NovaRetail launches 200-300 new consumer products each quarter across e-commerce and stores. The merchandising team needs a model to predict first-8-week unit sales for new launches so they can set initial inventory, pricing, and marketing budgets before launch.
Historical data contains prior product launches from the last 4 years. Each row represents a product launch in a specific market-channel combination.
| Feature Group | Count | Examples |
|---|---|---|
| Product attributes | 14 | category, subcategory, brand_tier, pack_size, list_price, margin_pct |
| Launch plan | 11 | discount_pct, promo_weeks, ad_spend, email_campaigns, launch_month |
| Distribution | 8 | planned_store_count, online_enabled, region, channel, shelf_placement_score |
| Product history | 9 | prior_brand_sales, category_growth_rate, similar_product_avg_sales |
| External signals | 6 | competitor_launch_count, holiday_flag, inflation_index, search_trend_index |
A good solution should achieve MAPE < 22% on mature categories and weighted MAE < 180 units overall, while producing calibrated forecasts that are usable for inventory planning. The model should also identify the main drivers of predicted demand for planners.