Nick Mines TikTok Comments for ChatGPT Use Cases

ChatGPT's explosive growth wasn't just the result of having powerful AI technology—it came from deeply understanding how people were actually using the product in unexpected ways. Nick Turley, head of ChatGPT at OpenAI, revealed a surprisingly simple but effective user research technique that helped fuel this understanding: mining TikTok comment sections.

When ChatGPT launched, the team faced a challenge common to horizontal platforms—understanding the vast array of use cases emerging from their open-ended product. Traditional user interviews couldn't keep up with the diversity of applications users were discovering.

"I was talking to as many users as I could in my calendar," Nick explains. "The weeks after ChatGPT was just fifteen-minute user interview the whole week through. And it was unusual—I usually stop doing interviews when I can predict what the next person's going to say. That's how I know I've talked to enough users. But it just wasn't happening. I just kept getting new stuff."

To supplement these interviews, Nick turned to an unconventional source: viral TikTok posts about ChatGPT. These posts would often generate thousands of comments from users sharing their own creative applications of the technology.

"There's these crazy TikTok posts that go viral and they have like 2,000 use cases in the comments," Nick shares. "I go through those in detail because it's not like I knew about those use cases either—they're very emergent. I just go through the comments and process because there's so much to learn."

This approach allowed the team to discover applications they never would have imagined on their own. The comment sections became a goldmine of user-generated ideas, with people freely sharing how they were integrating ChatGPT into their lives and workflows.

What makes this tactic particularly valuable is that it captures organic, unprompted feedback at scale. Unlike formal user research where participants might be influenced by the interview context, TikTok comments represent spontaneous sharing of real-world applications.

The approach also democratized product discovery. Rather than relying solely on the team's imagination or a small sample of interviewed users, they could tap into the collective creativity of millions of users experimenting with the product in real-world contexts.

Nick credits this "out-of-product discovery" as a key factor in ChatGPT's rapid evolution and retention. By identifying emergent use cases quickly, the team could prioritize improvements that aligned with how people were actually using the product, not just how they imagined it would be used.

This technique exemplifies a broader principle Nick emphasizes: in AI product development, you often "won't know what to polish until after you ship." By monitoring social platforms where users naturally share their experiences, product teams can quickly identify which capabilities to enhance and which problems to solve next.

For teams building emerging technology products, this approach offers a valuable lesson—sometimes your most valuable user research happens outside your formal research processes, in the spaces where users are organically sharing their experiences with others.