Going from absent to cited in AI answers across a legal niche

The challenge

The firm ranked in the top five for most of its target keywords but was cited in none of the sixty prompts we tested across three answer engines. Answer engine optimization was, at that point, simply not something anyone had done for them. Competitors with weaker conventional rankings were being cited consistently. The firm's expertise was real; almost none of it existed in a form models could resolve to a single, corroborated entity.

What we did

1. 1

   Established a baseline by running sixty practice-area prompts across three engines and recording every source cited.

2. 2

   Rebuilt the entity layer: consistent firm naming, practitioner schema, and factual alignment between the site, professional directories and third-party profiles.

3. 3

   Restructured key practice pages so definitions and answers sat in cleanly quotable passages rather than buried in narrative prose.

4. 4

   Built corroborating mentions in legal trade press so the same facts appeared in independent sources.

The outcome

Citation share on the tracked prompt set moved from zero to 41% by month seven, measured monthly against the same prompts. Branded search volume rose 29% over the same period. We're candid with the client that answer engines change sourcing often, so this is monitored continuously rather than treated as finished.