Does Brandlight show results for branded prompts?

Core explainer

What defines competitive performance for branded vs unbranded prompts?

Competitive performance is defined by lift signals—mentions, sentiment, share-of-voice, lead quality, and sales impact—normalized by cost and exposure to enable apples-to-apples comparisons across branded and unbranded prompts.

Brandlight's ROI framework standardizes these signals and anchors evaluation in a controlled pilot design: 10–20 prompts across 2–3 brands over 4–6 weeks, with outputs that include side-by-side BI dashboards and CSV exports to reveal consistent trend patterns and meaningful effect sizes rather than random spikes. Governance and privacy controls—GDPR alignment and SOC 2 considerations—support credible, repeatable comparisons, and the approach rests on a documented methodology that provides a single source of truth for claims. Brandlight ROI framework.

How is normalization by cost and exposure applied in the ROI framework?

Normalization by cost and exposure is applied by scaling lift signals by investment and reach, enabling apples-to-apples comparisons across branded and unbranded prompts.

In practice, the ROI method uses the signals—mentions, sentiment, SOV, lead quality, and sales impact—and reports them in dashboards and CSV exports; the pilot design (10–20 prompts across 2–3 brands for 4–6 weeks) establishes baselines and supports trend-based interpretation rather than single spikes. For governance and pricing context, see Authoritas pricing.

What governance and privacy controls support credible, repeatable comparisons?

Governance and privacy controls ensure data ownership, retention, GDPR alignment, and SOC 2 readiness, which makes cross-prompt comparisons credible and repeatable.

Key elements include defined data provenance, access controls, labeling standards, audit trails, and documented data sources; this prevents misinterpretation of lift and supports consistent decision-making. The approach emphasizes privacy and governance as core inputs rather than add-ons, aligning with the prior input's governance deliverables. Governance resources.

How should outputs (dashboards, CSV exports) be interpreted for decision-making?

Outputs (dashboards and CSV exports) should translate lift signals into actionable business decisions with attention to trend consistency and credible ranges, not isolated spikes.

In Brandlight's context, dashboards enable cross-prompt comparisons and provide export-ready data; practitioners should interpret normalized lift, confidence intervals, and anomalies, while governance rules and data provenance ensure repeatability. For additional context on AI signal interpretation, see Meaningful signals reference.