Always-on brand monitoring

Brand sentiment is the classified emotional valence of brand mentions across reviews, social posts, and support conversations. Mentions are typically sorted as positive, negative, neutral, or mixed. Net sentiment is calculated as the share of positive mentions minus the share of negative mentions, a structure similar to Net Promoter Score. Brand sentiment analysis relies on machine learning or language models to classify text at scale. Documented limitations remain: sarcasm, mixed statements within a single review, and category-specific slang can all lower classification accuracy. A single sentiment score is directional, not representative of the full customer base. It should be read alongside mention volume and topic breakdown.

Digital brand health signals are always-on online metrics used as proxies for attitudinal brand health between formal survey waves. They include branded search volume and share of search (a brand’s share of category search demand, tracked via tools like Google Trends), app store rating and review velocity (where recency and volume of reviews carry more algorithmic weight than the raw star average), and review-site score aggregation across platforms. Their appeal is cost and speed: no fieldwork, no sampling, daily granularity. Their limit is that they measure behavior and visibility, not stated attitude. They should supplement, not replace, survey-based brand health tracking.

Share of voice (SOV) measures a brand’s portion of total category conversation, advertising spend, or mentions over a defined period: SOV = (brand’s spend, impressions, or mentions ÷ total category spend, impressions, or mentions) × 100. The media-spend version, used in advertising planning, compares ad budgets or impressions against competitors. The social-mention version tracks a brand’s share of online conversation instead. Researchers Les Binet and Peter Field popularized excess share of voice (ESOV), the gap between a brand’s share of voice and its share of market, as a predictor of future growth, since brands with SOV above their market share tend to gain ground. One caveat for brand health tracking: raw mention-based SOV can spike during negative coverage, so it should be paired with sentiment data rather than read as a standalone positive signal.

Voice of customer is the discipline of turning reviews, support tickets, surveys, and conversations into operational decisions. The distinguishing feature of a working programme is the closed loop: findings reach the team that can fix the cause, and the resulting change is measured against contact volume.