Retail Big Data and analytics have the opportunity to impact margin growth and customer experiences. Retailers already have big data-sized transaction records, in addition to structured and unstructured interaction data. Combining these with supply, market, customer, and social data sources throws up opportunities across a number of areas to extract value for retailers.

Ignitiv’s focus is in the areas of Omnichannel customer experience across stores, e-commerce, mobile and social, marketing effectiveness and optimization of store operations. Ignitiv focuses on the following retail big-data use-cases:

  • Offers personalization
  • Customer Segmentation & Insights
  • Customer Lifetime Value
  • Cross-channel Offers mix
  • Promotion Effectiveness
  • Marketing Mix Optimization
  • Loss Prevention
  • Store Layout Optimization
  • Store Labor Optimization
  • Out of Stock Minimization
  • Customer Conversion

An example of how retail big data is put to use is in this Forbes article. An excerpt:

What is big data in terms of its relevance to the retail industry? In the simplest terms, retail big data offers a means to understand shoppers via myriad digital touch points – from their online purchases to their presence on social networks.

Big data has given Vera Bradley insight into what shoppers want while delivering a return on investment for the retailer/supplier of colorful quilted handbags.The company switched from sending shoppers blanket email promotions to sending targeted offers based on individual shopper purchases.