A user logs into your product for the first time, completes one or two actions, then never returns. This is an all-too-common situation that PMs aim to avoid.
Retention is the answer to 'What keeps people coming back to our product?' and is divided into two key areas: user retention and customer retention. By defining meaningful actions and periods, analyzing retention curves, and applying targeted strategies, PMs can build long-term engagement and loyalty. This highlights the potential of targeted strategies to inspire product managers.
This blog delves into retention curves and the methods to measure them effectively.
Why Is Retention Important?
Retention is the most effective and meaningful lever to drive growth. Good retention is a strong signal that there is PMF (product-market fit).
Good retention also signals a higher LTV (lifetime value) of your users. Higher LTV then allows you to power more acquisition channels.
Another way of thinking about retention is that it answers the question: "How many users are getting enough value to keep coming back?"
If the answer is none (or a low number), then you are failing at the most essential truth of creating products—creating long-term value for users. This underscores the responsibility and commitment of product managers to develop products that deliver long-term value to users.
What Is Retention?
Retention happens when users repeatedly do a meaningful action over a defined period.
Let’s take an example.
Consider Spotify's free users. One of the most meaningful actions on Spotify is to listen to a song (or podcast) for at least x seconds.
Assume that 100 users listened for ≥ x seconds today. So, the W0 (week 0) retention is 100%.
Then, we look at the same 100 users and determine what % of them came back in the next week and listened for ≥ x seconds. Let’s say 80% did. So, the W1 (week 1) retention is 80%.
Then, in W2 (week 2), repeat the process for the same 100 users from W0. Let’s assume that only 75% came back.
Keep repeating for multiple weeks, and you will get a curve like this:
Customer Retention: Typical Curve that Flatlines Above Zero
In the Spotify example:
- "Listening for ≥ x seconds" is a meaningful action.
- "One week (7 days)" is the defined period.
Note: This is just an example. The meaningful action could also be other user actions like opening the app, creating a playlist, or doing a search.
Similarly, you could measure retention on a daily or even monthly basis. It is essential to define the right meaningful action and period.
Whenever I think of retention, I answer the following questions to identify the meaningful action and the period:
- What action can the user take to get the most value?
- Given the user's needs, how often should they do the action?
To answer these questions well, I highly recommend deeply understanding user needs and the product’s value proposition.
My rule of thumb: If I can’t find a good answer to question 2, I start with monthly retention. I feel that if users do not use the product once a month, something is wrong.
Types of Retention Curves
Retention curves that go to zero (for some time)
Some products experience retention going to absolute zero, but only for short periods.These products are initially very popular but then die out. Think of games like Farmville on Facebook that were wildly popular but suddenly disappeared.For companies like Zynga (the creator of Farmville), this is common. They produce one hit after another, with retention for older games dropping to zero but sharply increasing for new games.In other industries, like streaming or social media, such curves could be better. Think of Orkut, Friendster, or Blockbuster, where retention dropped to zero and never recovered.This behavior signals user boredom—users stop using the product over time because it no longer holds their interest.
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 are also called "smiling" curves.
Initially, the curve slopes downward. But over time, it moves upward due to:
Network effects: More users make the product more valuable (e.g., Airbnb, WhatsApp).
New use cases/categories: Broadening value propositions (e.g., Uber adding food delivery).
New platforms: Launching on new platforms like Android or iOS.
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What is good user retention?
A typical retention curve (like the above) will trend downward in the initial periods. But over a more extended period, it will flat line above zero and will not decrease any more.
That is precisely what you want -- a curve that flatlines above zero.
(There are two more types of retention curves, which I will talk more about in the next edition)
The next question is: when should it start flatlining, and should it be at 25%, 30%, 50% or some other number?
Short answer: The sooner it starts flatlining—the better. The higher the level—the better.
Long answer: it depends.
When it starts flatlining depends on the kind of product, user needs, competition, and many other factors.
Similarly, the level at which it starts flatlining depends on multiple factors. Luckily, there is enough industry data to create good benchmarks for common industries.
- Consumer Social: ~25% is GOOD, ~45% is GREAT
- Consumer Transactional: ~30% is GOOD, ~50% is GREAT
- Consumer SaaS: ~40% is GOOD, ~70% is GREAT
- SMB / Mid-Market SaaS: ~60% is GOOD, ~80% is GREAT
- Enterprise SaaS: ~70% is GOOD, ~90% is GREAT
(Sourced from Lenny's Good and Great Retention research.)
How can PMs increase retention?
Maximize User Value
Deliver maximum value quickly and efficiently. Build empathy for your users to understand their needs and solve them better than competitors.
Example: Spotify’s Discover Weekly playlists help users find songs quickly and easily.
Make Value Explicit
Show users the value they gain from your product. Remind them of it regularly.
Example: Dropbox highlights benefits like secure storage and easy file sharing immediately after sign-up.
Give So Much That They Fear Losing It
Deliver high value frequently to make users reluctant to leave.
Example: Amazon Prime offers free shipping, music, video, and exclusive deals, making it hard to cancel.
Engage Users Who Might Leave
Identify at-risk users and give them reasons to stay. Analyze behavior before leaving and address it.
Example: Netflix uses personalized recommendations to re-engage users who are losing interest.
Win Back Lost Users
Reach out to users who have left, showing them new features or improvements.
Example: Grammarly emails users about updates that address past concerns, reminding them of its value.
Final Thought
By applying these strategies, you can make a significant impact on improving customer retention. The key takeaway is to focus on delivering consistent value to your users at every stage of their journey.
Understand their needs, address their challenges, and ensure they continue to experience the value your product provides over the long term. This approach not only enhances customer loyalty but also fosters lasting relationships with your audience.
FAQs: Retention Curve
- What is a retention curve, and why is it important?
A retention curve is a graph that shows how many users or customers continue to use a product over a specific period. It helps product managers measure user engagement, identify trends, and determine the product's long-term value.
- What are the types of retention curves, and what do they indicate?
Retention curves include those that drop to zero (indicating user boredom or irrelevance), flatline above zero (a sign of consistent user value), or "smiling" curves that increase over time due to network effects or new use cases.
- How can product managers improve user retention?
Product managers can improve retention by delivering maximum value, making the value explicit, engaging at-risk users, and winning back lost users with targeted strategies like personalized recommendations or feature updates.
- What is the difference between user retention and customer retention?
User retention focuses on keeping individual users engaged by analyzing their behavior and value gained, while customer retention emphasizes maintaining long-term relationships with paying customers through loyalty and satisfaction.
- What are industry benchmarks for good user retention?
Benchmarks vary by industry, such as ~25-45% for consumer social apps, ~30-50% for consumer transactional products, and ~70-90% for enterprise SaaS. The higher and sooner the retention flatlines, the better the retention performance.
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