5.9.3 (HL)—Data and customers

Customer data can improve segmentation, personalisation, service and retention when collected lawfully and used transparently.

Tracking creates value only if the insight changes an offer or interaction; misuse damages trust and may breach privacy rules.

Identify the customer decision, consent basis, data minimisation and expected benefit.

A loyalty app recommends products from purchase history while allowing customers to opt out.

Personalisation does not justify collecting every available data point.

A customer loyalty programme rewards repeat behaviour and records transactions, which can improve retention, targeting and personalized offers; however, rewards cost money, may attract deal-seeking rather than loyal customers, and can raise privacy or fairness concerns. Data mining examines large datasets to discover patterns or relationships that inform segmentation, demand forecasts and decisions. Its conclusions depend on data quality and interpretation: correlation may not show causation, historical patterns may encode bias, and opaque collection can damage trust. Evaluate whether the insight changes a useful decision and whether consent, access, retention and customer benefit are proportionate.