--- name: untapped-avatar-finder description: Use when you sell a crowded product and rivals already own the obvious buyer. It maps who rivals sell to, finds three or four buyer groups nobody serves from Amazon review stories, checks how big each is on Reddit, picks one, and sharpens it into layers to test. --- # Untapped avatar finder You help a store owner find a buyer group that a crowded product is not yet sold to, with evidence. You map who rivals talk to, find other groups in real review stories, check each group's size in public forums, rank them, and pick one. A hunch is not evidence: one story is not a market. ## Before you start This skill runs on its own. What's below makes the result better, but none of it is required. **Works best with** (or they can paste their own instead): - **Your question** (yours): the decision or problem, and what a good outcome looks like. **Makes it better (optional):** - **Competitors** (yours): the brands buyers compare you with. - **Customer words** (yours): reviews, testimonials, support tickets, survey answers or call transcripts. Export them or paste them in. How to start: 1. **Look first.** Use what they've already attached, pasted or put in their about-me note. In Claude Code, look in the project too for these by name. 2. **If something is missing, advise, don't block.** In one short message, say this skill works on its own and will be better with your question, competitors, customer words. They can attach them, paste them, or say where they are (in Claude Code, a file path). Then ask: "Add them, or shall I go ahead with what you've given me?" If their message already says to go ahead, skip this and start. 3. **When they say go ahead,** do the whole job with what you have. Mark each gap with `MISSING:` where it belongs and never invent a fact to fill it. Keep the answer tight: say each point once, merge steps that give the same thing, and aim for under 700 words unless the job truly needs more. In CHECKS MISSED, name only the checks that failed, or write “none”. **Tools that do this best:** - **Meta Ad Library:** Shows what rivals say and who they seem to talk to, free and public. - **Amazon reviews:** Long life stories from buyers show other groups who already buy the product. - **Reddit search:** Shows how many people discuss the same problem, which is your size check. - **Any good chat AI:** Compares the groups and ranks them against your notes. ## What you need - **Product name and the problem it solves** (required). - **Three to five rivals** (strongly advised): names or Meta Ad Library links for the brands that are winning. - **Amazon links** (strongly advised) for the top-reviewed product, or a similar one. - **Customer data** (optional): who buys from you now, and their order values. - The person pastes what they find (ad notes, review stories, forum threads). Use only what is pasted. If your AI can open pages, say so, and still show the source for each claim. Does not fit: a product that is already unusual, in a new category, or one with no rivals to learn from. Skip it if the product cannot truly help the new group. Do not stretch claims to fit a group. The rule behind this skill: if the product is not truly different, change who you sell to, not what you claim. A new mechanism needs a physically different product, which is rare for products bought from suppliers. Privacy: public posts and reviews only. Label each candidate with a tag or first name only. Never keep reviewer names, profile links or photos. Do not contact anyone. ## Steps 1. **Name the problem the product solves** in one line. Everything below follows it. 2. **Map the rivals' buyers.** In the Meta Ad Library, search the product. For each winning brand, write down the age range, gender, desires and selling points shown in the ads. In video ads, note who appears on screen and what they say. A traffic tool can show how big the rival is (visits, average order value). Repeat for as many successful rivals as you can. The group most of them share is the one to avoid. 3. **Open the Amazon reviews** of the top-reviewed product or a similar one. Sort by top reviews and, if you can, filter to reviews with photos or video. People who add pictures tend to write long stories. 4. **Look for long life stories.** The best reviews say who the writer is and what they went through. Each different story is a candidate group. The sources' examples: new mothers after surgery, men over 65. Short reviews rarely help. 5. **Tag each candidate** with a tag or a first name only, for example "Candidate 1, new mother". 6. **Check the size on Reddit.** Search the situation plus the word Reddit, for example "post C-section weight gain Reddit". Many threads about the same problem mean many people. A single thread means you may have found one person. 7. **Write each candidate's picture from the threads.** The beliefs they hold (for example "only surgery flattens it"), the fixes they tried, and how they feel. Quote the words, with no names. 8. **Choose one.** Pick the group with strong evidence, many threads, a clear wish for what your product does, and no brand talking to them yet. Check the last point in the Ad Library: if nobody is advertising to them, that is the opening. If you cannot show all four, say what is missing. 9. **Carve a layer.** Do not take a slice of the whole market. Take a small group inside it and aim to own all of it. Add layers one at a time. A fat burner for everyone, then for women, then for women over 40: each layer makes the message sharper. The source's examples of this: supplements for women at one life stage, a thinking supplement for entrepreneurs, a pillowcase for people with acne. 10. **Rank the layers** by three things: how strong the pain is, whether they can pay, and whether the group is still large enough. People tend to underestimate how big a group is, so do not cut a layer on a feeling. The source's dating example moves from a problem worth about $500 to one worth about $10,000 by adding "divorced". That is one marketer's illustration, not a rule. Treat any price or pain guess here as something to test. 11. **Run the contrast check.** Look at the top rivals' ads and ask what the polar opposite would be. Does the chosen layer stand apart from them in who it talks to and how? 12. **Write a one-sentence offer line** for the top pick: who it is for, what they get, what makes it different for them. 13. **Plan the test.** Test the top two or three layers with separate ad angles, not separate products. An ad test is what confirms the pain and buying power guesses. A small segment inside a proven market is safer than a brand-new category, because the demand is already shown. 14. **Optional deep research.** Only after you have a pick, you may run a deep-research prompt on that one group and read every source it cites. In the source's run it took about 22 minutes and produced a 39-page report. Treat its findings as ideas to check, not facts. ## What you hand back Use these labels in this order: ``` RIVAL BUYERS Brand | age range | gender | desires | selling points | source (ad link or note) Shared group to avoid: <...> CANDIDATES (3 to 4) | story in one line | quote | belief | tried | feeling | where found SIZE CHECK | search used | threads found (few / some / many) | note PICK because: | | | Not picked: LAYERS (ranked) 1. | pain: | can pay: | size: | evidence: <...> OFFER LINE (top pick): CONTRAST: TEST PLAN: CLAIMS NOTE: CHECKS MISSED: ``` ## After this When you've handed it back, suggest what they could do next in one short question. It's a suggestion: if they're done, that's fine. Offer these, and say they can type their own: - **Understand your buyers** with the [Job spec writer](https://useaiblocks.com/skills/job-spec-writer). It takes the shortlist. - **Make image ads** with the [Feared outcome image ad maker](https://useaiblocks.com/skills/feared-outcome-image-ad-maker). It takes the brand brain. - **Make an offer people want** with the [Hidden offer finder](https://useaiblocks.com/prompts/hidden-offer-finder). It takes the brand brain. - **Make video ads** with the [Video ad script writer from customer quotes](https://useaiblocks.com/skills/quote-video-ad-script). It takes the brand brain. - **Plan what to test** with the [Learn what sells from 50 different image ads](https://useaiblocks.com/workflows/image-ad-test-learnings). It takes the brand brain. If they pick one and that skill is added here, carry straight on with what you just made. If not, give the link and say what to bring. ## Checks Run these before handing back. Fix any that fail, or list them under `CHECKS MISSED:`. - Each rival row has a source. Any age, gender or desire taken from a guess is marked `[guess]`. - Each candidate has a real quote, a belief and a tried fix. No names, links or photos. - The size check shows what was searched and what was found, not just "big market". - The pick meets all four tests or says which one it lacks. - The test plan changes the angle, not the product. - No claim for the new group goes beyond what the product really does. Health, money and legal claims carry a line telling the owner to check with a qualified person. ## If something is missing - No rivals given: `MISSING: rival brands or Ad Library links`. Ask for three, or say the rival map cannot be done. - No review stories pasted: `MISSING: Amazon review stories`. Give the steps and stop at that point; never write a story. - No Reddit threads: `MISSING: forum threads for the size check`, and the candidate stays `[unsized]`. - No ads seen for a group: say "not checked", not "nobody is advertising". ## Avoid - Choosing a group from a single story, or because it sounds clever. - Stretching the product's claims to suit a sad or hopeful story. - Treating the $500 and $10,000 pain example, or any rule of thumb here, as a measured figure. - Starting a deep-research run before the pick. It is slow and it repeats what you tell it. - Splitting into groups so small that you cannot reach enough people.