Measure your success the right way.

Pinecast podcast analytics are driven by a powerful analytics engine that provides near-realtime data with unparalleled granularity.

A screenshot of the Analytics view for a podcast, including aggregate listen and subscriber numbers, a menu to choose the analytics view and time frame, the line chart of analytics results, and annotations showing when episodes were published.

The data you need, however you need it

We provide a wide array of views for your analytics data. You can choose time ranges for most views. For time series data, you can choose the granularity to view the results by (day, week, month). Most views are timezone-adjusted to your computer's clock.

Every analytics view includes an explanation of what you're looking at and how to interpret the data, so you're never without context. We'll even annotate your charts to show when episodes were published. And of course, you can download any view as a CSV.

More data than you're used to

Pinecast offers 19 analytics views for podcasts, 13 views for episodes, and 16 views for podcast networks (available with our Crew add-on). You'll be hard-pressed to find another host that provides as much data with the same quality as Pinecast.

See all of the details about our analytics

Podcast views

  • Total listens
  • Total listens on Spotify
  • Subscribers
  • Listens by episode
  • Listens by time of day
  • Top episodes
  • Listen growth
  • Listen growth by episode
  • Listens by source
  • Listens by agent
  • Listens by agent by time
  • Listens by OS
  • Episode listen totals
  • Listener locations
  • Subscriber locations
  • Short link visits
  • SL visits by browser
  • SL visitor locations
  • SL clickthrough breakdown
  • Top episodes

Episode views

  • Total listens
  • Total listens on Spotify
  • Listens by time of day
  • Listen growth
  • Listens by source
  • Listens by agent
  • Listens by agent by time
  • Listens by OS
  • Listener locations
  • Short link visits
  • SL visits by browser
  • SL visitor locations
  • SL clickthrough breakdown

Network views

  • Total listens
  • Total listens on Spotify
  • Subscribers
  • Listens by time of day
  • Top episodes
  • Listen growth
  • Listens by source
  • Listens by agent
  • Listens by agent by time
  • Listens by OS
  • Listener locations
  • Subscriber locations
  • Short link visits
  • SL visits by browser
  • SL clickthrough breakdown

The secret is in the data.

The competition

Most podcast hosts store analytics data in aggregate: listens get stored as counts in buckets. Each bucket usually represents a day. This approach is inexpensive, but can be limiting.

Pinecast

Pinecast stores every listen as a discrete record in a database. Listens are counted up when they're requested for a chart. This is more challenging, but offers the most freedom when looking at your data.

Diagram illustrating listens counted in a table, with one count per calendar day.A diagram illustrating listen data stored with one record per listen, showing a timestamp, a device icon, and an episode name.

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