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Modernizing Retail with Point of Sale Analytics

March 15, 2017

Modernizing Retail with Point of Sale Analytics

Retail has become more competitive  than ever. The Internet means consumers aren't limited to local shops, and smartphones let them compare prices even when they're in the store. Retailers need to pursue every possible advantage to beat out the competition.

Big data, driven by point-of-sale (POS) analytics, is one tool giving retailers an advantage. According to McKinsey, big data analytics could increase a retailer's operating margins by more than 60 percent.

There's plenty of data for retailers to analyze. In 2010, retail generated 1 zettabyte (1 trillion gigabytes) of data; in 2014, retailers generated 7 zettabytes of data. Retailers are using data collected from POS terminals and other systems in order to understand their customers, change how they shop and become more competitive.

Analytics for Retailers

Retailers use POS analytics in order to review customers' purchasing activities, such as  learn how much customers are spending and how often they return to the shop. Add in loyalty programs, and there's a lot of information that can be tied to individual consumers. Identifying similar consumers allows retailers to suggest additional items for purchase. Affinity analysis identifies which items frequently sell together, which helps retailers plan promotions and decide where to place items within the store. Another type of analysis can identify potentially fraudulent merchandise returns.

Analyzing POS data also helps retailers manage their inventory levels and make pricing decisions. They can predict which products will sell and which will linger until they are marked down. Data can be analyzed by store location and by store employee as well as by item, supporting operational decisions.

Retailers also can use POS analytics for real-time decision-making. Data can support the decision to extend hours, for example. More than that, real-time analytics can drive interactions with customers who are in the store right at that moment. Stores can use Wi-Fi to send tailored offers to customers and to collect data to feed into analytics.

Retailers need to be careful about the data they collect and the offers their analytics generates so that consumers don’t feel their privacy is being violated. In one well-known incident, Target sent a teenage girl coupons for baby products after their analytics suggested she was pregnant (she was, but the retailer is now more subtle in how it approaches marketing based on analytics).

Analytics for Suppliers

Retail analytics can help  identify opportunities for strategic alliances with suppliers, and many retailers also share POS data with their suppliers, typically through  electronic data interchange files. The suppliers can then use this data in order to analyze sales by location, retailer, time period and promotion, among other possible breakdowns. Once trends are identified, suppliers can work with their retailers in order to market products to the consumer.

Retailers send a supplier data only about their own transactions, but the suppliers can also see the bigger picture and get more information if the retailer sends data to a third-party aggregator. By accessing data through an aggregator's dashboard, suppliers can compare sales and perform analyses against competitive products.

Technology for POS Analytics

Gathering and analyzing all this data requires an environment that can collect, store and process it. Modern POS terminals record complete transaction information. Some retailers build their own data warehouses and use Hadoop in order to create their own analytics; others rely on cloud-based software with prebuilt analytics along standard industry metrics.

Some retailers may want to offer public Wi-Fi in their stores in order to encourage consumers to connect to their website or app. Others will want to implement technology, such as Indoor Positioning System, in order to collect data about customer movements through their stores.

For all retailers, a big challenge is integrating data from all their sales channels, as it's common for online and in-store systems to be isolated from each other. Making sure data is clean and complete, without missing fields, is a common problem. Retailers also need bandwidth in order to upload data frequently so that analytics—especially real-time analytics—are  based on the latest data.

Retailers will need help from their technology partners in order to build an environment that lets them leverage their data for increased sales. Partner with Ingram Micro and leverage our experience to sell big data solutions to your retail customers.