Product Market Fit Revisited

A window with doors in the wrong direction

A few months ago I posted a short series of posts about product market fit (PMF). You can find it all here, here and here.

Today I’d like to revisit this topic, from a different, and quite unique angle. You see… since I’ve posted this series, I had the chance to reflect a lot on this topic, since it currently occupies my day-2-day job as well.

And while reflecting on PMF, I took a closer look at several well known products and considered whether they have reached a product market fit or not. 

In this post I’d like to share my insights from my personal reflection, while focusing on two of the products I analyzed:

  • Spotify
  • Google Maps

Let’s dive in by discussing each product separately and afterwards I’ll share my own personal take about each.

 

Spotify

Spotify is the #1 app for streaming on-demand music. According to Google Play it has more than 1B downloads and 4.5 stars rating posted by 28M people. I didn’t visit the iOS store, but I assume it’s doing great there as well. Amazing!

On the face of it it has a great PMF. So many users, so many great reviews. Wow.

Guess who is unsatisfied by it? Me…

But we’ll get to it in a second.

 

Google Maps

GM positions itself as a “Real time GPS navigation & local suggestions for food, events & activities”.

It has 10B downloads on Android, but it’s not really fair, because the app is pre bundled on Android devices. The reviews, though, tell a different story, with an average of 3.3 stars rated by 16M people.

The ratio of people bothered rating it to the amount of people who downloaded it is much lower than the Spotify ratio, which also hints that most people didn’t actually download it or even try it.

So overall – doesn’t sound like it has reached PMF.

Guess who is satisfied by it? Me… 🙂

But as I noted above – we’ll get to it in a second.

 

PMF revisited

In the first post I wrote about it (linked above, but here it is again), I summarized the common practices for identifying whether your product has reached PMF or not. I quoted 5 of these industry practices, but let me paste here what I consider as the main two:

  1. At least 40% of your customers said they’ll be ‘very disappointed’ if they could no longer use your product
  2. When your users/customers stop churning. 

The products I discussed above are B2C products, so the term ‘customer’ is less dominant here. Only the premium users of Spotify can be considered customers. The rest (Spotify’s free tier users or all Google Maps users) are ‘just’ users.

Still, when you consider these criteria for PMF – then I think it’s safe to say that at least 40% of Spotify’s users & customers would be very disappointed if they can no longer use the app, and I guess Spotify’s churn is also extremely low.

Hence – I think it’d be safe to say that Spotify has reached PMF quite a long time ago.

 

When it comes to Google Maps, though, the story the reviews tell hints that the product hasn’t reached PMF yet. I don’t think that at least 40% of Google Maps users would be very disappointed if it’s gone (as there are other strong alternatives) and I do believe the product suffers from high churn (again, because there are other strong alternatives).

That being said – I don’t have access to the real data, so of course those are just speculations.

 

Now, so far I provided a very high level, but objective, analysis of the two apps in terms of PMF.

Let’s talk for a second about my personal take on those.

 

My personal take on Spotify and Google Maps

I have been a Spotify premium user for a few years now. The app is decent, but I’m craving for something much better. It’s not serving me very well.

You see – as I envision a music streaming app – I’d imagine that the main user flow should start with the mood I’m currently in. I believe that my current emotional state is the main indication for the type of music I’d like to hear right now, and on top of this the product should apply my personal taste in music.

If I am happy – I’d be happy to hear a dance or party music. 

If I am sad or just ‘down’ – the best music for me would be a calm music or motivational one.

If I am ‘focused’ I’d probably want to hear music that wouldn’t distract me, and instead disconnect me from the surroundings.

And if I am…. Well… you got the drift, right?

Currently, the app doesn’t work like that as the main flow is focused on playlists. And each time I launch the app I need to dig up a playlist that matches my mood. Yes – I could create a playlist for each mood – but this is tedious and static (not updated automatically by Spotify’s algorithms). I created a ‘happy’ list and a ‘quite’ list – but those are not fine grained to my rich emotional scale I can be in (or any other person for that matter).

Instead, a machine learning algorithm, based on 1B users could learn and generate playlists that match each of the 10 common moods people are in. Also their discovery algorithms could be tuned to moods as well.

 

This is my main problem with the app, but I’m also unhappy with how the app is dealing with classical music. Yes, you have all the classic pieces there, but classical music is played differently.

If I want to hear Beethoven Symphony #5 for example, then I expect Spotify to lay out for me the Symphony as a whole, and not expect me to ‘build’ myself the Symphony from its 4 tracks.

Also – classical music pieces usually have long titles, which are poorly supported by the app and it’s very hard to read.

 

Last – I find the discovery features of Spotify quite poor. The most popular songs will keep popping up in any list, and it does a poor job in helping me find ‘gems’ that I’ve missed in the 35 years I’ve been listening to music. It also suggests songs in languages I’m really not interested in, and I found no way to disable that.

 

Overall – I’m not very happy with the app as it doesn’t serve me well. I therefore went on a hunt to find an alternative and I did try the premium version of Deezer. Sadly, instead of being more innovative and taking a different approach than Spotify – Deezer is just a copycat of Spotify but just claims to do a better personalization. At the time I tested it (4 years ago) – I didn’t find it to be true, so I gave up and came back to Spotify.

Hence, I’m using Spotify not because I want to, but because there are no better alternatives.

 

As for Google Maps – I’ve been using it for years and it’s been serving me greatly. When I travel abroad this is my go-to app for discovering restaurants, shops and stuff around me. The reviews of each place are quite reliable, and I also found myself contributing to the reviews with my own experience to help others.

When I’m in NYC then I’m using it to plan my daily commute using the subway, and I’m using it for navigation when I travel on foot.

So, for me it’s great. I never looked for alternatives because I never felt the need.

 

So why does the app suffer from bad reviews? I think the problem is that with the value proposition it promises. When Google says it’s a navigation software then people would try to use it also when navigating with their car. And for that – it sucks. Waze (another Google’s product) is doing a better job (though personally I think Waze hasn’t delivered on its promise in the last few years – but that’s a discussion for another time).

Google also promises that you can plan your daily commute using it. For NYC – it might be true. But as you can see in the reviews – it’s not doing a great job in other cities around the world.

For this specific task, there are apps like Moovit which are doing a better job.

Hence, I think that the product owners of Google Maps should stop their marketing efforts and revisit their vision for the product. What should be the main value proposition of Google Maps?

If you want it to be a navigation software – then merge it with Waze and make the best navigation software out there.

If you want it to be used as a daily commuting planner – then focus on connecting to all public transportation APIs or leverage the crowd wisdom in a great way (you probably need to do both).

If you want it to be a discovery engine for your surroundings (like Yelp) – then focus on that.

The app lacks focus in terms of its value proposition and therefore it’s not getting love from users and has no PMF.

 

Are the PMF benchmarks good enough?

Now that you read my personal take on these two apps, let’s see how the PMF benchmark works for me when it comes to these apps:

Let’s start with Spotify:

  1. Would I be very disappointed if Spotify is gone? I guess so because there is no better alternative.
  2. Would I stop using Spotify? Not in the near future.. Again because there is no better alternative.

 

According to this test – Spotify has reached PMF for me, but this is not true. We’ll discuss it more thoroughly in a second, but let’s switch to Google Maps now:

  1. Would I be very disappointed if Google Maps is gone? Yes, because it delivers the value I need, and I’ll probably need to install 2 additional apps to get the same value in case it didn’t exist.
  2. Would I stop using Google Maps in the future? No. No reason for me to do so as I’m not craving for anything else.

 

So – according to this test – Google Maps has reached PMF for me. This is true for me, but as we’ve seen – it’s not true globally.

 

What can be learned from this?

  1. PMF is very personal. It’s not a surprise and it makes total sense. Practically it means that you can develop a product that it’s a great fit for many of your customers, but some wouldn’t be happy with it, even though they belong in the same industry and in the same domain. Should you make an effort to cater for them as well? Not necessarily. You must never lose sight of the big picture and your north star – focus on the features that will get mass adoption and only develop niche features if getting this niche ‘hooked’ is strategic for you. Sadly, for me it means that I’m not going to get the music streaming app I want anytime soon 🙂
  2. The PMF testing criteria are not good enough. And I think this is the main take away from this post: A true PMF is achieved when users/customers are no longer craving for a better alternative. E.g. – you might see a low churn, and they might be very disappointed if you’re gone – but they still don’t like you. They are only using you because they have to, as there are no better alternatives. This is something you must always check with your users/customers and therefore you can’t rely on the PMF tests as a solid indication of whether you’ve reached a PMF with your product. Meeting those criteria are a must, but not necessarily enough.

If you rely solely on those, as soon as a better alternative emerges – your churn will rise and it will catch you by surprise, pushing you to be on the ‘reactive’ side. The side you don’t want to be in.

 

The more I think about it, the more it makes sense to me. However, I never read such a statement before on any blog post that covers this topic, so I’d be happy to get your feedback on it and tell whether I’m up to something here, or I just misinterpreted reality 🙂

 

That’s it for today!

If you found this post/series useful – let me know in the comments. If you think others can benefit from it – feel free to share it with them.

Thank you, and until next time 🙂

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