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  Measurement rules

Several measurement rules can have a large impact on the metrics that are calculated.

Users

In web browsers, cookies can be used to track a unique user over time, but this is not possible with only server access logs. Using the IAB podcast standard of combining the IP and User-Agent to derive a "unique" fingerprint for each user is easy to understand and consistently apply and works with both IPv4 and IPv6 addresses.

Our analytics will ignore logs from any IP in the reserved IP ranges (ex 192.168.x.x).

Sessions

Each session is intended to track a unique listening session for a user. Sessions "expire" after a period of inactivity. When a user listens to the same content again after the expiry time, it is considered a new session. Web analytics typically use 30 minutes as the period of inactivity before activity is considered a "new" session.

IAB general definition of a website browsing session

A sequence of Internet activity made by one user at one site. If a user makes no request from a site during a 30 minute period of time, the next content or ad request would then constitute the beginning of a new visit;

Session expiry

  • Streams. For live streams, sessions expire when 15 minutes has elapsed since the last request. There is no industry standard for stream expiry time.
  • Podcasts. For podcasts, sessions expire after 24 hours have elapsed since the first request, as per the IAB podcast standard. Repeat listens by the same user within the 24 hours will be ignored.

Session exhaustion

Sessions are considered "exhausted" once they've reached a maximum value and are no longer tracked after that.

  • Stream sessions reach exhaustion after 24 hours of listening time.
  • Podcast sessions are exhausted when they've reached the full episode duration. A listening session can never be longer than the duration of the episode.

Users vs Sessions ratio

Because sessions expire, the same user can have multiple listening sessions in any reporting period. Due to this the number of active sessions is expected to always be larger than the number of unique users. Grouping may also affect this, for example when querying by a podcast show the same user may have listened to multiple episodes of the same show in the reporting period, and so cause a higher number of sessions than users.

Database approximation

To enable self-service analytics that queries over millions or even billions of rows, HyperLogLog approximation functions are used to derive the Users and Active Sessions metrics. This introduces a small margin of error, typically around 0.5%, but guarantees fast results regardless of data size. This type of approximation is widely used by analytics products to enable real-time dashboards.

Podcast notes

Podcast "Listen through rate" is based on file access. Podcast files are mostly downloaded in their entirety by listener apps, or in large chunks when listening in the browser. This skews the listen through rate strongly towards completed listens.

IAB Podcast measurement compatibility

Every effort has been made to be fully compatible with the latest IAB Podcast Measurement Technical Guidelines, but this analytics product is not officially IAB certified.