chapter three

3 Marketing first-party data: crawl, walk, run

 

This chapter covers

  • How to phase your first-party data strategy to maximize your team’s chance of success
  • How to prioritize your use cases to drive quick wins and build organizational momentum
  • How to demonstrate incremental impact and return on investment
  • How to implement advanced applications of first-party data

In practice, one of the most significant challenges in driving a first-party data strategy is change management. Adoption of a first-party data strategy often represents a new way of marketing for many organizations that is intentionally data-driven and forces an organization to confront changes along several dimensions, such as the following:

3.1 Phase 1: remove barriers

3.1.1 Self-serve audience capabilities for marketers

3.1.2 Standardized opt-outs and suppressions

3.1.3 First automated cross-channel audience

3.2 Phase 2: experiment and measure

3.2.1 Automate consistent experiments

3.2.2 Measure marketing performance on any metric

3.3 Phase 3: use predictive models

3.3.1 Incorporate predictive models

3.3.2 Adopt onboarding, retention, and cross-sell journeys

3.3.3 Try multivariate splits

3.4 Phase 4: use AI to create new ideas

3.4.1 Audience suggestions

3.4.2 Journey suggestions

3.4.3 Creative suggestions by channel

3.5 Summary