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Value-driven design

As explained in First-Party Data Activation

An approach to designing data and marketing initiatives by prioritizing representative use cases according to their expected business value.

Value-driven design prioritizes a few representative use cases that demonstrate business value before expanding a first-party data program. section 3.1

Choose initial use cases by comparing two dimensions:

  • Value: the business impact of delivering the use case, especially where existing approaches perform poorly. section 3.1
  • Level of effort: the availability of the first-party data needed to fulfill the use case. section 3.1
  • Launch two or three focused use cases before generalizing data models for broader operational scale. section 3.1

Travel e-commerce roadmap

A travel e-commerce company aligned data and marketing teams around churn and recent-purchaser use cases, testing ads and messaging at scale and launching within two quarters. section 3.1

How First-Party Data Activation covers it

How deep it goes
Explains selection through business value and data availability, stopping short of detailed operational scalability.
Examples
Uses churn, recent purchasers, SQL audience queries, ads, messaging, and a travel e-commerce roadmap.
What it assumes
Assumes identifiable marketing objectives and access to the first-party data required for candidate use cases.
What you can do after
Apply it by selecting and launching representative use cases that demonstrate value before broadening data models.
How it connects
Connects first-party data strategy with use cases, data models, marketing objectives, and business impact.
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This explainer was generated by Manning's knowledge graph from the text of First-Party Data Activation. The section links point to the parts of the book it draws on.