Go Big or Go Home: How Big Data Can Bring Big Sales

By Mark Ledbetter — July 16, 2012

There's no shortage of real-time customer and interaction data in today's retail environment. But what do you do with it and how do you apply this data to improving your business? Retailers that understand how to tap into Big Data can open new doors, new revenue streams, and new business models that were once unimaginable.
 
Spotting "Window Shoppers"

A key challenge in retailing has always been detecting and measuring lost sales. Who was in the store or on the website, and what did they look at and not buy? If a retailer can understand the actions that didn't result in a sale, they're more likely to know if they need to adjust product selection, pricing, or some aspect of displaying and promoting their offerings.
 
This type of information has been very difficult to track, but Big Data technologies such as Hadoop and in-memory computing are ideally suited to collecting and analyzing unstructured data types like the web logs that show the movements of every customer though an internet storefront. Web traffic data can then be combined with existing business intelligence applications and sales data to provide new insights.
 
For example, retailers can compare the volume of website traffic for a given product versus number of sales of that product. You'd expect a correlation between web traffic and sales – consumers find the product they want, then they buy it. But if you find a lot of web traffic and few sales, something is wrong. It's a signal to keep the product, whereas in the past, it may have been discarded due to low sales. Now you just need to confirm the product is competitively priced, has a compelling and informative presentation, an array of colors and sizes, and all other aspects that are required to incent the customer to make that final, and most important, step: the purchase.
 
What about physical stores? Is it possible to use the same techniques to better understand shopper behavior? Yes. Some leading-edge retailers are now using these new technologies to analyze video from in-store camera systems and create mappings of customer foot traffic throughout the stores. This Big Data stream is then combined with sales data to create new applications that help optimize store layout and product placement.
 
Staying Ahead of Traffic

In the past, dispatchers with clipboards and two-way radios would monitor daily customer deliveries and come up with workarounds to deal with traffic congestion, weather, construction and last minute rush orders. Not today. Now, retailers are using Big Data and predictive analytics to better utilize distribution networks and delight customers with improved on-time deliveries.
 
Radio transmitters on trucks along with bar codes or RFIDs on each package are combined with real-time mapping and traffic information to allow dispatchers to better monitor and visualize the progress of every delivery.

Literally, in the first minutes of the day, after just one or two deliveries, a predictive analytics application is already providing the dispatcher with revised estimated delivery times for the remaining orders based on past delivery data and current real-time traffic data on every truck's route. If a dispatcher predicts a truck will miss a delivery, they can take immediate corrective action, such as re-routing a delivery or rescheduling with a customer.

This new ability to provide organizations with easy-to-use applications that map incoming customer orders, real-time traffic and current truck location information has allowed leading organizations to do a much better job of meeting customer expectations and ensuring high operational efficiency in their distribution network.
 
The Road Ahead for Retail

The holy grail of retail has been to anticipate what consumers need even before they realize they need it. There's no better way to beat the competition than to make an attractive offer and get a customer's business before they even realize they need your product, or are considering evaluating alternatives.
 
Take printer cartridges, for example. There's nothing worse than having to print a boarding pass with the taxi waiting outside and realizing you're out of ink. Today, office supply retailers are able to track purchases of customers' in-store credit cards and rewards cards and, based on purchase history, anticipate when a consumer might need to reorder a product. Marketing can send an email offer for printer cartridges as well as an accompanying promotion for paper, with a guaranteed delivery time of 24 hours. Similar techniques are being used by travel companies (Time for your annual vacation?) and auto dealers (Looks like your car is due for service.) as well as other consumer-facing organizations.
 
Key to this whole-view into customer data is both the applications and the database. While storing and accessing Big Data has been commonplace in the financial, government and telecom markets for years, retailers are just now realizing the potential. Using tightly integrated systems can provide optimal storage for massive data and efficient retrieval and reporting.
 
Big Data is here to stay and it's only getting bigger. How retailers use it to change their business, how they take advantage of it to grow sales, and how they leverage it to reduce the bottom line, is only limited by their imagination.
 
Mark Ledbetter is Global Vice President for SAP Retail.

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