For many marketers looking at the world of data, building customer loyalty post-purchase probably feels like pay-back time.
You’ve done all the hard work acquiring prospects and establishing a relationship with them. You’ve nurtured them along their path to purchase, enriching the data you hold about them along the way. Now, finally, they’ve become customers and you can concentrate on straightforward loyalty conversations drawing on all that first-party data you’ve collected.
Would now be a bad time to remind you that you don’t know how much you don’t know?
Unknown unknowns
Talking to potential clients, it’s striking how many don’t realise the extent of the gaps in their knowledge, or the ways that exist to fill them. Take the automotive sector, for example. Car manufacturers build propensity models based on their CRM data to predict when a customer will be back in the market for a new car. But we work with car-buying comparison site Carwow, and by using their data, we’ve shown a manufacturer we work with that their propensity models under-estimate the number of buyers in-market by 25%. These people are configuring cars on Carwow, but they’re not showing up as customers the manufacturer should be emailing just yet.
That same data can also be used to validate whether the customers their model predicts should be back in-market actually are. What’s more, on the basis of knowing which cars they’re configuring – theirs or a competitor’s – they can tailor an appropriate communications strategy.
We see a similar pattern in consumer electronics. People shopping for a new TV don’t necessarily start on a retailer’s site. They might begin their research with the TV manufacturer, investigating the latest TV technology. By the time the retailer sees one of these buyers they could be well-educated and already part-way through the buyer journey. But if data can be shared from the brands’ sites, the retailer has far more insight into the customer journey, allowing the next stages to be optimised delivering a better consumer experience and ultimately a better outcome for both the manufacturer and the retailer.
Known unknowns
Even brands that hold very little first-party data about their customers – such as those in the CPG sector – can fill in the gaps through data partnerships. Recently we’ve started to see the phenomenon of dwindling loyalty. A number of factors, including price sensitivity and in-store shortages driven by Covid and Brexit, are leading shoppers to swap the brands they previously favoured for cheaper or more readily available alternatives.
In this situation, having retailer data that shows changing shopper habits week-on-week or month-on-month is invaluable. So we do a lot of work with CPG brands overlaying retail purchase data on the data in their CRM to understand the performance of their brand versus the home brand and competitor brands. Then they can start making better marketing decisions.
Unknown knowns
This leads us back to the other great imponderable; what you don’t know you know. In other words, what data is held in silos in other parts of your organisation, which no-one’s told you about? In particular, do you know what data your CRM team holds? Integrating CRM data is significant because it allows you to link online and offline touchpoints, but I’ve met clients that were so siloed the CRM team didn’t even know who the digital team were.
This needs to change. The growing emphasis on first-party data has pushed email back to the top of many marketers’ agenda, but there’s also increasing concern that email can be intrusive. As one client told me, “there’s only so many emails I can send to our customers before they switch off. ”
Instead, marketers need to build customer-centric campaigns that recognise where each person is in their journey, what their history is with the brand, and what they need to know at that precise moment in order to move them on to the next touchpoint. That means choosing which channel to use not on the basis of what’s easiest for you, but on what works best for the customer right now. And that requires a data strategy that brings together all the customer data from across the organisation, as well as from external partners.