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Introduction

The second of a two-part report series examining the complex forces impacting consumer data privacy in the AI era. This report focuses on recommendations and best practices including a consumer data privacy segmentation model.

Highlights

  • Consumers have a complex relationship with privacy that needs careful segmentation. Ovum has created a data privacy segmentation framework based on four key profiles: privacy activists, privacy rationalists, the privacy perplexed and the privacy indifferent.
  • Personal data exchanges (PDEs) could possibly disrupt traditional internet monetization models but face challenges in terms of consumer trust, lack of consumer understanding as to the value of their data, and consumers being locked into data super platforms such as Facebook.
  • Consent is presented as a complex, confusing compliance process, and this needs to change with greater transparency and better, more intuitive design. Consumers should also be told in concrete experiential terms how they can benefit from sharing data.

Features and Benefits

  • Understand why it is important to segment consumers based on different data privacy profiles, and learn from Ovum’s segmentation model.
  • Learn how to build a consumer-first, personal data privacy management framework, the components required, and what is involved.
  • Understand the steps that must be taken to win consumer consent to share their data.
  • Learn why AI-powered predictive consent is attracting attention, and understand the limitations.

Key questions answered

  • How can service providers go about creating a consumer data privacy segmentation model?
  • What can service providers do to make consumer encounters with data privacy policies easier?
  • What is the relationship between data privacy and data security?
  • How can AI be leveraged for data security and privacy; what are the developments, tools available?

Table of contents

Summary

  • In brief
  • Ovum view
  • Recommendations for consumer service providers

One size does not fit all: the need for data privacy segmentation

  • Consumers have a complex relationship with data privacy
  • Data privacy activists
  • Data privacy rationalists
  • The privacy perplexed
  • The privacy indifferent

Security and privacy are best treated in tandem

  • Data security and privacy are different but closely connected
  • Communicate your data privacy and security credentials

Empowering consumers encourages data sharing

  • Give consumers more control over their data

Consent must be made friction free for consumers

  • Regulations have tried to make consent more effective
  • But despite new rules, consent is still a burden for consumers
  • More complexity on the horizon
  • Be explicit; consumers must know what they are consenting to
  • Champion transparency
  • Show consumers the benefits of sharing data

Toward consumer-first data privacy management

  • Create data privacy tools and value-added services
  • Personal data privacy management components
  • Leverage AI for data security and privacy
  • The role of personal data exchanges

Appendix

  • Methodology
  • Further reading
  • Author