Personalization Platform

A Personalization Platform is a data-driven platform that can be used to develop a personalized system.

• Example(s):
  • Adobe Target Platform.
  • Quaero Platform [1].
  • …
• See: Personalized Recommender, Customer Data Platform.

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References

2020

• https://cmswire.com/digital-marketing/what-is-machine-learnings-impact-on-marketing-personalization/
  • QUOTE: ... “In our 2019 Magic Quadrant for Personalization Engines, vendors had as many as 14 prebuilt predictive machine learning models. Presence of machine learning is becoming ubiquitous, but the quality is not evenly distributed, so marketers need to know how to evaluate the potential of prebuilt AI for their specific use cases.”

    Here are some of the Gartner findings on vendors in that personalization engines vendor report:

    • Acquia Lift: stand-alone personalization engine that delivers personalized web content based on machine learning content recommendations
    • Adobe Target: applies Artificial Intelligence (Adobe Sensei) and machine learning for scoring, segmentation and personalization
    • Certona: participates in the Google Cloud Partner Program, providing access to Google’s machine learning
    • Dynamic Yield: Users can upload their own algorithms to enable native machine learning, outlier detection and removal
    • Evergage (recently acquired by Salesforce): Uses machine learning to build unified customer profiles supported by diverse predictive scores
    • Oracle: Includes Oracle Adaptive Intelligence Apps machine learning to define segments.
  • Gartner also found Customer Data Platforms (CDPs) includes some built-in personalization engine machine learning capabilities through standardized data feeds. And as for the personalization engines themselves, broader input data “has the potential to improve machine learning core to many of these platforms.”

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