Hey, it's Cindy 🌱 You commented idea, so here is the four-source research loop from the reel. It combines verified startup revenue, app-market estimates, trend direction, and customer complaints.
btw the waitlist for AI System Club is now open! If you're keen on using AI to automate your content, video editing, job search, business or build AI agents, feel free to sign up (only if you want to hehe). Ps. the waitlist gets first dibs:)
the outcome
What you get
A shortlist of five small app opportunities with revenue evidence, trend evidence, complaint clusters, build scope, and a cheap validation test.
Use the guide in order. Gather the real inputs, run the prompts against those inputs, inspect the evidence, then make one reviewable change at a time.
start here
Set it up step by step
Use TrustMRR to find small products with verified revenue. Record the provider badge, metric definition, and update date.
Use Sensor Tower and AppMagic for category, download, and revenue estimates. Treat every market-intelligence number as an estimate.
Use Appfigures to compare trend direction and keyword or category movement over time.
Read recent one-star to three-star reviews for repeated complaints. Keep exact store links and dates.
Score the opportunities, then validate demand with a landing page, interview, preorder, or waitlist before building the full product.
copy these
The prompts
Turn four sources into an opportunity map
📋 copy this
Research small app opportunities using TrustMRR, Sensor Tower, AppMagic, and Appfigures. For each candidate, record the exact product, category, platform, date range, revenue or MRR metric, whether the number is verified or estimated, downloads, growth direction, pricing, and at least twenty recent low-star reviews. Cluster the complaints by frequency and severity. Reject ideas that depend on copying branding, copyrighted assets, private data, or one short-lived trend. Score each remaining opportunity from 1 to 10 on pain intensity, willingness to pay, reachable beachhead, buildability in four weeks, differentiation, retention potential, and platform risk. Return five opportunities with source links, assumptions, the smallest paid validation test, and a kill criterion.
check the work
Quality gate before you trust it
1 Verified MRR and modelled app-store revenue are never presented as the same kind of evidence.
2 Every estimate includes its provider and date range.
3 Complaints come from current reviews and are grouped by repeated problem, not cherry-picked.
4 Each idea has a narrow first user, one job, one price hypothesis, and a validation test.
5 The result includes a kill criterion so weak ideas stop before a full build.
6 Save the source links, as-of date, and final evidence beside the output so another person can reproduce the check.
Guardrail. Revenue and download intelligence can be incomplete, modelled, delayed, or defined differently across vendors. Verify definitions before comparing rows. Market evidence reduces guessing; it does not guarantee product-market fit or profit.
keep it useful
Save the evidence with the workflow
Save the prompt with the source links and the date you verified them. When the tool, policy, price, interface, or documentation changes, update the guide before you reuse the workflow. Keep the inputs and outputs beside the project so the next run can be checked instead of reconstructed from memory.
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