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LinkedIn Ads Cost per Leads (Email)

Cost per Lead (Email) is a metric that measures the average cost incurred to acquire each lead who shares their email address through LinkedIn Ads. It is calculated by dividing the total advertising cost by the number of leads that provided their email information. This metric helps evaluate the cost-efficiency of campaigns specifically in terms of generating email contacts, enabling better optimization and budget allocation.

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

Cost per Leads (Email) 2.190,879 Start tracking this metric
  • About
  • Tech details

How to track Cost per Leads (Email) 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 Cost per Leads (Email) 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 Cost per Leads (Email) on the Performance screen
  6. 6
    Get Cost per Leads (Email) performance daily with Scorecards or as a weekly digest
  7. 7
    Set Goals to track and improve performance of Cost per Leads (Email)
LinkedIn Ads integration with Databox Track Cost per Leads (Email) from LinkedIn Ads in Databox GET STARTED

Basics

  • Description
    Cost per Lead (Email) is a metric that measures the average cost incurred to acquire each lead who shares their email address through LinkedIn Ads. It is calculated by dividing the total advertising cost by the number of leads that provided their email information. This metric helps evaluate the cost-efficiency of campaigns specifically in terms of generating email contacts, enabling better optimization and budget allocation.
  • Category
    Advertising
  • Subcategory
    Advertising
  • Date Added
    2017-11-11
  • Default Format
    PrefixCurrency
  • Cumulative Support
    No
  • Units
    Yes
  • Granularities
    daily, weekly, monthly, quarterly, yearly, allTime
  • Favorable Trend
    decreasing
  • Historical Data
    Yes
  • Changing historical data
    No
  • Forecast Support
    Yes
  • Benchmark Support
    Yes
  • Media Support
    No
  • Dimension
    N/A
  • Metric Type
    general Learn more
  • API Endpoint
    https://api.linkedin.com/rest/adAnalytics

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