Why product market-fit is so important for Growth Marketing12 min read

Apr 16, 2018

One year after launching, UBER’s growth was so strong that it got one new rider for every 7 rides – without spending a single dollar on marketing. [5]

 

Instagram had 25,000 signups on its first day. [6]

 

Within one day Dropbox went from 5,000 to 75,000 signups for the waiting list after launching a beta video. [7]

 

uber launch chicago 2011

A visibly pumped Travis Kalanick on UBER’s launch in Chicago (2011)


 

You guessed right, all these companies had (and have) product-market fit and that’s why they grew so fast. Product market-fit is when a product provides such substantial value to a segment of a market that people love it. They crave it.

 

If you’ve been only remotely following the startup scene or Growth Marketing community, you should be familiar with the term. We all understand that it’s important. But why? Can’t we just sprinkle some Growth Marketing magic over a product and market it to the customer? What’s the mechanism behind Product-Market Fit that creates all this growth?

 

The answer is: without PMF, we’re not getting the data we need to drive sustainable and rapid growth! Product-Market Fit only occurs when a couple of things work right in a product. In this post, I explain what’s going on.

Product Market Fit ♥ retention

Retention is one of the strongest indicators of Product-Market Fit. You can ask whether users like your product, but retention is the proof. It goes a step further: retention guides you to measure the right numbers. It literally tells you what to pay attention to in order to grow your startup.

product market fit

For a startup with Product-Market Fit, the retention over time curve flattens at some point (blue curve in image). For some products, it flattens earlier, for others later. Social networks usually retain 45-65% of their users over 12 months. SaaS companies keep maybe 25-35%. [2]

 

If the curve doesn’t flatten at all (yellow curve), the likelihood of your product having market-fit is slim to none. It’s like walking through a mall and not buying anything. In and out.

 

5 ways to use retention right

I already hinted at the guiding nature of retention and how it can help us to measure the right things.

 

First, be wary of it the correct time interval. Some business types have to look at retention over days, others over weeks or months. In B2C, we lean more towards smaller intervals, in B2B more towards bigger ones.

 

I mentioned social networks retain more users. They look at retention over days, rather than months. A typical retention metric for social networks is Day0DAU, meaning “users who are active from the day they sign up”. A SaaS product would look more at Week2WAU (weekly active two weeks after signing up) or Month3MAU (monthly active 3 months after signing up).

That’s not exclusive, though. At Atlassian, we look at both, DAU and MAU. The ratio of the two can say something about the stickiness of a product.

 

Second, when you look at where your overall retention curve flattens, you can identify what time interval to measure success by. If you look at weekly active users and see that the retention curve flattens after 3 weeks, Week3WAU is your success metric. That leaves you two options to design your growth marketing strategy around: try to retain more users after three weeks or get users to retain after two weeks.

 

Third, DAU/WAU/MAU will help you to measure retention over time but that’s all they do. They are also called “engagement metrics” but aren’t very actionable. They tell you that retention is going up or down but not why. It’s okay to monitor these retention metrics but It’s not enough.

 

Real engagement metrics tell you something about what users do. That could be connecting with other users, uploading a picture, creating a ticket, commenting, etc. That’s where the gold is. When you measure real engagement, you can influence the why behind retention. DAU/WAU/MAU are output metrics. As I mentioned in 3 ways to regain focus in Growth Marketing, you should focus on input, not output.

Engagement metrics examples

Fourth, you find the right engagement metric by looking at Core Product Value. Your product revolves around one or more core interactions that you should measure for engagement. For UBER, it’s completed rides. For Facebook, it would be making a certain number of friends. For Airbnb is booking nights. For Jira, it’s creating, assigning and closing a ticket. For Slack, it’s sending messages.

 

Of course, there is an optimal set of input metrics you should look at. UBER doesn’t only look at completed rides but also hailed cabs or average ride rating. However, there’s one engagement metric that strongly correlates with retention. If that one goes up, everything else usually follows. For Facebook, it is the famous “get a user to reach 7 friends in 10 days”. [1] That’s why it should be your North Star Metric.

 

Fifth, before having robust retention, it doesn’t make sense for startups to focus on scale. If product-market fit is weak you will fail. It’s like pouring gasoline over a too small flame – it suffocates instead of lighting up.

 

In the same likes, retention should go up over time. Newer cohorts should retain longer than older ones.

 

The relationship between Product-Market Fit, “Aha Moment” and retention

The “Aha Moment” is like meeting an attractive person and realizing you’re attracted to her/him. There’s no misunderstand or uncertainty about it. Now replace the person with a product and you understand the “Aha Moment” – the moment a user realizes the value of a product and retains.

 

In the Growth Marketing Funnel, the “Aha Moment” is part of activation. Your job as a Growth Marketer is getting users to the “Aha Moment” as quickly as possible.

 

Users who haven’t gotten to the “Aha Moment” usually don’t sign-up or churn. For Marketplaces and freemium SaaS businesses, it comes before paying for it. For high-touch and enterprise B2B companies, the Aha Moment happens either during demoing the product or after signing the contract. I’d argue that customers don’t sign the contract before the Aha Moment, but maybe there are some companies who do that ¯\_(ツ)_/¯.

 

Now, that puts onboarding into perspective! For non-demo products (think: B2C and low-touch B2B products), Onboarding must lead straight to the “Aha Moment”. For demo-products (think: products that require salespeople) the “Aha Moment” must occur during the demo, or maybe when the prospect has time to try the product out. That should be a manual for structuring demos: start with the Core Product Value!

The relationship between product-market fit, aha moment retention and retention

PMF, “Aha Moment” and retention are intrinsically connected and “impact” each other. They’re all different things: PMF is a state, “Aha Moment” is a point in time and retention is a behavior. However, they are all connected and dependent on each other.

 

The “Aha Moment” is part of Product-Market Fit. Users need to have a moment of realization before they can see the value of a product. That moment also needs to happen for users to retain. So, by optimizing the time it takes to get to the “Aha Moment”, you positively impact retention and PMF.

 

For some products, the “Aha Moment” happens within seconds after signing up, for others, it might take days or longer. It depends on the product’s simplicity and functionality.

app functionality vs time to core-product value

Compare an app like Instagram with Google Analytics. Instagram is easy and quick to understand. You open the app and instantly realize what you’re supposed to do. Everything is structured around 5 core interactions with the app. Users quickly understand what it’s all about. Logging into Google Analytics for the first time is a bit different. You can do 10,000 things. It takes users much longer to understand everything you can do with Google Analytics. That’s not a bad thing, it’s just a different product and something to be aware of.

 

I’d argue you find Core Product Value quicker in Instagram than in Google Analytics because the functionality is narrower. One way to speed up the time to “Aha Moment” is guiding users to a core feature. Google Analytics could lead new users straight to a traffic over time graph, for example.

 

Strong vs. weak indicators for PMF

It’s useful to look at qualitative and quantitative indicators to get a robust perspective on Product-Market Fit. Retention is a quantitative metric but can be misleading, especially when not segmented further.

 

Another quantitative indicator is NPS. The Net Promoter score is a simple means to find out how many users like a product by asking them how willing they are to recommend your product to others.

 

Calculating NPS

  1. Ask your customers “On a scale of 0 to 10, how likely are you to recommend this company’s product or service to a friend or a colleague?
  2. Then, group the responses into the groups of <6, 7-8, and 9>.
  3. Subtract the percentage of responses <6 from >9 and you get your NPS score.

Product usage is a simple yet often overlooked way to find out if users love your product. However, it’s not enough to look at how often users logs in. You need to look at how often they experience Core Product Value. We’re speaking about meaningful interactions.

 

Referrals are another good indicator of PMF. What’s often called “Virality” means customers are inviting their friends or colleagues to join. Nowadays, that only happens when a product is really good. Think of the UBER example in the first sentence of this article.

 

Qualitative indicators come from conversations with your customers. One way to bring depth into a quantitative perspective is to ask, “How disappointed were you if the product wasn’t available anymore”. According to Sean Ellis, if 40% of users would be very disappointed, chances for having PMF are high. [8]

 

It makes sense to send out an electronic survey to ask customers simple questions about the product. Good questions to start are “What do you like?”, “what do you not like?”, “would you pay double the price for it?”. It doesn’t have to be complicated.

 

Talking to customers face-to-face is always a fantastic idea and as qualitative as you can get. You can much better understand their reactions. You can look over their shoulder while they’re using your product. You can have them beta-test new features live. There’s always something to be learned from that.

 

Weak indicators of Product-Market Fit are high traffic, many logins, and trials. Those make you feel good, but they don’t necessarily drive business. They can, but don’t have to. You want to look for numbers that are evident of value and business.

 

In the end, most of the time these assessments help you understand why Product-Market Fit has not yet occurred. You quickly find out when you have it. Only in some industries – often in the enterprise business – you really have to analyze whether you have PMF or not.

 

PMF = retention = $$$

Bottom line: without Product-Market Fit, there is no “Aha Moment” and therefore no retention. It sets the stage for hyper-growth and robustness. No business survives long-term without retention, which is why Product Market-Fit is so important.

indiana jones finding pmf

A couple more thoughts on PMF:

When Ben Horowitz sold Loudcloud to EDS, he did it because he saw the market going down the drain but Opsware had PMF. The “pivot” was brutal but necessary to survive. [9] Microsoft Windows was once the dominating OS but then it started to lose Product-Market Fit and MacOS became dominant. The market doesn’t stand still. Finding Product-Market Fit is hard, but once you have it you can lose it.

 

PMF can be deceiving. Sometimes you see promising signals but what you actually have is traction. Say you got in touch with your customers and they all love your product, but your customers base is not growing quickly (2x, 5x, 10x). Do you really have PMF?

 

But PMF can also bring valuable insights. On the expedition to find product-market fit you learn whether the market is good or not. A good market is big enough to grow into and has customers that are willing and able to pay for a great solution. Having PMF for a small market is a trap: it’s nice to have but not the “be-all end-all”. You don’t want to sell cars on a small island.

 

When finding product-market fit, you should also get an idea of good growth channels. Most startups grow predominantly on 1-2 channels. Even though PMF comes with lots of Word of Mouth and referrals, you will see early signs of channels that do well. Sometimes you see that a lot of early customers are also part of another platform you could grow on. Sometimes you realize lots of users come through SEO.

 

Most startups fail before they find PMF. [3] At the same time, every successful startup you see has achieved PMF. You have to do whatever it takes to get there.

 

Do whatever is required to get to product/market fit. Including changing out people, rewriting your product, moving into a different market, telling customers no when you don’t want to, telling customers yes when you don’t want to, raising that fourth round of highly dilutive venture capital — whatever is required.” (Marc Andreessen)

 

References

  1. https://www.youtube.com/watch?v=raIUQP71SBU
  2. https://blog.ycombinator.com/growth-guide2017/
  3. https://pmarchive.com/guide_to_startups_part4.html
  4. Eric Ries – The Lean Startup
  5. https://web.archive.org/web/20140828024737/http://blog.uber.com/2011/09/22/chicago-ubers-biggest-launch-to-date/
  6. https://www.scribd.com/document/89025069/Mike-Krieger-Instagram-at-the-Airbnb-tech-talk-on-Scaling-Instagram
  7. https://www.slideshare.net/gueste94e4c/dropbox-startup-lessons-learned-3836587/13-Private_beta_launch_video_12000
  8. https://blog.growthhackers.com/have-you-validated-product-market-fit-4822fdbd25a8
  9. https://a16z.com/2010/03/17/the-case-for-the-fat-startup/