Overview
Developed predictive customer segmentation models from transaction and behavioural data for B2C retailers, enabling evidence-based marketing decisions replacing broad-list campaigns with targeted, trigger-driven communications. Delivered customer cluster identification, predictive trigger frameworks for purchase and churn signals, campaign architecture aligned to segments, and measurement models connecting segmentation to revenue and customer lifetime value.
Who This Is For
Online retailers, subscription businesses, book clubs, consumer platforms, or B2C organisations with 50,000-2,000,000+ customers and transaction data spanning multiple years. Investing in email, content, and digital advertising but relying on broad audience targeting rather than data-driven segmentation. Common traits: large customer database with behavioural and transactional history, email and digital marketing managed on broad segments, high unsubscribe rates or declining engagement, and limited ability to predict which customers are likely to purchase, churn, or respond to specific campaigns.
The Challenge
The organisation has a large customer database and years of transactional history, but marketing campaigns are sent to broad segments. High-value customers receive the same communications as inactive ones. Campaigns are evaluated on open rates rather than revenue contribution. Churn is identified retrospectively - after customers have already left. The data exists to predict which customers are most likely to buy, most likely to churn, and most responsive to specific offers. But turning transaction data into actionable segmentation requires analytical capability the team does not currently have in-house.
What We Propose
Customer Data Audit - Assessment of available data and its suitability for segmentation modelling. Segmentation Model - Data-driven customer segments defined by purchasing behaviour, lifecycle stage, value, and engagement patterns. Predictive Triggers - Identification of behavioural signals that predict purchase readiness, churn risk, and category interest. Campaign Architecture - Campaign workflows and content strategies aligned to each segment. Personalisation Design - Email, content, and offer personalisation aligned to segment characteristics and trigger events. Measurement Framework - Performance metrics connecting segmentation-driven campaigns to revenue, retention, and customer lifetime value.
Why It Matters
Revenue efficiency - Marketing investment concentrated on customers most likely to respond. Churn reduction - At-risk customers identified and engaged before they leave. Relevance at scale - Personalised communications based on behaviour, not assumptions. Predictive capability - Moving from descriptive reporting to forward-looking marketing decisions.
Over several years, delivered repeated cycles of content strategy, content production and content localisation in up to 20 European and Asian languages for a global industry association serving the seafood sector. Covered web content across three CMS platforms simultaneously, localisation of reports, infographics, video and complex presentations, and multilingual SEO for organic discovery across priority export markets.
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