Gartner Research

Optimize Digital Customer Experiences With Machine-Learning-Enhanced Analytics

Published: 25 June 2018

ID: G00353819

Analyst(s): Bill Delrieu, Jeffery Skowron


Digital analytics applications enhanced with machine learning capabilities enable businesses to stay competitive and innovate. Technical professionals responsible for CRM and CX should use this research to gauge their organization's readiness to use these tools and improve digital experiences.

Table Of Contents


  • Assess Your Readiness for Machine-Learning-Enhanced Analytics
    • Assessment Part 1: Evaluate Your Data Preparedness Level
    • Assessment Part 2: Examine Your Skills' and Tools' Level
    • Result of Your Assessment: Where Are You on the ML Complexity Scale?
    • Establish Your Practical Starting Point
  • Explore Use Cases to Improve Customer Experience Through Machine Learning
    • Use Case 1: Augmented/Predictive Analytics
    • Use Case 2: Audience and Customer Segmentation
    • Use Case 3: Personalization Engines
    • Use Case 4: Customer Journey Orchestration
  • Strengths
  • Weaknesses


  • Assess Your ML Analytics Readiness
  • Prepare Your Data
  • Use Your Metadata for Cross-Team Conversations
  • Remember That ML Model Management Is Ongoing
  • Create Optimized Customer Segmentation Definitions
  • Leverage ML to Surface Historical Patterns

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