Personalisation means adjusting what a customer sees or receives, such as product recommendations, email content, offers or menu suggestions, based on what is known about them. It ranges from using a first name to recommending items based on past purchases.
It works by combining data, such as purchase history, browsing activity, loyalty status, location and stated preferences, with rules or machine learning that choose the best content. The result may appear on a website, in an app, in email or SMS, or at the POS.
Online retailers show recently viewed items and related products. Hospitality venues remember favourite orders, dietary preferences and visit patterns to send relevant offers. Loyalty programs use purchase data to reward the behaviours a business wants more of.
More data does not automatically mean better results. Poor-quality or duplicated customer records produce irrelevant suggestions, and overly specific messages can feel intrusive. Be transparent about the data you collect, follow the Australian Privacy Principles, offer easy preference controls, and start with simple, high-value use cases before attempting something complex.
When it works, customers find things faster and a business gets more from each interaction. It relies on joined-up data, which RetailCare helps connect between POS, ecommerce and marketing systems.