We look at seven structural reasons a brand fails to enter AI answers, which gap each one points to, and the order in which to diagnose them.

We look at the three different reasons a brand is missing from AI answers, their symptoms, the order of diagnosis and how each gap is closed.

We look at the six links a brand needs to enter AI answers, the real technical counterpart of each link and how to find the weakest one.

We look at what B2B decision simulation with synthetic data shows compared with focus groups, what academic research says, and how results are validated.

After the removal of FAQ rich results, we look at what FAQPage, Schema and llms.txt actually add to AI visibility, where they're overstated and how to prioritize them.

We look at how to measure the visibility a brand shares with competitors in AI answers, why share of voice needs a new definition and how to read why a competitor leads.

We look at how LinkedIn, press and third-party sources shape AI recommendations, what citation research shows and which source to prioritize when.

We look at why the same brand appears differently in the AI questions of each buying group member, and how a Persona GAP Analysis turns that difference into action.

We break down the four components of a decision question, where buyer questions are collected from, and how a persona × stage map is built and read.

We explain why keyword rankings can't measure AI visibility, which indicators a decision-question-based measurement uses, and how Recro's four-pillar simulation works.