March 01, 2018, 00:06 / Business

X5 Retail Group wants to better understand customers using big data

The growth resource due to network expansion and rising prices is gradually disappearing Natalya Ishchenko

New sources of growth are needed, since the resource for increasing store space and increasing prices is gradually disappearing / Maxim Stulov / Vedomosti

The largest Russian retailer X5 Retail Group, which manages Pyaterochka, Perekrestok and Karusel, is betting on projects in the field of big data analysis. The retailer has created a directorate that will manage projects in this area, according to a message from X5 Chief Executive Officer Igor Shekhterman to employees. The information was confirmed by a representative of the group.

Big data management is a way to increase sales and profitability of X5’s business, Shekhterman said in a letter: better knowledge about customers will help, in addition, it can be a source of new income through data monetization. There are opportunities to cooperate with telecommunications and digital companies, banks, it is said there. Discussions are currently underway with some of them, says an X5 representative: “We are not ready to disclose the details yet.”

Responsible for growth

The resource for increasing efficiency due to an increase in retail space and inflation is gradually being exhausted, explains a representative of X5, so it was decided to explore new sources of growth, in particular working with large amounts of data. The new directorate for big data projects will report directly to Shekhterman, and will be headed by the group’s director of strategy, Anton Mironenkov.

From March 1, Sergei Goncharov, a native of the main competitor, Magnit, will be responsible for the X5 strategy, who will also join the board of X5, according to the network’s materials for employees. Now the main goal is to update the X5 format strategy and find new growth points “through the development of new directions and technological platforms.” Among these, as follows from the letter, are “omnichannel” trade (using all possible channels for online and offline sales) and marketplaces (an online platform where sales are carried out by several sellers unrelated to each other). Goncharov and an X5 representative confirmed this.

Foreign example

So far, most major Russian players have teams involved in big data projects working within specific business units, says Dmitry Larin, director of retail chains at SAS in Russia and the CIS. In international practice, as a rule, retailers separate this area either into a separate business (for example, Wal-Mart Labs within the Wal-Mart structure) or into a separate department, the head of which is directly subordinate to the general director. This is what Casino, Kroger, Albertsons, Tesco, Coop did, a representative of X5 gives an example.

Technology doesn't lie

One of the largest American grocery chains, Target, assigns each customer a personal guest number linked to his bank card, name or email address. This way the retailer retains the entire purchase history. The company decided to use this data set. Network analysts noticed that starting from the second trimester of pregnancy (from the 13th to the 27th week), women buy unscented lotions in large containers, and at the 20th week they begin to actively buy vitamins. Target began sending them coupons for the purchase of children's products. The New York Times described a related conflict several years ago. One day, in a store near Minneapolis, a man caused a scandal. It turned out that his daughter, a high school student, had been sent promotional offers for maternity clothing, advertisements for children’s furniture, and so on. “Do you want to persuade her to become pregnant?!” – the father was angry. The man apologized. But after some time he already apologized himself. It turned out that his daughter was really pregnant.

Artificial intelligence technologies can transform trade in several areas at once, Moody's analysts noted in a review on February 8, 2018. Networks have data on purchases and customer profiles, which can be used to predict future spending.

Some applications analyze people's behavior in stores and develop individual offers, analysts recall. In the future, Moody's believes, retailers will use artificial technology to predict individual store traffic and sales and decide, for example, what assortment to offer.

Companies that successfully implement new technologies will benefit, Moody's believes: sales will increase, assortment will more closely match demand, and chains will be able to optimize pricing and reduce manual labor.

Big data in Russia

One of the most famous examples of the use of big data in Russian food retail is the experience of Lenta. A special group is working on the project here, says a company representative. The main source of data is the loyalty card; 95% of online purchases are made with it. But the network also takes into account other information about customers, including data from social networks, notes a Lenta representative. First of all, big data is needed to analyze customer behavior and more personalized communication with them, he adds.

Magnit has a separate big data team, says the retailer’s CEO Khachatur Pombukhchan. group also has it The Dixie , adds the group’s IT director Vladimir Muravyov.

At the technological level, this already works well - there is no problem connecting customer personification with big data, argues Muravyov: “For example, in Victoria supermarkets, the My Victoria loyalty program operates based on SAP solutions, its goal is to understand customer preferences.” Dixy, he said, is also looking for ways to monetize big data in collaboration with partners - companies that provide mobile applications, Internet applications, and banks.

Why do networks need technology?

Russian networks have a great desire to adopt the practices of banks and Western colleagues, notes Larin from SAS. But there is also skepticism due to the size of the country, large regional differences, the variety of offers and the size of the networks themselves, he adds: “That is, the mood is “yes, we want to, but is all this technically feasible?”

The growing interest of networks in big data is due to the fact that the market is becoming saturated, crisis sentiment has not gone away, and competition is intensifying, says Larin. Big data makes it possible not only to speed up the processing of information and extract more benefit from it, but also to increase the accuracy of analysis and the complexity of the tasks being solved, the expert concludes. In the meantime, according to him, the goals and objectives for which projects are launched are mainly in the field of marketing and increasing sales: selecting the optimal assortment for each specific store, making the correct display of goods, increasing the accuracy of forecasts and optimizing inventory, making the most relevant personal offers to stimulate demand, etc.

Irina Sinitsyna participated in the preparation of the article