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Forecasting system for grocery retail
Reduce food wastage and improve operational efficiency with DSLab's machine learning technologies
DSLab builds forecasting systems to help grocery retailers increase operational efficiency and reduce costs by leveraging machine learning technologies. We assist our clients in uncovering potential applications of ML, incorporating it to business processes and deriving benefits from historical data.
Our clients obtain measurable results such as increased on-shelf availability and turnover, and reduced overstock.
Step-by-step approach to launching machine learning initiatives that bring measurable business results.
Practical Guide to Machine Learning Projects in Retail
What can and cannot be achieved using machine learning, what use cases for the retail industry are, how to measure results, and steps to implementing machine learning projects.
Get highly accurate demand forecasts, optimize sales promotions, prices and safety stock, and improve operational efficiency with DSLab's forecasting solutions for grocery retail.
Demand forecasting is a barebone of every retailer's business. Order too much, and you accumulate overstock; order too little, and you lose sales and customers. Machine learning, however, gives a fresh perspective on how to strike a balance and predict demand as accurately as possible. Get an automated, highly accurate forecast for every SKU on a store level with DSLab's demand forecasting.
With fresh food, retailers have always faced a trade-off: order too little, and you lose sales; order too much, and you get excess stock and food wastage. Our machine learning technology allows grocers to predict demand for items with a shelf life of 1-7 days more accurately, increase on-shelf availability and reduce write-offs. Keep your perishables fresh with DSLab's demand forecasting for fresh food.
With an average of 60% of goods being on offer constantly, demand forecasting for discounted products is more important than ever. Improve on-shelf availability without keeping excess stock with DSLab's machine learning technology. Get a granular forecast for each item on a sales promotion, on a store level, for 16 weeks ahead.
The fear of being left with an empty shelf drives an understandable motive to order a "little extra" inventory. DSLab's machine learning safety stock forecasting eliminates the emotional factor of inventory management, reduces the level of manual fine-tuning, and optimizes safety stock for seasonality, upcoming holidays, and sales promotions.
Embrace the opportunities of smart pricing to offer customers the right price optimized for both internal and external parameters, such as time of day or weather. Maximize sales, increase margins, and boost store traffic with DSLab's intelligent pricing.
Instead of focusing on accuracy only, we optimize for business metrics, such as write-offs and out-of-stocks. After all, it is not the percentage of error but the cost of error that makes a difference.
Our forecasting solution is easily integrated with standard data sources such as Hadoop or SQL-based data storages, as well as replenishment systems.
Team of A-players
We are experts with 10+ years of practical experience in data analysis, machine learning and artificial intelligence in world-leading IT companies.
Our solutions deliver measurable business results within the first 3-6 months.
Predictive Analytics World
DSLab CEO and Founder Alexey Shaternikov to speak at Predictive Analytics World in Berlin. Alexey will showcase the project on demand prediction for the leading retail chain Lenta.
18-19 NOVEMBER 2019, BERLIN
Alexey Shaternikov, CEO and Founder at DSLab, spoke in Gdansk at the annual DataMass Summit. Alexey shared DSLab experience in incorporating AI-based demand forecasting into business processes.
04 OCTOBER 2019, GDANSK
Get in touch to see how machine learning can benefit your business