Average demand forecasting accuracy improves10%
Average management efficiency improves60%
Average inventory turnover days reduces20%
Average inventory capital occupation reduces10%
Average in-stock rate increases5%
Average overall revenue / profit performance improves10%
Application scenarios in the retail industry
Accurate demand forecasting:
driven by AI
Combine internal and external data, time series and machine learning algorithm to help enterprises make accurate predictionmore
Auto replenishment plan:
covering all product categories
Customize the optimal replenishment strategy for each category to achieve automatic replenishmentmore
Real time dynamic pricing:
Intelligent price management to build a community of shared future for the retail industry and consumersmore
Intelligent precision marketing:
optimizing input and output
Precise cost allocation + flexible product portfolios to win in complex scenariosmore
Optimizing through data+algorithm to provide accurate, efficient and stable smart retail solutions to achieve:
Higher demand forecasting accuracy
Faster replenishment response
Less storage-related operational cost
Less inventory capital occupation
Shorter response time to customers
Stronger overall revenue / profit performance
A Chinese flagship e-commerce platform
We provide salespersons with an automatic pricing system according to different product positionings and business goals, solving common problems in traditional pricing methods. (Problem 1: price adjustments rely on labor; Problem 2: lack of pricing for long-tail products), to significantly improve sales, profits, and efficiency of corporate price management.
An international FMCG giant
Promotion optimization project
We establish a comprehensive promotion management plan, considering different promotion mechanisms, product correlation factors and traditional business logic through the analysis of the company’s historical promotion data on the e-commerce platform. Promotion cost-benefit ratio and sales have been significantly improved.
A large international beer brand
Offline retail price optimization
We give optimal price recommendations with pricing logics and pricing targets of different regions/ channels, considering detailed consumer sensitivity and regional environmental information. This is the first retail price optimization model established and adopted by this beer company in China.
A cosmetics brand
Integrate sales and market data of the e-commerce platform; consider various factors such as promotion intensity, advertising intensity, holidays, etc; provide dynamic weekly sales forecast of more than 100 SKUs on the flagship e-commerce platform as a reference for inventory optimization; achieve a significant improvement in prediction accuracy of star products as well as regular products.
A retail giant
Store-Level automatic replenishment
Achieve automatic replenishment of all categories of merchandise by:
1、finding correlations between raw material consumption and corresponding merchandise sales through daily demand forecasting
2、external factors such as surrounding events and weather
Greatly reduces the time required for store managers to place daily replenishment orders; improves in-stock rate through precise replenishment, compared to results under prior methods based on personal experience.
A flagship e-commerce company
Multi-level warehouse allocation and
Design an integrated strategy of replenishment, allocation, and distribution under multi-level warehousing system; optimize the replenishment method of conventional products and long-tail products in RDCs; establish product selection and allocation strategies in FDCs; achieve a more flexible and agile inventory network which significantly improves order fulfillment rate, reduces turnover days and inventory costs, and allows automatic replenishment.