Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

From checkout-free to self-checkout

737 views

Published on

Presentation from NRF 2019 Retail's Big Show
Francois Chaubard, CEO, Focal Systems, Inc.
Lindon Gao, Co-Founder and CEO, Caper
Steve Gu, Co-Founder and CEO, AiFi
Krishna Motukuri, Co-Founder and CEO, Zippin
Pradeep Pydah, Founder and CEO, Maxerience

Published in: Retail
  • Be the first to comment

From checkout-free to self-checkout

  1. 1. From checkout-free to self-checkout – What you need to know about the latest convenience-basedpayment technologies Monday, January 14 2:45 pm - 3:15 pm Chris Hardisty VP, Retail and Digital Lacoste Steve Gu Co-Founder and CEO AiFi Francois Chaubard CEO Focal Systems,Inc. Krishna Motukuri Co-Founder and CEO Zippin Pradeep Pydah Founder and CEO Maxerience Lindon Gao Co-Founder and CEO Caper
  2. 2. Coverage Vending Machines Daily Revenue 10 miles 2-3 miles < 500 ft $500 $2k $10k >$100k
  3. 3. Coverage Vending Machines Daily Revenue 10 miles 2-3 miles < 500 ft $500 $2k $10k >$100k Hypermarket
  4. 4. Coverage Vending Machines Daily Revenue 10 miles 2-3 miles < 500 ft $500 $2k $10k >$100k Supermarket Neighborhood Market Convenience Store Hypermarket
  5. 5. Coverage Hypermarket Vending Machines Daily Revenue 10 miles 2-3 miles < 500 ft $500 $2k $10k >$100k Supermarket Neighborhood Market Convenience Store
  6. 6. Coverage Vending Machines Daily Revenue 10 miles 2-3 miles < 500 ft $500 $2k $10k >$100k Supermarket Neighborhood Market Convenience Store 24/7, unstaffed, automated Hypermarket NanoStore
  7. 7. Introducing NanoStore: Automated Checkout, 24/7
  8. 8. NanoStore as 24/7 satellite stores
  9. 9. Instant AutoCheckout pilot Payback < 1 yr Great new business
  10. 10. NanoStore is on pre-order today!
  11. 11. DEEP LEARNING COMPUTER VISION TO DELIGHT MORE CUSTOMERS January, 2019
  12. 12. Point #1: The retailer that makes customers happiest will win.
  13. 13. “Determine what your customers need, and work backwards.” - Jeff Bezos TO SURVIVE THE NEXT DECADE, RETAILERS MUST:
  14. 14. GOAL #1: Happy Customers “Determine what your customers need, and work backwards.” - Jeff Bezos Right product, right price Fully stocked shelves Friendly & dedicated staff What Makes Customers Happy? Immediate Checkout TO SURVIVE THE NEXT DECADE, RETAILERS MUST:
  15. 15. GOAL #1: Happy Customers “Determine what your customers need, and work backwards.” - Jeff Bezos Fully stocked shelves What Makes Customers Happy? Immediate Checkout TO SURVIVE THE NEXT DECADE, RETAILERS MUST: $600k / year / store $800k / year / store
  16. 16. Point #2: Deep Learning Computer Vision is the most scalable way to achieve those things today
  17. 17. 1: Automatic PLU Input at Self Checkout •Eliminate PLU Lookup •Increase throughput from 30/hour to 50/hour •Increase adoption from 30-50% •Reduce Produce Shrink by 60% •$150,000 Economic Benefit per year per store
  18. 18. 2: Eliminate Scanning •Eliminate Barcode Scanning Completely •Increase throughput from 22/hour to 52/hour •Reduce Produce Shrink and sweethearting •$500,000 Economic Benefit / year / store
  19. 19. 3: Out-of-Stock Detection •Eliminate Manual Scanning •Real-time reporting of out of stocks •Get to 96% On-shelf Availability •Increase pick velocity by 30% •$310,000 Economic Benefit per year per store
  20. 20. Point #3: AUTOMATED GROCERY IS THE NEW “ONLINE”… DON’T MISS IT.
  21. 21. AMAZON GO IS NOT SCALABLE, BUT….. DEEP LEARNING COMPUTER VISION IS!
  22. 22. OperatingProfit Kroger Operating Profit Scenario Analysis 1)Pay us $100m a year to automate 2% of labor 2)Grow online sales 30% for 5 years 3)Do nothing
  23. 23. AUTOMATION IS THE MOST IMPORTANT INVESTMENT A RETAILER CAN MAKE Invest in online or in in-store automation with Deep Learning? 63% can be automated today
  24. 24. 10+ Major Retailers, 3 Continents francois@focal.systems
  25. 25. checkout-free shopping for every store Krishna Motukuri
  26. 26. Vision Transform retail by banishing checkout lines.
  27. 27. The Problem People hate waiting in lines. Rising labor costs are making checkout lines even longer. Self-checkout kiosks are clunky and increase friction for customers.
  28. 28. S T E P 1 : E N T E R credit card / mobile Integrated Advanced Tech Deep learning. Computer Vision. Sensor Fusion. S T E P 2 : S H O P multi-camera tracking
  29. 29. S T E P 1 : E N T E R credit card / mobile Integrated Advanced Tech Deep learning. Computer Vision. Sensor Fusion. S T E P 2 : S H O P multi-camera tracking S T E P 3 : P I C K pose estimation product recognition
  30. 30. Customizable Shelf Sensors Easy to retro-fit any store WORKS WITH EXISTING SHELVING PLUG AND PLAY MODULAR
  31. 31. Pre-fabricated turn-key solution (optional) No need for wiring Assemble in any layout. Carry refrigerated as well as dry goods. Ideal for Grab-and-go stores at airports, malls, buildings.
  32. 32. Biggest shift in retail since bar codes Retailer net profit goes up by ~3x 1. Lower labor costs 2. Higher sales / sq ft 3. Real time inventory tracking and forecasting 4. Advanced analytics 5. Fewer losses due to theft
  33. 33. Solution accessible to all retailers CapEx $25 - $30 / sq ft OpEx Savings 5 – 10% of sales Payback in 6-12 months Cameras, Sensors, Wiring and Installation After paying Zippin’s SaaS fees
  34. 34. Zippin-powered stores opening soon 50 retailers and real estate owners 4 major retailers
  35. 35. Thank You • High accuracy • Easy to deploy • Boosts sales • Lowers costs www.GetZippin.com
  36. 36. IOT Vision AI PROVIDING SMART RETAIL Leveraging our Scalable IOT and AI Platform
  37. 37. 40 Sell anywhere, Anytime!
  38. 38. 41 Using checkout free, self serve assets
  39. 39. 42 Improve your market execution
  40. 40. 43 Leveraging instant actionable insights Select outlet Simple Image Capture with Quality Check Instant Result processing Actionable Insights & Core KBI’s Outlet Located (GPS)1 Retail Shelf/ Cooler Captured 2 Shelf/Cooler Analyzed3 Prescriptive Analytics4
  41. 41. 44 Remotely know how you products are performing Using our Stick-n-Play IOT and Machine Vision Solutions
  42. 42. 45 Monetize retail IoT and Image Recognition data Monetization of retail IoT and Image Recognition data Key KBI’s Out- of-the box actionable insights Self-service Machine Learning
  43. 43. ` 46 Enabling Scale via our Instant Product Cataloging Technology Factories Distribution Centers < 3 Minutes to Capture Products @ Source < 24 Hours Start Recognizing New Products
  44. 44. 47 USA China India Bulgaria 7+ Million Outlets 1+ Million Connected Devices 42 Countries Across 5 Continents Leveraging IOT & AI for retail At Scale
  45. 45. 48 VISIT US FOR LIVE DEMOS BOOTH – 7102 INNOVATION LAB- 4TH FLOOR Pradeep V Pydah | CEO 22994, Lavender Valley Ct, Ashburn, Virginia 20148 1-510-8960953 pradeep.v.pydah@maxerience.com 22994, Lavender Valley Ct, Ashburn, Virginia 20148 1-917-4590915 karan@ebest-iot.com Karan Bakshi | CEO

×