Activation Analysis
Last updated
Last updated
The future depends on what we do in the present - Mahatma Gandhi
"what my users should do in the pre period to retain/uninstall/ activate to specific event in the post period". - Apxor Insights
To figure out what are the actions that are taken by the user inside the app are leading to certain metrics like Retention, Churn or Doing a aha moment and many more.
Select the user journey days in the app in which you believe the opportunity window to nudge the user that will lead for the conversion event in the post period
Include a event or list of events, on which you are sure that they will have the impact on the conversion event
Exclude a event or list of events, which you don’t want to include this analysis, might be some SYSTEM EVENTS etc
Select the user journey days in the app in which the conversion event should happen
Select Metrics such as “Retention” or “Activation”
Retention: Opening the app in the post period
Activation: Select the event that you want to label as the conversion event
Select whether this analysis should be performed on
All users: who ever opened the app
Segment: A pre defined segment based on certain specific user behavior
Cohort: A fixed set of users, that you obtained it from some other platform
Once you fill these details, click on “Generate Results”
Note:
The report generation might take 2 to 3 minutes based upon the data that is being analyzed
By default, the analysis will be run on the last 30 days data, and once can change to last 15Days or last 7 Days.
The table will provide the following:
Event: the event name that is done in the pre period
Impact: indicates whether it has the positive impact on the metric selected during the post period
Score: It is the uplift in the conversion when the user has done this event in the pre-period , compared to just opening in the app
Confidence: It is the statistical significance that doing this event has significantly effect on the conversion during the post period. Usually the events that bear ≥0.95 can be considered as significant events that have impact on the conversions
% Users: It is vital to observe the percentage of users that have done the specific event in the pre period. One can considers such events that are done by at lease 1% of the users in the pre period
From the above table, one can select the events for further analysis based on the frequency that the specific action is performed:
Pick Automatically: By checking the box “Pick Automatically”, we will select the events automatically and dig further on the Frequency Chart
Using the corresponding values, pick the events you want to analyze further using the Frequency Chart
This chart lets you know how many times an event should be done ideally in the pre-period so that the user converts in the post period.
The X-axis will denote the number of times an event is done in the pre period
The Y-axis will denote the score, uplift from the baseline conversion that is opened the app in the pre-period
On hovering , we can observe,
Event: Name of the event
Score: Uplift from the baseline
Count: the number of times the pre-event is done
Confidence: Statistical significance
Using this one can observe the following patterns:
The score increases as the frequency increases - indicates that user must habituate to this action in the pre period
The score increases till N number of times and starts descending from there- indicates that the user will get vexed once he does the action N number of times
The score will keep steady after N number of times - indicates that there would not be much difference , once he does the action N number of times and there after
The score decreases as the frequency increases- indicates that the action negatively impacts the conversion
