Top AI/ML Retail Data Labeling Challenges Solved



AI-driven applications are rising in importance in every industry and retail is no exception. Retailers have been paying careful attention to the progress that AI is making, and they can see the opportunities that it holds. It’s no surprise that AI for the retail market is predicted to reach $23,426 million by 2026 with a CAGR of 33.7%. AI is already having a dramatic impact on numerous retail use cases, from improving logistics and demand forecasting to increasing the accuracy of personalized offers and promotions.

Over 75% of retail executives expect to see AI impact supply chain planning, demand forecasting, customer intelligence and targeted marketing.

  • Human workforce challenges in the retail industry
  • Managing consistent quality across retail datasets
  • Balancing the financial cost of quality labeled data
  • Complying with privacy requirements for retail customer data
  • Maintaining smart retail data management ML tooling at scale
  • The right data platform helps retailers overcome data labeling challenges

© Dataloop Ltd. 2021