There’s more to loyalty cards than just loyalty. Rewards programs have been popular for years, but a new report from the Sydney Morning Herald sheds some light on exactly why businesses are falling over themselves to sign up customers: the sheer amount of information they can mine.
With 65% of the population signed up to a program, companies like Coles, Qantas and Virgin have access to massive amounts of personal information. That information can turn into actionable insights on what customers want and how they buy – which creates more value for the customer.
That information in turn becomes its own product allowing companies to cross-sell and make targeted campaigns. It gets even more lucrative when companies match loyalty program data with other sources. Qantas has even created its own analytics group for this exact purpose.
As Data Republic’s chief analytics officer Steve Millward says, being able to match against other data sets provides a much fuller picture of a customer’s life. “Most companies are collecting data about their customers just through the lens of how they interact with them, which might only be 1 per cent of their lives,” Data Republic’s chief analytics officer Steve Millward explains.”But there’s a lot of insights from other organisations that can help them get a better insight to their customers.”
Meanwhile, the insurance industry has always used data for creating risk profiles. Now that data is being used in new and exciting ways.According to a new survey conducted by EY, insurers are now using predictive analytics to create more accurate policies. Geospatial data is the most commonly used information, followed by “big data”, “sensors”, “machine learning” and even Facebook information.
Survey author and EY principal Gail McGiffin tells Information Management that “these early stage investments are focused on singular technologies”. Future investments will be focused on combining tech – like using machine learning and predictive modelling to segment out account renewals. “We believe that the greatest business value will be achieved as digital technologies are more integrated,” says McGiffin.
In other news:
As square footage becomes less relevant, retailers with the ability to access the most important data and mine it for actionable insights will become stand out from the pack. A new profile on iconic fashion brand Burberry in Forbes gives examples of how the company is doing just that.
Customer service agents in stores use mining and sharing data through loyalty and reward programs to create customised recommendations – both online and in stores. Products are fitted with RFID tags to communicate with smartphone apps, providing information on how the products were produced – or even tips for how they can be worn. Chatbots are now a huge experience, with customers able to even order an Uber to a Burberry store simply by chatting.
Image recognition technology and machine learning is also being used to crack down on counterfeiting. With these elements and more, Burberry is standing out as an example of how retailers can survive the consolidation of physical retail and build its success on something new: data-driven personalisation.
Worth a read:
Raj Jetty is an economist with a huge amount of pedigree: including a recipient of the John Bates Clark Media and 2012 MacArthur fellowship. His introductory course on big data and how it can solve social problems is now completely online, and completely free.
Keeping all your data, knowing what questions to ask and having to hire dedicated data teams: just a few myths about analytics that Information Week has tried to dispel in a new article.
Until next week.