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Pinterest Saves by Pin

Saves by Pin is a metric on Pinterest that shows how many times a specific Pin has been saved (re-pinned) by other users. It indicates the popularity and engagement level of a Pin, as well as its potential reach. The more Saves a Pin has, the more visibility it can gain across the platform, leading to increased website traffic and brand exposure. Monitoring Saves by Pin helps Pinterest users understand which content resonates best with their audience and optimize their Pinning strategy for better results.

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

Saves by Pin 2.190,879 Start tracking this metric
  • About
  • Technical Details
  • Notes
What is "Saves by Pin"?
Saves by Pin is a metric on Pinterest that measures the number of times a pin has been saved or re-pinned by users to their own boards, indicating popularity and engagement with the content.
Example: A fashion brand measures Saves by Pin to track how many users save their latest collection of dresses to their boards for future reference and inspiration.

Visualizations

  • Databox visualization

    Bar and Line Chart

    Used to show comparisons between values.

How to track Saves 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 Saves 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 Saves by Pin on the Performance screen
  6. 6
    Get Saves by Pin performance daily with Scorecards or as a weekly digest
  7. 7
    Set Goals to track and improve performance of Saves by Pin
Goals

Set Goals to track and improve your performance
Scorecards

Get your daily progress every morning with Scorecards
Metric Digest

Receive detailed weekly performance updates
Metric Builder

Built your own custom metrics with Metric Builder
Data Calculations

Set Goals to track and improve your performance
Performance Screen

Get instant insights into your top-performing metrics
Pinterest integration with Databox Track Saves by Pin from Pinterest in Databox GET STARTED

General

  • Description
    Saves by Pin is a metric on Pinterest that shows how many times a specific Pin has been saved (re-pinned) by other users. It indicates the popularity and engagement level of a Pin, as well as its potential reach. The more Saves a Pin has, the more visibility it can gain across the platform, leading to increased website traffic and brand exposure. Monitoring Saves by Pin helps Pinterest users understand which content resonates best with their audience and optimize their Pinning strategy for better results.

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

  • 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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