Interpreting a Funnel Analysis

Overview

Analytics Funnels provide best in class intelligence and insight on how users are completing key steps and where users are encountering friction and failing to achieve KPIs. At a high level, Funnels are much more than SQL or BI reports. Funnels contain complicated multi-step computations that can’t be reduced to simple SELECT-FROM-WHERE statements. The events in the funnel must occur in sequential order. And the order of events can either forward in time or backward, as explained in the Funnel Direction article. And report options are available that further refine results to align with the business logic of each step in the report. Funnels show overall completion rate and time to complete. And each step in the funnel has additional statistics and details available.

Metrics

Within Funnels, there are a number of important data points to take note of. Funnels are user-centric and reflect unique user counts and conversion percentages. Funnel metrics are constrained to both the Funnel Entry Date Range. when the user completed the first step of the funnel, and Conversion Limit selected. With simple report settings changes, you can explore how completion rates vary as these times are adjusted. For example, funnel completion rates should go up as the time range increases because users are given a longer window to complete the steps.

• Average Conversion Time is the average time it took users to get from the first step to the last.
• Total Conversion Rate is the percentage of users who successfully completed the entire funnel.
• Events are represented by blue circles, each containing the unique count of users who completed a particular event or series of events.
• Webbing is the area that connects each event in the funnel. Within the webbings, you can view the conversion rate between each step.

Path insights

Path Insights displays a variety of important funnel metrics. To access Path Insights, select an event in your funnel.

• Path displays which step users completed before completing the selected step.
• Total Drop displays the percentage of users lost in the progression from the previous step to the selected step.
• Total Conversion displays the percentage of users that made it from the previous step to the selected step.
• Average Step Time displays the average amount of time it took users to get from the previous step to the selected step.

Conversion precision

In the Conversion Precision article, you can see all the options to fine tune your results to match business use-cases. Key among these settings is the ability to allow some overlap in events by a few seconds. This feature is important in cases where events are collected around the same time. For example, a funnel tracking a front-end Registration Button Click event followed by a back-end Account Created event may need to allow a few second overlap in timestamp values to capture all new accounts. Funnels allow the overlap - along with precise control of the maximum number of seconds events could overlap and still be considered sequential.

In the Path Insights, you may choose a path to access the Data Insights Menu. From there, select “Open in Cohort” or “Open in User Insights” to view the funnel information in other contexts. These features give you the ability to download the users at a specific step for validation or re-targeting. See Cross-Tool Compatibility in Funnel for more information.

Zoom

You may zoom in and out of your funnel by using the dropdown menu in the top right corner of the chart window.

Funnel flexibility

Funnels typically follow the critical steps to complete a user journey. For example, a commerce app would have browse, cart and buy as steps. But Analytics Funnels support more complex business logic including optional steps. The only steps in Funnels that are required are the first step and the last step. All others can be flagged as optional. When users flow through the optional steps, there is path exclusivity. That means that a user can appear in only one path or if the user appears multiple times, it is once for each path that they completed. In the commerce example, this could be the product compare feature or a size chart. For more information, see the Multipath Funnel article.

Funnels allow you to test the importance of funnel steps by setting steps to inactive without completely deleting them. This is useful for understanding the impact of a step in overall conversion. And once your key funnel reports are in use, the trending option helps you monitor funnel performance over time.

When there are key user characteristics that significantly contribute to conversion patterns, funnels can be built to group together users by an additional attribute. User by age group or user by sign up channel are interesting ways to dig into how users interact with a digital property. Depending on the attribute selected, users may land in the funnel more than once. Consider a user who visits first from search and then shortly after from a social ad. The grouped funnel can handle the complexity of treating those visits separately to understand which inbound channel has a more positive impact on conversion.

Conclusion

Many tools have funnel and conversion reporting. Analytics Funnels take funnel reporting to the next level with controls and exploratory features. Funnels are simple to adjust even as they seamlessly turn on the complex computational logic needed to understand digital behavior.