Long-term retention is the metric OpenAI prioritizes above all others for ChatGPT, because it signals that the product durably solves people's problems, and revenue follows from that rather than needing to be optimized directly.
Asked to allocate 100 priority points across possible metrics, Turley puts them all on long-term retention, arguing it's the truest signal of product value and that revenue naturally follows. ✦ AI generated
Nick Turley · BG2 Pod · 2026-03-15 · original ↗
starts at this moment · 3:42
“If you were to allocate a 100 units of points to these metrics, which metric can you like distribute the 100 units across these metrics in order of importance for you right this second?”
I care a lot about long-term retention and I would put all my points there. Um because I'm really proud of the retention stats we have. Huge, but ultimately the sign of durable value[s], whether or not people are coming back in three months because that means you're really solving their problems. And I think things like revenue, they follow from that.
verbatim transcript · starts at 3:42
3:33look at, um, all kinds of stuff in aggregate because really there isn't like this one single thing that you can optimize for. >> If you were to allocate a 100 units of points >> to these metrics, which metric can you like distribute the 100 units across these metrics in order of importance for you right this second? It's a good question. I I care a lot about long-term
3:51retention and I would put all my points there. Um because um I'm really proud of the retention stats we have. >> Huge, >> but ultimately the sign of durable values, whether or not people are coming back in three months because that means you're really solving their problems. And >> yeah, >> I think things like revenue, they follow from that. Um >> yeah. >> Um versus like, you know, trying to go
4:10on those things directly. And we've we've had a lot of success making very principled decisions u on this stuff. Like one good example is you GPD4 used to be behind a pay pay wall because we couldn't serve it to everyone and then we had GPD4 which was a total breakthrough >> in um in in our ability to inference it and um >> so we just gave it away for free and
4:31that ended up being totally revenue positive and retention positive because it just provided access to the tech and I think when you make your decisions that way and you focus on the customer >> you end up with a great product and revenue obviously follows too. >> Phenomenal. >> Yeah. Well, it uh it shows up in the numbers. You know, I I posted this chart uh yesterday on the data that we have,
4:50you know, from a third party. The retention curves for chat GPD are smiling. Look at that. Just like that. And that is a rare that is a very rare occurrence, you know, as as we know. And um why why do you think like if you were to give us a narrative on that smile curve? What is the why do these smile curves exist? What are you seeing in
5:09Chad GPD that has people who have who have maybe turned off for a couple of weeks or months coming back and why are they coming back? >> Look, there isn't one single thing. You know, the way you build a retentive product is lots and lots of little things and really trying to make it better systematically. I will say that you know with AI and in particular chat
5:29GBT I found that it takes people some time to really understand all the parts of their life they can delegate right and I think many users for that it's a multi-month process for them to understand how can this thing help me and what are all the different ways >> that um I could plug chatbt into my life >> um and um but you know when I think
- ·All 100 priority points go to long-term retention
- ·Signals product durably solves users' problems
- ·Revenue follows retention, not optimized directly
- ·Turley: 'proud of the retention stats we have'
- ·Coming back in 3 months = real problem solved
- ·Revenue treated as downstream, not a target