top of page

OpTeamizer Developed Advanced Machine Learning System for Belle: The Ultimate AI Demand Forecasting


The AI-powered demand forecastingBelle is a product of the collaboration between Road2 Innovation Center, MATI Haifa, NVIDIA, and OpTeamizer. Belle is a solution that provides in-depth insights into customer behavior and preferences, allowing companies to make data-driven decisions. By leveraging this information, companies can optimize their inventory, improve efficiency, and ultimately increase their profits. Belle empowers companies with the tools to make informed decisions that drive their success.


The Road2 Innovation Center in Haifa has chosen OpTeamizer Ltd to operate as its professional center and AI expert in collaboration with MATI Haifa (a business development center) and NVIDIA. The Road2, MATI Haifa, NVIDIA, and OpTeamizer alliance are intended to support startups with innovative product or service concepts, including artificial intelligence solutions. Road2 provides access to capital, networking, and further mentoring for startups, and OpTeamizer offers AI development to help startups grow their business.


Contribution of OpTeamizer to the Success of Belle

OpTeamizer's machine-learning system and Belle's retail expertise have created a powerful solution for demand forecasting in the retail industry. By combining Belle's deep understanding of the retail market with OpTeamizer's advanced technology, retailers can now access new customer insights. Utilizing the cutting-edge machine-learning technology developed by OpTeamizer to revolutionize the way businesses forecast demand, retailers can now make data-driven decisions to optimize their inventory and increase efficiency and profits.


Startup Case Study: Belle - AI-Powered Demand Forecasting at its Finest

With Belle, retailers can gain deep insights into customer behavior and preferences, allowing them to make data-driven decisions to optimize their inventory and increase efficiency and profits.

The system uses cutting-edge machine-learning technology to analyze vast amounts of data, including sales data, customer demographics, and market trends. This allows it to make highly accurate predictions about future demand, enabling retailers to plan their inventory more effectively. The system also monitors real-time sales so retailers can quickly adjust their inventory levels to keep pace with changing demand.

Belle's advanced analytics also allow retailers to identify patterns and trends in customer behavior that may be difficult to spot using traditional methods. This can help retailers to target their marketing efforts more effectively, increasing sales and improving customer loyalty.

Overall, Belle is a game-changing solution for retailers looking to improve their demand forecasting and stay ahead of the competition. With its advanced machine-learning technology and deep understanding of the retail market, retailers can make data-driven decisions to increase efficiency, improve inventory management, and increase profits.


The Challenge

The growth of the e-commerce market has brought many benefits to consumers but has also led to some challenges for retailers. One of the biggest challenges is the return increase for products that don't fit. According to recent estimates, the cost of returns is as high as $600 billion in losses for retailers worldwide. This is mainly because people order products online without trying them on first, resulting in too big or too small.


Another challenge facing retailers is the low customer satisfaction with online shopping. A recent global survey of consumers indicates that only 15% of respondents are happy with their online shopping experience. This suggests a significant opportunity for retailers to improve the online shopping experience and increase customer satisfaction.

By leveraging Belle's powerful technology, retailers can increase efficiency, reduce costs, and improve customer satisfaction, ultimately leading to more sales and higher profits. Retailers can also implement solutions like size recommendations, virtual try-ons, and predictive returns management to reduce the number of returns and increase customer satisfaction.


Solution

Belle's innovative technology analyses consumer taste profiles and goods with comparable qualities to forecast user purchasing preferences effectively.

"Our aim is to provide customers with a seamless shopping experience and help brands understand their shoppers better," says Lihi Raichelson, CEO of Belle. "Once they are registered, they’ll get personalized product recommendations and tailored offers that correspond to their needs.”

Background


Lihi Raichelson, Belle AI
Lihi Raichelson, Belle AI

Belle was established in 2019 by Lihi Raichelson, a Demand Planner at Intel for many years. "The idea of developing such forecasting on what customers will get the best recommendations was initially proposed by my daughter. The idea was to create a machine learning algorithm to inspect customer reviews and personal features and recommend the best goods. To develop such forecasting, we had to do lots of research, analytics, and technical work". During negotiations with retailers, Lihi also discovered that Belle could estimate consumer needs and preferences by taste, color, size, and price to help buyers plan to manufacture and distribute. That is why during the last year, Belle has done a semi-pivot and shifted into demand forecasting for retailers.


Product Launch Goals

Currently, Belle is available in the UK, cooperating with ASOS, New Look, PrettyLittleThing, Topshop, Adidas, Armani, Calvin Klein, and many other favorite brands. Soon, Belle plans to expand to other markets and be available on different online retailers.

35 views0 comments

Commentaires


bottom of page