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How to Make Your In-Store Data Meaningful

Jul, 10, 2015 Hi-network.com

As an omnichannel retailer, you are probably offering your products to shoppers both online and in brick-and-mortar stores. And, like most retailers, you are no doubt collecting online data and running detailed website analytics that help you track preferred products, pricing, shopper behavior, ratings, and so on.

But are you able to gather these same detailed metrics in your physical store, telling you why shoppers choose your store over your competitor's? How to create a better experience on the floor? Or optimize staffing? Most importantly, are they helping you increase sales?

Until now, the answer to these questions has been "No," simply because the technologies to gather such metrics weren't available. It hasn't been until now, the era of the Internet of Everything, when edge computing is available to gather and analyze the data that gives you a 360-degree view of your store.

Studies show that in-store analytics is a key area of innovation, which may allow retailers to gain up to 11 percent in value. Today's in-store analytics tools should be able to do three things:

  • Integrate data from multiple services
  • Automate data collection processes
  • Analyze data to identify actionable insights

With these capabilities available, you can use the power of your investments in mobile technology, social media, and in-store applications to collect -and understand -more and more customer information.

Join us for an hour on Tuesday, July 14 at 10:00 am PT/1:00 pm ET for a webcast on "How to Make Your Data Meaningful: New Strategies for Improving In-Store Shopping Experiences and Retail Operations." This free one-hour session will discuss:

  • Which in-store metrics generate real-time recommendations to boost operational efficiency
  • How analytics can help you offer hyper-relevant shopper experiences and forge enduring customer relationships
  • Use cases that demonstrate the outcomes of connecting data to decision making

Register Today. We'll see you there!


tag-icon Etiquetas calientes: Internet of Things (IoT) Internet of Everything (IOE) Análisis de análisis datos #Retail BigData operations shopper Dianne Lamendola

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