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Optimizing DV360 Campaigns based on Offline Conversions An Introduction to Attribution Modelling in the Cloud
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Incubeta DQ&A

Goals

Charlotte Tilbury is an internationally renowned makeup and skincare brand who wanted  to better use their existing investment in mar-tech to drive ROAS improvements across their international display channels. Simple first-party audiences like basket abandoners showed great promise but they wanted to explore “what is possible” when using ML to build these audiences from all the available signals in Google Analytics 360. Incubeta DQ&A was tasked with building a more sophisticated retargeting strategy that would drive ROAS improvements and demonstrate the value of Data Science.

  • Increase campaign ROAS KPIs
  • Activate effective First-Party audience segments in DV360
  • Demonstrate & quantify the value that Data Science can bring when activating large volumes of first party data

Strategy

  • Built a ML model to ingest key indicators of purchase intent from GA360 and predict the purchase propensity of each user
  • Created Audience Segments based on users’ purchase propensity
  • Pushed segments to DV360 to action more sophisticated retargeting strategies

Results

  • 86% reduction in CPAs
  • 5x increase in ROAS

 

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