Every claim about your firm — name, address, phone, founding year, practice areas, the lawyers on the roster — exists in dozens of places you control and hundreds you forgot. Search and AI engines read all of them and do something unforgiving: they compare. Agreement builds confidence, and confident engines give knowledge panels, accurate answers, and citations. Contradiction breeds hedging — the engine cites someone cleaner, or worse, states the wrong version as fact. An entity consistency audit is the systematic hunt for those contradictions, and for most firms it is the highest-leverage half day in all of entity SEO.
Step 1 — Write the canonical fact sheet
Before hunting discrepancies, define truth. One document, one page: exact legal name and the exact public-facing name (decide, once, whether the "LLP" appears); address in one canonical format; one primary phone number; founding year; current lawyer roster with credentials; practice areas in fixed wording; official domain, and the canonical URL format for key pages. Every correction in the rest of the audit copies from this sheet verbatim. Most inconsistency is not error but drift — three well-meaning people abbreviating differently — and a canonical sheet is the only durable cure.
Step 2 — Audit what you control
Start where fixes are instant. Your website first: does the Organization schema match the footer, the contact page, and the about page word for word? Firms routinely fail inside their own domain — an old suite number in the schema, a departed partner in a sidebar, two spellings of the firm name between header and footer. Then the profiles you administer: Google Business Profile, LinkedIn, Facebook, X, YouTube, and every directory login someone at the firm still has. Fix each against the sheet, and record the login while you are there — orphaned profiles nobody can access are next year's inconsistencies.
- Site: schema vs footer vs contact vs about — zero tolerance for internal drift
- Google Business Profile: name, categories, hours, phone, and the exact site URL
- Social profiles: names, bios, links — including the accounts nobody has posted to since 2023
- Directory profiles you own: bar association, Avvo/Justia/FindLaw-style listings, chambers and awards profiles
Step 3 — Hunt the record you don't control
Now search like an engine. Query your firm name in quotes, plus each variant spelling, plus each old address and former phone number, plus each departed lawyer's name with the firm's. The fossils this surfaces are the audit's real quarry: the aggregator that scraped your address in 2019, the chamber-of-commerce listing from an office two moves ago, the news article crediting a lawyer who left, the duplicate Google Business Profile a former employee created. For each, claim and correct where possible, request correction where there is an owner to ask, and request removal where the listing is beyond repair. Log everything — including the refusals, because a documented record of what remains wrong tells you exactly which errors might resurface in AI answers.
Step 4 — Verify against the machines' own beliefs
Finish by asking the engines what they currently believe. Google your firm and read the knowledge panel line by line. Ask ChatGPT, Gemini, and Perplexity: "What is [firm name]? Where is it located, who are its lawyers, and what does it practice?" Wrong answers are diagnostic gifts — each one traces to a source you either missed in step 3 or fixed too recently for a recrawl. Note them, wait a cycle, re-ask. This closes the loop between the record and its consumers, and it converts the audit from a cleanup exercise into a measurement practice: the entity strategy is working when the machines' answers converge on your fact sheet.
Triage: which contradictions to fix first
Not all discrepancies are equal, and a half day forces choices. Fix identity-level conflicts first — firm name variants, duplicate Google Business Profiles, wrong primary phone — because they can split your entity into two weaker ones in an engine's graph. Contact facts come second: a wrong number or address costs real consultations today. Roster and practice-area drift is third; it misleads without usually misrouting. Cosmetic variation — abbreviations, "Street" versus "St" in otherwise-matching listings — goes last, and honestly may never be worth chasing across sources you cannot log into. Engines normalize trivial formatting; they do not normalize two different phone numbers. Spend the audit where the ambiguity is real. A useful rule of thumb: if two sources disagree in a way that could make an engine describe you as a different business — different name, different number, different location — that is a today problem. If they merely phrase the same truth differently, it can wait for the annual pass, or forever.
Cadence, ownership, and the payoff
Run the full audit annually and a light version — site, Business Profile, engine answers — quarterly. Give it an owner by name; consistency work without an owner reverts within a year, because every hire, move, and rebrand mints new discrepancies. The payoff arrives on three fronts at once: knowledge panels appear or correct themselves, AI answers about the firm stop containing surprises, and citation rates rise because you have become the safe entity to quote. None of it is glamorous. All of it compounds — and unlike almost everything else in marketing, a fact, once made consistent, mostly stays fixed.
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