Sales Funnel Analysis in Online Stores Using Google Analytics 4

Sales funnel analysis is extremely important for every online store aiming to optimize conversion rates and increase profit. The funnel illustrates the path a potential customer takes from their first contact with the store to making a purchase.

Understanding each stage of this journey allows for identifying weak points and taking measures to improve them.

1. When and at what stage do 80% of online stores analyze the sales funnel?

Our observations show that sales funnel analysis in online stores most often occurs not before, but after the launch of an advertising campaign, and even more frequently – after the launch of two or three advertising channels. 

And when advertising channels do not yield results, and the agencies that worked on them throw up their hands – the search for the problem begins not in the advertising channels, but in the sales funnel. 

What are the consequences? Direct costs – budgets for advertising campaigns and commissions for agencies that launched these campaigns. 

Whether an advertising agency should check the sales funnel is a question we will leave for another article. 

2. What is a sales funnel in an online store?

A sales funnel (or conversion funnel) – is a visual representation of the user’s journey leading to a target action, such as a purchase. A typical funnel for an online store, which can be built using Google Analytics 4, includes:

1. Sessions. 
2. Add to cart. 
3. Begin checkout. 
4. Purchase. 

These 4 funnel stages are present in 99% of online stores. Sometimes there are 5 or 6 such stages. But it doesn’t matter – the analysis principle remains the same. 

3. Why is it important to analyze the funnel?

• Identifying “bottlenecks”: Understanding at which stage you lose the most potential customers.
• Conversion optimization: Focusing efforts on improving specific stages, which will lead to increased sales.
• Marketing effectiveness: Assessing how effectively your marketing campaigns attract and convert traffic.
• Cost reduction: Optimizing the funnel can reduce the cost of customer acquisition (CAC).
• Improved user experience: Removing obstacles in the user’s path makes interaction with your store more pleasant.

4. Stages of funnel analysis and key metrics

4.1. Data Collection

For data to be collected for analysis, it is necessary to set up Ecommerce Google Analytics 4 or Google Analytics 4 e-commerce. This module allows collecting and tracking user data within the sales funnel. 

Spilno Agency, an ROI-focused agency, offers Ecommerce Google Analytics 4 setup services. They also assist with sales funnel analysis and other marketing services.  

You also have the option to do this yourself. We have described a case on how to do it. 

After setting up Ecommerce Google Analytics 4, data should be collected for analysis. We recommend choosing data for 1 month or more. The more data, the more representative the statistics will be. 

4.2. Table Construction

For effective funnel analysis, Google Analytics 4 and Google Sheets will be needed. 

Our main task is to analyze the funnel described in section 2. Therefore, in Google Sheets, we describe the funnel stages in columns:  

Where the % metric indicates the ratio of the current metric to the previous funnel stage. The “Overall Conversion Rate” metric is the ratio of purchases to sessions. 

4.3. Filling the table using Google Analytics 4

We will use site-wide data for the last 30 days. Data can be conveniently obtained from advertising channel reports in Google Analytics 4. 

After this, your table will be filled

If you analyze the data in the table regarding how traffic converts into a customer step by step, the stages can be divided into 3 conversion indicators: 

• low;
• medium;
• high.

Low, where conversion between stages is very small. High, where conversion is sufficiently high. And medium, where conversion is not problematic but worth attention. 

If these results were colored, it would look approximately like this: 

If these data are interpreted correctly, it can be noticed that the funnel has a very low conversion rate for adding to cart. The percentage for beginning checkout is normal, and the conversion rate to a buyer is medium. 

According to marketing and process building rules, the number of sales directly depends on the stage with the lowest conversion. However, all stages should be worked on simultaneously.  

Thus, based on the collected data, two tasks can be set: 

1. Investigate and optimize the “add to cart” stage (conversion rate 0.6%).
2. Investigate and optimize the “begin checkout” stage (conversion rate 12%).   

5. How to understand if conversion between stages is low if it’s not obvious?

There are cases when, after building a funnel, it is difficult to draw conclusions because it is unclear what the average conversion between stages should be. 

This can be resolved by contacting agencies that provide such services – based on other metrics, they can help understand what is considered the industry norm. 

For example, if metrics from other online stores for the same stages are added for comparison, the data becomes clearer – explaining why we focused on a 12% conversion rate. 

Thanks to average data from other stores, it is easier to identify problems and accurately pinpoint problematic areas of the funnel. 

If you need help analyzing your sales funnel and identifying problems at these stages – leave a request on our website – digital agency Spilno Agency. 

6. Example of a sales funnel analysis table

Link to the table – link.