Hey there,
Hope you are well and having a great start to the new year.
For me, 2024 is about 3 things: Health, Learning, and Creating Value. And it is about doing less, not more. (More details)
I would love to know your 2024 plans.
Feel free to reply to this email and let me know -- what is the ONE thing you want to do in 2024 that will make you look back and feel happy about the year?
With that, let's get to today's post on retention curves.
In the December edition, I spoke about retention -- what it is, what is a retention curve, and how can PMs improve retention.
In that edition, I mentioned one specific type of retention curve, that flatlines above zero👇
Today, I talk about two more types of retention curves that are not typical, but still exist. Both of them look similar, but have a very different story.
Retention curves that go to zero (for some time)
There are some products where retention goes to absolute zero. But only for short periods of time.
These products are very popular to begin with, but then one fine day they are not. And they die.
To put this into perspective, think of games that became extremely popular when they launched (like Farmville on Facebook.) But then disappeared all of a sudden.
Zynga, the creator of Farmville, created many more smash-hit games after Farmville. And, as you can see below, all of those games were bigger hits than Farmville.
So in the long run, the retention curve for Zynga users might look like this 👇
Every spike in the graph would typically correspond to the launch of a new game.
So, when retention curves go to zero in the long-run, it is not always bad. You need to interpret retention curves based on the right context, which includes the type, maturity, and stage of the product.
As we see in Zynga's case, this is just the way things work for them (and other products like them.) They produce one hit after the other, and see retention dropping to zero for older games, but then sharply increasing for new games.
In other cases, like streaming, social media, etc., these types of retention curves are bad. Think of Orkut, Friendster, Blockbuster, Napster, etc. Their retention touched zero, never recovered, and the products permanently died.
It's interesting to note that this type of retention signals a different type of user behaviour -- users get bored after a while, which makes them use the product lesser and lesser, until they stop using it altogether.
Whereas in the case of flatlining curves, the user behaviour is different -- there is a percentage of users who like the product so much that they keep using it even in the long-term.
Retention curves that flatline, but then increase sharply
These curves are also called "smiling" curves, because they look like a smile.
First, these curves are downward-sloping. But, over time, they move upwards again, and a smile occurs 👇
Theoretically, this happens because the product offers more value than before or more users are get value than before. This could happen because of three reasons:
- Network effects: when there are more users using the product, the product becomes more valuable for the existing users. And that is why the flattened curve starts moving upwards. Airbnb is a great example. With an increasing number of hosts signing up, you see more users booking on Airbnb. Whatsapp and Instagram are two other examples -- when users see more of their friends using the products, they also start using it more.
- New use cases / categories: users start using the product more often when they see new categories or use cases that become available to them. A few examples: Uber experienced increased usage after they launched food delivery, grocery delivery, etc. Google Maps: would have seen a usage increase when they broadened their value prop from being an "only navigation" app to also being a "business discovery" app.
- New platforms: this happens when products launch on newer platforms like Android, iOS, Web, etc. Every launch leads to an increase in retention, pushing the curve in an upward direction. Instagram and Clubhouse were iOS only when they launched. And saw a great surge of users when they launched on Android.
That is it for this post. I truly hope this post helped you get a better understanding of user retention.
Other Learnings
- A lot of people want to disrupt the way they take showers. Some great ideas here.
- Feature or bug? Uber's hidden way of overriding OTP (one time password) verification.
- As a PM, I don't need to know all the answers.
