Give Your AI Better Social Research: A Workflow That Beats Blank Prompts

The quality of an AI’s content ideas is capped by what you give it. A blank prompt gets a blank answer. Here is the workflow we use.

“Give me ten content ideas for a mushroom coffee brand.” Every AI will answer that instantly, and every answer will look like every other brand’s feed. The model isn’t the problem. It has nothing to work with except the average of the internet.

The fix is to give it evidence: real posts from your niche, with the numbers that show which ones worked. That turns the AI from an idea generator into an analyst.

Why blank prompts produce generic content

  • No performance data. The AI can’t tell a post that flopped from one that broke out.
  • No niche context. It doesn’t know which creators your audience follows or what they respond to.
  • No recency. Its sense of what works on a platform can be months or years old.

The workflow

  1. Choose three profiles your audience already follows. Competitors, adjacent brands, or creators your customers trust.
  2. Capture a few months of posts from each with the Marketpon extension. Just scroll the profile as normal.
  3. Check the research library for outliers and the plain-English findings on each profile.
  4. Export the research as a Markdown brief, or connect your AI directly with the Marketpon MCP connector.
  5. Ask analysis questions first, ideas second. Make the AI explain the pattern before it writes anything.
Marketpon findings such as Reels earning 2.8 times what carousels do, with the post counts behind each finding
Findings are counted from captured posts, with the sample size behind each one. Real screen, other creators blurred.

Prompts that work with real research

Paste your export (or connect the MCP connector), then try these in order:

1. Using this research, what do the outlier posts have in common that the typical posts don’t? Cite the posts.
2. Which opener styles appear most often in posts above 5x their author’s median?
3. Is there a format or day of the week that consistently beats the rest? Only claim it if the sample size supports it.
4. Based only on these patterns, suggest five original post ideas for my brand. For each, name the pattern it borrows and what makes it ours.
Make the AI show its workAsking the model to cite posts and respect sample sizes is the difference between analysis and confident guessing. Our findings show their counts, for example “Reel averages 264 across 551 posts, versus 93 for carousel across 106”, so the AI can weigh them properly.

What good output looks like

A good answer names a pattern, points at the posts that show it, and turns it into an idea that fits your brand. For example: “Three of the five biggest outliers open with a direct statement rather than a question, and all three are Reels under 30 seconds. Idea: a 20-second Reel that opens with ‘Most coffee crashes you at 2pm. Here’s why.’”

If the AI starts inventing statistics or names creators you didn’t give it, push back and ask it to work only from the research. Grounded answers are the whole point.

Your AI, your subscription

Marketpon doesn’t write your posts. It gives your AI better material. Use Claude, ChatGPT, Gemini, Grok or Perplexity, whichever you already pay for. See how to connect your AI so it can read your research directly.

Frequently asked questions

Does Marketpon write posts for me?

No. The research launch is for capturing and studying posts. You bring your own AI tool and subscription for writing.

Which AI tools work with Marketpon exports?

Any of them. The Markdown export pastes into any chat. The MCP connector works with AI clients that support remote MCP servers, such as Claude and ChatGPT.

Is it OK to reuse the posts I capture?

Capturing a post doesn’t grant permission to reuse its wording, images or video. Study the patterns, verify the facts, and make your own work.

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Trevor builds Marketpon and uses it every day to research the brands he runs. He writes about turning social feeds into research you can actually act on.

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