Insights

Answers: one buyer question at a time

The questions owners and marketing leads ask when AI recommends a competitor or gets a fact wrong, each answered from what we measure: what the engines say today, who they name, and what changes it.

Case study · 3 min read

What eight AI engines said about Eidomai before we published anything

Our own baseline, in public: 286 answers, zero mentions, 39 wrong claims, and the two questions nobody in the category owns. The case study starts at zero, and we will show every month what moved.

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Answer · 3 min read

Why does ChatGPT recommend my competitor instead of my practice?

Three reasons cover almost every case we have measured: the engine holds a wrong fact about you, a source it trusts names them and not you, or their page answers the customer's question and yours answers a general one.

Answer · 4 min read

Who fixes wrong information ChatGPT gives about my practice?

Nobody, by default. The engines do not take corrections, and no tool in the category owns the job. Here is what a correction is, where wrong answers come from, and the four steps that change them.

Answer · Childcare and education · 3 min read

When a parent asks AI for a preschool, does it recommend you?

A parent asks ChatGPT for a play-based preschool near them with openings this fall and gets two names. What decides which two, what the engines get wrong about centers, and what a center can publish to be the name.

Answer · Nonprofits · 3 min read

When a donor asks AI where to give, does it recommend you?

A donor asks ChatGPT for the best local charity for youth programs and gets three names. A grant seeker asks which community foundation funds nonprofits in the county. What decides the answer, and what a nonprofit can publish to be it.

Answer · Real estate · 3 min read

When a buyer asks AI for a real estate broker, does it recommend you?

A buyer asks ChatGPT whether a flat-fee broker in their city is worth it, or for a broker who works with buyers only. What decides the answer, why brokerages get described wrong, and what a brokerage can publish to be the name.

Answer · Wine and alcohol · 3 min read

Who can help a winery get recommended when people ask ChatGPT where to go wine tasting?

A couple planning a Saturday asks an AI where to taste and gets three names. What decides which three, why a winery's own site usually loses to a listicle, and what ten years in the wine business taught us about fixing it.

Answer · Healthcare · 3 min read

Who can get my medical practice recommended by ChatGPT?

A patient asks ChatGPT which clinic to call and gets a name. What decides whose name it is, what a HIPAA-conscious practice can publish without touching patient data, and who does the work.

Answer · Hospice and home care · 3 min read

When a family asks AI about hospice, does it recommend you?

A daughter asks ChatGPT how to start hospice for her father and gets a name and a phone number. What decides whose, why the engines get hospice facts wrong more than most, and what an agency can publish to be the name.

Answer · Therapy and counseling · 3 min read

AI visibility service for a counseling or therapy practice

Someone asks ChatGPT for a trauma therapist who takes their insurance and gets three names. What decides which three, what a practice can publish without saying a word about any client, and who does the work.

Answer · Legal · 3 min read

Best AI search visibility service for a law firm

The engines answer this question with software names. A firm does not need software; it needs pages that answer the client's question in the client's words, facts checked, and a monthly read on who the engines name. Here is how the two compare.

Answer · Financial services · 3 min read

Who can help a financial advisory firm show up in ChatGPT without breaking the SEC marketing rule?

An advisory firm can be named by AI engines with pages that state services, credentials and approach as fact, with no performance claims and no unreviewed testimonials. Here is where the line sits and how the work runs inside it.

Case study · 2 min read

What we measured before we had a name

398 claims checked, 48 flatly wrong, and why the accuracy layer is the first thing Eidomai publishes rather than the last.

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We run your measurement before the call, so the demo opens on your own battle map: which questions you hold, which a competitor holds, and what the engines get wrong about you today.