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Retail AI Trends To Watch In 2021 Summary

Core Content

The document outlines key AI trends that are expected to shape the retail industry in 2021, highlighting how AI has become a critical tool for adaptation and innovation post-pandemic. It discusses the growing importance of AI in e-commerce fraud prevention, micro-fulfillment infrastructure, food waste reduction, first-party data strategies, auto-tagging for product categorization, and hyper-local inventory management. Additionally, it explores the increasing accessibility of checkout-free solutions.

Main AI Trends

1. AI for E-Commerce Fraud Prevention

• Context: The pandemic led to a surge in online transactions, increasing the risk of fraud.
• AI Role: AI tools help detect and prevent fraudulent activities by analyzing real-time data such as location, device ID, and behavioral patterns.
• Key Players:
  • Sift: Raised $50M in Q2'21 at a $1B valuation and acquired Chargeback to expand its dispute management capabilities.
  • Forter: Raised $300M at a $3B valuation, supported by major venture capital firms.
  • BioCatch: Uses behavioral biometrics to authenticate customers without requiring traditional biometric data like fingerprints or voice.

2. Micro-Fulfillment Infrastructure

• Definition: Mini, vertically stacked warehouses used to fulfill e-commerce orders efficiently.
• Use Cases:
  • Walmart: Scaling micro-fulfillment centers with partners like Alert Innovation, Domatic, and Fabric.
  • PepsiCo: Partnering with Dematic to improve online order fulfillment and reduce costs.
  • Takeoff Technologies: Planning to have 40 automated MFCs operational by the end of 2021.
• Benefits: Reduces last-mile delivery costs, improves efficiency, and enhances customer experience.

3. AI for Food Waste Reduction

• Challenges: Food waste costs supermarkets billions of dollars annually, especially with perishable items.
• Solutions:
  • Wasteless: Uses reinforcement learning to predict product demand and adjust pricing.
  • Afresh: Leverages historical sales data to optimize inventory and reduce waste.
  • Farmstead: Spun off FreshAI to offer a B2B SaaS solution, cutting food waste to under 10%.
• ESG Impact: AI helps retailers meet sustainability goals and improve ESG scores, which are increasingly important for investors.

4. First-Party Data Strategy

• Background: Third-party cookies are phasing out due to privacy regulations and browser changes.
• AI Role: AI-powered consumer data platforms help retailers unify and analyze shopper data from multiple sources.
• Key Players:
  • Bloomreach: Acquired CDP Exponea to enhance its data capabilities.
  • Twilio: Acquired Segment for $3.2B to support first-party data collection.
  • ActionIQ: Offers personalized customer experiences by combining first and third-party data.
• Importance: Retailers are focusing on direct data collection to maintain control over consumer relationships and improve targeting accuracy.

5. Auto-Tagging for Online Retail

• Purpose: Enhances product discovery and searchability through AI-generated taxonomies.
• Technologies:
  • Natural Language Processing (NLP) and Computer Vision are used to automatically generate product tags.
  • Lily Al: Trained on 1B manually tagged data points and offers psychographic consumer profiles.
  • Syte: Uses computer vision for detailed product tagging and description.
  • Glisten: Provides APIs for fast, AI-generated tagging of thousands of products.
• Benefits: Improves sales, enhances consumer experience, and supports competitive intelligence.

6. Hyper-Local Inventory Planning

• Definition: AI helps retailers manage inventory based on local demographics, market conditions, and real-time data.
• Use Cases:
  • Levi's: Clustered 300+ stores in China based on consumer behavior and preferences.
  • Google Cloud: Observed a 8,000% increase in searches for in-stock items, emphasizing the need for localized inventory strategies.
• Tools: AI software simulates SKU changes and optimizes promotional strategies across store networks.

7. Checkout-Free Solutions

• Adoption: Retailers are adopting cashierless technologies to improve convenience and reduce theft.
• Technologies:
  • Amazon Go: Uses sensors, cameras, and computer vision for seamless checkout.
  • Amazon Just Walk Out: Offers cashierless tech as a service to other retailers.
  • Smart Carts: Like Imagr's Halo Cart and Kroger's Caper-powered KroGo, are being tested in various markets.
• Benefits: Increases speed, convenience, and data collection for consumer behavior analysis.

Key Information

• AI Investment: Retail AI funding hit a record in 2021, with significant investment in fraud prevention, fulfillment, and data analytics.
• Regulatory Shifts: The decline of third-party cookies and increased focus on ESG compliance have driven retailers to prioritize first-party data and sustainable practices.
• Consumer Behavior: Shifts in shopping habits, such as increased online purchases and demand for in-stock items, have accelerated AI adoption.
• Technology Partnerships: Major retailers like Walmart and Kroger are collaborating with AI startups and tech giants to implement innovative solutions.
• Market Growth: The retail AI market is expected to grow rapidly, driven by the need for efficiency, personalization, and sustainability.

Conclusion

AI is becoming a foundational technology in the retail sector, reshaping how companies manage fraud, fulfillment, inventory, and consumer data. With the end of third-party cookies and the rise of ESG considerations, retailers are increasingly relying on first-party data and AI-driven tools to stay competitive and meet evolving consumer demands.