Why Fast Data Adoption is Critical for Retailers

Today’s retail customer is extremely mobile and cross-channel in their path to purchase. They use a variety of touch-points to research and purchase products and services, including traditional web, mobile web and apps, email, chat, social media, online forums, physical stores, and other channels.

For instance, while just 3% of global consumers use smartphones and other mobile devices as ‘preferred’ payment methods when shopping, mobile devices are used extensively by consumers to research products (49%), compare prices with competitors (49%), and to locate stores (31%), according to PwC’s Annual Global Total Retail Consumer Survey published in February 2015. Meanwhile, 71% of in-store shoppers who use smartphones for online research say their device has become more important to their in-store experience, according to Google.

As consumers dart between multiple touch-points during their buying journey, it is critical for retailers to have access to Fast Data–such as current location and behavioral information gathered from a customer’s smartphone, IP addresses, and other forms of customer identification, web pages being viewed, product, or brand sentiment as it’s being shared–that can be used to inform them where a customer is in their shopping process as well as additional in-the-moment information that can be used to deliver the right messaging at precisely the right time.

For instance, geo-location data can inform a cosmetics retailer that a high-value customer has entered one of its stores or a particular aisle where certain products are located. Blending a mix of historical and real-time customer data, including the customer’s most recent purchases along with the products she’s currently viewing, the customer can have a customized offer instantly sent to her smartphone based on the products and price points she’s most likely to respond to.

Fast Data can also be leveraged by retailers to track and respond quickly to consumer behaviors and shopping patterns. For example, a convenience store manager has positioned a discounted laundry detergent in a high traffic area. However, real-time point-of-sale data reveals that unit sales for the detergent are lagging while the fastest-moving products at the moment are non-alcoholic beverages. Acting on these insights, the store manager quickly replaces the detergent display with a high-margin iced tea brand that immediately performs well.

As shoppers increase their use of digital channels to guide their buying decisions, the use of Fast Data can help retailers to intelligently determine the stage that a customer is at in the buying journey and the most effective action that should be taken to support the customer’s experience while improving conversion rates.

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