Retention and loyalty are driven by all sorts of things. Brand relationship, value product, cross- sell opportunity in your product base, ongoing need, customer life stage – the list goes on. The best place to start is always in understanding as much about your customers and what makes them tick as possible and then using that data to spot patterns.

Transaction & Marketing Data

You already hold a lot of that data internally across your transaction and marketing systems. Recency, frequency and value of purchase give you a simple starter segmentation to identify your best customers, your dormant customers and everything in between, to allow you to target them with appropriate messaging to drive the behaviours you want. Understanding metrics like propensity to repurchase should hopefully help you better target the message with the right product at the right time, to increase that repurchase rate and drive basket value. 

Operations & Financial Data

Connect in your Operational systems and you can see even more about your customers. Take for example, returns behaviours. Customers can look exceptional when looking at basket value alone. If they’re returning 90% of their purchases however, their shine dulls rapidly. Being able to identify customers who are driving your costs up, as well as the ones who are driving your profit and link them back to their marketing acquisition source, can again have a big impact on who you target and where you spend your budgets. If you can connect your product margin data to your transactions, you can see which customers are driving the most towards the bottom line.

External Data sources

Finally, the best kept secret in data land? Open data… This is FREE data openly available from government and national agencies that you can append to your customer data to understand more about them. Did you know you can get free socio-demographic segmentation from the Office of National Statistics for example? Other data freely available are things like house size and type, number of rooms, lifestage, energy consumption and wifi speed. 

The type of products you sell will obviously drive the type of open data you might be interested in. For example – people in inner city flats are not going to want your 8-seater outdoor sofa set, so target them with the tiny bistro set for their balcony instead! If you’re a charity, indicators of affluence can help shape your messaging to drive significant donation outcomes. Weather data is hugely important to the product mix in an outbound email for outdoor apparel brands. What do you wish you knew about your customers? Is it out there in an open data set somewhere?

Ultimately, you need to define what YOUR best customer looks like, where they came from and how you measure their loyalty/value. Is it purely spend-based? Interaction with the brand? Length of relationship? What data points do you use to measure this and how do you create a segmentation around this definition? Getting all your data in a centralised location to track and segment your customer base is key to building out and automating your personalisation strategy to drive long term value. 

Being able to track your most valuable customers back to their acquisition source(s) is invaluable in supporting strategies to attract more customers like them.