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Consent Management Platform (CMP) analytics overview

Access Type: Analytics - Viewer

Didomi Consent Management Platform (CMP) analytics provides your organization with a variety of dashboards that can be subsequently filtered to review key data on how your consent notices are performing on your domains/apps. In this article, we will cover the following for CMP analytics:

  • Dashboard updates​​
  • Historical data limits​
  • ​Measured events​
  • ​Data sampling​

Note: The following refers to aggregated analytics data captured in Didomi structured CMP dashboards. Consent proofs (the individual historical records of an end-user's consent choices are stored by Didomi for 5 years). 

Dashboard updates

Didomi CMP analytics dashboards are updated daily (at approximately 7:00 AM UTC) with a 1-day delay.

Historical data limits

 The look-back window for data is dependent on the available date aggregation for a particular dashboard. Please refer to the table for the historical data limits for each dashboard:
Shortest aggregation
Historical data limit
Dashboards

Hourly

14 days

  • Exploration

Daily

1 year

  •  Domains & Apps
  •  Countries
  •  Tech
  •  Web Pageviews
  •  App Sessions
  •  North America
  •  AB Tests
  •  Notice implementation

Measured events

 Didomi SDKs automatically collect events when an end-user interacts with your website, mobile app, etc... The following events are collected and aggregated to generate CMP analytics dashboards:
 Some events are also stored as a legal proof for consent.
Events Description

Website pageviews

A pageview event is fired on every page browsed by an end-user on your website where the Didomi SDK is present.

Note: Pageviews are only tracked when the Didomi SDK is present on the page so ensure to embed the Didomi SDK tag on every page of your website.

This event includes the following data points:

  •  Date and time
  •  Consent status of the end-user for purposes and vendors
  •  Domain name (but not the actual URL/page visited by the user)
  •  Country of the end-user
  •  Experiment (if any)
Mobile app sessions

App sessions are tracked every time your mobile app is launched.

Note: App sessions are only tracked when the Didomi SDK is initialized so ensure to embed the Didomi SDK in your app and initialize it on every app launch.

This event includes the following data points:

  •  Date and time
  •  Consent status of the end-user for purposes and vendors
  •  Mobile app ID
  •  Country of the end-user
Notice display

Event tracks when consent notices are shown to end-users for collecting their consent.

This event includes the following data points:

  •  Date and time
  •  Purposes and vendors shown to the end-user
  •  Consent status of the end-user
  •  Domain or mobile app ID
  •  Country of the end-user

End-user consent decisions

Event tracks consent decisions made by the end-user (both positive and negative). consent.given is sent every time an end-user agrees or declines purposes or vendors in a consent notice (or any other UI displayed by Didomi) in order to register the new consent status of the end-user.

This event includes the following data points:

  •  Date and time
  •  New consent status of the user for purposes and vendors
  •  Previous consent status of the user for purposes and vendors
  •  Domain or mobile app ID
  •  Country of the user

Note: This event is stored as a legal proof of consent.

UI interactions

Event tracks the end-user's interactions within the consent UI (showing the list of purposes, expanding vendor details, etc.).

This event includes the following data points:

  •  Date and time
  •  Identifier of the interaction with the UI
  •  Domain or mobile app ID
  •  Country of the user

Data sampling

Aside from the end-user consent decisions event (which is collected and stored by Didomi as legal proof of consent and to demonstrate end-user choices), the remaining events collected by the Didomi SDKs on websites and mobile apps are sampled.

Sampling refers to the collection of events from random end-users and then extrapolating the analytics data in your organization's CMP dashboards. The Didomi sampling strategy is currently:

  •  Every end-user is associated with a unique and random user ID
  •  User IDs are uniformly distributed into N random buckets through hashing
  •  Users from the top X% buckets are selected as being part of the sample
  •  All events from users in the sample are collected

Note: The sampling rate varies across event types and platforms.

This strategy ensures that the sample is representative of the entire end-use base by selecting purely random end-users and logging all events for those end-users (which ensures that we capture the full behavior of those end-users).