Getting Started

What is Data Studio (formerly Looker Studio)?

Data Studio is Google's free reporting tool, formerly called Looker Studio. What it does, what it really costs, what it connects to, and whether it fits how you work.

Lazarina Stoy·

What is Data Studio?

Data Studio is Google’s free tool for turning marketing data into shareable dashboards. You connect a data source — Google Analytics, Search Console, a spreadsheet, your ad accounts — and build a report that updates itself, so you stop rebuilding the same monthly deck by hand.

If you searched for “Looker Studio” and landed here, you’re in the right place: it’s the same product. Google renamed it Looker Studio in 2022 and has since moved it back to Data Studio. Most people still say Looker Studio out of habit, and Google’s own documentation now uses Data Studio, so you’ll see both names for a while yet. We untangle the naming properly below, including where the separate product called Looker fits in.

This guide covers what the tool actually does, what it genuinely costs, what it can and can’t connect to, and — the part most introductions skip — whether it fits the way you work, whether you’re a solo in-house marketer with no budget or an agency reporting on fifty clients.

One thing up front, because it shapes everything below: a lot of people pay for Data Studio connectors they don’t need. The tool is free, and if your reporting lives on Google properties it stays free indefinitely. I’ll show you exactly where the free path ends and paying actually starts — and if you never reach that line, spend nothing.

What Data Studio actually does

Three things, in order:

  1. Connects to your data where it already lives. Nothing is uploaded or copied by hand.
  2. Visualises it as charts, tables and scorecards you arrange on a page.
  3. Shares it as a live link, an emailed PDF, or an embed — and it refreshes on its own.

That third point is the one that changes how you work. A Data Studio report is not a snapshot. Send a client the link in January and it still shows current numbers in June, without you touching it. The monthly reporting scramble is what the tool exists to delete.

It is worth being equally clear about what it is not. Data Studio is a reporting and visualisation layer, not a database, not an analytics platform, and not a data warehouse. It doesn’t collect data — something else has to do that. It doesn’t store your data — it queries the source every time someone opens the report. And it isn’t a spreadsheet: you can’t type a number into a cell to fix it.

The name: Data Studio, Looker Studio, Google Data Studio — and Looker

This confuses people enough to be worth ninety seconds, because two genuinely different products are involved.

Name you’ll see What it means
Data Studio The current, official name. This tool. Free.
Looker Studio The same tool, under the name it carried from 2022. Still what most people type into Google.
Google Data Studio The same tool again — the original name, still widely used.
Data Studio Pro / Looker Studio Pro The paid tier of this tool. More below.
Looker A different, enterprise BI platform Google also owns. Separate product, separate pricing, separate skill set.

The one that trips people up is the last row. Looker and Data Studio are not the same product, and they aren’t tiers of each other. Looker is a governed enterprise BI platform built around a modelling layer called LookML, sold to data teams. Data Studio is a free self-serve reporting tool a marketer can learn in an afternoon. If a job ad or a vendor mentions “Looker”, check which one they mean before you panic about your skills.

For the rest of this guide: Data Studio means the free tool you’re reading about.

Is Data Studio free?

Yes. Google’s documentation calls it “a no-cost tool”, and it’s free both for the people building reports and the people viewing them. There’s no seat cost, no viewer cost, and no trial that expires. You need a Google account; that’s the entire entry requirement.

There is a paid tier, Data Studio Pro, at $9 per user, per project, per month. It’s aimed at organisations rather than individuals, and it adds things you’ll notice only at a certain scale:

  • Organisation-owned content. Reports belong to a Google Cloud project rather than to whoever created them — so dashboards don’t leave when an employee does. For most agencies this is the single line that justifies it.
  • Team workspaces and IAM-controlled access.
  • Enhanced scheduling — up to 200 delivery schedules per report, delivery into Google Chat, and chart-level alerts.
  • Gemini in Data Studio, plus Google Cloud Customer Care.

There’s a 30-day Pro trial with no user limit, but note that billing starts automatically when it ends unless you cancel.

The honest answer for most readers: start free and stay free. Nothing in this guide requires Pro. You’ll know you need it when losing access to a report because someone left the company stops being hypothetical. We go deeper in Data Studio free vs Pro: which do you need?

The cost that catches people out isn’t Data Studio. It’s the connectors. The tool is free; getting non-Google data into it is where money appears. That’s the next section, and it’s the most important one in this guide.

What Data Studio connects to

A connector is the bridge between a platform and your report. There are two kinds, and the difference decides your budget.

Google’s own connectors — free, and there are 23 of them

Google builds and maintains these, and they cost nothing. The ones that matter to marketers:

If your reporting lives entirely on Google properties, your total software cost is zero, permanently. That’s a real position to be in and a lot of people pay for connectors they don’t need.

One exception worth flagging, because it surprises people: Google Business Profile is not a native connector. Despite being a Google product, it’s only available through third-party partners. If you do local SEO, that’s a line item.

Partner connectors — everything else, and mostly paid

Here’s the thing to internalise: Google provides no native connector for any non-Google marketing platform. No Meta/Facebook Ads, no Instagram, no LinkedIn, no TikTok, no Microsoft Ads, no Pinterest, no HubSpot, no Shopify, no Mailchimp. Every one of those needs a partner connector.

The gallery holds around 1,446 connectors — 21 built by Google and roughly 1,425 built by 347 partner companies. Google is explicit that it doesn’t stand behind the partner ones: they’re “not provided by Google”, which “makes no promises or commitments about the performance, quality, or content” of them. Most charge a monthly subscription; a handful are free.

So the practical rule:

Google data → free, forever. Anything else → you’ll be paying someone, monthly.

Buy a connector only when there is no free path

I want to be blunt here, because the internet is not short of articles that will sell you a connector you don’t need. I’ve written before about the risks of leaning on them — in my piece on Looker Studio’s limitations for advanced users I put it plainly:

“Whenever possible avoid over-reliance on third-party connectors.” Directly integrate via available APIs as opposed to using connectors.

That still holds, and it’s worth understanding why before you spend anything. A third-party connector is a dependency: it can change its pricing, change its field names, break quietly, or clutter a report into instability. In that same piece I noted something that surprises people — “bulky, ugly-looking spreadsheets or a Big Query-hosted dataset make the best type of data sources.” Unglamorous, but they don’t send you a renewal email or deprecate a field.

So the order to work in:

  1. Use the free native connector if one exists. For GA4, Search Console, Google Ads, Sheets and YouTube, one does.
  2. Consider Sheets as the middle step. Plenty of platforms will export or push to a spreadsheet, and Sheets is a free, native, entirely stable data source. It’s less elegant and more reliable.
  3. Pay for a connector only when the platform gives you no other route — which, realistically, means Meta, LinkedIn, TikTok, Microsoft Ads, Shopify, HubSpot and Google Business Profile.

If you’re in that third case, the rest of this section is for you. If you’re not, you can stop reading here and spend nothing — and a lot of readers genuinely are in that position.

Which connector to pay for then depends far more on how you work than on feature lists. That’s the next section.

Who Data Studio is right for — and what you should actually do

Most introductions stop at “it’s for marketers”. That’s not useful when you’re deciding where your money and afternoon go. Below are the five situations we see most often. Find yours.

1. In-house marketer, one brand, Google data only, no budget

You need: nothing but Data Studio. Spend £0.

If you’re reporting on organic traffic, search performance and Google Ads for one company, the native connectors cover you completely and permanently. No trial, no seat cost, no expiry.

Start by copying a template rather than building from an empty page — you’ll learn the tool faster by taking apart something that already works. Copying and reusing a template takes about two minutes, then build your first report from what you’ve learned.

The one thing to get right early is filter controls and date range controls. A report where stakeholders can change the date themselves is a report you stop being asked about.

2. In-house marketer who also runs Meta, LinkedIn or TikTok ads

You need: one paid connector. Budget roughly $20–35/month.

The moment non-Google ad spend enters your reporting, free stops being an option — there is no native connector for any of those platforms. You’re choosing a paid one.

For a single brand with a handful of ad accounts, the entry tiers are close enough in price that the deciding factor is how many accounts you connect, not headline features:

  • Windsor.ai (51 templates) is the gentlest place to start, because it’s the only one of the four with a genuinely permanent free plan (one data source, one account). If you need exactly one non-Google source — say Meta Ads alongside your free GA4 connector — you may never need to pay at all. Paid starts at $23/month ($19 annual) for 3 sources and 75 accounts, and there’s a 30-day trial with no card.
  • Coupler.io (76 templates) suits you if you also want the same data landing in Sheets or a warehouse, since every plan can reach all 14 destinations. $32/month ($24 annual). Its free plan exists but is manual-refresh only at 100 rows per run, so treat it as a demo rather than a starting point.

3. Freelancer or small agency, a handful of clients

You need: a connector priced by accounts, not by sources. Budget $23–49/month.

This is where a detail most comparison posts miss will save or cost you real money. At almost identical entry prices, the number of client accounts you can connect differs enormously:

Tool Entry price Accounts included
Windsor.ai Basic
All 51 Windsor.ai templates →		 $23/mo ($19 annual) 75
Catchr Starter
All 50 Catchr templates →		 $24/mo ($239/yr) 10
Coupler.io Starter
All 76 Coupler.io templates →		 $32/mo ($24 annual) 3
Supermetrics Starter
All 31 Supermetrics templates →		 €49/mo (€39 annual) 3 per data source

If you report on ten clients, that table is the whole decision. Windsor.ai‘s 75 accounts at $23 is unusually generous for client work; Coupler’s three accounts means one Google Ads plus one GA4 plus one Search Console and you’re already full, with extra accounts at $5.99 each.

Two honest caveats before you act on that table. Catchr‘s pricing page currently contradicts itself about which destinations the Starter plan includes — confirm before you buy if you need warehouse access. And prices move, so check the live page rather than trusting a number in a blog post, including this one.

4. Agency scaling past a few dozen clients

You need: to think about ownership and process, not just connectors. Budget grows fast.

Two things break at this size, and neither is about charts.

The first is report ownership. Reports created on personal Google accounts leave when that person does. This is the specific problem Data Studio Pro solves at $9/user/project/month, and it’s usually cheaper than the alternative of rebuilding client dashboards after someone resigns.

The second is account limits. Every connector meters differently, and the vocabulary is inconsistent on purpose. Supermetrics counts “accounts per data source” (3 on Starter) — for them an account is an ad account on Facebook Ads, or a view in Google Analytics. Catchr counts platforms and accounts separately: three Facebook Ads accounts plus five Google Ads accounts is eight accounts, not two. Windsor.ai counts accounts, and quietly bundles 10 Google Business Profile locations as a single account — genuinely useful if you run multi-location local SEO.

Supermetrics (31 templates) is the one most large agencies land on, and it’s fair to say why: it’s the most established, with the widest maintained connector library at 170+ sources, and it’s used by networks including Dentsu, Publicis and Omnicom. From €39–49/month for one destination, three data sources and one seat, with a 14-day trial and no card.

One thing worth knowing before you upgrade there, because their pricing page buries it: the refresh-frequency ladder does not apply to Data Studio. Their own comparison table notes the weekly/daily/hourly tiers are “Google Sheets only” and that this “does not apply to Looker Studio, as Looker Studio dashboards are always updated on-demand.” If you’re a Data Studio user, moving from Starter to Growth buys you more sources and seats — not fresher data. Don’t upgrade for a benefit you won’t receive.

5. Ecommerce

You need: to join store data to ad data. Budget $24–32/month.

Shopify and WooCommerce both need a partner connector, and the reporting job is usually joining store revenue to ad spend so you can see real return rather than platform-reported ROAS. Look for a connector whose entry tier covers both your store and your ad platforms without tipping you into the next tier.

If you have no experience at all

Ignore every tool decision above for a week. Open Data Studio, copy a free template that uses the native GA4 or Search Console connector, and change things until you understand why they change. You’ll make a better connector decision after you’ve felt what the tool does than by reading feature tables — including this one.

One distinction worth learning before you build anything

This is the mistake I see most often, and it costs people more time than any technical limitation: a dashboard is not a report. I’ve argued this at length in a piece on data storytelling, and it’s the thing I’d most want a beginner to internalise:

You can’t use a dashboard in place of a report. While dashboards are for letting people explore, reports are for explaining and telling a story.

Data Studio builds dashboards beautifully. What it does not do is the explaining. A live link showing twelve charts answers “what happened”; it does not answer “so what”, and stakeholders will keep asking you that until something does.

The practical fix is cheap: put your commentary inside the dashboard. I keep annotations in a Google Sheet — date, event, description — and blend it onto the report on the Date field, so context sits next to the number it explains. It also has a useful side effect, which I’ve described elsewhere as insurance:

Include commentary and annotations, whenever possible. These elements will make sure that even when the charts encounter loading errors, the page will still be useful for people accessing your report.

The other beginner trap is rushing to build before understanding the data:

Novices might rush to create a report without taking the time to analyze the data. They may focus on building a visually appealing presentation but fail to dig into the performance metrics… Creating pretty reports with improperly conveyed or understood data is also a huge waste of time.

Which leads to the one rule that will improve your charts faster than any tutorial: “Choose visualizations that are appropriate for the type of data you are visualizing. Don’t just choose them cause they look pretty.”

Where Data Studio gets hard

Every introduction should include this section and almost none do. These are the walls you’ll hit, all of them documented by Google:

  • Blending is capped at five sources. “A blend can have up to five tables”, and blends can’t be reused across reports — each is trapped in the report where you built it. I’ve called this “one of the most frustrating limitations I have encountered”, and I’d add what I said then: “While this may sound like a lot, trust me — it isn’t.”
  • Blending hides its own workings. This one matters more than the cap. “When you blend data sources, Looker Studio handles the underlying data manipulation and joins automatically. This can make it more difficult to verify the accuracy of the blended data.” That’s a real risk when someone makes a budget decision on a blended number — so verify anything important by a second method before it drives spend.
  • Reports get slow, and the fix has its own ceiling. Data Studio queries the source live every time someone opens a report. The standard remedy is an extracted data source, which is “a static snapshot of up to 100 MB”.
  • GA4 API quotas surface as errors. Reports connected to GA4 “are subject to Google Analytics Data API quotas” and “reports that exceed these quotas may display an error message.” Also worth knowing early: GA4 segments and comparisons aren’t available through the connector at all.
  • Search Console is split in two. A single data source uses Site Impression or URL Impression, not both — a report needing page-level and site-level data needs two sources. And query data is deliberately incomplete: “to protect user privacy, Search Analytics doesn’t show all data”, with withheld queries aggregated into a blank row.
  • It is not a data warehouse. Data Studio has no memory. If a platform only retains 90 days, your report only shows 90 days. Keeping history means putting a warehouse like BigQuery underneath.

And a general one, said with affection. If you build in Data Studio for any length of time you will meet what I’ve previously called the kiss of death — “breaking charts, unknown data sources, user configuration error, data set configuration error…. error, error, error” — and the tool “does not have a good reputation in terms of being kind or helpful when your tables break.” A good defence is architectural: keep “a good, stable holistic overview, which links to fancy, less-stable, granular data views”, so a broken chart on page four never takes down page one.

None of this should stop you starting. I criticise the tool because I use it every day — we criticise the things we love the most — and all of these are cheaper to learn now than three months into a client relationship.

Data Studio vs Power BI, Tableau and Looker

Briefly, since this is a beginner’s guide:

  • vs Power BI — Power BI is more capable at modelling and handles larger data better; Data Studio is free, browser-based and far quicker to share with a non-technical client. If your organisation is Microsoft-shop and licences already exist, Power BI is reasonable. Otherwise the free, link-shareable option usually wins for marketing reporting.
  • vs Tableau — Tableau is a specialist visualisation tool with a steeper learning curve and real licence costs. For marketing dashboards, that power mostly goes unused.
  • vs Looker — as covered above, a different product entirely: enterprise BI with a modelling layer, bought by data teams, not an upgrade path from Data Studio.

How to actually get started, today

  1. Open Data Studio and sign in with the Google account that already has access to your analytics.
  2. Copy a template rather than starting blank. Here’s how, and our template library is free to browse by data source.
  3. Connect one source — GA4 or Search Console if you have them, since they’re free and instant.
  4. Change one chart so it answers a question you’re actually asked in meetings.
  5. Share the link with one person and see what they ask for.

Step five is the one that matters. A dashboard nobody opens is a hobby; the questions you get back are what turn it into reporting.

Frequently asked questions

Is Data Studio really free?

Yes — free to build and free to view, with no expiry. Data Studio Pro at $9 per user, per project, per month adds organisation ownership, team workspaces and enhanced scheduling. Connectors for non-Google platforms are where costs actually appear.

Is Data Studio the same as Looker Studio?

Yes, the same product. Google renamed it Looker Studio in 2022 and has moved it back to Data Studio. It is not the same as Looker, which is a separate enterprise BI platform.

Is Data Studio part of Google Workspace?

No. It’s free to anyone with a Google account, Workspace or not. Some Pro features connect to Google Cloud projects rather than Workspace.

Do I need to know SQL?

Not to get started, and not for most marketing reporting. But it pays off in two specific places. The first is joins — blending in Data Studio is a join wearing a friendlier name, and if you understand left vs inner joins you’ll immediately understand why a blend is dropping rows or duplicating spend, which is the single most common blending bug. The second is calculated fields: Data Studio’s formula language borrows CASE, IF and aggregate functions almost directly from SQL, so anyone who has written a CASE statement can write a custom field on day one. You can learn Data Studio without SQL — but a weekend on joins will save you weeks of confused blends.

How often does data refresh?

Data Studio queries the source when someone opens the report, so data is current on load — subject to the source’s own freshness and any caching your connector applies.

Can I use Data Studio for client reporting?

Yes, and it’s one of the most common uses. Reports share by link with no login required for viewers. If you’re doing this at scale, read the agency section on report ownership before you build twenty dashboards on a personal account.

Where to go next

Scroll to Top