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Legal owner · AI citation gap

REFERRED. STOPPED.

Your accountant still refers four clients a year, and the calls have changed shape.

The buyer typed "do I need a lawyer for [situation]" or "personal injury attorney in [city] for [case type]" at 10pm. AI named three firms. The buyer then asked their accountant, who confirmed one of the three. Your name is referred when the AI happens to include it.

Get this fixed Open the structural pattern →

What to check

Six checks to run.

  1. Why AI started recommending other legal businesses instead of yours
  2. The pattern: how AI builds the legal shortlist
  3. What you have already tried that did not move the citation
  4. Questions for the AI search gap
  5. Stan's take on the citation fix
  6. Common questions before the BUILD starts

AWhy legal buyers see competitors not you

The buyer asks AI. AI names three. You are not on the list.

Some buyers use AI assistants while researching providers. Run a dated prompt set and record the businesses, pages, and sources shown; list size and selection behavior vary by assistant, query, place, and time.

Check 01

Buyer wording.

Collect real law firms buyer questions and use them to define the prompt set. Do not assume category keywords represent how buyers ask for help.

Check 02

Public business detail.

Verify identity, service, location, credential, availability, and proof details on the public pages relevant to those questions.

Check 03

Visible source evidence.

Record which pages and third-party sources the assistants show. Treat schema and page structure as observable inputs, not a disclosed ranking formula.

Check 04

Qualified outcome evidence.

Connect repeat prompt results to referrals, qualified introductions, and new matters. A citation without a qualified outcome is visibility evidence, not revenue proof.

A prompt result is a dated observation. Repeat it, record the sources, and connect it to qualified outcomes before changing the plan.Evidence standard · Stan Consulting

BThe pattern in one diagram

AI can shape a comparison. Record the businesses and sources shown.

Run the same dated buyer prompts across the assistants being evaluated. Record the businesses, pages, and sources shown; one response does not represent every buyer path.

Diagram. AI citation funnel for legal buyers
STAGE 1. BUYER ASKS AI ChatGPT / Perplexity "personal injury attorney in my city for car accident" 11pm, real legal buyer STAGE 2. AI RETURNS NAMED LIST Competitor A. cited Competitor B. cited Competitor C. cited STAGE 3. BUYER CONTACTS ONE Phone call to one of the three brands the AI just named WHAT HAPPENS TO BRANDS NOT CITED Your legal business. Not in the answer Not cited. Not on the shortlist. Not contacted. The buyer chose between the three the AI named. Your reviews never get assessed. Your website never gets visited. The decision happened entirely upstream. WHAT THE BUILD INSTALLS Schema markup CRAWL ACCESS + LOGS Clear public identity + GBP 3-5 buyer-prompt pages Track assistant mentions, cited sources, referrals, and qualified demand against a dated prompt set.

BUYER REALITY CHECK

Open the structure.
Or pay for the leak.

Stan Consulting · operator observation

The funnel moved before you noticed

TEST THE PROMPTS.
CHECK THE SOURCES.

Visibility is query-specific. Record which businesses and sources appear, then compare changes in referrals and qualified demand.

CWhat the owner has already tried

Four moves that did not put you on the AI list.

Legal owners try the standard fixes first. Each one improves something else and leaves the AI citation gap untouched.

What was tried

What you tried

  • Sponsoring the local bar association charity event
  • Updating attorney bios with more cases handled
  • Buying Avvo Premium and Lawyers.com directory placement
  • Running TV commercials with the practice-area phone number
  • Increasing the Google Ads spend on practice-area keywords

What closes the gap

What gets you on the AI list

  • Service schema per practice area with jurisdiction and representation type
  • Buyer-prompt content matching the situation vocabulary buyers actually type
  • Editorial citation strategy targeting bar journals and local legal publications
  • Person schema for each attorney with credentials, years admitted, areas
  • Clear public identity for the firm as a distinct practice from similar-named competitors

DCheck this in your own week

Six questions. Answer them honestly.

Use the answers to identify which claims need evidence before changing pages, channels, or budget.

  1. Ask ChatGPT "personal injury attorney in [city] for [case type]." Are you named?
  2. Has new-client introduction volume held steady or compressed while referral counts stayed flat?
  3. Does each practice area have its own Service schema markup?
  4. Has a bar journal, legal publication, or local news outlet cited the firm in the last 18 months?
  5. Do your referring accountants and other professionals mention using AI to refresh their recommendations?
  6. Is each attorney's Person schema deployed with admission dates and practice areas?

Stan's take

AI visibility needs evidence. Test the prompt set before assigning lead impact.

For law firms, discovery can include search engines, maps, directories, referrals, and AI assistants. The mix varies by buyer situation and market.

Review the public identity, service and location detail, relevant credentials, useful buyer answers, and cited third-party sources. These are observable inputs, not a disclosed assistant-ranking formula.

Run a dated set of relevant buyer prompts, record the businesses, pages, and sources that appear, and repeat the same set after any change.

Use referral data, qualified introductions, and new matters to decide whether visibility changed. Scope and timing depend on crawl state, evidence, query set, and buyer volume.

Stan Tscherenkow, Principal · Stan Consulting LLC

ECommon questions

What operators ask before the first call.

Does this apply to solo practitioners or only firms?

Both. Solo practitioners may have a simpler attorney-to-entity relationship, but structure alone does not promise faster citation. Firms benefit from individual Person schema per attorney plus firm-level Organization schema.

What about practice areas where the buyer's situation is highly specific (e.g., complex commercial litigation)?

Highly specific practice areas require their own prompt and source review. Competition depth and timing have to be measured.

Is this just for plaintiff-side or defense-side too?

Both. The buyer-prompt research separates plaintiff-side and defense-side query patterns; the schema treatment handles both representation models.

How does this interact with our existing Avvo / Justia / Martindale presence?

Third-party legal directories become entity-clarity signals. The BUILD treats them as supporting infrastructure.

Stan ConsultingWhat to check next

What to decide next.

If this is happening in your business, check the marketing problem first: Your accountant still refers four clients a year, and the calls have changed shape. Then look at proof, the matching service, and whether a Written marketing plan is the right next step.

Problem

What is leaking

  • AI systems cannot clearly explain or cite the business for buyer searches.
  • search demand can move into AI answers while the brand stays absent or misunderstood.

Next step

What to review before changing the plan

Next step

Stan Consulting reviews the visible site, entity, and source evidence against a dated prompt set. Scope, timing, and price are confirmed after intake.

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