---
title: "How to build an ecommerce report in Looker Studio"
author: "Performetic Ekibi"
url: "https://www.performetic.com/en/blog/looker-studio-ecommerce-report"
published: "2026-03-21T08:00:00.000Z"
updated: "2026-10-05T02:41:55.346Z"
---

# How to build an ecommerce report in Looker Studio

> To build an ecommerce report in Looker Studio (renamed Data Studio in April 2026), connect GA4 and Google Ads, put a few metrics such as revenue, orders, spend and ROAS on one summary page and add your own KPIs with calculated fields. A good report is a simple dashboard that makes the weekly decision easier.

## How do you build an ecommerce performance report in Looker Studio?

To build an ecommerce report in Looker Studio, first connect GA4 and Google Ads as data sources, then gather a few core metrics (revenue, orders, average order value, ad spend and ROAS) on a single summary page. Move channel and product breakdowns to separate pages and create company-specific KPIs with calculated fields.

Update note: in April 2026 Google renamed the product back to Data Studio, and lookerstudio.google.com now redirects to the new domain automatically. You do not need to change your existing reports, and every step in this guide works the same under either name.

## Why build a separate report instead of using GA4?

GA4 is a powerful analysis tool, but it was not designed for management meetings. Ad spend is not in GA4, and the Google Ads dashboard cannot see other channels. Pulling numbers from three screens into a spreadsheet every week takes time and creates errors.

Looker Studio combines this data in one dashboard, makes everyone look at the same period through a date control and is shared with a link. The real benefit is organizational rather than technical: the team stops arguing about "which number is right" and moves on to "what should we do?".

## Which pages should an ecommerce report include?

The four-page structure below is enough for most brands:

| Page | Question | Core metrics | Source |
|---|---|---|---|
| Summary | Are we on target this week? | Revenue, orders, AOV, spend, ROAS | GA4 + Google Ads |
| Channels | What does each channel bring? | Sessions, conversion rate, revenue by channel | GA4 |
| Campaigns | Which campaigns are efficient? | Spend, clicks, conversion value, ROAS | Google Ads |
| Products | Which products sell? | Item revenue, items purchased, add-to-carts | GA4 |

Use no more than 6 to 8 scorecards and one time series chart on the summary page. Turn on comparison with the previous period in each scorecard; the percentage change often says more than the absolute number.

## How do you build the report step by step?

1. **Connect GA4.** On the home page, choose Create, then Data Source, and add the Google Analytics connector. Google's documentation says you need at least Read & Analyze permission on the GA4 property.
2. **Connect Google Ads.** Add the ad account through the Google Ads connector. Campaign-level spend and conversion value come from here.
3. **Choose credentials.** Owner's credentials let viewers see the data even without access to the source account. Viewer's credentials require each viewer to have their own access. For internal reports, owner's credentials are usually more practical.
4. **Build the summary page.** Add scorecards, place a date range control on the page and set the default to "last 28 days" or "last week".
5. **Add calculated fields.** Create company-specific metrics here (examples below).
6. **Add breakdown pages.** Put channel, campaign and product tables on separate pages with sorting and conditional formatting.
7. **Share and schedule.** Share the report with a link and, if useful, schedule email delivery.

### Which calculated fields are useful?

Calculated fields let you create new metrics from fields in the data source. Common ecommerce examples:

- **ROAS:** Conversion value / Cost
- **Average order value:** Purchase revenue / Transactions
- **Cost per order:** Cost / Conversions
- **Campaign type:** A CASE statement on campaign name that groups campaigns into "Brand", "Shopping" and "Prospecting"

The last one is very powerful if you have a solid campaign naming convention. Messy campaign names look messy in the report too.

### Which chart types should you use?

One chart type per question is enough. Show status against target with scorecards, change over time with a time series, and channel or campaign comparisons with a sorted table or bar chart. Avoid pie charts and too many colors on one page; nobody in a meeting has time to compare slices. Conditional formatting on ROAS or conversion rate columns makes rows below target visible at a glance.

## How do you combine GA4 and Google Ads data?

Looker Studio's blending feature joins different sources on a shared field. According to Google's documentation, a blend can include up to five data sources and join conditions only support equality. For example, you can blend Google Ads spend with GA4 purchase revenue on the date field to chart "site revenue against total spend".

Two things deserve attention. First, if you join on campaign name, the names must match exactly in both sources: the GA4 campaign name comes from your UTMs, while the Google Ads one comes from the account. Second, blended tables are grouped before they are joined; without a unique field some rows collapse and numbers may differ from what you expect.

## How do you add Meta and other ad channels?

Google's own connectors cover products such as Google Ads, Google Analytics, Search Console, YouTube and BigQuery. For Meta, TikTok or marketplace data there are two routes: partner connectors, or exporting the data regularly to Google Sheets or BigQuery and connecting from there. Partner connectors are often paid and mean a third party accesses your data, so read their data processing terms first.

Once Meta spend is in the report, do not add Meta's self-reported purchases to GA4 numbers in the same table. Because the two systems use different attribution, the total comes out larger than real sales. A healthier approach is to add up spend and divide real revenue by it for a cross-channel efficiency metric, an idea we also cover in our [CAC vs LTV vs ROAS guide](/en/blog/cac-vs-ltv-vs-roas-ecommerce).

## Why is the report slow or showing errors?

The two most common causes are quotas and data freshness:

- **GA4 quotas:** Google states that reports connected to GA4 are subject to Google Analytics Data API quotas. Reports with many charts and frequent views can exceed them and show errors. Fewer charts, split pages and removing unnecessary dimensions usually fix this.
- **Data freshness:** According to the documentation, connectors for Google marketing products such as Google Ads and Google Analytics refresh every 12 hours, and that rate cannot be changed. This report is not the right tool for watching today's numbers in real time.
- **Connector limits:** GA4 segments and comparisons are not available through the connector. Looker Studio matches GA4's standard reports but may not match explorations exactly.

If the numbers do not match GA4 at all, the problem is usually tracking, not the report. First make sure your [GA4 ecommerce tracking](/en/blog/ga4-ecommerce-tracking-setup) works correctly.

## Example: using the report in a weekly meeting

As an example, a home decor brand uses the report every Monday like this: the summary page shows revenue and ROAS against target. If revenue is below target, the channels page shows which channel dropped. If the problem is a paid channel, the team moves to the campaigns page; if it is a category, to the products page. The meeting ends in 20 minutes with one action per page.

## Key takeaways

- Looker Studio has been called Data Studio again since April 2026; existing reports are unaffected.
- A simple four-page structure (summary, channels, campaigns, products) works for most brands.
- Build ROAS, AOV and campaign type with calculated fields.
- Blends hold up to five sources; make sure shared fields match exactly.
- Google connectors refresh every 12 hours and are subject to GA4 quotas, so keep the report lean.

If you would like a report structure built on your own data that makes weekly decisions easier, the Performetic team can review your current measurement setup in a [free growth analysis](/en/contact).

## FAQ

### Are Looker Studio and Data Studio the same product?

Yes. In April 2026 Google returned Looker Studio to its original name, Data Studio. The product moved to datastudio.google.com and the old lookerstudio.google.com address redirects automatically. According to Google, you do not need to change your existing reports.

### Is Looker Studio free?

The core product is free, and Google's own connectors let you connect GA4, Google Ads, Search Console and Google Sheets at no extra cost. The Pro edition with enterprise administration and collaboration features, and some partner connectors used for sources like Meta, can be paid.

### How do I get Meta ads data into Looker Studio?

Meta ads data is not among Google's own connectors. The two common methods are partner connectors, or exporting Meta data regularly to Google Sheets or BigQuery and connecting from there. Whichever you choose, check which party gets access to your data.

### Why don't my report numbers match GA4?

Common causes are different date ranges or time zones, comparing against explorations, data freshness delays and grouping effects in blends. Google says Looker Studio matches GA4's standard reports but not necessarily explorations. Start by comparing with a standard report using the same filters.

## Sources

- [Data Studio overview and name change (Google Cloud Documentation)](https://docs.cloud.google.com/data-studio/welcome)
- [Connect to Google Analytics (Data Studio Documentation)](https://docs.cloud.google.com/data-studio/connect-to-google-analytics)
- [How blends work in Data Studio (Google Cloud Documentation)](https://docs.cloud.google.com/data-studio/how-blends-work)
- [Manage data freshness (Data Studio Documentation)](https://docs.cloud.google.com/data-studio/manage-data-freshness)
- [About calculated fields (Data Studio Documentation)](https://docs.cloud.google.com/data-studio/about-calculated-fields)