Webinar: Know Where, Why, What: Big Data’s Role In Predictive And Location Analytics
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The webinar on big data and the role of predictive and location analytics focused on enhancing customer insights through the analysis of social media and retail data sources. Panelists discussed the importance of real-time data and understanding consumer behavior to respond to market changes effectively, emphasizing tools for decision-making and operationalizing insights. Key objectives included improving customer engagement, increasing sales, and achieving competitive advantages in the retail landscape.
Webinar: Know Where, Why, What: Big Data’s Role In Predictive And Location Analytics
- 1. Know Where, Why, What: Big Data and the Role of Predic9ve and Loca9on Analy9cs Webinar Sponsored by #LocAnaly*cs
- 2. Welcome Webinar A6endees #LocAnaly*cs
- 3. Follow This Webinar On Twi6er #LocAnalytics #LocAnaly*cs
- 4. About Retail TouchPoints ü Launched in 2007 ü Over 26,000 subscribers ü To provide executives with relevant, insightful content across a variety of digital medium Free subscription to our weekly newsletter: WWW.RETAILTOUCHPOINTS.COM/SIGNUP #LocAnaly*cs
- 5. Panelists ShiSh Shridhar Global Director, Business Intelligence Solutions Microsoft Simon Thompson Director Commercial Solutions Esri MODERATOR #LocAnaly*cs Debbie Hauss Editor-in-Chief Retail TouchPoints
- 6. KNOW WHERE, WHY, WHAT BIG DATA AND THE ROLE OF PREDICTIVE AND LOCATION ANALYTICS ShiSh Shridhar, Microsoft Simon Thompson, Esri
- 7. Retail has a multitude of devices that generate petabytes of potential insights Monitoring and Mining Social Media Data enables Retailers to enhance customer insights The Retail Big Data Ecosystem Open Data Sources and Internal Sources enables Retailers to better understand customers
- 8. 50b 5 connected devices gadgets per person 2020: The Internet of All Things
- 9. Connected Consumer; Collecting Insight
- 10. Cisco Connected Consumer; Collecting Insight
- 11. Big data is driving us to a tipping point Real-time data creation Multiple data types Large data volumes User expectations Hardware and storage economics Mobility
- 12. Action Knowledge Context Decision Gain Insight then Act On It Know By Trying Leverage Understanding Democratize Decision Making Turn Data into Outcomes
- 13. Visualize Compare Attain Challenge Seeing is Understanding Measure and Evaluate Set and Reward Goals Question and Query Turn Data into Outcomes
- 14. 80 39 % purchase within 10 miles of home or work Place Matters % will visit somewhere unfamiliar
- 15. big data collections merchandise demographic behaviors spreadsheets people analytics social media customer records mobile devices footfall Making Sense of Place traffic point of sale
- 16. Put a Face to Your Customers So you can connect with them better
- 17. Changing Influences and Expectations Social Media Impact Local Promotion Demand Making the Unfamiliar, Normal and Usual
- 18. Place Impressions - Driving Sales
- 19. Enrich Your View + Your Data + Esri Data
- 20. Weather Crime Market Segmentation Growth Trends Real Time Traffic Demographics Media Habits Consumer Spending Landscape Info Sentiment Supply & Demand Occupation Labor Force Market Potential Competition Income
- 21. Sentiment Analysis Social Media Insights Location Based Coupons Indoor Mapping Place Impressions – Understanding Behaviors
- 22. Brand Analysis Fraud and Loss Prevention Compliance Price Optimization Social Media Analytics Risk Analysis Operations IT Integration Business Continuity Workforce Management Advertising Sales Apply Location and Big Data Insight Marketing Inventory Management
- 23. Harness the power of a complete data platform Take action and operationalize Relational Collaboration Non-relational Scalable physical and virtual compute Virtualized storage Corporate apps Analytical Streaming Virtualized networking Windows Server Scale user-driven BI Action over data in real time § Self-service Windows Azure Quality and accuracy § SQL Server § § Office Security, governance, and compliance § Cloud and on-premises Data Search ü Internal & External SAN like intelligence built into OS
- 24. Objectives Tactics Results • Respond quickly to changing customer needs • Increase sales • Attract new customers • Lower costs, improve margins Implemented a comprehensive data warehouse solution for real-time visibility, fast performance and scalability • • • • Deeper customer view Quicker response to trends Faster delivery of critical business data Positioned to meet growing data needs “In this marketplace, we really need to understand our customers and how they’re changing. Because we can react to their changes faster, we’ll be more competitive.” Tom Settle, Assistant Vice President, Data Warehousing, Hy-Vee Anticipate and Act Responding quickly to buying habits for competitive edge
- 25. It’s not the strongest of the species that survives, nor the most intelligent, but the ones most responsive to change. Charles Darwin
- 27. Q & A // Panelists ShiSh Shridhar Global Director, Business Intelligence Solutions Microsoft Simon Thompson Director Commercial Solutions Esri MODERATOR #LocAnaly*cs Debbie Hauss Editor-in-Chief Retail TouchPoints
- 28. Thanks for a6ending! Download and view this presenta*on at: h6p://rtou.ch/bdanaly9cs #LocAnaly*cs