Connection at scale via conversational chatbots
Something that comes up with a lot of creators we talk to is being able to extract value from a “back catalog”. They’ve built an incredible catalog of content over the years, but their audience can't always find the specific answer they need when they need it.
(Seriously, if we had a nickel for every time we heard a creator say “oh ya, I made a video about that years ago”…Iwe'd have like, 20-25 nickels).
Maybe someone is looking through your 200+ YouTube videos for that one piece of advice about X or Y. Or they're digging through months of Instagram posts trying to find your take on A, B, or C (or maybe they are one of the 1 in a million people who actually look through their saved posts). The information exists, but finding it quickly? Pretty much impossible.
Conversational chatbots trained specifically on a creator's content catalog are turning these “stale assets” into tremendous value.
We've built these for creators like Dr. Becky and Good Inside, as well as Shan Boodram, and while the specific implementation varies (some live in free areas of their platforms as lead gen, others are part of paid memberships) the core concept remains the same: allow users to quickly and easily leverage the creator’s expertise.
Here's how it works:
- The AI is trained on the creator's entire content library
- Users ask questions in natural language
- The bot responds in the creator's authentic voice and tone
- Most importantly: it cites specific articles, videos, and resources where the information came from
The last point is crucial, especially in the context where a creator’s content might be focused on a sensitive area. AI can still hallucinate, so we invest a ton of time and effort into ensuring that you can’t get an answer that doesn’t have a specific piece of content to reference.
We're not trying to replace the creator's expertise or create some mysterious black box. Instead, we design these tools to be completely transparent about what they are: a way to help users navigate and access the creator's existing knowledge more efficiently.
A Dr. Becky’s use case is really helpful to visualize this idea 👇️
It's 3 PM, your toddler is having a complete meltdown in the grocery store, and you're at your wit's end...the anxiety is building. Instead of needing to frantically scroll through Dr. Becky's hundreds of videos trying to find her advice on public tantrums, you can ask her chatbot: "My 3-year-old is screaming in the store right now. What should I do?"
The bot immediately responds with Dr. Becky's approach (validation first, then connection, FYI - we’re a Good Inside household over here) and points you to the specific pieces of content where she breaks down her tantrum strategy. Crisis averted, sanity preserved. Well, maybe not, but at least you probably made it out of the grocery store.
The result? Creators can scale their expertise, leverage their existing content, and provide tremendous value to their audience/customers.
Providing customer service for thousands without hiring a team
There has always been a blessing and a curse of scale, especially if you’ve launched a successful low-ticket digital product (anything under $100).
The blessing: reaching thousands of customers and generating significant revenue. 💸
The curse: every single one of those customers has questions. ☠️
For creators, this creates a real dilemma. Hire customer support staff (expensive and often not feasible for lower-margin products) or handle it yourself (hello, immediate burnout!).
We recently experienced this firsthand with Dr. Jen Ashton and her Ajenda Wellness Experiment, which quickly exceeded 10,000 customers. Normally, that level of scale would require hiring dedicated support staff to manage the constant stream of questions.
And while we’ve brought on part-time support to help handle the immediate influx, we are actively developing AI agents trained specifically on those customer support interactions to help support the scale.
Here's what changes in this new paradigm:
- Instead of manually answering 20 variations of "How do I reset my password?" the AI immediately provides the answer and points to relevant resources
- The system learns from previous support tickets, getting smarter with each interaction
- Human support can focus on genuinely complex issues that require personal attention
- Operational costs stay manageable even as customer volume grows
The impact goes beyond just saving time. When you can profitably serve customers at scale without drowning in support requests, it fundamentally changes what kinds of products become viable for creators to launch.
We’re planning a similar approach for a creator with 30M+ followers that we’re launching a $25 product with…will report back in a couple of months to let y’all know how it goes!
Why this actually matters for creator-led products
Neither of these applications will make for exciting social media posts. There's no viral moment when you implement a customer service chatbot. And in theory, neither of them are particularly tied to driving revenue.
But here's what they do accomplish:
- They solve real business problems that have actual financial impact
- They improve the customer experience without compromising authenticity
- They allow creators to focus on what they do best instead of getting buried in operational tasks
We can’t tell you the number of creator-led products that fail because the creator underestimates how involved it is to serve customers vs. make content for an audience. AI is making it easier than ever to provide value to a customer on an ongoing basis, freeing up the creator to keep creating.
So ya…the flashy stuff gets the attention. The practical stuff pays the bills.
