Looker Studio / Data Studio Agency

Below are dashboards we have built in Looker Studio for clients in retail, pharma, manufacturing, logistics and insurance. Each was built against the client's own data rather than a demo set, so the screenshots show the layouts and controls as delivered: date range pickers, filter bars, scorecards and paged tables. Client names and confidential figures are not shown. If you want a sense of what a business dashboard can look like across tools, our business performance dashboard service and WolfSight pages cover the same ground in more general terms.

Templates are a good start and often all a small team needs. Google publishes a template gallery inside the product, and connector vendors and the community publish many more, including GA4 dashboard and Google Ads Looker Studio templates. You copy the template, point it at your own data source, and the charts fill in.

A template is usually enough when:

• Your data comes from one source with a native connector, such as GA4, Google Ads or Search Console.
• The standard metrics are the ones you report on, with no custom definitions.
• One person reads the report and knows the platform it came from.

A template starts to fail when:

• You need several sources in one view, for example ad spend from four platforms against CRM revenue. Templates assume one source per chart.
• Your KPIs have business definitions: qualified leads, contribution margin, net revenue after refunds.
• The data is large enough that live connections time out or hit API quotas, which GA4 reports with many charts often do.
• The report goes to a client, a board or several teams and has to reconcile to another system.
• You need access control by region, client or team.

A custom build starts from the questions the report must answer and the data model behind them. Many of our builds keep a template's layout and replace everything underneath it.

Looker Studio can connect to BigQuery natively, and for anything beyond a few sources or a few million rows this is the setup we recommend. Instead of blending data in the report, you load each source into BigQuery, model it into clean reporting tables with SQL, and point the dashboard at those tables. The report then does very little work, so it loads fast and every page agrees with every other page.

What it costs: BigQuery on-demand queries are billed per TiB of data processed, with the first 1 TiB each month free per billing account; Google's list price in US regions was $6.25 per TiB beyond that as of October 2026, and storage is billed separately. A dashboard reading small, partitioned reporting tables rarely gets near the free allowance; one running live queries over raw event tables can.

The pieces we usually put in place:

• Pipelines that load ad platforms, CRM and ecommerce data into BigQuery on a schedule (see our ETL service).
• Partitioned and clustered tables, so a query for last month does not scan five years.
• Scheduled queries or materialised tables that pre-aggregate to the grain the dashboard needs.
• BI Engine, Google's in-memory layer for BigQuery, when a report needs sub-second response for many concurrent users.
• Row-level access by client, region or team where readers must only see their own data.

If the bigger problem is that your data is scattered and inconsistent before it ever reaches a dashboard, start with data management rather than reporting.

Data Studio Pro is the paid edition of Data Studio, called Looker Studio Pro until April 2026. It keeps every free feature and adds team ownership, administration, security controls and support. The table reflects Google's documentation and pricing page as checked in October 2026.

Google's documentation also states that eligible Looker customers receive at least 1,000 complimentary Pro licences, with exclusions for Looker contracts and instances created after 1 August 2026. For most small and mid-sized teams the free edition is enough. Pro earns its cost when reports must outlive the person who built them, when you send many scheduled reports, or when security review asks about encryption keys and data residency.

Looker Studio pricing has four parts, and only one of them is the tool itself.

How we price a build. We do not publish a rate card, because the number depends on things we can only see in your data: how many sources, whether they need modelling in BigQuery first, how many KPIs need agreed definitions, how many pages and audiences, and whether access must be restricted by team or client. A single dashboard on one clean native source is a small piece of work; a multi-source report on a modelled warehouse is mostly data engineering. We scope it on a call, then give you a fixed quote and a list of any third-party costs, such as connectors or BigQuery, before anything starts.

Looker Studio is widely used for white label reporting because viewers pay nothing and reports can carry your logo, colours and domain links rather than Google's branding on the page. The pattern that scales is one master template per service line, connected to a data source that switches by client, with sharing set so each client sees only their own report. Adding a client then becomes a data source change, not a rebuild.

Settle early who owns the reports (the builder on the free edition, the organisation on Pro), how client data is separated in a shared BigQuery dataset, and how partner connector costs grow with each client account.