Dis-Chem Pharmacies has introduced a shopper personalisation and targeting offering that will elevate its ability to develop shopper insights to provide significant benefits for customers and suppliers.
Dis-Chem will be able to expand and scale its ability to power engagements across its media channels and deliver benefits for its customers, its brand partners and suppliers, and its business.
Saul Saltzman, executive director at Dis-Chem says the further development of the group’s customer-focused personalisation programme will allow it to achieve personal customer engagements at scale, across channels and in real-time, and will increase the impact of its joint marketing activities with suppliers. The technology optimizes Dis-Chem’s personalization efforts by predicting demand and understanding the preferences of each customer across all brands and categories.
“This innovation illustrates our commitment to customer-centricity by leveraging our well-entrenched Benefit Card loyalty programme. We can now give our 6,8 million loyalty card customers the individualised offers they need, at the right time and on the right channels. Shoppers will benefit from in-depth personalisation and targeting via bespoke special offers tailored to individual profiles and shopping patterns that will create engagements that matter for them by delivering content that brings them true value,” he says.
Suppliers can access deep and broad data, giving them information and insights across several categories and criteria. Shopping patterns can be tracked by various metrics: purchase patterns including detail of frequency and size and make-up of basket; region, demographics and ages; and shopper responses to promotions across categories or brands.
“This innovation gives us an in-depth and thorough understanding of our shoppers with the ability to drill down into granular shopper and customer detail. Our data is simple and user-friendly and brings a unique opportunity to grow categories through supplier partnerships based on the integrity and depth of the data we can extract,” Saltzman says.
