The use of analytics in retail: Better advice at the point of sale

“The use of analytics at the point of sale is not limited to the digital sphere,” emphasizes Dirk Schäfer, Director of CRM Analytics. “The POS can be an online store accessed by the user via a browser or app, or it can be the traditional bricks-and-mortar branch.” That’s because valuable data is also generated at the terminals and checkouts during customer visits to traditional stores, where a large percentage of purchase decisions are made. It is therefore all the more important that retailers arrive at a data-driven working and decision-making culture at the POS in their stores too. “I think a lot will happen in this field over the coming years in terms of optimizing the customer journey on the basis of customer data and improving the shopping experience for consumers,” explains Schäfer. The question is whether the industry is prepared to implement this.

Companies keen to resolutely exploit these new opportunities should seek expert support and advice when designing and implementing these kinds of projects. Companies such as Arvato CRM Solutions utilize the available data using powerful analytics solutions for the retail trade based on artificial intelligence (AI), and can – depending on the retailer’s wishes – provide updated analysis results and recommendations for action in real time, hourly, or daily.

Retailers have some catching up to do

Online retailing continues on its strong growth path, but the digital revolution also presents one major challenge for online retailers: 77 percent of retailers see themselves as latecomers when it comes to digitization, as demonstrated in the Bitkom study “Digital shopping – How digitization is shaking up the retail world” (available in German only).

And there is still plenty of untapped potential in the offline world, especially in Germany. “In food retailing, for example, there is a huge number of checkouts producing data,” explains Schäfer. In many cases an enormous volume of data goes to waste and is not used to tailor the customer experience. Loyalty cards and bonus programs, through which such personal data is gathered, still have a much lower reach in Germany than in other European countries: “German retailers often give out non-personalized coupons at the checkout. It would be possible to make that much more personalized,” says Schäfer. Plus there is the question: How do you achieve greater acceptance among consumers? “The people participating in these kinds of programs are asking themselves what they’re getting out of it. Using analytics, you could develop targeted special offers that are really tailored to individual consumers and that are relevant for them – instead of handing out special offer coupons with a ‘scattergun’ approach.”

Customized value for consumers

A range of options going in different directions are currently being considered. One of these options is to establish partnerships. “Imagine you’re doing your food shop and you’re given a discount coupon for the petrol station across the road,” says Schäfer. This kind of offer works best at the POS itself, at the checkout and in real time. “Because no one goes back into the store just to get an item for which they’ve been given a discount for their next shop.”  Some German food retailers also use loyalty card formats that do not gather and store personal data (such as addresses, phone numbers, etc.). “This customer approach could also be supported with analytics,” says Dirk Schäfer. This would make an optimized issuance of personalized discount coupons based on the customer’s current shopping basket a realistic prospect.

Added value in customer advice

However, it could also be possible to optimize the customer experience through the use of analytics in a number of other sectors, especially in areas where – unlike food retailing – customers require more advice and the product is more expensive, e.g. electronics, telecommunication, fashion, and cars. There is a trend in car dealerships towards using mobile devices such as tablets, which the salesperson uses to configure the prospective customer’s dream vehicle down to the last detail. If the salesperson in this situation had further information based on real-time analytics solutions, e.g. previous vehicles and preferences, those could also be included in the customer dialog. The sales consultation can thereby be improved, and the salesperson can tap into significant upselling potential.

That is all the more consequential since the online pre-purchase preparation process, which generates data, is also becoming increasingly important. According to ECC Köln’s 2017 study “Cross-channel in upheaval,” almost 40 percent of cross-industry purchases made in bricks-and-mortar stores are researched beforehand in online stores; this figure rises to more than half among so-called “smart natives.” If this data were to be utilized by powerful analytics solutions and made available in sales talks, a huge range of possibilities opens up.

Interleaving data gathered from online and traditional stores in this way can also open up extensive synergies between offline and online business. The analysis of this data leads to improved customer understanding, which can then be used to better exploit potential additional sales, for example through target-group-specific communication measures.

Individual and personal

The fundamental recipe for success in retail has not changed: The customer must be offered an extraordinary shopping experience – be that online or in traditional stores. Analytics solutions help retailers to design and individually customize their portfolio of products and services, customer advice, and customer service.

Author: Editorial team at Future. Customer.
Image: ©sdecoret – AdobeStock