Looking only at the final result of a conversion can tell us how many users completed a specific action, but not necessarily what happened before that point. In many processes, understanding the previous steps and identifying where users drop off is just as important.
Google Analytics 4 Funnel explorations allow us to analyze these sequences visually. We can define the steps we want to study, see how many users progress from one to the next, and use different settings to better understand their behavior.
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What is a Funnel exploration in GA4?
Funnel exploration is one of the report types available in the Explore section of Google Analytics 4. Its purpose is to represent a sequence of actions and show how users progress through the different steps we define.
A simple e-commerce example would be analyzing a journey that starts when a user views a product, continues when they add it to the cart, moves on to the checkout process, and ends with a purchase. Instead of analyzing each of these events independently, a funnel allows us to connect them within the same sequence.
This makes it possible to identify drop-off points that may not be as obvious when looking only at aggregated metrics. For example, we may find that many users add products to their cart, but only a small proportion go on to start the checkout process.
Funnels do not have to represent purchase processes exclusively. They can be used to analyze almost any journey that can be expressed through events or dimensions available in GA4, such as sign-ups, form submissions, or specific interactions within an app.
What are funnel reports used for in GA4?
Funnel reports are mainly used to understand how users move through a process. They not only show how many people reach the final step, but also what proportion continues after each interaction and where the main drop-offs occur.
This is particularly useful when a conversion depends on several consecutive actions. If we only analyze the number of purchases, registrations, or leads generated, we know the final result but have little information about the journey that led to it.
A funnel adds this context. If we identify a particularly large drop between the cart and the beginning of checkout, for example, we can focus our analysis on that specific point instead of treating the whole purchase process as a single block.
We can also use these reports to compare the behavior of different groups of users. The same funnel may perform very differently on mobile and desktop, among new and returning users, or across different markets and traffic sources.
A funnel exploration will not explain by itself why users abandon a process, but it can help us identify where further investigation is needed. From there, we can combine the analysis with other quantitative or qualitative data to better understand the possible causes.
How to create a funnel exploration in GA4
To create a new exploration, go to the Explore section in Google Analytics 4 and select the Funnel exploration template. You can also start with a blank exploration and select this technique afterwards.
As with other Explorations, we can choose the date range we want to analyze and add segments and dimensions that can later be used to configure or break down the report.
The main part of the setup is the funnel steps. These steps determine which journey we want to analyze and, as a result, which users will appear at each stage of the report.
Defining the funnel steps
GA4 allows us to configure up to ten steps within a Funnel exploration. Each step can have its own name and one or more conditions that determine what a user must do to complete it.
In an e-commerce funnel, for example, we could use view_item as the first step, add_to_cart as the second, begin_checkout as the third, and purchase as the final step.
A step can also be made more specific. Instead of including every purchase event, for example, we could add additional conditions based on available dimensions if we want to limit the analysis to a particular type of user, product, or context.
Conditions can be combined using AND and OR operators, which makes it possible to create steps that are much more precise than a simple sequence of event names. Steps, however, cannot be defined using metrics.
It is important to define them according to the question we are trying to answer. Adding more steps does not always lead to a better analysis. In some cases, a simpler funnel makes the main drop-offs easier to identify before we investigate them further with additional explorations.
Direct and indirect steps
From the second step onwards, GA4 lets us decide whether that step must occur directly or indirectly after the previous one. This setting determines what can happen between two steps without causing the user to leave the funnel.
When we specify that a step must directly follow the previous one, the two actions need to happen consecutively. If another event occurs between them, the sequence no longer meets the condition we defined.
When we specify that a step may indirectly follow the previous one, other actions can take place in between. What matters is that the user eventually reaches the next step while respecting the order of the funnel.
In a purchase journey, for example, it may be perfectly normal for a user to view other products or perform additional interactions between view_item and add_to_cart. Requiring the two events to happen immediately one after the other could therefore exclude journeys that are still relevant to the analysis.
GA4 also allows us to set a maximum amount of time for the next step to be completed. We could, for example, require an action to occur within 30 minutes of the previous step or allow several days for a longer decision-making process.
How to interpret funnel data
Once the steps have been defined, GA4 shows how many users reached each one and what proportion continued to the next. The report makes it possible to visualize both progression and drop-off between the different stages of the journey.
It is important to keep in mind that these reports are primarily user-based. The objective is not to show how many times each event occurred, but how many users completed the sequence we defined.
This can lead to differences compared with other reports. If one user adds five products to their cart, for example, they will not appear five times in that step. The funnel analyzes whether that user meets the conditions required to progress through the sequence.
The relationship between steps is usually the most useful part of the report. A reduction in users is normal as we move further through the funnel, but a particularly large drop can help us identify a point in the journey that deserves further analysis.
Standard funnel
The standard visualization represents each step as a column and shows directly how many users reached it. We can also see the proportion of users who continue and the number of users who drop off before the next step.
This format is particularly useful when we want to analyze the overall performance of a process over a specific period. It makes the main points of user loss easy to identify.
It also works well when we add comparisons or breakdowns, as it makes differences between groups at each stage easier to see.
Trended funnel
The second available visualization is the Trended funnel. Here, the different steps are represented in a line chart to show how the number of users changes over time.
This format is useful when we are not only interested in where users drop off, but also whether the behavior of the funnel is changing. We may notice, for example, that the number of users reaching a particular step starts to decrease from a specific date.
The visualization allows us to view all steps together or focus on a particular one. When a funnel contains many steps or segments, however, the chart can become harder to interpret, so the standard visualization may be more convenient for some comparisons.
Open and closed funnels in GA4
One of the most important settings in a Funnel exploration is whether we want to use an open or closed funnel. The difference determines the point from which a user can start being counted within the journey.
By default, the funnel is closed. This behavior can be changed by enabling the option to make the funnel open in the exploration settings.
Choosing one or the other can significantly change the results. It is therefore important to understand what each option measures and select the one that best matches the process we want to analyze.
What is a closed funnel?
In a closed funnel, a user must complete the first step before they can enter the funnel. If they start directly at a later step, they are not included in the analysis unless they eventually complete the first step and continue from there.
Imagine a funnel made up of A → B → C. A user who completes A → B → C will be counted at all three steps. Another user who only completes B → C will not appear in the funnel because they never completed the initial step.
A third user could complete A → C. In this case, they would be counted at A because they entered the funnel correctly, but they would not appear at C. Since B was not completed, the sequence is considered to have ended after the first step.
Closed funnels are particularly useful when we want to analyze a process with a clearly defined entry point. If we want to understand what happens after users begin a specific registration process, for example, it makes sense to require everyone to have completed that first step.
What is an open funnel?
An open funnel allows users to enter the journey from any of its steps. They do not need to complete the first step before becoming part of the analysis.
If we return to the A → B → C funnel, a user who completes B → C would appear at both B and C. Another user who only completes C could also appear at the final step, as the funnel allows users to enter at different points.
This is useful when a process does not have a single entry point. On some websites or apps, users may reach the same action through different journeys, and excluding them simply because they did not pass through the first step we defined may not always make sense.
However, an open funnel does not mean that users can skip steps after entering it. If a user completes A → C without completing B, they will be counted at A but not at C. From the moment they enter the funnel, they still need to follow the defined sequence in order to progress.
How GA4 calculates open and closed funnels
The difference becomes clearer if we look at several journeys within the same A → B → C funnel. A user who completes all three steps will appear in the same way in both an open and a closed funnel.
If another user completes B → C, the result changes. They will not appear in a closed funnel because they never passed through A. In an open funnel, however, they can enter directly at B and continue to C.
A user who only completes C would not be counted in the closed funnel either. In an open funnel, they can appear at C because that step can become their entry point.
The A → C journey works differently. Even though the user completed two actions included in the funnel, they skipped B. They will therefore only be counted at A, regardless of whether the funnel is open or closed.
There is also an important detail when the same user completes different sequences during the selected period. GA4 only records the first valid sequence through which the user enters the funnel. The same user cannot later re-enter and generate a second independent progression.
This has a particular consequence in open funnels. If B is the first step a user completes, GA4 considers that their entry point. If they later complete A and then go through B and C again, that later A does not restart the funnel. Their original entry point remains B.
In a closed funnel, the logic is different because GA4 looks for the first time the user completes the initial step. From there, it checks whether they continue through the rest of the sequence as defined.
When should you use an open or closed funnel?
The choice mainly depends on what the first step represents within the process. If we want to analyze what happens after users perform a specific action, a closed funnel will usually make more sense.
For example, if we want to analyze the progression of users who start a registration form, the first step is part of the question itself. We are not necessarily interested in including users directly at later stages because we want to understand what happens from the beginning of that process.
An open funnel is more useful when users can legitimately enter the journey at different points. It can also help us understand the number of users reaching later stages even if they did not complete the starting point we initially defined.
In some analyses, comparing both configurations can be useful. A large difference between the number of users in an open and a closed funnel may indicate that a relevant share of users is reaching certain stages through journeys other than the one we originally expected.
Options for analyzing a funnel in more detail
In addition to defining the steps, Funnel explorations include several options that allow us to investigate the results in more detail. These settings are particularly useful once we understand the main journey and want to explore differences between users.
There is no need to use all of them in every analysis. In fact, adding too many variables can make the report harder to interpret. It is usually more useful to start with a simple funnel and add new dimensions as specific questions arise.
These options include segment comparisons, dimension breakdowns, elapsed time between steps, users’ next actions, and filters.
Comparing segments
Segment comparisons allow us to analyze the same funnel for different groups of users. GA4 allows up to four segments to be added to the same exploration.
We can use them, for example, to compare new and returning users or to study the journey of users coming from different acquisition channels.
This helps us determine whether a problem affects the funnel as a whole or is concentrated within a particular group. A high drop-off rate may look concerning in aggregate, but it could mainly be driven by one of the segments being analyzed.
Breaking down the funnel by dimensions
The Breakdown option allows us to split each step using a dimension. A common example would be using Device category to compare mobile and desktop users within the same funnel.
There are many other possibilities depending on the analysis, such as breaking the funnel down by country or by other dimensions available in the property.
There is one important detail to keep in mind. When a breakdown is used, GA4 assigns the user to the first value of that dimension with which they enter the funnel. If a user enters on mobile and later completes the following steps on desktop, they will continue to appear under the mobile breakdown throughout the journey.
This behavior prevents the same user from changing category as they progress through the exploration, but it is important to understand it so that the breakdown is not interpreted as an exact representation of the device or value used at each individual step.
Analyzing the time between steps
The Show elapsed time option adds information about how long users take on average to move from one step to the next.
This can add useful context to the conversion rate. Two processes may have a similar progression rate while showing completely different times between steps.
It can also help identify stages where the decision takes longer or show whether a change to the website has reduced the time required to complete part of the process.
The value represents the average time between the previous step and the current one among users who reach that new stage. It should therefore be interpreted as a characteristic of users who progress, rather than of everyone who originally entered the funnel.
Analyzing next actions
The Next action setting allows us to select a dimension and see what users do after completing each step. The exploration shows the most common subsequent actions and provides a different perspective on the sequence we defined.
This can be particularly useful when there is a large drop-off. The funnel tells us that many users do not continue to the expected next step, while the next action can help us understand where they are going instead.
For example, after viewing a product, some users may add it to the cart while others return to a category page or continue browsing other products. Understanding these actions helps show that dropping out of a funnel does not necessarily mean leaving the website.
Seeing “(no next action)” does not necessarily mean that the user abandoned the site either. When using certain page- or screen-related dimensions, it may simply mean that the value of that dimension did not change after the step being analyzed.
Applying filters
Filters allow us to limit the exploration data to the conditions we are interested in. We can use them to analyze only a specific part of the website, a particular market, or another subset available through GA4 dimensions.
This can be useful when we want to keep the overall funnel structure but analyze a more specific context without creating a completely new exploration.
When several conditions are applied, the data shown must meet all of them. It is therefore worth reviewing the filters carefully if the exploration produces unexpectedly low volumes or results that differ significantly from other reports.
Example of a funnel exploration in GA4
A common example for understanding these explorations is the purchase process of an e-commerce website. We can create a funnel made up of view_item → add_to_cart → begin_checkout → purchase.
The first step represents users who viewed at least one product. From there, we can see how many added a product to their cart, how many later started the checkout process, and how many eventually completed a purchase.
In most cases, it would make sense to configure these steps so that they can follow each other indirectly, as many other interactions may take place between them. A user may view several products before adding one to the cart or navigate through different pages during the purchase process without necessarily invalidating the journey.
Once the funnel has been created, we can see where the largest user loss occurs. If the main drop-off happens between view_item and add_to_cart, the follow-up analysis will be different from what we would investigate if the largest drop appears after begin_checkout.
We can then add a breakdown by device category. If the drop between the beginning of checkout and purchase is significantly higher on mobile, we have a more specific signal about where to start investigating.
We can also enable elapsed time to understand how long users take to move between the different stages or use the next action to see what users do when they do not immediately follow the expected journey.
Finally, comparing the result with an open funnel can help us identify users who enter directly at intermediate steps. This does not necessarily mean that one of the two reports is more correct than the other. They simply answer different questions about the same process.
Considerations and limitations of GA4 funnels
A Funnel exploration depends directly on the data we are collecting. If the required events are not implemented correctly or do not accurately represent real user actions, the funnel will not provide a reliable view of the journey either.
It is also important to remember that the report primarily works with users. We cannot interpret the volume at each step as the total number of times an action occurred. If we need to analyze repeated events, sessions, or other metrics, we will need to complement the funnel with other reports or explorations.
The order of the steps also has a direct impact on the result. A user may have performed every action included in the funnel and still fail to reach the final step if those actions were not completed in the sequence we defined.
Likewise, open and closed funnels should not be confused with direct and indirect steps. The first setting determines where a user can enter the journey. The second determines what can happen between two consecutive steps once the sequence is being evaluated.
We should also keep in mind that if a user completes the sequence several times during the selected period, GA4 uses only their first entry into the funnel. The exploration is not designed to count every possible repetition of the same journey.
Finally, differences identified within a funnel should be treated as a starting point for further analysis. Knowing that there is a drop between two steps is useful, but it does not prove why that drop occurs. Answering that second question will usually require additional analyses, segments, or other sources of information.
In short, Google Analytics 4 Funnel explorations allow us to analyze how users progress through a specific sequence and identify where the main drop-offs occur. The ability to define custom steps, compare segments, add breakdowns, and analyze elapsed time or subsequent actions makes them one of the most useful exploration techniques for studying conversion processes.
To interpret the data correctly, it is especially important to understand how the steps are defined and the difference between open and closed funnels. The report helps us identify where user behavior changes and provides a useful starting point for investigating the possible causes.
