Retail
Developing Sales Forecasting and Footfall Prediction Models for the World’s Largest Shopping Festival
23K SKUs and 24 stores accurately forecasted
Sales
predicted for 23K SKUs across 6 product categories.
Footfall
prediction for 23 brick-and-mortar stores and their online store.
20%
increase in trading volume within 3 months.
Successfully
operationalized forecasting models for sales.
Why this Global Bank Loves nanoBI
- AI-driven predictive analytics for sales.
- AdStock transformation for ad effectiveness insights.
- 360° Investigative Analytics.
- Product Saleability Index for strategic planning.
- Random Forest XGB Ensemble Model for variance analysis.
Sales
predicted for 23K SKUs across 6 product categories.
Footfall
prediction for 23 brick-and-mortar stores and their online store.
20%
increase in trading volume within 3 months.
Successfully
operationalized forecasting models for sales.
Loved it? Ready to try nanoBI?
About the client
A leading electronic store marketplace in the United Arab Emirates, catering to a diverse customer base with both physical retail stores and an online presence.
The client participates in major shopping festivals, requiring accurate demand forecasting and footfall prediction to optimize inventory, promotions, and store layouts.
Challenges Before nanoBI
- No accurate method to predict footfall and sales for peak shopping events.
- Inefficient assortment planning, merchandising, and store layout decisions.
- Needed better prediction of promotional performance to maximize conversions.
nanoBI Solution
- AdStock transformation was done to calculate AdStock Rate for Advertisement variables and later Linear regression techniques deployed for Footfall prediction in R.
- A Product Saleability Index was created based on Product Categories, Brands and Time periods before and after the promotions to collate market price and units against Sales and Prices.
- Further Random Forest XGB, an Ensemble Modeling approach was taken for Promotional Sales Predictions to compute the variance of sales across outlets and products
How Things Have Changed
- nanoBI’s AI-powered predictive models have transformed sales and footfall forecasting, enabling the client to optimize store layouts, promotions, and inventory planning.
- The operationalized forecasting model led to a 20% increase in trading volume within 3 months.
- With sales predictions for 23K SKUs and footfall insights for 24 stores, the client was able to make data-driven decisions for high-traffic shopping events, maximizing sales opportunities.
