The use of analytics in retail: Focusing on the customer

“Online retail is still on a growth curve,” says Julia Miosga, a retail expert at industry association Bitkom. Around 98 percent of Internet users — approximately 61 million people in Germany — shop online. On the retailer side, 70 percent of companies are also active online or exist solely on the Internet. Digital transformation remains a challenge for retailers, however. That is the implication of the Bitkom study “Shopping digitally — how digitization is radically changing retail”: 77 percent of retailers see themselves as latecomers when it comes to digitization. “Yet so many opportunities await in e-commerce, such as the possibility of gaining new target groups,” says Miosga.

Despite all of the changes that digitization brings with it, the fundamental recipe for success in retail has not changed: the customer must be offered an extraordinary shopping experience. This includes sound information and advice, suitable product recommendations, and good service. Or, as the Bitkom expert puts it: “Retailers must make it their prime objective to focus on their customers.” With more than 60 million potential customers, that is no easy task, considering that every customer would like to be addressed and dealt with personally to the greatest extent possible.

The solution is analytics, which takes advantage of artificial intelligence (AI) to make use of the masses of data that companies are confronted with nowadays. Here too, companies have catching up to do, as shown by the study “Enterprise AI Promise” from the software company SAS: only 24 percent of European companies believe they are equipped for AI solutions and have the necessary infrastructure; 29 percent say they still have no platform suitable for AI. “Particularly for bigger retailers, the use of artificial intelligence is recommended in order to be able to analyze user behavior and present individualized offers,” says Miosga (see examples of analytics in the insurance industry: The competitive factor of analytics in the insurance industry).

With effective analytics solutions, retailers could, for example, show their customers personalized advertising, create individual sales offers, or display relevant new products. When they need support, customers also benefit from an analytics solution, because it significantly improves customer service and customer management (see also Analytics in customer management). And why shouldn’t companies take the opportunity to pre-structure any large amounts of available data that may be of use to their customers? At the online store of mail order company Otto, for example, visitors can be shown customer reviews of products based on keywords. The solution behind that is based on artificial intelligence: an algorithm evaluates the reviews and identifies the most common topics.

The uses of analytics are not limited to the digital world. In brick-and-mortar stores, customer visits generate valuable data every day, and this information can be put to use. The data is collected with sensors that analyze the Wi-Fi signals of customers’ mobile phones as soon as visitors give their permission. This gives rise to heat maps, analyses of the routes taken, and records of how much time people spend at particular points in the store. This has the potential to make physical stores just as transparent as the online shops. Currently, Telefónica is testing this technology in sixty O2 shops.

Whether online or offline, an analytics solution puts large amounts of data from different sources to use and achieves measurable results, because product and service offers as well as customer services can be tailored to each individual customer and structured in the best possible way.

Author: Editorial team Future. Customer.
Image: Montri – AdobeStock