Looker Studio — the free Google dashboard tool that was called Google Data Studio until Google renamed it in October 2022 — connects to your data and turns it into charts other people can read without asking you first. That last part is the point. Most reporting problems are not analysis problems; they are "the only person who can produce this report is on holiday" problems.
Below are the patterns it is typically used for, industry by industry, and where it stops being the right tool. These are illustrative scenarios rather than accounts of particular organisations.
Marketing: client and campaign reporting
The natural fit. Looker Studio connects directly to Google Analytics, Google Ads and Search Console, so a monthly report that used to be assembled by hand becomes a link that is always current.
What makes these dashboards work in practice:
- A date-range control at the top, so people answer their own "what about last quarter" questions.
- One page per audience. What a client wants to see and what the person running the campaign needs are different reports, not one crowded page.
- Filters on channel or campaign, rather than a separate dashboard per campaign.
The trap is including everything the connector offers. A dashboard with forty metrics gets read once.
Finance: internal reporting from sheets
Finance teams often start with Google Sheets as the data source, because that is where the numbers already are. That works, with one caveat worth knowing before you build: Looker Studio reads the sheet as it is. If someone inserts a column, the report breaks or, worse, quietly reports the wrong field.
Keep the sheet the report reads from separate from the sheet people edit, and treat it as a data table rather than a formatted document — no merged cells, no blank spacer rows, one header row.
For anything larger, BigQuery is the usual source, and it is where Looker Studio stops feeling slow.
Healthcare and education: reporting on people
Both sectors want the same shape of dashboard — outcomes over time, plus operational measures like scheduling or attendance — and both carry the same constraint: the underlying records are personal data.
The practical rule is that the dashboard should read from a prepared, aggregated table rather than pointing at the source records, and access should be granted through the data source rather than by sharing a link. Looker Studio's sharing model is Google's, which means a report shared "with anyone who has the link" is exactly that.
Retail and e-commerce: sales and stock
Sales figures, conversion rates and stock levels usually live in different systems, and this is where Looker Studio's limits show. It is a visualisation layer, not an integration tool. Blending two sources works for simple joins; anything more and you want the data combined before it arrives, not stitched together in the report.
If the dashboard is slow, the cause is nearly always that it is doing work at display time that should have been done upstream.
When Looker Studio is the wrong answer
- Your data is not in a database. A dashboard on top of a messy spreadsheet inherits the mess and adds a layer where the mess is harder to see.
- You need to write data back. It reads and displays; it does not capture. Data entry needs an application.
- The numbers disagree between systems. Visualising a disagreement does not resolve it, and a chart makes a contested number look settled.
- You need row-level security. Restricting different viewers to different rows is possible but awkward, and easy to get wrong in a way nobody notices.
The commonest version of the first point: the "database" is an Access file or a set of Excel workbooks that grew into the reporting system by accident. A dashboard on top of that will look like progress for a few months. Fixing what sits underneath is the work that lasts.
Our services page covers database and reporting work, and a free system review will tell you whether you need a better dashboard or a better foundation under it.
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