How to achieve Product-Market-Fit
Our journey towards a scalable business model for alphabeet
Every startup is looking for product-market-fit. And they do so for a good reason: it makes or breaks the foundation of every business. If you have it — boom — rocket speed. If you don’t, forget about exponential growth. It might still be possible to create a successful business, but you will have to compensate with high advertising expenses. So how do you know you’re there?
This is a question that is super relevant for every founder. It is the kind of question that keeps you up at night, desperately trying to find a way to know for sure. It’s not necessarily something you need to prove to someone else, but rather to yourself. Are we on the right path? Is our idea truly genius or just mediocre? While no one can tell you, there is an easy way to find out yourself. This is how we did it.
Finding a way out of the jungle
Founding a startup feels like being in the jungle. You can see nothing but trees, leaves and bushes. Wherever the thicket opens, a path could lead along. But you can’t clearly see it and even if it is there, each path leads you in a different direction and you have no idea where you might end up.
It is impossible to make long-term-plans in an environment like this and, of course, this is why lean and agile have been invented. They rely on continuous feedback cycles: build, measure, learn, repeat. Fortunately, we no longer feel like we’re deep in the jungle. The barely visible path has turned into a beaten track and then even to something like a bumpy runway.
Our startup alphabeet was growing fast last gardening season, about 8% every week for paid accounts and 11% per week for free accounts. It was very tempting to drastically raise our ad spend next spring, when the next gardening season kicks in, but is it the right time?
Where we came from
We’ve had quite a journey with farmee that lead to our current product. We waded through the cold waters of vertical farming (failed), built an MVP to revolutionise agricultural consulting together with Delphy (failed again) and then decided to focus on hobby gardeners, growing vegetables for themselves and their families. On a curvy path, this lead to alphabeet, a garden planning app for hobby gardeners. It creates the perfect bedding plan for vegetables, provides an extensive library of crop varieties, plants and diseases, loads of valuable content as well as a community of hobby gardeners.
Building a company
Let’s say we did everything right so far: we focused on a clearly defined target audience, spent an awful amount of time to really understand their needs, identified an important problem to solve and found a compelling solution for the problem. Then the only thing we would need to do was prove that our solution was a fit for the problem of the audience. Easy, right?
Hell, no. It is hard as fuck. You might have hundreds of users, but very rarely someone comes and says “Thank you, you really solved my problem”. Fortunately for us, my good friend Philipp of reruption.com pointed me to this excellent blog post by Rahul Vohra, CEO of Superhuman. If you haven’t already, please go read it, even if it is super long, it is that good. Following the bread crumb, we also built on the ideas of Julie Supan and created a persona for a high-expectation customer (HXC). I’ll walk you through how we did that und how we used data to support informed decisions instead of pure gut feeling.
HXC: High-expecation customer
It’s tempting to assume your early adopters are also your HXCs, but that’s not always the case — and failing to make that distinction can prove challenging to a young company. — Julie Supan
We asked ourselves: Who is the customer who needs or wants our app the most? Why is our product important for this person? How do they feel about alphabeet? What is the main benefit they get from the application?
To learn more about our HXC customers we started gathering all available data from our analytics tools. We looked for sheer numbers, but also for patterns and surprises in our data. Here’s what we found:
- At the time, we had 22.000 users
- ~600 of them were paying for a pro subscription
- ~33.000 garden bed plans had been created in our app
- More than 5.000 crop varieties had been created by our users (for comparison: we had about 220 varieties in our database)
The last one came as a surprise and felt a bit like a punch in the face. Creating your own varieties had been developed as a total after-thought. To be honest, the whole experience was a total piece of crap. Time-consuming, cumbersome, fiddly. We already knew we needed to fix this mess, but it became clear how important it was for a lot of people. Someone had created 150 varieties for herself!
My main point is, there were people who spent a lot of time using our app and they invested a lot of time and effort to make it work for them, even if it had glitches and missing features. So we spent some more time searching for people like this. Narrowing down to ~2.000 users with more than 10 logins over the gardening-season, we manually screened their usage data to identify those with the most activity and the greatest number of logins.
We identified 53 people. These are our high-expectation customers.
Our average HXC has the following attributes:
- ∅ 40 square meters bedding area (~430 square feet)
- ∅ 14 garden beds or pots
- ∅ 34 crop varieties in use
- ∅ 25 own crop varieties, created by themselves
By the way, two thirds of the group are women, a distribution that we’re also seeing among other usage data as well. We used this data, mixed it with a bit of gut feeling, stirred it with a great portion of customer feedback and created the following HXC-persona.
Meet Laura, our high-expection customer
Laura is an enthusiastic hobby gardener. She is in her third gardening season and incredibly proud of her garden. She spends every free minute in the garden, it is her safe space. She wishes she had more time outside and is never one hundred percent satisfied with her results, even if she experiences moments of great satisfaction between her plants. It is difficult for her to simply shed her perfectionism, she still sees herself as a beginner. Whether she wants to or not, she always expects the best of herself and wants to improve continuously – in life as well as in the garden.
Laura likes to try out new, exotic or old-fashioned varieties. She cultivates almost 50 square meters of bedding area and has almost 60 different crop varieties in her bed. Laura finds it incredibly important to create garden plans that reflect how her garden looks in reality. Her plan never feels perfect, there are simply too many factors that need to be taken into account. Something can always be improved.
Boy, this was a relief. Up to this point we always had two target audiences in mind and had a really hard time deciding for one of the two:
- Beginning gardeners, eager to learn more, but with very little experience
- Experienced gardeners with great enthusiasm and self-catering ambitions
Studying the data and writing the above persona made it crystal clear that we had to focus on the latter only. There was no way beginners had 40 square meters of bedding area and handled 34 crop varieties in a single season.
Why you should narrow your target audience
Ideally you want to make large numbers of users love you, but you can’t expect to hit that right away. Initially you have to choose between satisfying all the needs of a subset of potential users, or satisfying a subset of the needs of all potential users. Take the first. – Paul Graham, founder of YCombinator
It is tempting to think your solution is for everyone. We have very little competition, as there are only a small number of apps for gardeners. So should we build alphabeet to suit all the needs of all gardeners at the same time? Impossible. Studying our main target audience and then purely focus on their needs makes it possible to build a product that is worth their time.
In theory, this narrow target audience might max out at some point, but in reality this never happens, as Paul Graham writes in his excellent blog post startup=growth.
Adapting the framework for product-market-fit
Raul Vohra did an excellent job explaining the “engine” he and his team at Superhuman built to achieve PMF. It is based around four simple questions they had delivered to their users as an email-survey. It all goes back to Sean Ellis and his book Hacking Growth. Ellis proposed to simply ask your users how the would feel if they could no longer use your product.
If 40 percent or more of respondents are “very disappointed”, then the product has achieved sufficient must-have status, which means the green light to move full speed ahead gunning for growth. — Sean Ellis in “Hacking Growth”
We used the exact same four questions Raul used for Superhuman:
- 1. How would you feel if you could no longer use alphabeet?
A) Very disappointed
B) Somewhat disappointed
C) Not disappointed - 2. What type of people do you think would most benefit from alphabeet?
- 3. What is the main benefit you receive from alphabeet?
- 4. How can we improve alphabeet for you?
Rolling out the survey
As we haven’t had great success with email campaigns for our users, we decided to deliver the survey in-app. It looks like this and is really easy to complete in just a couple of minutes.
One of the harder parts is figuring out what a active user actually is and what qualifies him or her to take part in that survey. Ellis proposes to ask people who had recently experienced the product. For us, we decided on a threshold of six log-ins. After they had logged in the sixth time, we showed them the survey on the left, both in-app as well as our browser application.
It took some time, as we conducted the survey during off-season (nobody gardens in the fall). But a couple of days ago our 50th complete survey arrived in our database, posted by a trusty slack bot to a dedicated slack channel. It was a huge moment for our startup.
Have we reached product-market-fit?
The results are astonishing: 44% percent of all complete responses fall into the “very disappointed” category, which feels huge. Of course, we only have 50 returns, so far, so results in the future will vary. Still, people love our app far more than we had imagined. We had run another type of survey in spring and were far away from PMF at that time. We had introduced quite a number of improvements since then, but we were also faced with critical reviews and support mails over the last few months. Not a lot of them, but enough to heat up some self-doubt.
While it can be incredibly rewarding being an entrepreneur, it can also be excruciating. There is this nagging feeling that what you’re offering might not be good enough, irrelevant or unnecessary. As we’re building an app for gardeners, something that has rarely ever been done before, this feeling is a constant companion on our shoulders. It was a great relief to be rid of it for five minutes, until the next pressing question comes to mind. Off to the next season, spring is just around the corner!
As Eric Nohlin, an inspiring ultra-endurance cyclist once put it: It never gets easier, you just get faster. (*Edit: This quote is actually by Greg LeMond)
What now?
Up until now I was just writing about question one of the survey, but there are two more that are especially important to determine our roadmap of new features. Just like Superhuman, we used the answers to questions three (What is the main benefit you receive from alphabeet?) and four (How can we improve alphabeet for you?) to generate word clouds, see if patterns arise. Here is what we saw (sorry if it’s in German, I’ll break it down to English):
What is the main benefit you receive from alphabeet?
The biggest words are Planung (planning) and Übersicht (overview), which makes it pretty clear whats the most important feature of our app. It is a vegetable bed planning app and this is what people take home. Not many surprises here, please move on to the next round.
How can we improve alphabeet for you?
This is where it gets more interesting. The biggest words are Pflanzen (plants), which translates to a bigger database of crop varieties. This is consistent to a lot of people we spoke to via support channels and in the community. The other word is Fruchtfolgen (which means crop rotation). This is a feature that we had been speaking about for quite some time but always pushed back to a later point in time. Maybe it is the time to do it now!
As there are only 50 returns so far, it is pretty manageable to read the answers, which is even more helpful. For example, one of our users wrote:
I would like to enter all my desired plants in a list and Alphabeet makes the best combination and turns it into a plan for my garden beds, which takes everything into account. Time, neighbours, crop rotation.
I would also like to see recommendations for crop rotation as a separate function.
This is just amazing. A great feature, described in easy to understand words and almost ready to go into design (it is, by the way). There are a couple more feedbacks like this and I look forward to every survey that comes flying in, because they are so valuable for us.
Key takeaways
I cannot overestimate the value of this framework for us as a startup. It is and will be our compass for the next months, at least for the next gardening season. The framework helps to determine our roadmap, measure product quality and get customer feedback regularly. Product-market-fit is not something that happens once, but needs to be considered at all times.
It is amazing to build on top of the ideas of such great minds as Sean Ellis, Paul Graham, Eric Ries and others and I think what Raul Vohra and Superhuman shared with the startup community in their blog post is of incredible value. Thanks to all of them, what a great time to be an entrepreneur.
