Brian Gentile examines how business intelligence can help retailers turn big data to their advantage
Large volumes of customer data can help retailers to profile their customers and reach them more effectively across multiple mobile, online and offline channels.
But to be of any use, profiles must be aligned with retail processes, according to Brian Gentile, senior vice president and general manager of TIBCO Analytics
. “It is this alignment that adds value to the customer and can be achieved by feeding information into new interactive experiences.”
Finding the gold nugget
Gentile comments that e-commerce has greatly simplified the process of selling, with the result that fulfillment now represents the main cost factor for retailers. “Like traditional department stores and retail traders, online retailers accumulate large piles of valuable data sourced from a variety of sales channels,” he explains. “This includes the customers’ log-in details, purchase history and payment methods. For over-the-counter trade, we can add the debit and credit card data recorded at the point-of-sale. The challenge then lies in finding the gold nuggets in this mountain of raw data.”
In order to extract useful information about a customer and their buying behaviour from the data pool, retailers must first correlate the data and use these insights to create a profile. With strict legislation in place to protect customers' personal data and with security breaches continuing to undermine customer confidence, so this isn't always a simple process according to Gentile.
“While it can be challenging for brands to capture, manage and process data within traditional database systems, there are large rewards for those who sucessfuly achieve this,” he says. “Trust is actually the retailer's biggest asset and statistics indicate that it costs seven times more to acquire a new customer than to retain an existing one.”
Gentile explains that once all processes are in place, the retailer stands in a stronger position to understand customer buying habits and is therefore able to harness the data to encourage future sales.
“One well-known example is the American retailer Walmart which offers Friday evening special of six-packs of beer and nappies,” he says. “Walmart decided to combine the data from its loyalty card system (providing demographic data about its customers) along with that from its point of sale systems (uncovering where, when and what those customers bought).
“Walmart was then able to spot a correlation between nappy and beer sales. An interesting find to say the least, one suggesting that when purchasing nappies, they also buy a six-pack of beer to enjoy over the weekend.”
For Gentile, this is a prime example of how customer centricity remains the golden rule in retail. “Satisfied customers who repeatedly report a positive shopping experience become loyal customers, recommending the retailer through word-of-mouth marketing,” he explains.
Smartphones as a source of data
Modern smartphones provide user data on a number of levels: GPS data, the IMEI number of the SIM card, data transmitted via UMTS, WLAN, Bluetooth, NFC and increasingly also iBeacon.
“With the right receiver technology, it is easy to identify users and their data, with a generally high level of anonymity, and incorporate this data into the retailer's IT process flow,” explains Gentile.
He gives the example of John Lewis, that recently established its own technology incubator to find products that will shape the future of retail. “It's no
surprise that a number of the finalists are designing products that not only tap into customer data but also create in-store digital engagement,” says Gentile.
He notes that it’s possible to set up in-store micro-networks which allow the retailer to get a precise fix on their customers. “With this added level of insight, customers can be sent relevant offers, e-vouchers, or QR codes, straight to their mobile phone, all based on their customer profile. This can increasingly be done in real time, so the customer can be contacted while they browse the store.
“Retailers are now quickly learning that customer loyalty can be increased if contextual services and offers are provided in what is quickly becoming a more personal shopping experience.”
Is real-time important?
Real-time processing is not absolutely necessary, for Gentile, who feels that in most cases, big data analysis over one week or even one day is sufficient to gain valuable insights. “The key success factor for the retailer is the ability to align all processes and channels with the overarching aim of creating a positive customer experience both during and after their purchase.
“If a customer buys an item online and they subsequently decide that they don't like it, they should be able to go to one of the retailer's stores and get an immediate refund. Many stores still have tough return policies - there is
definitely scope for improvement here.”
Gentile notes that the UK, the 'click and collect' model is gaining in popularity.
“Take Marks & Spencer for example, who now offers these services where customers can drive to their nearest store on a Saturday to pick up the goods they had ordered online during the week,” he adds. “It’s interesting to note that the number of UK shoppers using click and collect is set to more than double by 2017, according to recent research.”
Making shopping fun
The future of retailing lies in entertainment and the key to creating that entertaining experience is to connect processes with the relevant customer data across all channels, according to Gentile.
“Meanwhile, the interlinked data and processes have to be managed by sophisticated policies and rules, and evaluated with intelligent analytics tools,” he says. “Rules engines now come as standard practice with business software
like SAP or Tomax, a retail package.”
Gentile concludes that Business intelligence (BI) tools like reporting, analytics and dashboards are equally important in retail management. “With the right backend infrastructure, retailers can build a much more rewarding shopping experience for their customers.
"And with trillions of bytes of information available for companies to collect about their customers, not to mention suppliers and operations, it is apparent that those brands that invest in big data now are likely to reap the rewards in the future.”