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From checkout-free to self-checkout
The document discusses emerging technologies that are changing in-store checkout and payment processes. It summarizes presentations from several companies at a conference on checkout-free shopping technologies using computer vision and artificial intelligence. The companies describe solutions like automated checkout systems without cashiers that track customers and identify purchased items in real-time to charge customers. These new approaches aim to improve customer experience by reducing checkout wait times and could lower costs for retailers through reduced labor needs.
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From checkout-free to self-checkout
- 1. From checkout-free toself-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. Coverage Vending Machines Daily Revenue 10 miles 2-3miles < 500 ft $500 $2k $10k >$100k
- 3. Coverage Vending Machines Daily Revenue 10 miles 2-3miles < 500 ft $500 $2k $10k >$100k Hypermarket
- 4. Coverage Vending Machines Daily Revenue 10 miles 2-3miles < 500 ft $500 $2k $10k >$100k Supermarket Neighborhood Market Convenience Store Hypermarket
- 5. Coverage Hypermarket Vending Machines Daily Revenue 10 miles 2-3miles < 500 ft $500 $2k $10k >$100k Supermarket Neighborhood Market Convenience Store
- 6. Coverage Vending Machines Daily Revenue 10 miles 2-3miles < 500 ft $500 $2k $10k >$100k Supermarket Neighborhood Market Convenience Store 24/7, unstaffed, automated Hypermarket NanoStore
- 7. Introducing NanoStore: AutomatedCheckout, 24/7
- 11. NanoStore as 24/7satellite stores
- 12. Instant AutoCheckout pilot Payback< 1 yr Great new business
- 13. NanoStore is onpre-order today!
- 14. DEEP LEARNING COMPUTERVISION TO DELIGHT MORE CUSTOMERS January, 2019
- 15. Point #1: The retailerthat makes customers happiest will win.
- 16. “Determine what yourcustomers need, and work backwards.” - Jeff Bezos TO SURVIVE THE NEXT DECADE, RETAILERS MUST:
- 17. GOAL #1: Happy Customers “Determinewhat 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:
- 18. GOAL #1: Happy Customers “Determinewhat 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
- 19. Point #2: Deep LearningComputer Vision is the most scalable way to achieve those things today
- 20. 1: Automatic PLUInput 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
- 21. 2: Eliminate Scanning •EliminateBarcode Scanning Completely •Increase throughput from 22/hour to 52/hour •Reduce Produce Shrink and sweethearting •$500,000 Economic Benefit / year / store
- 22. 3: Out-of-Stock Detection •EliminateManual 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
- 23. Point #3: AUTOMATED GROCERYIS THE NEW “ONLINE”… DON’T MISS IT.
- 24. AMAZON GO ISNOT SCALABLE, BUT….. DEEP LEARNING COMPUTER VISION IS!
- 25. OperatingProfit Kroger Operating ProfitScenario Analysis 1)Pay us $100m a year to automate 2% of labor 2)Grow online sales 30% for 5 years 3)Do nothing
- 26. AUTOMATION IS THEMOST IMPORTANT INVESTMENT A RETAILER CAN MAKE Invest in online or in in-store automation with Deep Learning? 63% can be automated today
- 27. 10+ Major Retailers,3 Continents francois@focal.systems
- 28. checkout-free shopping forevery store Krishna Motukuri
- 29. Vision Transform retail by banishingcheckout lines.
- 30. The Problem People hatewaiting in lines. Rising labor costs are making checkout lines even longer. Self-checkout kiosks are clunky and increase friction for customers.
- 31. S T EP 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
- 32. S T EP 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
- 33. Customizable Shelf Sensors Easyto retro-fit any store WORKS WITH EXISTING SHELVING PLUG AND PLAY MODULAR
- 34. 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.
- 35. Biggest shift inretail 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
- 36. Solution accessible toall 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
- 37. Zippin-powered stores openingsoon 50 retailers and real estate owners 4 major retailers
- 38. Thank You • Highaccuracy • Easy to deploy • Boosts sales • Lowers costs www.GetZippin.com
- 39. IOT Vision AI PROVIDING SMARTRETAIL Leveraging our Scalable IOT and AI Platform
- 40.
- 41. 41 Using checkout free,self serve assets
- 42.
- 43. 43 Leveraging instant actionableinsights 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
- 44. 44 Remotely know howyou products are performing Using our Stick-n-Play IOT and Machine Vision Solutions
- 45. 45 Monetize retail IoTand Image Recognition data Monetization of retail IoT and Image Recognition data Key KBI’s Out- of-the box actionable insights Self-service Machine Learning
- 46. ` 46 Enabling Scale viaour Instant Product Cataloging Technology Factories Distribution Centers < 3 Minutes to Capture Products @ Source < 24 Hours Start Recognizing New Products
- 47. 47 USA China India Bulgaria 7+ Million Outlets1+ Million Connected Devices 42 Countries Across 5 Continents Leveraging IOT & AI for retail At Scale
- 48. 48 VISIT US FORLIVE 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