Change management guides people through the organizational shifts required to use first-party data effectively. Those shifts can affect team focus, marketing processes, and measurement—not just technology. section 3.0
A phased approach can build capability while delivering value along the way:
- Remove barriers by giving marketers self-serve access to first-party data and enabling initial use cases. section 3.0
- Experiment and measure with standardized methods to identify which efforts improve outcomes. section 3.4
- Build on those foundations with predictive models and multichannel customer journeys. section 3.4
Table 3.1 Summary of key recommended stages to drive first-party data adoption
| Stage |
Key focus |
Main actions |
Outcome |
| Phase 1: remove barriers |
Establish self-serve audience capabilities for marketers |
Enable marketing teams to access and use first-party data directly, create initial use cases, and integrate audience activation tools |
Faster campaign execution and early wins to justify investment |
| Phase 2: experiment and measure |
Implement standardized experimentation and measurement methods |
Introduce controlled experiments, establish performance metrics, and automate cross-channel testing |
Systematic improvement of business outcomes |
| Phase 3: Try advanced methods |
Employ predictive segmentation, customer journeys, and multi-variate experiments |
Incorporate ML-driven predictions (e.g., churn), create multi-step journeys, and scale creative tests |
Improved marketing effectiveness with proactive, smarter targeting |
Compare each adoption phase by its focus, actions, and intended outcome. section 3.0
Changing marketing roles
As generative marketing evolves, marketers may move from creating campaigns manually, to approving AI-generated suggestions, and eventually to advising AI systems. Clear principles can help teams navigate the transition. section 9.3.5
