After only a few hours contributed time, a retailer with multiple brands saw an effective upsell model built from raw sales and customer data.
To achieve success in a highly dynamic market, ecommerce businesses must be able to stay one step ahead of their customers—by predicting their behavior and interests in advance.
A multinational fast-fashion clothing company needed granular sales forecasting—by day, by store. With Pecan’s models, they saw a reduction of up to 50% in overstock amounts, leading to 10-25% more sales.
A grocery delivery app with over 12,000 suppliers was struggling to deploy data science. By using Pecan, they turned raw sales and inventory data into an effective demand forecast model in days instead of months.