Personalisation is not about mail-merging. It's about understanding your customer well enough to be able to adapt your message to what he or she wants, and to use that knowledge as a platform for increasing customer loyalty, satisfaction and spend.

The greatest success comes when you're able to target customers according to what they do, instead of what they are. Many marketers still rely on demographics for their targeting, because they don't know how to analyse their transactional data.

One frame¬work for defining customer behaviour, using data that you already have access to, is the RFV model.

Recency. Frequency. Value.

It’s hardly a new concept, but one that is more important than ever.

Recency is a measure of when the customer last engaged with you. It could be when they last purchased or interacted with you in some way. The metric is a proxy for that customer's awareness of your brand and a yardstick for the goodwill the customer will feel towards you.

The frequency of orders can hint at how high the customer's demand is for a particular product, and how strongly he or she advocates your version of it. Frequent shoppers are not necessarily the big spenders or the most profitable to serve, so an additional value parameter is used.

Value is the amount your customer spends with you over a given period.

Customers can be clustered according to their RFV values. Your content, offer and targeting should reflect each segment in order to leverage the best response. For example, frequent customers with a recent purchase should receive cross-sell and upsell campaigns. Those who are dormant should be sent re-activation offers, whilst those at risk of becoming Dormant should be targeted with retention offers.

It may sound a bit daunting, so if you need help with RFV segmentation, Please feel free to talk to one of our Data Planning experts.