Data Studio

The CrunchJunkie community connector brings your AI-visibility data into Google Data 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.

Two things: a plan that includes the REST API (Pro, Agency or Scale), and a team-scoped API key. Create the key in Settings → REST 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. In the app, the connector's card under Data sources → Add a source (in the Export & other connections group) links to both: the API keys and the connector.

Open Add the CrunchJunkie connector, 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. Google completed its OAuth verification of the connector on 23 September 2026, so you won't see an "unverified app" warning and there is no cap on how many people in your team can authorize it. The connector asks for one permission, to call the CrunchJunkie API — nothing in your Google account. Data 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.

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. Scans usually run once a week, so a daily time series shows separate points rather than a line: use the Week field as the dimension for trend lines. Engine shows the product name (ChatGPT, Gemini, Perplexity and so on); Engine id holds the stable channel id behind it. One accuracy note: Visibility and Share of voice are calculated fields. Data Studio sums the counts behind them (Mentioned runs ÷ Total runs; the brand's mentions ÷ all brands' mentions) and divides once, so a scorecard over a month, several engines or several markets shows the same figure as the CrunchJunkie app. Averaging the daily percentages instead would over- or understate the real rate, because days and engines have different sample sizes. Avg position and Sentiment are calculated the same way, weighted by mentions, so a day with many mentions counts for more than a day with one. Any date range is fetched in full: the connector splits it into 180-day windows and reads every row, up to 100,000 rows; beyond that it shows a clear error asking for a shorter range or fewer markets or engines, instead of cutting the data off.