Find the unmet need before anyone else builds it.

What NicheRadar does

It answers one question: where are groups of people actively asking for a tool or product that doesn't exist yet — and which of those gaps is actually worth building into a business?

How the value score works

When live, each signal gets a 0–100 value score blended from five pillars — all shown on the card so you can see why:

• Demand (25%) — upvotes, comments, and how many people raise the same need.
• Persistence (25%) — in how many of the last 12 months this theme has shown up. Durable beats a one-week fad.
• Momentum (20%) — whether demand is rising or cooling (recent months vs. earlier).
• Monetizability (20%) — a business audience plus explicit "I'd pay / $ / subscription" language.
• Whitespace (10%) — "is there an app that…?" means they looked and found nothing.

Each card carries a sparkline of demand over time, a persistence read ("seen in 5/12 mo"), a momentum arrow, and a plain-English verdict. A confidence tag shows how much history backs the score — so a brand-new spike isn't mistaken for a proven trend.

How demand is tracked over time

To judge whether demand is consistent — not just hot today — the refresh does two things: it backfills from Reddit's top-of-year posts (real activity from the past ~12 months) and it saves every run to a local history.json that accumulates forever. Each theme is tracked by its dominant keyword, so the same need is followed month over month — building the past-and-future track record you asked for.

From raw posts to a handful of ideas

Individual posts are noisy, so NicheRadar clusters them into named opportunities. A Claude model reads every scored signal and groups them by the underlying need — "Family account & password management," "Grocery-receipt recipe generator" — and writes each a one-line thesis; the card then inherits a combined value score, a demand sparkline, and the source posts beneath. Clusters need two or more separate posts, so repetition itself acts as a validation filter. (If the model is offline, a keyword heuristic groups them as a fallback.)

Cross-checked against Google Trends

Reddit tells us people want something; Google Trends tells us whether the world is searching for it more over time. For each named opportunity, Claude picks a search term and judges whether a big-tech product already owns that space, and the pipeline pulls the term's real 12-month Google Trends curve. The board flags the sweet spot — rising search interest with no big-tech incumbent — and sorts those to the top by default. Every card carries two sparklines: Reddit demand and Google search.

Where the data comes from

How the refresh works

Run node refresh-local.mjs on your own machine: it reads public old.reddit.com listings for a set of idea & builder subreddits, detects and scores the demand signals, pulls Google Trends, and injects the fresh data straight into this page. Re-run it (or schedule it) and redeploy — that's what moves the "Last refreshed" date, with no server running 24/7.

Why it runs from your machine (and what's next)

Reddit now returns 403 Blocked on its .json API for everyone, and self-serve API apps were closed by its Nov-2025 Responsible Builder Policy. The public old.reddit.com pages still load fine from a normal home connection — so the refresh runs locally, from your own IP, and needs no Reddit app. Next steps:

• Post bodies + AI clustering — fetch each post's full text and group raw requests into named, summarized product opportunities.
• Breakout Google Trends per niche — beyond the general top-trends feed.
• Physical-product signals — Amazon Movers & Shakers, r/BuyItForLife and r/Anticonsumption gap-spotting.
• Always-on option — a hosted refresh so the shared site updates without you (the worker/ folder is a start, though Reddit often blocks cloud IPs).