Analytics & A/B testing
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Analytics & A/B testing
Dashboard → Analytics turns your raw consent events into the metrics you actually care about: how many visitors opt in, which categories they grant, and where they're coming from — plus an A/B testing tool to improve opt-in rate.
KPIs
At the top of the page:
KPI | What it means |
|---|---|
Consents | Total consent decisions in the selected range |
Opt-in rate | Share of decisions that granted at least one non-necessary category |
Impressions | How many times the banner was shown |
Ratio | Consents ÷ impressions — how many banner views convert into a decision |
Each KPI shows a delta against the equivalent prior period (e.g. the previous 30 days), so you can spot a regression (a copy change that tanked opt-in rate) quickly.
Use the range selector (7d / 30d / 90d / All) to change the window everything on the page reflects.
Charts
Opt-in trend — daily opt-in rate over time.
Consent volume — daily opt-in vs. opt-out counts, stacked.
Implied vs. strict — donut of decisions made passively (implied) vs. via explicit interaction (strict/explicit).
Per-category opt-in — trend lines for Preferences, Statistics, and Marketing opt-in rates individually, so you can see e.g. that visitors are happy to accept Statistics but reject Marketing.
Top countries — bar chart + table of consent volume by country. Click a country (in either the chart or the table) to filter every other chart on the page down to that country; click it again to clear the filter.
Funnel — impressions → opt-ins → opt-outs, showing drop-off at each stage.
Note: All charts respect the active country filter and the selected date range simultaneously — drilling into "DE" and switching to "7d" narrows every chart at once.
Multi-property
If your org has more than one site, use the site switcher in the page header — analytics are always scoped to one property at a time to keep the numbers meaningful.
A/B testing
Under Banner settings → Targeting, enable A/B testing to split visitors between your current banner (variant A) and a challenger (variant B) at a configurable split percentage. Results (impressions and opt-ins per variant) feed back into the same consent-stats pipeline, so you can judge whether a design or copy change actually moves opt-in rate before rolling it out to everyone.
Note: A/B testing is a paid ("Scale" plan) capability — see Banner settings for where it lives in the editor.
See also: Consent log · Banner settings