Free lesson

Picking a winning niche with AI

A free taste of the course. In about ten minutes you'll go from a blank page to a validated niche and three product angles — with AI doing the heavy lifting.

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Most people pick a product first and hope a market exists. We do it the other way round: find a group of people with a problem and money to spend, then let AI surface products that solve it. Here's the short version.

1

Start with a problem, not a product

Pick a person and a frustration before you ever look at products. Niches with a clear, repeating problem convert far better than random trending items.

Try this prompt
Act as a market researcher. Give me 10 specific groups of people who repeatedly spend money to solve an everyday frustration. For each: who they are, the problem, and why they keep buying.
2

Use AI to size the demand

A niche only works if enough people are already searching and buying. Use AI to estimate demand and seasonality before you commit a cent.

Try this prompt
For [niche], summarise current demand: search interest, whether it is growing or seasonal, typical price points, and 3 sub-niches with the most buying intent.
3

Find the gap competitors leave

Look at who is already selling and where they are weak — slow shipping, ugly stores, no content. The gap is your opening.

Try this prompt
List the top 5 brands selling to [niche]. For each, note their angle, price, and one weakness a small, fast brand could beat them on.
4

Pick three angles to test

Don't marry one idea. Choose three product angles and let the ads tell you which one wins — that is the whole testing game.

Try this prompt
Give me 3 product angles for [niche], each with a hook, the buyer it targets, and a one-line ad concept I could film or generate.

What you just learned

  • Pick a person and a problem before a product.
  • Validate real demand with AI before committing.
  • Win on the gap competitors leave open.
  • Test three angles and let the data pick the winner.

That's lesson one.

The full course walks you through both store models end to end — research, build, ads, and scaling — with AI doing the heavy lifting.

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