Did [not] Perform Clauses

The Did [not] Perform clause allows you to limit query rows to users who did or did not do a selected event before or after performing the initial event. It is a great way to examine users who performed more than one event in a sequence you can define in Analytics. Here's a simple example: you could use a did [not] perform clause to view users who did Subscribe after Email Clicked.

This feature is only available in Segmentation.

Prerequisites:

• A query row that already has an initial event

"Did [Not] Perform" Clause Basics

Creating a "Did [Not] Perform" Clause

To use a Did [not] Perform clause, select an event from the Did [not] Perform data dropdown. This article contains information about modifications that will provide you with more ways to understand your users.

Did vs Did Not Do

After selecting an event in the Did [not] Perform dropdown, decide whether you want to understand the data of users who did this event or did not do this event. For example:

• Show the total count of events where users who did Subscribe also did Email Clicked at least once within the prior 7 days.
• Show the total count of events where users who did Subscribe did not do Email Clicked within the prior 7 days.

When the query is set to “Total count of”, users may be counted in the results even though they explicitly meet the did not perform clause criteria. This is because, in “Total count of” mode, the query may count a user multiple times if they satisfy the query criteria.

To illustrate this, consider a query measuring “Total count of Subscribe for users who did not do Email Clicked within the prior 1 hour”.

A user who logs on for the first time at 12pm and performs Subscribe will have their action counted because they did not perform Email Clicked within the prior hour.

If the same user then performs Email Clicked at 1:30pm, and then performs Subscribe again at 2pm, their action will not be counted twice because this instance does not meet the criteria, as they did do Email Clicked within the hour prior.

Adjusting Event Count

After adding an event using the Did [not] Perform clause, you can adjust for the number of times users performed this event, such as greater than or equal to one time, less than five times, or greater than three times. For example, you can view the event count for users who did Subscribe, and also did Email Clicked greater than three times within the seven days prior to subscribing.

Adjusting Date Range

After adjusting the event count, customize the date range. The first menu allows you to select whether the Did [not] Perform clause event should have occurred prior to the initial event, subsequent to the initial event, or between two selected calendar dates. When using between, the second menu displays a calendar, allowing you to select a specific date range.

When using within the prior/subsequent, the second menu allows you to select a preset or custom count based on minutes, hours, days, weeks, or months.

Multiple "For" Clauses

Multiple Did [not] Perform clauses may be added by selecting additional events from the Did [not] Perform dropdown.

As events are added, you can adjust the event count and date range of each additional Did [not] Perform clause. When using a relative date range, the date range is always relative to the date of the base event in the query and not the other Did [not] Perform clauses.

For example, you could view the event count for users who did Subscribe for users who also did Email Clicked two times or more within the prior seven days, and also did Blog View three times or more within the prior seven days. This will show users who clicked email links and viewed content within seven days before subscribing.

Difference between Funnel and a Did [not] Perform Clause

The most common method of analyzing a user journey is to use the Funnel tool. The Funnel tool is specifically designed to measure user journeys, and is highly customizable through features such as Conversion Precision, Optional Steps, and Tracking Properties. However, user journeys combined with a Conversion Limit can be recreated in a Segmentation query combined with a did [not] perform clause. However, these two methods can yield different results. Consider the following queries:

Funnel:

Did [not] Perform:

These two queries are measuring the same user journey - a user who does Email Clicked, and then within 24 hours also does Subscribe. However, the funnel query shows a considerably lower amount of converted users. This is due to the following:

• A Funnel query only counts a user once. Therefore, the funnel tool will only consider the first instance of an event.
• A Segmentation query will count users more than once. Therefore, the segmentation tool considers all instances of an event.

Consider the following example:

• User performs Email Clicked at 10:00 AM on 2/27
• User performs Email Clicked at 13:00 PM on 2/27
• User performs Subscribe at 11:00 AM on 2/28

The funnel tool will look at the first instance of Email Clicked (at 10AM), and see that the user did not complete Subscribe within 24 hours of that instance of Email Clicked. This user is therefore not counted in the funnel analysis.

The segmentation tool will look at all instances of Email Clicked, and therefore see that the user performed Email Clicked at 13PM, and Subscribe within 24 hours of that event. This user is therefore counted in the segmentation analysis.

So, when comparing user journeys in Funnel to user journeys in Segmentation, the user count will always be lower in Funnel due to the fact that the Funnel tool only counts each user once, and looks at the first instance of the initial event.

How It's Done

Take a look at the following example query: 

To decide which blog view events will be counted, Analytics will look at the timestamp on each blog view and check to see if there is a create profile event that falls in the 7 subsequent calendar days. If this is the case, the blog view will be counted in the analysis.