Local discovery is becoming a source-consensus problem
A traditional local search is easy to picture. A customer types a service and city into Google, scans a map or list of links, and decides what to open.
AI-assisted discovery changes the shape of that research. The system may search more than once, retrieve information from several sources, and assemble a response before the customer visits any website at all.
That makes one question increasingly important for local businesses: what does the rest of the web say about you when the system goes looking?
SC Marketing & AI tested 25 standardized local recommendation-style queries across South Carolina. The queries covered HVAC, plumbing, roofing, and electrical services in seven markets. Each query used the same simple format, such as Recommend a plumber in Charleston, SC.
The same query strings were captured in two environments: an OpenAI search-backed retrieval layer used for the research and conventional live Google results collected through DataForSEO.
