Dashboards
Reporting your team already knows how to open.
Every new BI platform arrives with training sessions, seat pricing and a second source of truth — and adoption dies at the login screen. So the reports are built on Google Data Studio (formerly Looker Studio) and fed straight from the data models in your own BigQuery: no new tool to roll out, no per-seat licenses to justify, and sharing that works like every other Google doc your company already uses.
How it works: built on Google Data Studio, fed by your data models
Nothing between the chart and the warehouse but Data Studio’s own BigQuery connector.
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Data models in BigQuery
Dashboards read modeled, documented tables — never raw event exports.
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Native connection
Data Studio’s built-in BigQuery connector, running in your own Google Cloud project.
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Templates applied
Report templates per domain — acquisition, SEO, revenue — adapted to your data models, not the other way round.
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Shared like a doc
Google-account sharing, viewer or editor, company-wide or per person — with no per-seat cost.
Why Data Studio is the advantage
There is no new UI to learn — your team has almost certainly opened a Data Studio report before. There is no license line item on top of the engagement. And the report lives in your Google account next to Sheets and Drive, so sharing, permissions and access reviews work the way your company already works.
Templates, not blank canvases
Each domain starts from a proven report template — acquisition, SEO, revenue — and gets adapted to your data models. Nobody stares at an empty canvas, and every chart traces back to a documented table in your warehouse, so a number on screen always has a definition behind it.
What you control
The reports are yours; the platform is one you already own. Three things are yours to decide — and some things this deliberately is not.
Which reports exist
The report set is scoped to the questions your team actually asks — acquisition, SEO, revenue — rather than a template pack you then have to prune back.
Who can see what
Sharing works like any Google doc: per person, per group or per domain, managed by you. There are no seats to buy and nobody to ask when a new colleague joins.
What the numbers mean
Every figure traces back to a data model with a documented definition, so a metric on a chart and the same metric in a digest cannot quietly disagree.
Where it stops
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It runs on Data Studio — and inherits its limits.
We build on Google’s product; we don’t extend it. If Data Studio can’t render it, neither can we.
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It is not an enterprise BI platform.
No Tableau- or Power BI-class governed semantic modeling, no permission matrices beyond what Google sharing provides.
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It is not a custom application.
If you need a bespoke product interface for your own customers, this isn’t the tool.
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It does not paper over data quality.
A broken pipeline gets fixed in the warehouse layer — never hidden behind a chart.
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It does not move your data out of your project.
Data Studio reads your data models in place through its read-only connector. Report and warehouse both live in your own Google accounts — if the engagement ends, everything stays.
What the reports answer
Dashboards read data models, not raw exports — which is what lets a chart group by something meaningful instead of by URL. Each of these leans on a data model or a source you can read about.
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Which kind of page is winning
Search Console performance read by page type rather than one URL at a time, so a template-level problem finally looks like a template-level problem.
Page Types -
Where two of your pages compete
A view that ranks the searches where your own URLs fight each other by the traffic at stake, instead of hunting them query by query.
Keyword Cannibalization -
What people actually wanted
Performance split by query intent, so an informational drop and a commercial drop stop being the same line on the same chart.
Query Intent -
Cost next to what it earned
Ad spend and results in the same report as the sessions and revenue they produced, joined in the warehouse rather than in a spreadsheet.
Google Ads
What the reports look like
Three of the standard templates — each listing the data models that feed it.
Sessions
372,480
Users
268,940
Conversions
9,412
Revenue
€563,200
Clicks
48,220
Impressions
2.14M
Avg. position
6.8
Brand — 34% of clicks
Non-brand — 66% of clicks
One dot per day · orders (x) vs revenue (y)
Reporting your team already knows how to open.
Free discovery call · Leave with a template shortlist for your data models