What is the HIDO Scoring Method?
The HIDO Scoring Method is Eric Downing's framework for measuring how visible, credible, and AI-readable a local business is across the signals that influence AI-generated recommendations.
The HIDO Scoring MethodA Named Score for
A Named Score for
Local AI Visibility.
The HIDO Scoring Method is a structured approach to making independent local businesses discoverable through AI-generated search results. It is the framework behind the book, the agency, and the platform.
01
Audit and Score
Measure current AI visibility across website, GBP, reviews, directory presence, and structured data. Assign a baseline score with red, yellow, and green indicators.
02
Build the Signal Stack
Systematically strengthen the signals AI engines use to evaluate credibility, authority, and relevance. Reviews, citations, schema, and content that answers real questions.
03
Track and Compound
Monitor AI mentions, score changes, and citation patterns over time. Every signal added compounds the ones before it. Results build as the signal stack strengthens.
Method FAQ
How does the HIDO Scoring Method work?
The method starts by auditing a business across core AI visibility signals, then scores the gaps that prevent AI engines from confidently understanding and recommending that business. The score becomes a baseline for prioritizing schema, content, citations, reviews, and local profile improvements.
Why does a local business need an AI visibility score?
A score gives the business a measurable starting point. Instead of guessing whether AI systems can understand the business, the owner can see which signals are strong, which are missing, and which improvements are most likely to increase AI recommendations.