufficient choice, respect, and control drivers?

How actively do customers use your products?

What are the inactivity or dormancy rates?

Are you getting significant referral business?

Which customers use a service once and then never use it again?

Which customer/ customer groups are terminating? Why are they terminating?

Refer to Mastering Retention,by Amplitude

7.7 How do I know when I'm at PMF?

"You can always feel when product market fit isn't happening. The customers aren't quite getting value out of the product, word of mouth isn't spreading, usage isn't growing that fast, press reviews are kind of 'blah', the sales cycle takes too long, and lots of deals never close. And you can always feel product market fit when it's happening. The customers are buying the product just as fast as you can make it - or usage is growing just as fast as you can add more servers. Money from customers is piling up in your company checking account." - Marc Andreessen

Metrics from Product Market Fit, by Marty Cagan (SVPG)

For a B2B product, I consider the product to have demonstrated Product Market Fit once you have achieved a threshold number (I advocate at least 6) of live, referenceable customers for a given vertical market.

For platform products, the idea is similar but we're looking for a threshold number of applications to have been successfully built and deployed using your API or platform services.

For consumer products, especially those that are free services, we're looking for an indicator of serious engagement. I like Sean Ellis' 40% benchmark but we often need to craft the test for Product Market Fit based on the unique situation

Common product market fit challenges

Not separating the problem from solution, or jumping into the solution too quickly before you really understand the customer and their pain points.

Starting with a technology and focusing on how you're going to sell it. Start with the customer experience and work backwards to the technology.

Being too responsive to a few MVP customers. The first people who use the product are likely to be non-representative of the larger market, so you need to know what the problem is you're trying to solve, who you're designing a solution for, and what your vision is. Blindly following customer feedback just because it's coming in can be risky.

Fooling yourself into believing you've reached PMF by only focusing on the user groups that are responding well to early versions of the product.

Declaring victory too quickly, or thinking revenue traction is PMF. It's tempting to declare that PMF is done and spend a lot of money trying to scale when the product is not yet ready.

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Measuring Product market Fit - Catalyst Fund Toolkit

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Chapter 7: Keeping the dynamic process of product market fit in mind as your company grows Product market fit is not reached at a defined point. Brian Balfour suggests thinking of it as a "series of tests and checkpoints that increase in difficulty, but also decisiveness."

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Insights vs. Observations! Difference between Observation and Insight with Simple Real Life Example

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Stanford Webinar - Design Thinking vs. The Lean Startup

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As product managers and entrepreneurs, we know the importance of validating an idea beforecommitting to getting it built. However, validation is easier said than done. In fact, it's possibly one of the hardest things you will ever do in your product life cycle, otherwise products and startups wouldn't have the abysmal 90%+ failure rate they've become famous for.

In this post I will draw on what I've learned over the years, through first-hand experiences and other sources and leave you with a validation framework that I hope you'll be able to use. And, in the remote case that you've been living under a rock and the whole lean startup movement somehow got past you, this post will try to bring you up to speed (and possibly, get you slightly ahead of the pack), provided you force yourself and your team to take action!

But first...

1. When it comes to new products, by definition you're making assumptions, sometimes a lot of them. You need to validate your key hypotheses and assumptions as early as possible. Some of your assumptions are going to be wrong. If the ones you get wrong are significant, you're not going to be in business for very long.

2. Validation will help you avoid the most common problem of them all, spending time and money building something nobody wants. If you ever come across a failed product, chances are that it was based on an idea that the founder was enamoured by or found cool and interesting, rather than something that solved a real pain point for real people.

3. Validation also forces you to get in touch with your users, which could save you the pain of building a product that is hard to use or understand, or something that is ahead of it's time. (Remember Webvan?)

4. If you figure out that you're headed down the wrong path, it's also easier (and a lot cheaper) to change course sooner rather than later. And, it's all the less likely that you'll have to pivot later.

5. Validation will help you refine your ideas and learn more about your users.

6. And last (but certainly not least), it will help you figure out if people will buy your product before you build it.

Validation will help you answer questions like:

What is the target market that I want to address? How big is the addressable market size?

What is the biggest problem these people face? Is it an isolated or recurring problem?

What kind of product would help relieve that pain?

Are there real people willing to pay for such a product if it existed?

Will building it be worth it? Or, is the market big enough?

And, am I building the right product?

So let's get to it.

People don't want to buy a quarter-inch drill. They want a quarter-inch hole!
-Theodore Levitt

We need to have a clear understanding that customer needs are separate and distinctfrom the solutions that people buy to address those needs. Keeping this in mind, validation comes in many forms:

Validating market demand

Validating the customer problem/pain point

Validating the productor solution

Validating demand and validating the problem come first. Then you come up with a solution (a prototype or design of your product) to solve the problem that you have identified. Finally, you validate the product you have thought up, separately. Validating the product you have imagined (before building it) is important, because there are a gazillion ways to solve the same problem.

The goal of validating demand is to get an answer to the question:
What is your total market potential, and how much of that market can you/will you be able to capture?
Here, you want to work out a realistic market size that is feasible, otherwise you risk there not being enough demand for the product because it doesn't solve a big enough problem for its market or it doesn't solve the problem in a way that works well for users.

You want to ensure that the market is big enough and that there are enough people willing to pay for your product or service. Ideally, at the end of this exercise you should be able to understand your users' interests and motivations better, and hone in on a small group of people who feel enough pain to buy your product. Also, if done right, you'll be able to use what you've learned to find similar (or parallel) markets to expand into in the future.

Be sure to hone in on a specific target market where the constituents have similar behavior patterns. It doesn't matter if it is small, as long as it is sizable enough and there is potential to expand into other niche markets in future. For example: music lovers is too broad; college students that listen to punk rock music is better.
Methodology, tools and techniques for validating demand:

Industry reports

Look at traffic of competing websites, using tools like comScore, Compete and Quantcast. If you know that your competitor has 1 million unique visitors per month, at the very least you know that the market potential for your website is 1 million.

Google Adwords Keyword Planner - use the Google Adwords Keyword Planner to determine how many searches related to your market take place on Google each month

Look at Google Trends data to look at search query volume

Look at competitor offerings and try to find (or make an accurate guess of) pricing and revenue numbers

Note: Be wary of forecasts of market size, many of which use questionable methodologies or flawed assumptions

The goal here is to make sure that we find a real problem or customer pain point that enough people face, so that we can later focus on solving that problem.
Methodology, tools and techniques for validating the problem:
As Laura Klein mentions in her book UX for Lean Startups:

Now that you've picked your specific market, find five people who are in it. If you can't do this fairly easily, either you've picked too small a market, your market is too hard to reach, or you're just not trying hard enough.

Don't just go out and start talking to friends, family and random strangers on the street - that could be a mistake. These people are (likely, but not always) going to be very different from your target market. Go where your REAL target users are, observe what they are doing, and think about how you can make those tasks better and/or easier. Sometimes, your users are out there in the real world, but sometimes they are more easily accessible online (for example, on discussion forums, Facebook groups, and online review sites like Yelp or Epinions, etc. If possible, schedule a Skype call with them.)

Ask them open-ended questions about the tasks they go about doing in the identified problem domain and the pain they are experiencing. Ideally, they will be able to show this to you first hand. This will help you learn how people do things, why them do them a certain way, and also what solutions or workarounds they are currently using to solve their problem.

Look out for patterns - groups of people doing things the same way, or complaining about the same thing and either observe or ask them how they solve those pain points today. Keep in mind, however, that sometimes users don't know they had a problem until they're shown the solution (your product). Dropbox is a classic example of that. Just remember that you're there to observe, listen and learn - not to sell your test subject on your product idea.

This kind of thing can have a big impact on your product implementation, your user interfaces and so on and will help you ensure that your product more naturally fits into the daily lives of your customers. It will help you minimize the amount of training you will have to give your customers once the product gets built because they don't have to learn new habits to use your product, thereby shortening abandonment rate and increasing the likelihood of the customer sticking it through after the first interaction with the product. It will help you trash bad ideas that you were previously considering very quickly. All this before you start building anything. At the end of this exercise, you should be left with a validated problem in a validated market.

Ideally, building and validating the product should go hand-in-hand and be an iterative process, with some amount of validated learning along the way (or at the very least, with every iteration you make). This is the final step and comes after validating demand and validating the problem. It involves constantly asking yourself the question: 'Does this product really solve the problem, in the market we have identified?'. Product validation is more complicated and should be done via iteration. Ideally, it looks something like this:
Methodology, tools and techniques for validating the product or solution:
You can use landing page tests to market and sell your product before it even exists. Now, drive relevant, targeted traffic to your landing page using some marketing channel (free or paid) - Google Adwords, Facebook Ads, or anything else you can think of.

If you're unable to generate enough interest in your landing page tests before you have a product, it either means that your marketing strategy isn't good enough (in which case A/B testing more landing pages is the way to go), or you're trying to sell a product that there isn't enough demand for. This is not to say that the problem you have identified cannot be solved in another way (you have validated the problem already, after all). It just means that you need to create a different solution for the problem. This approach drastically reduces your chances of failure when you eventually hone in on a product worth building and also helps you prioritize your product features based on how users react to your marketing copy. Landing page tests have the added advantage of validating the market at the same time, so you could start here if you have already narrowed down a problem you want to solve.

Once you have validated the idea, you need to validate the product you have imagined (before building it), because there are still several ways to solve the same problem. The best way to do this is by showing potential users a semi-functional (or even easier, a non-functional, but interactive) prototype that looks and feels like the product. This is as opposed to asking them for an opinion on your idea, which bears no correlation with real people using your product).

Then, you (silently) observe how potential users interact with your prototype, looking for common problems, symptoms and patterns, find out if it's compelling enough to pay for, and course-correct if needed. Just don't bias your test subjects by treating them as potential customers - now's not the time to sell them on your product. If they don't 'get it', either because they don't understand what it does or how to use it, or they're unable to find all the features, that's an obvious sign that something needs to change. As you can see, including prototyping in the product validation cycle will both help communicate your ideas and allow you to harness the power of failure to create something truly innovative.

You could also make your users interact with your competitors' products, to uncover holes in their products that you will smartly fill.

You may have to iterate through a number of prototypes before you end up with a validated prototype at the end of the exercise. The same validation would then have to be done for your designs and, eventually, the end product you are building.

The validation story doesn't end here, of course - it goes on at every step of the product life cycle. And then again later, after the product is out there, every time you fix a bug, add a new feature or make a product change.
A few resources worth mentioning:

1. fivesecondtest.com - to help you guage a user's 'first impression' of your exer experience or design

2. unbounce.com - to help you create landing pages easily

3. aytm.com (ask your target market) - could be a useful tool to find your target market and send them surveys

4. optimizely.com (Google Analytics also offers A/B testing functionality) - to run A/B tests and measure click-through rates on different page elements

5. usertesting.com - to help you get real user feedback (though, not necessarily from your target demographic)

If you use validation the right way (at every step of the product development cycle, and are disciplined enough about it), your customers will practically lead you to the goldmine, telling you virtually everything you need to know to make your product a success.
References:

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Validate or Die: Using Validation to Build the Right Product - Mind the Product

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As product managers and entrepreneurs, we know the importance of validating an idea before committing to getting it built. However, validation is easier said than done. In fact, it's possibly one of the hardest things you will ever do in your product life cycle, otherwise products and startups wouldn't have the abysmal 90%+ failure rate [...]Read More...