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LinkedIn Ads Average Frequency by Ad

Average Frequency is a metric that indicates the average number of times each unique member account was exposed to an ad, split up by Ads. It is calculated by dividing the total number of impressions (or sends) by the reach, which is the estimated number of unique member accounts with at least one impression. This metric helps understand how often target audience is seeing their ads, aiding in the assessment of ad exposure and potential ad fatigue.

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

Average Frequency by Ad 2.190,879 Start tracking this metric
  • About
  • Tech details

How to track Average Frequency by Ad 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 Frequency by Ad using Databox, follow these steps:

  1. 1
    Connect LinkedIn Ads 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 Frequency by Ad on the Performance screen
  6. 6
    Get Average Frequency by Ad performance daily with Scorecards or as a weekly digest
  7. 7
    Set Goals to track and improve performance of Average Frequency by Ad
LinkedIn Ads integration with Databox Track Average Frequency by Ad from LinkedIn Ads in Databox GET STARTED

Basics

  • Description
    Average Frequency is a metric that indicates the average number of times each unique member account was exposed to an ad, split up by Ads. It is calculated by dividing the total number of impressions (or sends) by the reach, which is the estimated number of unique member accounts with at least one impression. This metric helps understand how often target audience is seeing their ads, aiding in the assessment of ad exposure and potential ad fatigue.
  • Date Added
    2017-11-11
  • Cumulative Support
    Yes
  • Units
    No
  • Granularities
    daily, weekly, monthly, quarterly, yearly, allTime
  • Favorable Trend
    increasing
  • Historical Data
    Yes
  • Changing historical data
    No
  • Forecast Support
    Yes
  • Benchmark Support
    No
  • Media Support
    Yes
  • Dimension
    Yes
  • Metric Type
    general Learn more
  • API Endpoint
    https://api.linkedin.com/rest/{endpoint}

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