Hype Index
Market signal rankings from rlegaltech.com — who's getting shopped vs. who's getting used?
Methodology & collision detection
Hype Index = Prospect searches / User searches (monthly, US geo via Google Ads)
- Prospects = pricing + review + demo + free trial + alternative + vs (purchase-intent + evaluation)
- Users = login + support + help (active-user signals)
Bayesian Hype Score adjusts the raw ratio for volume confidence:
hypeScore = (U × rawHype + C × M) / (U + C)
U= user searches (more data → trust the ratio more)C= median U across ranked vendors (confidence threshold)M= median raw hype across ranked vendors (prior mean)
Effect: Harvey (U=350, raw 15.91×) barely shrinks to 9.64×. Helloprenup (U=30, raw 16×) shrinks to 1.94×.
Collision detection (3-tier):
- Automated ratio check: if modifier volume / primary volume < 5%, the brand name is dominated by a non-legaltech entity.
- Minimum threshold: U ≥ 30 monthly user searches required.
- Manual triage flags:
keywordCollision: truein triage for edge cases.
Churn Index = (alternative + cancel + vs searches) / User searches. Flight risk signal.
The Hype Index hasn't launched yet
We're finalising the methodology and collision detection before making this public. The data is computed and powers vendor page market signals already — the full interactive index is coming soon.
Interested in early access or have feedback? Contact alexdenne@gmail.com