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Digital Exhaust · daily ban:medium tB

Google Trends breakout micro-queries for regional store brands

relative search interest (0-100) for hyper-specific regional retail/restaurant chain names by DMA

Feed detail
Measures
relative search interest (0-100) for hyper-specific regional retail/restaurant chain names by DMA
Source
Google Trends via pytrends unofficial API (trends.google.com backend)
Access
scrape-hostile
Cadence
dailyupdates once a day
Thesis
regional search-interest breakouts for a specific small chain precede same-store-sales beats/misses for regional restaurant/retail small caps
Maps to
regional restaurant chains and small-cap retailers (e.g. specific QSR franchises)
Crowdedness
contested
Tier
tB
Ban-risk
ban:medium
Where this stands

This is a catalogued data feed with a research idea attached, not a validated edge. Being listed here means it has a specific source and a one-sentence causal mechanism mapped to what it should move — it doesn’t mean it has cleared the five-stage validation gate (point-in-time hygiene, out-of-sample holdout, multiple-testing correction, and the portfolio-layer backstop). As of today, every score on this site is prior-only; zero signals in the catalog have been promoted to “measured” status. See the methodology page for the full validation process and current counts.

Browse the rest of Digital ExhaustApp-store rankings, job postings, web traffic, and other byproducts of running a business — the exhaust that leaks intent early.