What is Brand Drift?

Brand drift measures how a brand’s recommendations in large-language-model outputs shift across model versions, time, and retrieval contexts. Unlike brand share of voice — a single snapshot — drift captures movement: gaining, holding, or losing ground in AI answers. It is formalized as the Brand Drift Score (BDS), a composite of citation rate, rank quality, sentiment, and source-link presence, so teams can track generative visibility as a trendline rather than a one-off audit.

Why brand drift matters for B2B

Enterprise buyers return to AI assistants weeks apart during long cycles. A brand can slip from default recommendation to footnote between Q1 and Q2 with no website change — as model retraining or retrieval shifts rebalance the consideration set. Tracking drift instead of a single audit is how B2B teams catch erosion before it shows up in pipeline.