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Looker Studio
Pull your CrunchJunkie AI-visibility metrics into Looker Studio with the official community connector.
What the Looker Studio connector does
The CrunchJunkie community connector brings your AI-visibility data into Google Looker Studio, so you can blend it with Google Ads, GA4, Search Console and everything else in the same dashboard your clients already look at. It reads a project's daily snapshots — brand visibility, share of voice, sentiment, average position and mention counts, broken out by engine (ChatGPT, Perplexity, Claude, Gemini and the rest) and by market.
It's built on the CrunchJunkie REST API, so the numbers match the app exactly — the same pooled rates, the same engines, the same markets.
What you need
Two things: a plan that includes the REST API (Pro, Agency or Scale), and a team-scoped API key. Create the key in Settings → API — give it a name, copy it once, and keep it safe. The connector is read-only and scoped to your workspace, exactly like the key itself.
Connecting
Open the connector's link — while it's rolling out, request it from support — then click Authorize and paste your CrunchJunkie API key when prompted; the connector validates it against your workspace. Then pick the AI-Visibility project you want to report on and choose a date range.
Looker Studio caches the data source; refresh it (or set a data-freshness interval) to pull new snapshots as scans run. Each row is one snapshot: a date × engine × brand, with the visibility and share-of-voice metrics as pooled rates.
Building charts + a note on aggregation
Drop the fields onto a time-series to watch visibility per engine, a bar chart to compare your brand against competitors, or a scorecard for the latest share of voice. Filter by "Is your brand" to separate your own line from the competitor set, or by Market to compare locales.
One accuracy note: Visibility and Share of voice are pooled rates. If you aggregate across rows in Looker, sum Mentioned runs and Total runs and divide, rather than averaging the Visibility percentages — averaging rates over different sample sizes overstates or understates the real number. This is the same metric-contract rule the CrunchJunkie app follows, so your Looker figures stay identical to ours.
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