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Introduction

Customer journey mapping in the experience economy requires a shift to a more holistic and actionable approach of customer journey management. With this shift, enterprises can track, map, analyze, visualize, and act on customer journeys in real time and in personalized ways.

Highlights

  • Customer journey mapping and analytics converge. Static customer journeys evolve into actionable and relevant interaction moments.

Features and Benefits

  • Assesses the tools and technologies required to evolve to an enterprise customer journey management approach to tracking and responding to customer journeys.
  • Instructs enterprises how to prepare culturally for the shift from customer journey mapping to customer journey management.

Key questions answered

  • What are the key technologies necessary for customer journey mapping to evolve from static to actionable?
  • What are the critical steps and capabilities necessary for customer journey management to succeed?
  • What are the ways that AI, predictive analytics, machine learning, and speech analytics are working to evolve customer journey mapping?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations

  • Recommendations for enterprises
  • Recommendations for vendors

Customer journey mapping and analytics converge

  • Enterprises must adopt an enterprise customer journey approach
  • Several categories along the perimeter are converging
  • Twelve essential capabilities for connecting customer pathways

Static customer journeys evolve into actionable and relevant interaction moments

  • API strategies enable adaptable journeys
  • AI takes users from anonymous to known
  • ML algorithms help close customer experience gaps and predict intent
  • Speech analytics contextualize journeys that start in the contact center
  • AI lifts the limitations on customer segmentation

Appendix

  • Methodology
  • Further reading
  • Author

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