Historical Count, part 3: Funnels and behavioral cohorts

This article is third in a series about Historical Counts. If you haven't done so already, read parts one and two.

Historical count in funnel analyses

In Funnel Analysis charts, a user could enter the funnel multiple times, or perform the various steps multiple times. To decide if a user counts as converted in a Funnel Analysis chart with a Historical Count filter, Amplitude considers two things: 

1. The Nth instance must be within the date picker dates; and
2. The Nth instance must occur within the conversion window of the other funnel steps.

As an example, imagine a two-step funnel. In this example, the Historical Count filter is set to 2 on event_a, with a date range of December 21st, 2020 to December 22nd, 2020. This means that you want to know when event_a was performed for the second time (Historical Count filter = 2).

The funnel is:

Step 1 = event_a

Step 2 = event_b

And the user has performed the events in this order: BBABAB.

The chart looks back 12 months (to December 21st, 2019 in this example) for historical context. If the second time the event happened wasn't within the stated date range (December 21st, 2020 to December 22nd 2020) and, instead, was some time previous, the chart doesn't include the user in the chart.

The user must perform the second instance of event_a within the specified date range (December 21 to December 22, 2020) to be counted as converted.

If the Historical Count filter is applied to the second event (event_b), and the user performs the event in this order: BBABAB

Then all of the following must occur for the user to appear in the chart:

• event_a occurred within the specified time period (December 21st, 2020 to December 22nd, 2020)
• event_b occurred within the specified time period
• event_a (the occurrance within the specified time period) happened before the second occurrence of event_b

If either of the events occurred outside of the specified date range, or if event_a did not occur before the seccond instance of event_b within the timeframe, then the user isn't included.

Historical Count in behavioral cohorts

Historical Count and behavioral cohorts are related but separate concepts in Amplitude.

A behavior cohort can define a group of users who took a specific action with a certain frequency within a specific time period. For example, users who completed a workout five times in the last 30 days. A fitness company might want to know which of its users fit this description, as it may be their definition of a recent power user.

Conversely, Historical Count allows you to pinpoint a user’s fifth workout. So if they completed only two workouts in the last 30 days, but had also completed three workouts before that, the most recent workout was actually their fifth. This is an important distinction, as a user’s fifth workout overall could also mark an important milestone in their overall user lifecycle in that they have now transitioned into a long-term group of users.

Amplitude allows users to combine the power of both, by creating a cohort with historical count as a condition. You can also see the cohort population over time as well.

To add Historical Count to a behavioral cohort, review Creating a behavioral cohort in Amplitude.