After a two-year stint as vice-president of loyalty and consumer insights at BMO, Rob Daniel is back at Bond Brand Loyalty (formerly Maritz Canada). A long-time employee of Maritz, he returns as executive VP of client services and head of consumer loyalty solutions.
Marketing talked to Daniel about the new era of loyalty card analytics and where it’s headed.
Rob Daniel
What are some new ways to leverage loyalty card data?
The ways companies are leveraging data aren’t necessarily new, but people weren’t in the habit of doing it. Years ago, loyalty marketers had to spend time convincing clients and prospects that the purpose of loyalty is for data rather than just value-add rewards for customers. Today, loyalty card data has more holistic value proposition than it has in the past.
So, some ways to leverage the data include intelligent offers, tailored and delivered communications, and how you can use the pool of best customers to move the rest of your customers. In retail environments, even merchandising and merchandise selection can emerge from loyalty data. All those things are becoming much more prevalent as more marketers recognize that the purpose of loyalty is to collect that data and insert it into your marketing and operations business-decision making.
Why are they recognizing that now?
The biggest reason is our ability to process large volumes of data with real speed – and serve it up in a way that is actionable – has moved forward dramatically over the past three years. As a result of that, we have seen an explosion of people talking about the potential value of data. And marketers are starting to realize some real benefits from [big data], which makes it more than just a fad. You may have seen the teenage sex quote on big data: ‘everybody’s talking about it, but nobody’s doing it.’ There is an element of that, but frankly, we’ve improved our capabilities dramatically.
How can companies better leverage data to improve the customer experience?
One well-documented strategy on customer experience is to give the best possible experience to your pool of your best customers to eventually move the rest. You don’t have to necessarily provide a top customer experience for all segments and all customers within your business: start with the concentration of your best customers. Loyalty programs will enable you to do that really well.
As data is disseminated to more channels, the customer experience is improving
[Secondly], in some cases, loyalty program data is now being fed to front-line representatives so they can enhance the customer experience. For example, with a hotel chain loyalty program, the front line staff are able to address customers with a pool of knowledge that’s in front of them on their screen.
And as data is disseminated to more channels, the customer experience is improving as well. For example, in the past, you may not have connected a purchase online with a purchase in the store and you’re able to do that now really well. So, if I just bought a pair of blue shoes, a retailer can tailor a whole slew of accessories that go with those blue shoes for me online. We do a lot of work thinking about the degree to which that is creepy and the degree to which it’s really cool.
What are the opportunities for loyalty in the mobile channel?
Mobile brings the communication and the loyalty offer very close to the point of purchase. So, when a mobile app picks up that I walked into a mall, and says ‘retailer ABC would like to offer you a coupon,’ that is bringing the marketing conversation and the marketing offers closer to the point of transaction. And that to me is the biggest offering that mobile can provide: real-time offers, real-time rewards, real-time relevant communication.
Where is data analytics headed?
I believe that we are still at a foundational phase of data analytics. Our capabilities have grown tremendously in terms of our ability to process large volumes of data with meaningful velocity. But many of our clients are still replacing old, clunky legacy data warehouses and building new ones. We will shortly enter a phase where the data foundations for most big organizations have been built and are well established. And when that happens, then the energy that was put against building the foundations will be put against creative ways to use data. And that’s when the promise of big data will kick in.
