Sales Forecasting System for a Home Goods Retail Chain

Challenge

A home goods retail chain faced challenges in sales planning and inventory management.
To optimize revenue and supply chain operations, the company needed a forecasting system capable of predicting product demand across multiple categories and estimating the expected revenue for each individual store.
Without accurate forecasts, stores frequently encountered overstock or stockout situations, reducing operational efficiency and profitability.

Solution

The Hidden Core team developed a custom AI-based sales forecasting system capable of generating forecasts for each store in the retail network individually.
The solution was powered by a transformer-based model, fine-tuned on the client’s data and enriched with external factors influencing sales performance.

Our data preparation pipeline included:

• Three years of historical daily sales data for each product category;

• Weather conditions;

• Public holidays, school breaks, and promotional campaigns;

• Local competition data near each store.

The system delivers:

• Revenue forecasts one month ahead;

• Category-level sales forecasts two weeks ahead;

• Forecast accuracy up to 90%.

All forecasts are visualized in an interactive dashboard accessible to the company’s management team for real-time monitoring and decision-making.

Impact

The new forecasting system enabled the company’s management to improve financial planning and react faster to demand fluctuations.
Accurate category-level predictions helped optimize stock distribution between warehouses and stores, reducing both shortages and overstocks.
As a result, the retailer achieved higher sales stability and improved profitability.

Hidden Core Contribution

Hidden Core delivered a complete end-to-end solution — from data preparation and model training to integration and dashboard deployment.
The forecasting pipeline was designed for scalability, allowing the system to expand across new regions and store formats as the business grows.