The Pitfalls of Customer Misidentification (and How to Avoid Them)
Businesses want to understand their customers so they can plan investments and deliver personalized experiences at scale. However, most rely on customer data management and unification practices that leave them with an incomplete and erroneous view of their customers. The result is a cascade of negative consequences, which often has the greatest impact on their highest-value customers. In this report, Amperity analyzed several global consumer retail and hospitality brands to uncover the impact that bad data can have on a brand. The results show that businesses are misidentifying 23% of their best customers, individuals responsible for over half of their revenue, and explore the data challenges at the foundation of these errors.
3 Key Takeaways:
- Identities at the foundation are wrong: Brands, on average, misidentify the 23% of customers responsible for 52% of all revenue (i.e. their best customers) using deterministic data matching rules
- So insights are wrong: This means you think you have more customers than you do, but that they’re all worth less than they are, and the people you think are your best customers aren’t
- So campaigns are wrong (and have lower ROI than they should): This leads to customers routinely being put into the wrong segments, targeting the wrong people with the wrong offers at the wrong times.
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