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There’s a schism in modern retailing today that’s headline news: Some companies are creating a virtuous feedback loop with deep customer knowledge, while others are driving profitability into a sea of red with generic discounts and endless sales. 

Nowhere is this more apparent than with online shopping. Cyber Monday grabs media attention and wallet share, notching record sales of $6.59 billion this year. However, online shopping is expected to reach just 8.8 percent of total retail spending in 2018, indicating there’s a lot of room for growth.    

We all know that tech-savvy shoppers value digital shopping for its convenience and discounts, as well as their ability to comparison shop across sites. Consumers are increasingly using smartphones, not desktops or tablets, as their device of choice to browse and buy. Retailers know that it’s never been tougher to connect with time-pressed, screen-overloaded and ad-resistant shoppers.  

Although discounting is integral to industry success, savvy retailers have realized that emerging cloud technologies like advanced analytics can light a fire under their efforts to engage deeply with customers and maximize the profitability of deal days — and every day.  

Here are five strategies many retailers are already using to drive profit with analytics-driven personalization, service, and pricing: 

  1. Map the customer journey. Understand the thought processes and steps your customer takes between considering a purchase and making it. Then remove friction from any step. Case in point: McDonald’s uses data and analytics with Microsoft partner Plexure to shorten customer transaction time and offer customized menus based on past purchases.
  2. Differentiate the shopping experience. Integrate data from multiple sources and leverage machine learning to offer personalized promotions, recommendations and next-best offers. ASOS, a London fashion retailer, uses Microsoft Azure Cosmos DB, a scalable, managed database and analytics tool, to enable real-time product recommendations and instant order updates to its 15.4-million-strong customer base. ASOS offers 85,000 products on its website, with 5,000 new products going live each week, creating a rich digital laboratory for testing offers and measuring demand.
  3. Provide exceptional online service. Customer service is often the bane of retail shopping, souring shoppers on what could otherwise be a good experience. Customers want fast service, in-session answers to questions and streamlined returns. Macy’s provides a virtual agent that uses Microsoft’s Dynamics 365 AI solution and connects to back-end systems to answer one out of every four customer questions — transferring customers to live agents when necessary.
  4. Use IoT to gain in-store intelligence. Retailers can leverage connected devices, beacons and mobile apps to analyze real-time data and time in-store deals to periods and locations when customers are highly likely to buy. Kwik Check, a convenience store chain, uses Microsoft Azure IoT services to entice customers stopping for fuel with real-time, personalized digital discounts that bring them into the store.
  5. Use analytics to optimize pricing. Leading retail companies use analytics based on myriad data sources — such as seasonal and real-time demand, weather patterns, and competitor offerings — to continually and dynamically adjust prices across all their channels. Meijer, a supermarket chain, depends on Microsoft Power BI to analyze individual stores’ sales versus regional performance, which helps internal teams identify localized problems and boost performance on product sales across 80 different departments.

Join Microsoft at NRF 2018 to see how our solutions are powering personalization and advanced decision making in retail. And read our Microsoft Azure case studies to learn how retailers are getting closer to their customers.