How BrisTechTonic Uses Personas To Map Related Search Queries

What the skill does: Runs a query fan-out per audience segment (2-5 personas per run). Tags every related query with which persona surfaced it. Detects shared queries (appearing across 2+ personas) vs persona-distinct queries (only one persona). Produces a CSV + DOCX showing both views. Recommends pillar content (shared topics) vs persona-targeting content (distinct topics).

Why it matters: Same seed keyword can have very different sub-query universes depending on who's searching. A small-business owner searching 'CRM' wants different things than an enterprise procurement lead. Most query research collapses all personas into one fan-out — useful for breadth, hides segment opportunities.

What's new: Cross-persona detection — surfaces queries every persona shares (cornerstone candidates) and queries only one persona asks (segment candidates) in one pass. The output drives strategic content decisions: do we build one comprehensive pillar or multiple persona landing pages? Persona tags persist into the CSV so downstream brief skills can scope per-segment.

Use cases: Multi-persona B2B clients. Multi-region clients. Multi-product clients. Pre-rewrite audit of a generic pillar page.