GA4 benchmarking option
For companies who use Google Analytics, you may see the first graph on your Home Page, which contains many benchmark KPIs across different industries, like the example below:
source: Google Merchandise Store (données Web)
Using this graph, you can identify your benchmark sector and select the available benchmarking KPI you want to compare with your own data, allowing you to immediately see where you stand within the market performance percentiles.
If you want to learn more about how Google Analytics collects and display this data, please read Google Analytics Benchmarking documentation
For example, if your company is a food retailer, you can choose “Food and Drink” as the market sector. If you want to understand your company’s position in the market based on the number of “Add to cart per active user”, you can select this KPI to view the market percentiles and see where your own KPI falls within them.
Explore limits
This graph is useful for understanding your performance in the market, but there are some limitations to how you can use this data:
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- You can only explore the data within this graph and compare each KPI with your own one by one, making the process mostly manual.
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- The data must be used as presented in the default graph, with no way to further personalize or customize the analysis.
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- By default, you can only display your company’s performance data for up to one year, while the benchmarking data is only available for the last 30 days.
source: Google Merchandise Store
source: Google Merchandise Store
All these limitations make peer analysis less flexible, even though this data could be used more effectively in several ways, such as:
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- Cross-market analysis with all KPIs available simultaneously (for example, if your company sits between two benchmark industries and you want to compare against both).
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- Integrating the benchmarking data into existing dashboards for more customized and detailed analysis.
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- Long-term monitoring of your company’s KPIs versus market benchmarks to track trends over time.
This is why Datama, a data analytics company that provides clients with automated data exploration and insights through its own solutions, aims to automate the collection of these benchmarking datasets and unlock deeper analytics insights.
Scrapped GA4 benchmarking data
We are pleased to announce that we have successfully scrapped all the benchmarking KPIs across all available industries from this graph. You can find an example for June 2025 here.
This Gsheet dataset captures industry benchmarks drawn from the Google Analytics 4 (GA4) Home Page, offering a snapshot of how businesses in the Arts & Entertainment and all other industrial sectors were performing as of June 1, 2025.
It brings together key performance indicators across e-commerce, events, page and screen engagement, revenue, and session activity, with each metric anchored to the 25th, 50th, and 75th percentile benchmarks. These reference points reveal what’s typical for lower performers, the industry median, and the top quartile of peers, making it easy to see where a business truly stands.These reference points reveal what’s typical for lower performers, the industry median, and the top quartile of peers, making it easy to see where a business truly stands. For example, if a business’s conversion rate falls above the 75th percentile, it means their performance is better than 75% of their peers.
By using these benchmarks, teams can quickly spot where they’re outperforming the market and where there’s room to grow. Whether it’s understanding if low engagement reflects a broader trend or uncovering opportunities to push into the top tier of performance, this dataset transforms raw analytics into meaningful context. It’s not just numbers — it’s a lens into the competitive landscape, helping businesses make smarter, data-driven decisions.
Automated approach and script
This data was collected using a custom javascript code developed by Datama’s team that automates this extract in the GA4 environment.
This script automatically gathers GA4 industry benchmark data for a given period of time, covering any industry sectors such as Arts & Entertainment, Finance, and Travel. It pulls percentile benchmarks (25th, 50th, 75th) for key metrics like purchases per user, session engagement, revenue per buyer, and user retention ratios (DAU/MAU, WAU/MAU) etc. It can target any GA4 property (Here is data from google merchandise store demonstration account, but can be replaced by your company’s google property) as long as you have the access to the GA4 interface.
Once the data is collected, the script cleans, organizes, and formats it into a single CSV file, with each metric grouped by category (e-commerce, events, sessions, users, revenue). It also converts technical GA4 metric names into clear, presentation-ready labels, making the output easy to use for peer analysis and reporting.
If you want to measure your performance using these benchmarking data, please contact us so that we can apply this script on your data on a regular basis.
Go further with Datama solutions
So, how can we dive deeper into this data? How does Datama’s solution enable a more advanced and personalized analysis?
Firstly, Datama Detect helps you monitor changes in your KPIs compared to benchmarking data over time. By default, it compares your KPIs with the market average, but you can also set it to compare against the 25th or 75th percentile for a more precise view.
You can integrate all the GA4 benchmarking KPIs mentioned earlier into Datama Detect—whether through our web app or via extensions for Power BI, Looker Studio, Tableau, or Qlik. The tool can send you alerts whenever significant drops or anomalies occur.
Here’s an example of how it works:
In this example, we imported all GA4 Benchmarking KPIs for the “Shopping&Retailers” sector and focused on one specific metric: Purchase per Active User.
Demo Looker Studio + Data source
We observed that, for the vast majority of June, the ratio of Company Purchase per Active User to Market Average Purchase per Active User remained consistently below 1. This indicates that the company is performing below the market average for this KPI.
Red dots indicate that the company’s performance relative to the industry average has dropped, which might be concerning, especially if you set Datama’s significance calculation at a high level (which is not the case in the screenshot). You may want to be alerted automatically when this happens. This is exactly what Datama Detect is made for.
Why this Underperformance?
To understand the reasons behind this underperformance, we continue the analysis with Datama Compare, another smart solution (available in our web app or as an extension for Power BI, Looker Studio, Tableau, or Qlik). This tool allows for a deeper, more detailed comparison to help pinpoint the exact causes of the performance gap.
We built an automated analysis to examine the difference in Purchase per Active User between the targeted company and the Market Average (50th percentile). To achieve this, we added a funnel analysis from “Add to Cart” to “Purchase”, allowing us to identify where in the conversion flow the underperformance is most pronounced.
Demo Looker Studio + Data source
We can see that the company’s Purchases per Active User for June 2025 (0.318) is above the market 25th percentile (0.256), primarily due to a higher Add to Cart traffic per active user compared to the 25th percentile.
However, the same funnel performance (0.318) is significantly below the market average (0.533). This underperformance is driven by a lower conversion rate from Checkout (per active user) to Purchase (per active user), despite the company achieving a higher Add to Cart traffic (per active user) than the market average.
Therefore, the company should prioritize improving the conversion rate after the Add to Cart step in order to catch up with the market average. Strategies could include encouraging users to complete their purchases and reducing cart abandonment, rather than focusing primarily on driving more Add to Cart actions from product pages (which, while helpful, is less targeted at fixing the core issue).
With all these GA4 benchmarking indexes, there are countless opportunities to deepen the analysis and uncover valuable insights.
We can develop highly customized and actionable use cases tailored to your specific challenges, helping you identify opportunities, address weaknesses, and drive performance improvements. We’re here and looking forward to sharing more with you.
