Practical Guide
Plinc’s CRM Data Foundations Guide
A practical guide for marketers, CRM leaders and customer strategy teams who want to understand what good customer data foundations look like, and how to build toward them.
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What’s in the guide?
Customer marketing problems are rarely caused by poor intent. They are usually caused by data that is too narrow, too slow, or too fragmented to use confidently at scale.
This guide focuses on what good customer data foundations actually look like, independent of any specific platform or technology trend. It covers four foundational pillars framed as design principles rather than technical requirements, because the goal is marketing effectiveness, not architecture for its own sake.
Read it to understand:
- The four pillars that determine whether customer data supports effective targeting, personalisation and measurement
- How to identify where weak foundations are showing up as marketing problems in your programme
- Why investment in data foundations pays off now and why it also happens to be what AI readiness requires
Highlights
A quick peek at a few of the findings inside.
- Weak foundations show up as marketing problems. When customer understanding is shallow, behavioural signals are lost and personalisation is constrained by data availability rather than ambition. Those are symptoms of the underlying structure, not the campaign.
- Foundations built for today are the foundations AI needs tomorrow. AI does not create new understanding of customers. It learns from existing data patterns. If that data is incomplete, poorly structured or lacks historical depth, AI systems will reinforce those limitations rather than overcome them.
- Investment in foundations should be justified by present-day value. Future readiness is a secondary benefit. The primary case for stronger data foundations is richer insight, more accurate targeting and faster movement from question to action. None of which requires AI to be worth doing.
See it in action
Learn how Plinc helps some of the UK’s top brands connect, analyse and activate their customer data to drive business decisions and create exceptional customer experiences.
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