Recency-Frequency-Monetary (RFM) analytics is useful as a measure of customer behaviour against purchases, browsing and engagement. Using Customer personas is complementary to RFM in adding value to intelligent customer segmentation.
Customers leave their footprints on the websites via their browsing, product reviews, service level feedback and last but not the least purchases. Further the catalogue of products and their categories bought, browsed tell a thing or two about the kind of a person as well if we listen closely. If a person has been recently browsing baby products, chances are that he's probably had a new addition to the family. If a person has gifted first time on your site to his brother/sister on the anniversary, a new persona of "gift-giver" emerges. Karl Worth, blogging at Chief Marketer calls this RPI over RFM, where the intent to purchase gives contextual understand of the 'why' of the purchase decision.
For example – following are some of the personas that a person could be exhibiting in your store:
1) Middle Aged Fashion Photographer
3) Family person
4) Outdoor person
Most of the times, it could be that all these distinct personas could be exist within a single individual. These personas give interesting titbits about the customer that can be leveraged for campaigns around birthdays, anniversaries that can have a booster shot by having them into the mix. Combining these avatars with behaviour in terms of purchase RFM, browsing RFM, and engagement RFM would give you a treasure trove of information, about the customer for effectively segmentation and targeting in you marketing campaign
The personas built can be contextually used to send birthday promotions, anniversary promotions. More value can be gained by leveraging this with the product category based browsing RFM, engagement RFM to look into those categories where the person has shown interest lately and improve the chances of conversion. In fact, to venture into the real analytics that gives value, upon clustering the customer into groups with the RFM scores, personas can be used to predict customer behaviours in addition to the typically tried and tested customer demographics information.
Continue building personas Once these personas are used for segmenting the list of customers for targeted promotions, it's not the end. As customer's interests change, personas keep changing as well. Keep a close watch on how they perform and evolve as their online behaviour changes. More on this in the next one.