AI Products Average Retention: Why ChatGPT Keeps Users Coming Back While Others Lose Them

A new study from yipitDATA looked at how well the top AI chat tools keep their users over time. The data tracks real people from the day they first tried each product and follows them month after month.

The chart shows average retention across different groups of users (cohorts) for up to 24 months after their first use.

Here is what the numbers reveal:

• ChatGPT (blue line) starts around 40% and dips a little in the early months. After that it climbs steadily and ends at about 76% after two years. It is the only one showing this strong upward trend; often called a hockey-stick pattern. Users who stay past the first few months tend to keep using it a lot.
• Gemini (black line) begins close to ChatGPT at around 39%. It drops to about 30% in the middle months but then rises gradually to nearly 49% by month 24. It is stable and improving, but still sits well below ChatGPT.
• Claude (yellow line) starts at 32%, falls to around 23%, and stays flat for a long time. Then after month 20 it shoots up sharply and reaches 42%. This late recovery is the most noticeable among all four tools.
• Perplexity (red line) shows the weakest pattern. It begins at 28%, drops quickly to 20%, and keeps sliding lower, ending around 16% after two years. It follows the classic “leaky bucket” behaviour; many people try it once or twice and then stop coming back.

The data comes from yipitDATA and looks at actual user behaviour across large groups, not just downloads or sign-ups.

What These Retention Curves Actually Mean

Retention is one of the clearest signs of whether an AI product is truly useful in daily life. If people keep opening the app month after month, it means they are getting real value from it.

ChatGPT’s steady rise shows it has become part of many users’ regular workflow. Once someone gets comfortable with it, they tend to stick around and use it more over time.

Claude’s late jump after 20 months is interesting. It suggests that some users who stayed with it discovered deeper uses; maybe for coding, writing, or research; and then increased their usage sharply.

Gemini is growing but slower. It has a solid base but has not yet matched ChatGPT’s stickiness.

Perplexity’s steady decline points to a common problem in search-style AI tools. People try it for a specific question, get an answer, and then move on. It has not yet turned into a daily habit for most users.

Why Retention Matters for AI Founders

In the AI space, building a good model is only half the battle. The real challenge is making sure people keep coming back after the first few weeks.

High retention means:

• Users see ongoing value
• The product becomes harder to replace
• Revenue becomes more predictable (especially for paid plans)

The yipitDATA numbers show that not all AI tools are equal when it comes to long-term user loyalty. ChatGPT has clearly figured out how to turn first-time users into regular ones. The others still have work to do.

For anyone building an AI product today, this chart is a useful reminder. Early downloads or hype can look impressive, but what really counts is whether people are still using it 12 or 24 months later.

Data source: yipitDATA study on AI product retention \(tracked across user cohorts\).

This is part of our case studies series looking at Indian and global startup trends and product metrics on desifounder.com. We will share more updates as new reports and data come in.