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Advanced Analysis in Google Analytics 360: Part III – Funnel Feature tool

Anton Dolgiy   
August 8, 2019  4min. read
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Advanced Analysis is a flexible feature set within Google Analytics 360 that offers easy-to-use data exploration and visualization capabilities. Its primary goal is to provide analysts and marketers with a full and actionable view of the customer journey, allowing for advanced and customized insight into specific customer paths.


The Custom Funnels feature in Analytics 360 used to be the best at visualizing how users progress through the conversion funnel, where they drop-off and how they behave at each funnel stage – this was before Advanced Analysis was introduced by Google. The new feature set has improved building custom funnels in Google Analytics and made it more flexible.

Core Value

The value proposition for the Funnel technique is to increase the depth of the customer journey analysis and to simplify the ability to take action based off the findings. They have many things in common with Custom Funnels: they are retroactive and don’t require preliminary planning; all changes can be made on the fly and are instantly applied to the historical data; they are based on users so each stage, drop-off, or outflow represents a ready-to-use set of user cookies that can be activated in ad-serving platforms. 

It is key to note the differences from Custom Funnels as well:


  • Doubling the number of steps to 10 vs five previously in Analytics 360.
    Similarly, each stage can now have up to 10 rules while Custom Funnels only allows five. These enable you to build more detailed funnels including more granular rules for a better understanding of a customer journey.


  • Applying up to four segments to a funnel vs one segment in Custom Funnels.
    You can now analyze, for example, the sequence of steps for a couple traffic segments side-by-side to look for common patterns or differences (e.g. New Users vs Returning Users, Organic traffic vs Paid Search traffic).


  • Use a segment as a step to enhance flexibility.
    If you’re exploring some stages of a customer path separately, you are able to drop them to the Steps pane with no need to recreate them in Analytics.


  • Contains a data table below the graph for additional context and display information in a readable way.
    Seeing an exact number which represents a drop-off or completion rate may give you an idea of how to handle this data.


  • Ability to include a breakdown dimension that appears as a new column in the data table.
    Once you’ve taken a glance at the funnel progress you can drill down into particular dimensions to identify where the issues are coming from (e.g., a location, traffic source, device or browser).


  • Applying a filter to the entire funnel can help save time defining additional rules to all the stages.
    After breaking down the analysis by dimension, it might make sense to analyze a part of the funnel segmented by a particular location, source or user type.


  • Metric-based rules to set a step.
    For instance, you may need to isolate a subset of users by who spent more time on your site, visited more pages, viewed product lists, or product details more frequently. This feature is another one (in addition to #3) that makes funnel steps resemble custom segments in Analytics.


  • All funnels are closed in Advanced Analysis, meaning they require users to go through all previous stages to be qualified for a certain step.
    Users who entered the funnel at the second or third step will not be included in the analysis. This requirement was built-in because all funnels in Advanced Analysis are based on users. Similar to the functionality of Custom Funnels, user-based funnels can only be closed.


  • Additional usability for creating a funnel: you can arrange the stages in any order by dragging them.
    Previously, you were only able to delete rules and create new ones in Custom Funnels when you needed to change the order in which the stages are applied. Now, you can simply drag and drop.

How It Works

The funnels in Advanced Analysis resemble Custom Funnels. At the top you’ll see step names, and the completion rate from a previous step. Below the graph the drop-offs are shown along with the abandonment rate for each segment applied to the funnel. The data table at the bottom displays the steps, segments, any breakdown dimensions included into the view, and the corresponding metrics: users, the completion rate, abandonments, and the abandonment rate.

Hovering over a bar in the chart, or the abandonment pane, will highlight all steps of a corresponding funnel.


If you right-click on the bars, abandonments, dimensions, or values in the data table you’ll find the menu with the following options:

  • create segment from users – quickly saves the segment in the analysis with the ability to publish it to all other reports.
  • create audience from users – takes a user to the audience setup dialogue in the Admin area.
  • view users – opens the User Explorer report with a segment builder containing the rules based on a clicked value.
  • create segment from abandonments – immediately creates a segment based on a drop-off from a specific step.
  • build audience from abandonments – opens the audience builder in the Admin area.
  • view abandonments – opens the User Explorer report filtering data based on a certain drop-off.

Funnel Analysis displays the data in a way that unveils opportunities for optimization and activation. Experimenting against some hypotheses in Google Optimize may help improve the conversion funnel and user experience. In addition to that, you can also remarket to users who abandoned the funnel and make them convert in Google Ads, Display and Video 360 and Salesforce Marketing Cloud. Then, you’ll be able to update the funnel in a few clicks in Analytics 360 and to see positive changes in the performance.

Continue reading part IV of this article