Picking blog topics without knowing if anyone is searching for them is just guessing with extra steps. This two-part prompt finds topics with real search demand, buying intent, and a starter draft for each, cutting research time roughly in half.
A Redditor named u/Chris-AI-Studio posted it in r/ChatGPTPromptGenius from their personal prompt collection. The post is short and the prompt even shorter, but the structure behind it is worth understanding before you run it.
The Base Prompt
Here it is, word for word as the original poster shared it:
“Find blog or video topics that rank well for [target audience] interested in [industry/niche]. Prioritize those with high intent, decent search volume, and relevance to my [product/service]. Include a short draft for each.”
37 words. And it’s doing three separate jobs that most people handle in three separate conversations with AI.
Why It Works
Most topic research prompts ask for something like “popular content ideas in [niche].” The problem is that popular doesn’t mean converting. A topic can pull solid search volume and still attract people who will never buy anything from you. Think beginner tutorials in a tool that only professionals pay for. Great for traffic, useless for revenue.
This prompt fixes that in two ways. The [target audience] + [industry/niche] pairing forces the AI to think about who’s searching, not just what’s trending. Then [product/service] at the end builds in a relevance filter. The AI isn’t generating popular ideas. It’s generating ideas that actually connect to what you sell.
The “short draft for each” instruction is the quiet win. Most topic research prompts give you a list and leave you to figure out the angle on your own. This one returns a list plus a usable starting draft for every entry. That’s two steps collapsed into one, and if you’re running a content calendar under deadline pressure, that difference adds up fast.
The Advanced Version
The original poster also shared a deeper version that takes this a step further. Instead of describing a general audience, you build a specific buyer profile first. Name, job role, pain point, what they’ve already tried, what they want, why they’re stuck. Then the AI finds content topics that would attract exactly that person at exactly the right moment.
One commenter in the thread suggested adding even more behavioral context: what support tickets look like, what buyers say in reviews before they pay, what objections come up in sales calls. That kind of grounding shifts the output from “AI-generated content ideas” to “topics my customers are Googling right before they buy.” Big difference in practice. The more the AI understands the emotional state behind a search, the closer the output gets to the kind of content that actually moves someone to act.
Use Cases
- Solopreneurs building a niche blog around a course or service
- Content marketers who need to pitch topics with built-in SEO rationale attached
- Agency writers onboarding fast into an unfamiliar client niche
- Newsletter operators who need to bridge editorial content with product promotion
- Founders running early-stage content strategy without a dedicated marketing team
🎯 Prompt of the Day
This is the advanced version, reproduced exactly from the original post. Fill in the brackets with real data from actual clients and the output changes significantly:
“My ideal client is [Name], a [job role] who’s struggling with [pain point]. They’ve tried [solution], but it didn’t work. They want [goal], but feel stuck because [reason]. Find 10 high-converting content topics to attract them, each with a short draft and call-to-action.”
Six brackets. Each one narrows the result toward a real person instead of a demographic category. The more specific the inputs, the more the output sounds like it was written for a single frustrated person rather than a general audience.
Worth noting: the call-to-action requirement is built into the research phase. A lot of content underperforms not because the topic is wrong but because nothing in the post guides the reader anywhere. Starting with the CTA in mind keeps the conversion logic visible from the first draft.
For the best results, pull your bracket data from real sources. Sales call notes, support ticket language, review mining, customer interviews. Hypothetical personas give you generic output. Real customer language gives you something you can actually publish.
Take It for a Run
Start with the base version to get a feel for the output. Swap in the advanced version once you have a real client profile to work with. Run it a second time with slightly different bracket inputs and compare the two sets of topics side by side. Small phrasing changes in your audience description often surface completely different angles. And before you finalize your version, check the original thread in r/ChatGPTPromptGenius. The community suggestions in the comments are worth reading, especially if you want to push the buyer-intent angle further.
Frequently Asked Questions
Q: Should I focus on ranking topics or buyer intent?
Focus on what buyers are actually doing right before they convert , that’s more valuable than pure ranking potential. Look at support tickets, sales calls, refund reasons, and comparison queries in your niche. These real buyer behaviors tell you what content actually moves people toward a decision.
Q: Where should I get topic ideas from?
Pull from your own business data first: support tickets, sales conversations, and refund reasons reveal actual pain points and objections. Then layer in search research , look for “X vs Y” comparisons and niche-specific conversations. This combo of internal intel plus market research beats generic SEO tools.
Q: Should I organize topics by funnel stage?
Yes. Structure them strategically: 3 pain-aware topics, 3 solution-aware, 3 product-aware, and 1 objections breakdown. This keeps your content mix balanced and moves people through their actual buying journey instead of just churning out awareness posts.
Q: What tools should I use?
Use a mix: Ahrefs for keyword data, SparkToro for audience insights, and Pulse for Reddit/social data. Reddit especially matters , seeing what your target persona discusses in real communities gives you unfiltered insight into actual concerns and the language they use.
Prompt to Find Blog Topics with Demand, Intent, and Conversions
by u/Chris-AI-Studio in ChatGPTPromptGenius