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Pinterest Average Video Play Time by Pin

The Average video play time by Pin metric on Pinterest measures the average duration that users watch a video on a specific Pin. This metric helps content creators and advertisers understand viewer engagement and preferences. It provides valuable insights into which videos are resonating with the audience and can inform strategies for creating more compelling and engaging video content. By tracking this metric, businesses can optimize their video marketing efforts to drive higher engagement and achieve their goals on the platform.

With Databox you can track all your metrics from various data sources in one place.

Average Video Play Time by Pin 2.190,879 Start tracking this metric
  • About
  • Technical Details
  • Notes
What is "Average Video Play Time by Pin"?
Average video play time by Pin is a metric on Pinterest that shows the average amount of time users spend watching a video Pin. It helps creators understand engagement and optimize content.
Example: Monitor the average video play time by Pin metric to evaluate the effectiveness of video content on Pinterest for a beauty brand promoting makeup tutorials and product demonstrations.

Visualizations

  • Databox visualization

    Bar and Line Chart

    Used to show comparisons between values.

How to track Average Video Play Time by Pin in Databox?

Databox is a business analytics software that allows you to track and visualize your most important metrics from any data source in one centralized platform.

To track Average Video Play Time by Pin using Databox, follow these steps:

  1. 1
    Connect Pinterest that contains the metric you want to track
  2. 2
    Select the metric you want to track from the list of available metrics
  3. 3
    Drag and drop the selected metric onto your dashboard
  4. 4
    Watch your dashboard populate in seconds
  5. 5
    Put Average Video Play Time by Pin on the Performance screen
  6. 6
    Get Average Video Play Time by Pin performance daily with Scorecards or as a weekly digest
  7. 7
    Set Goals to track and improve performance of Average Video Play Time by Pin
Goals

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Scorecards

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Metric Digest

Receive detailed weekly performance updates
Metric Builder

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Data Calculations

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Performance Screen

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Pinterest integration with Databox Track Average Video Play Time by Pin from Pinterest in Databox GET STARTED

General

  • Description
    The Average video play time by Pin metric on Pinterest measures the average duration that users watch a video on a specific Pin. This metric helps content creators and advertisers understand viewer engagement and preferences. It provides valuable insights into which videos are resonating with the audience and can inform strategies for creating more compelling and engaging video content. By tracking this metric, businesses can optimize their video marketing efforts to drive higher engagement and achieve their goals on the platform.

Specification

  • Metric Type
    general
  • Dimensional
    Yes
  • Decimal Digits
    No
  • Currency Units
    No
  • Granularities
    Daily, weekly, monthly, quarterly, yearly and all-time.
  • Custom Relative Periods
    Yes
  • Data Availability
    At sync, it ranges from 90 days ago midnight to now.
  • Retroactive Data Updates
    Newly synced data is merged with existing data, replacing values for matching periods.
  • Future Data Available
    No

Visualization

  • Default Format
    Duration
  • Cumulative Graph
    Yes
  • Favorable Trend
    increasing
  • Media Creatives
    No
  • Forecasts
    Yes
  • Benchmarks
    No

  • Slower loading times or sync delay errors for dimensional metrics attributed by pin

    Dimensional metrics attributed by pin may experience slower loading times or temporary sync delays because, unlike non-dimensional metrics, they require separate requests for each individual pin, with a fixed rate limit of 55 requests per minute. Accounts with a high number of pins are more likely to encounter syncing issues due to the volume of data being processed. To reduce delays, we recommend minimizing frequent date range changes within a single session, as this can further impact loading performance.

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