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Rtp webinar-fujitsu-cisco-08-9-2016-final deck-opt (1)

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For today’s retailers, a connected mobile experience helps to provide delightful and personalized customer experience through actionable insight from the store. Listen to Fujitsu’s Joe Hnilo and Cisco’s Ashees Sinha on Aug. 9th, 2016 at 1 PM ET as they discuss how to deliver the best in-store customer engagement experience: http://rtou.ch/2am3zM3

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Rtp webinar-fujitsu-cisco-08-9-2016-final deck-opt (1)

  1. 1. #AnalyticsInStore Questions, Tweets, & Resources Submit your questions here Download today’s resources Join the conversation #AnalyticsInStore
  2. 2. #AnalyticsInStore Follow This Event On Twitter #AnalyticsInStore Retail TouchPoints: @RTouchPoints Debbie Hauss: @Dhauss Fujitsu: @interstage Cisco: @CiscoRetail
  3. 3. #AnalyticsInStore About Retail TouchPoints ü Launched in 2007 ü Over 34,000 retail subscribers ü To provide executives with relevant, insightful content across a variety of digital medium Sign up for our weekly newsletter: www.retailtouchpoints.com/subscribe
  4. 4. #AnalyticsInStore Panelists MODERATOR: Debbie Hauss Editor-in-Chief, Retail TouchPoints Ashees Sinha Practice Architect, Digital Transformation Cisco Systems ashees@cisco.com Joe Hnilo Vice President, Software Business Fujitsu America, Inc. joe.hnilo@us.fujitsu.com
  5. 5. Ashees Sinha Practice Architect, Cisco Systems August 9, 2016 Digitization of Customer Experience through Cisco Connected Mobile Experiences (CMX)
  6. 6. 6© 2016 Cisco and/or its affiliates. All rights reserved. A Mobile World 1 Cisco® Visual Networking Index (VNI) Report Mobile Devices Increase to Over 10 billion by 20181 Organizations Looking to Monetize Wi-Fi Wi-Fi as a Platform to Deliver Services
  7. 7. 7© 2016 Cisco and/or its affiliates. All rights reserved.
  8. 8. 8© 2016 Cisco and/or its affiliates. All rights reserved. What if You Could…? § Send location and dwell-time notifications? § Offer personalized promotions? § Access customer analytics? § Show maps with featured attractions? § Deliver personalized third-party advertising? § List nearby amenities? § Reduce wait times, improve traffic flow? § Provide gate directions? § Deliver third-party advertising ? § Offer way-finding patient apps? § Simplify onboarding? § List nearby services? § Improve safety and security? § Provide intuitive campus maps? § Enhance tours and stadium experiences? Retail EducationHealthcareTravelHospitality Consumers StudentsPatientsPassengersGuests
  9. 9. 9© 2016 Cisco and/or its affiliates. All rights reserved.
  10. 10. 10© 2016 Cisco and/or its affiliates. All rights reserved.
  11. 11. 11© 2016 Cisco and/or its affiliates. All rights reserved.
  12. 12. 12© 2016 Cisco and/or its affiliates. All rights reserved. 90% Of shoppers use their phones while in store** 96% of shoppers prefer to shop in locations with free Wi-Fi* 71% Of shoppers say their device has become more important in their instore experience Shoppers Rely on Mobile Devices While Shopping “Shoppers want to stay connected while they’re here, which makes mobile access the key.”
  13. 13. 13© 2016 Cisco and/or its affiliates. All rights reserved. What it Brings to Your Business Customer Engagement and Insights 25% of Customers Buy on Their Mobile Device While in Store Lift in conversion Extends digital investments into the store New source of shopping insights Test store layouts and fixtures with more precision Cater to preferences of various demographics Increase effectiveness of associates Increase customer loyalty “Knowing our customers is key to being able to engage and inspire them...Understanding their behaviour in the store is key to our multichannel leadership strategy.”
  14. 14. 14© 2016 Cisco and/or its affiliates. All rights reserved. Companies that make extensive use of customer analytics • 126% profit improvement • 23X more likely to outperform competitors in new customer acquisitions • 21X more likely to migrate customers to profitable segments Customer Insight drives Customer Experience 86% of Consumers Will Pay More For a Better Customer Experience CashierCashier Dressing Rooms Jewelry Junior's FormalWearShoes EmployeeOnly Men's Boy’s Girl’s Women's Suites Belts Cosmetics Sleepwear Swim Wear BeddingKitchenSeasonal Low Traffic Low Product Demand Overcrowding No Shoppers, change display? Shoppers not reaching interior High Traffic, Need more Associates
  15. 15. 15© 2016 Cisco and/or its affiliates. All rights reserved.
  16. 16. 16© 2016 Cisco and/or its affiliates. All rights reserved.
  17. 17. 17© 2016 Cisco and/or its affiliates. All rights reserved.
  18. 18. 18© 2016 Cisco and/or its affiliates. All rights reserved.
  19. 19. 19© 2016 Cisco and/or its affiliates. All rights reserved.
  20. 20. 20© 2016 Cisco and/or its affiliates. All rights reserved.
  21. 21. 21© 2016 Cisco and/or its affiliates. All rights reserved.
  22. 22. 22© 2016 Cisco and/or its affiliates. All rights reserved.
  23. 23. 23© 2016 Cisco and/or its affiliates. All rights reserved.
  24. 24. 24© 2016 Cisco and/or its affiliates. All rights reserved. Capabilities: Traffic Quantification Hyper Awareness Informed Decision Making ▪ Understand shopper behaviors ▪ Connecting silo’d customer data sources ▪ Insight into who did and did not make a purchase during visit ▪ Identify highest value customers Business Challenge ▪ Traffic Quantification ▪ Tailored Brand-Specific Guest Wi-Fi Experiences ▪ Comprehensive Conversion Capture ▪ Labor Optimization ▪ Loss Prevention Business Capability Enabled ▪ Greater understanding of shoppers desires and needs ▪ Deliver differentiated and relevant engagements ▪ Provide relevant and world class experiences each visit ▪ Personalized attention for high value customers Business Outcome Fast Execution
  25. 25. 25© 2016 Cisco and/or its affiliates. All rights reserved. Use Case: Way Finder ▪ Create more compelling shopping experiences ▪ Differentiate between regular shoppers and loyal/preferred ▪ Deliver relevant ads based on known customer preferences ▪ Avoid lines for check-out Business Challenge ▪ Enable customers to navigate within the mall ▪ Integrate location and big data analytics ▪ Drive loyalty with location-based capabilities ▪ Insert targeted ads onto guest’s mobile app Business Capability Enabled ▪ Convert regular shoppers to preferred loyal shoppers ▪ increase revenue with relevant promotions Business Outcome
  26. 26. 26© 2016 Cisco and/or its affiliates. All rights reserved. Use Case: Location Based Pushed Notifications Connect Welcome Promotion Analytics ▪ Understand shopper needs and likes ▪ Reward loyal shoppers without overwhelming them ▪ Deliver real time promotions ▪ Stock stores to customer preferences Business Challenge ▪ Deliver personalized in-store shopping experiences ▪ Provide relevant information that helps make the purchase decision ▪ Insert targeted ads onto retail app (where the shopper is using one) Business Capability Enabled ▪ Increase revenue through real-time deal notifications and brand promotions ▪ Adapt to drive customer loyalty ▪ Build strong customer relationships with differentiated, valuable engagement Business Outcome
  27. 27. 27© 2016 Cisco and/or its affiliates. All rights reserved.
  28. 28. 28© 2016 Cisco and/or its affiliates. All rights reserved.
  29. 29. 29© 2016 Cisco and/or its affiliates. All rights reserved. Enhancing the Customer Experience Through Analytics Phase 1: Wi-Fi Only Phase 2: Wi-Fi, POS Phase 3: Wi-Fi, POS, CRM, Social Presence Detection Aisle Traffic Flow Department Traffic FlowPresence Detection Fixture Dwell Time Department Dwell Time Dept Path Analysis Associated Device Traffic Associate Engagement Queue Management Customer Demographics Social Engagement Store Layout Heat Maps Zone Analysis Loss Prevention Dwell Conversion Department Conversion OmniChannel Experience Customer LoyaltyShowrooming Customer Intimacy/Personalization BusinessImpact HIGH LOW Detailed Traffic Conversion E-commerce
  30. 30. 31 © 2015 FUJITSU Connect. Challenge. Inspire. FUJITSU Retail Solution Engagement Analytics Joe Hnilo VP, Software Business Fujitsu America August 9, 2016
  31. 31. 32 © 2015 FUJITSU Fujitsu in Retail – at a glance Revenue $1.6b Solutions Retail R&D/Innovation >$20m Years 50 Global Retail Strategic Team Partnerships 8,000 Countries 53 Analytics Omni-channel Self Service ICT Services Customers >500 Copyright Fujitsu 2016
  32. 32. 33 © 2015 FUJITSU Who we work with EMEA Japan & Asia Americas Oceania Copyright Fujitsu 2016
  33. 33. 34 © 2015 FUJITSU Retail Engagement Analytics Transforming Retail Operations and Shopping Experience in the Store
  34. 34. 35 © 2015 FUJITSU Online shopping analytics is very mature…
  35. 35. 36 © 2015 FUJITSU …in-store analytics is far behind
  36. 36. 37 © 2015 FUJITSU Stores account for 90% of transactions.
  37. 37. 38 © 2015 FUJITSU Fujitsu Retail Engagement Analytics q Fujitsu Retail Engagement Analytics provides retailers with an effective solution for understanding and analyzing shopper behavior while they are present in the store: § Collect and aggregate live customer location data § Combine location data with sales data to provide actionable insights § In-store traffic monitoring and alerting for better store operations § Patented Automated Flow Discovery to visualize traffic flows § Visualized analytics insights - dashboard/heat maps/flow maps § Secure cloud hosting with global reach § Strategic partnership with Cisco Copyright Fujitsu 2016
  38. 38. 39 © 2015 FUJITSU Core Benefits for Retailers We can track key customer behavior in the store… Number of people by store & zones Peak time in store/zone New compared to repeat visitors Common traffic patterns Where people spend time So retailers can… Optimize floor layouts vs hot spots Optimize # checkouts & location Understand visit patterns Manage in-store congestion proactively Optimize staff allocation and scheduling Copyright Fujitsu 2016
  39. 39. 40 © 2015 FUJITSU Turn Analytical Insights Into Action via BPM Time of day Threshold CustomerCount n Real time monitoring of customer traffic and staff allocation n Alert store manager and staff to initiate pre-emptive action Visualization: Location of Store Staff, customers and behaviors Predicted customer arrival rate Pre-emptive Alert to Shift Supervisor Reactive Alert to Store Manager Actual customer arrivals Store Traffic Map Call out Stocking Break Cashier Supervisor Copyright Fujitsu 2016
  40. 40. 41 © 2015 FUJITSU Key Differentiators q Turn analytics insights into actions with Business Process Management (BPM) capabilities. q Capture and correlate live customer location data with the PoS data to deliver actionable insights. q Visualize traffic flow for detailed shopper path analysis using Fujitsu patented Automated Flow Discovery technology. q Superior processing speed and scale leveraging advanced data processing technology, which is 500x faster than traditional databases. q Secure cloud hosting with global reach on Fujitsu’s own secure private cloud S5, delivered via our global network of data centers. q Complete, end-to-end solution delivered by Fujitsu Copyright Fujitsu 2016
  41. 41. 42 © 2015 FUJITSU Passers-by 5,000 Visitors 2,437 Engaged 2,013 Purchases 564 Sales $14,091 Traditional Approach REA - Store Performance Impact Passers-by 5,000 Visitors 2,437 Engaged 2,037 Purchases 591 Actionable Intelligence with REA 1% 5% Sales $14,771 5%
  42. 42. 43 © 2015 FUJITSU Customer Case Study
  43. 43. 44 © 2015 FUJITSU Leading Fashion Clothing Retailer q A multinational retail-clothing company, known for its fashion clothing for men, women, teenagers and children q Fujitsu gathered and analyzed location and sales data including the period of a store-wide promotion Copyright Fujitsu 2016
  44. 44. 45 © 2015 FUJITSU 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 Repeat Customers New Customer Customer Visits - New vs. Repeat Key Finding Potential Action Loyal customers consist nearly half of the total traffic Loyalty program to reward repeat customers Traffic drops significantly on March 19-20 Examine the cause of traffic drop * This data is representative data Copyright Fujitsu 2016
  45. 45. 46 © 2015 FUJITSU Customer Traffic by Department by Week 0 5000 10000 15000 20000 25000 Shoes Ladies Home Kids Cosmetics Week1 Week2 Week3 Week4 Key Finding Potential Action Traffic to cosmetic department almost doubled during week 4 Examine and analyse the promotion effectiveness during week 4 at cosmetics department * This data is representative data Copyright Fujitsu 2016
  46. 46. 47 © 2015 FUJITSU Sales Conversion/Dwell Time by Zone Key Finding Potential Action Men’s department has the low dwell time but high conversion rate Ladies department has the long dwell time but low conversion rate Examine the reason behind this and design corresponding strategy to boost the conversion rate at Ladies department * This data is representative data Short dwell time & high conversion rate Problem Focus: Long dwell time & low conversion rate Copyright Fujitsu 2016
  47. 47. 48 © 2015 FUJITSU Traffic Density Across the Store Key Finding Potential Action “Hot spots” across the store layout Allocate more staff resources to the right spot at right time * This data is representative data Copyright Fujitsu 2016
  48. 48. 49 © 2015 FUJITSU Key Findings q Identified most prominent routes taken by customers § Majority Visitors to one dept.- Floor plan optimization § Signage to encourage department visits q Quantified the effectiveness of promotions § Marketing effectiveness q Developed actionable intelligence for departments where conversion rate was low q Identified relationship between staff allocation and conversion § Staffing Optimization q Identified most effective time periods to run promotions Copyright Fujitsu 2016
  49. 49. 50 © 2015 FUJITSU
  50. 50. #AnalyticsInStore Q&A | Panelists MODERATOR: Debbie Hauss Editor-in-Chief, Retail TouchPoints Ashees Sinha Practice Architect, Digital Transformation Cisco Systems ashees@cisco.com Joe Hnilo Vice President, Software Business Fujitsu America, Inc. joe.hnilo@us.fujitsu.com
  51. 51. #AnalyticsInStore Thank You For Joining Us View this presentation on-demand at: http://rtou.ch/AnalyticsInStore

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