(A)How retailers can boost their sales through personalized offers

ADVERTORIAL

The reduction of sales for consumer goods is a reality strongly impacting both producers and retailers, and companies have to undertake measures that can counteract this fall. An action of utmost importance for retailers is the focus on a detailed knowledge of all information about customers and their consumer behavior, so as to face competition.

By Fair Value

For making these predictions, retailers have to analyze millions of data and information, whether there are known customers – those registered through loyalty cards in stores’ data bases or unknown customers – whose shopping pattern can be drawn up solely through an overall analysis, by using the history of cash receipts. Such a prediction of the customers’ needs and their expectations from retailers is absolutely vital. The retailers and the producers of fast moving consumer goods traditionally have access to large pools of data regarding daily transactions, with companies collecting data about every SKU sold, to each customer, in each store.

New technologies make it truly possible nowadays to carry out a predictive analysis, and the roll out on the market of the In-Memory SAP HANA technology has dramatically reduced the duration and cost of data processing, by allowing the analysis of an extensive volume of data in real time.

By using the new technologies, combinations of products sold in stores can be determined depending of various variables such as the month, day, time of day, weather, etc.

Thus retail companies can focus on the unknown customers, by analysis the big amounts of data generated by the cash receipts. For instance, the affinity analysis of market baskets provide a deep understanding of correlations between products acquired by each individual customer depending on the season, week or day. By using such information, retailers can adapt their sales and marketing strategies so as to make them as efficient and relevant as possible.

By analyzing real time data of know customers, their exact consumer pattern can be determined and personalized offers can be set up and optimized, which supports gains in sales, profitability and customers’ loyalty.

However, what are the necessary ingredients for the optimum usage of these data?

At first sight, companies need to have the ability to select the relevant information and efficiently manage the multiple sources they originate from. In addition, they need to have the capacity of designing the right models for turning the data into relevant information, and thirdly, the most important aspect, managers have to adopt a program through which the accessed information can be translated into actions.

Retail companies can now benefit from this type of mathematical analysis through the SAP Customer Loyalty solutions, operating on the best platform In-Memory – SAP HANA.

SAP solutions allow the design of complex predictable models in an environment marked by huge data volumes, permitting the usage of sales data to detect key trends on the market regarding the market basket. SAP solutions on predictive analysis are implemented in Romania by the SAP GOLD partner – Fair Value. You can find out more about these solutions at www.fairvalue.ro.