ShiSh Shridhar. Global Director, Industry Solutions Retail Sector Microsoft Corp. Cloud Computing. Big Data. Mobile Workforce. Internet of Things

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1 Using Data to Create Amazing Customer Experiences ShiSh Shridhar Global Director, Industry Solutions Retail Sector Microsoft Corp Mobile Workforce Big Data Cloud Computing Internet of Things 1

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3 Listening to the voice of the customer Sales Forecast in 1999 What Really Happened Traditional Cameras Digital Cameras Traditional Cameras Digital Cameras

4 Democratization of data Retail has a multitude of devices that generate petabytes of potential insights Monitoring and mining social media data enables retailers to enhance customer insights Open data sources and internal sources enable retailers to better understand customers

5 Cortana Analytics Suite Transform data into intelligent action

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7 ML STUDIO API

8 Telemetry Data Analysis Buyer Propensity Models Social network analysis Predictive Maintenance Web app optimization Churn Analysis Natural resource exploration Weather forecasting Healthcare outcomes Fraud detection Life sciences research Targeted Advertising Network Intrusion Detection Smart meter monitoring 8

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10 Backed by the trillions of bytes' worth of shopper history that is stored in Wal-Mart's computer network, the company could "start predicting what's going to happen, instead of waiting for it to happen The experts mined the data and found that the stores would indeed need certain products - and not just the usual flashlights "We didn't know in the past that strawberry Pop-Tarts increase in sales, like seven times their normal sales rate, ahead of a hurricane. And the pre-hurricane top-selling item was beer"

11 Delight customers with the right offers Use technology to determine what customer would purchase next Objectives Give customers a better experience and selection Understand what customers are looking for based on online search Tactics Combine online and instore transactional and behavioral data to predict what products customers would be most likely to purchase next Results Customers have more personalized choices Targeted campaigns Better inventory forecasts We are especially pleased that our analysts can focus on the results and not worry about the complex algorithms behind the scenes Andrew Laudato Pier 1 Imports

12 Business Value Geographical visualization of the outcomes by store location Differentiated lift by channel modelled Correlation to temperature showing the sales correlated to temperature changes Ability to load millions of data points on the map if desired

13 Predicting what customers will order Use technology to streamline the ordering process Objectives Make recommendations to customers based on demand patterns Improve ordering process by predicting what customers would order Tactics Use predictive analytics to determine what customers would need based on patterns. Use recommendations online as well as in call centers Results Quicker and easier ordering process for customers Better inventory management With Azure Machine Learning, the wow factor is huge. Customers are amazed that we can predict so accurately what they need. Mushtaque Ahmed COO JJ Food Service

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21 What is the Internet of Things? Things Connectivity Data Analytics

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25 Track shelf inventory in real time 1 Track your products through shelf sensors, RFIDs, price tags or Wi-Fi Way Finding. As inventory is removed from store shelf, store info updates in real time 2 Configure the system to notify an employee to restock when inventory drops below a preconfigured range 3 Access real-time inventory data on your devices 4 Track inventory end-to-end from the manufacturer, through shipments and stocking, to the floor and to sale

26 Gain valuable real-time insights into customer behavior 1 Use location tracking on carts, cell phones or video cameras to see what items customers are viewing 2 Compile customer viewing info with billing info at checkout to track purchases and provide recommendations 3 Use this info to analyze store layout and reposition inventory 4 Combine customer in-store purchasing data with online purchasing data to get a holistic view of customer interests + =

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28 Kohl s Delivering enhanced shopping experiences to customers Objectives Increase customer service and personalization Grow perception of innovation Tactics Connected Fitting Room pilot in stores Associate productivity with tablets Assisted selling kiosks in stores Guided selling for mobile devices Results Increased insight into customer likes Improved sales performance by equipping associates with easily accessible information Extended support for customers through immediate catalog access 28

29 Shopperception: In Store Engagement Analytics

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31 The VMob powered McDonald s Japan app: Revitalize the app Personalized promotions Personalized mobile coupons Targeted push messaging Closed Loop Analytics Engine

32 Microsoft Power BI Dashboard. With full sales data gives a live, revenue focused view of sales and marketing activity from first impression, to app engagement, right through to point of sale. *This is not actual Japan data. Actual Japan data is confidential

33 TAQTILE TQ1 Mobile Content Management Deliver the relevant content to the right person at the right time. TAQTILE Key Features: Campaign Management In-app/Push Messages Segmentation/Targeting Geofencing/geotriggers Personalization Surveys Interval Control On/off premise support Results/Analytics 12

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35 Cnova Apps in Windows Store TAQTILE Extra Pontofrio Casa Bahia

36 SPONSOR GOLD OmniChannel Customer 361 Enriqueciendo los canales con las últimas tecnologías

37 Next steps Leveraging technology to achieve operational excellence across the value chain? Business Outcome Workshop 1:1 customer workshop prepared and led by Microsoft Services to scope innovative solutions and next steps. Deeper Solution Session Explore any of our solution areas in a more detailed session Private Preview & Customer Focus Groups work directly with engineering teams on innovative new capabilities Proof of Concept with support of key engineering teams and partners

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