How Lantern scores Brand AI Health

Brand AI Health is a single 0–100 number that captures how a brand is doing on AI-assisted commerce surfaces. It is a composite — not a single measurement — and the composition matters. This piece documents what the number contains, how it is computed, why we chose this particular weighting, and how it fails in revealing ways.

The three dimensions

Website Signals is the dimension your Catalog and Content agents own. Brand Reputation is the dimension the Offsite agent owns. Content Strategy is the dimension the Query agent owns most directly, with Content as a secondary owner.

The formula

formulaBrand AI Health = round(
    0.40 * Visibility_score
  + 0.35 * Favorability_score
  + 0.25 * Citation_Score_driver
)

where each component is scaled to 0–100 before weighting:

  Visibility_score        = aggregate Visibility (%) * 100  // clamped 0..100
  Favorability_score      = 0.7 * sentiment_score + 0.3 * descriptor_cloud_score
  Citation_Score_driver   = count-weighted median Citation Score of Own URLs

Confidence interval:
  CI_95 = base_score ± 1.96 * sqrt(variance_n / n)

Surfaced confidence tiers:
  single-event  n <= 2      // visible, never auto-actioned
  low           n in [3, 7]
  medium        n in [8, 24]  // default surface threshold
  high          n >= 25

Why the weights are 0.40 / 0.35 / 0.25

The weighting is empirical. Across the 200-brand Lantern sample, the partial correlations between each driver and AI-assisted conversion are: Visibility 0.58, Favorability 0.52, Citation Score 0.41. The composite is re-calibrated quarterly.

Confidence intervals and tiering