Applied Intelligence Briefing
Edge Analytics / Applied Intelligence BriefingCase study
Customer segmentation for targeted retail marketing
A leading independent UK garden-centre operator transformed loyalty and transactional data into distinct behavioural segments, enabling more relevant customer communications and offers.
- Client
- Large UK garden centre
- Method
- Customer segmentation
- Purpose
- Targeted marketing
Behavioural segmentation for more relevant customer engagement
The business challenge
How can loyalty data become a practical framework for targeted marketing?
Context
The retailer's loyalty scheme generated valuable customer and transaction data, but the business wanted to move beyond recording purchases to understand behaviour, engagement, value and opportunities for growth.
Requirement
Distinguish customers by recency, frequency and spend; reveal product and seasonal behaviours; and translate the resulting insight into practical marketing activity with improved ROI.
Method
- 01
Behavioural measures
Analysed recency, frequency and spend, together with product and seasonal purchasing patterns.
- 02
Customer groups
Segmented customers by engagement and value, profiling regular shoppers and less-frequent visitors.
- 03
Operational delivery
Designed the segmentation for implementation within existing customer-management and marketing processes.
Outputs & significance
Actionable customer segments
RFM
Implemented segmentation
Assigned every loyalty customer to a segment based on observed purchasing behaviour.
Customer understanding
Clarified differences in value, engagement, product preferences and seasonal purchasing.
Targeted opportunity
Enabled more relevant campaigns and identified ways to increase frequency, spend and loyalty.
Significance
Marketing shifted from broad campaigns to behaviour-led engagement
RFM (Recency, Frequency and Monetary value) segmentation converted existing loyalty data into an operational framework for ongoing targeting and growth.