DOP Cold Audit Protocol — Live Evidence Standard

Purpose: Produce verifiable, first-hand visibility evidence for a target business to replace Tier-3 competitor self-reports in GTM materials.

Signals measured (each scored 0–5, human-verified)

GBP completeness — categories, hours, phone, attributes, posts, Q&A, review count/rating. (observed on Google Business Profile)
Foursquare claim status — is the listing claimed and correct? (ChatGPT draws ~70% of local data from Foursquare)
Website schema — LocalBusiness / Service JSON-LD present and correct (service types, area, hours).
AI-answer presence — does ChatGPT / Perplexity name the business for 3 high-intent queries?
Citation consistency — NAP (name/address/phone) across GBP, Foursquare, Yelp, Facebook, BBB, industry directories.

Evidence tiering (honesty standard)

Tier-1 — observed directly on a business-owned asset (GBP, the business's own website schema). Highest trust.
Tier-2 — observed via an independent third party but verifiable (Foursquare claim status, AI-answer screenshot, directory NAP). Medium trust.
Tier-3 — vendor or business self-reported dashboard numbers. Excluded from DOP proof. Used only as wedge framing in outreach.

Method per signal

GBP: browser inspect the live profile; record completeness gaps.
Foursquare: query the business; note claimed/unclaimed + wrong fields.
Schema: web_extract the site; check for JSON-LD LocalBusiness/Service.
AI-answer: run 3 high-intent queries (e.g. "emergency plumber open now near "); capture whether the business appears.
NAP: cross-check 5+ directories for consistency.

Output per target

One markdown file: target name, metro, queries tested, observed results, gaps, per-signal score, tier breakdown, evidence references (URLs/screenshots). No self-reported numbers presented as fact.

Commit path

research/cold-audits/<vertical>-<business-slug>.md — authored as tonyjbala.

2.0 KiB Raw Blame History Unescape Escape