Overview
Brand Share of Search is an analytics platform developed by Havas Middle East that measures daily Share of Search using Google Trends data. It helps brand managers and marketing teams evaluate brand visibility against competitors on a single relative scale.
Beyond basic share tracking, the platform measures campaign incrementality to determine whether marketing efforts caused a genuine lift in interest. It models counterfactual baselines using competitor performance as a control group to evaluate real campaign impact.
The system also integrates optional survey metrics from YouGov BrandIndex for internal agency teams. By capturing both search interest and panel data, users receive an empirical view of campaign performance and brand health.
Key features
- Daily Google Trends tracking: Automatically fetches search data every morning and normalizes brand interest across chosen markets.
- Anchor-based scaling: Splits competitor sets larger than five brands into anchored batches to maintain a single scale adding up to 100 percent.
- Historical data retention: Loads up to three years of daily search history at setup and continually appends daily data without expiration.
- Incrementality testing: Uses a Bayesian structural time-series model to calculate a counterfactual baseline and isolate true campaign lift.
- Statistical confidence scoring: Delivers clear verdicts such as Strong, Moderate, or Not Significant based on statistical confidence intervals.
- YouGov BrandIndex integration: Allows eligible agency users to track panel metrics like ad awareness and consideration on the same share scale.
Pros and cons
Pros
- Automatically normalizes Google Trends data across unlimited competitor sets.
- Measures causal campaign impact rather than relying solely on volume correlations.
- Preserves daily historical search data beyond standard Google Trends limits.
Cons
- Pricing and access details are not publicly available and require contacting Havas Middle East.
- Re-scaling by Google Trends can occasionally cause minor shifts in historical numbers over time.
Best for
- Brand managers
- Agencies


