Trend Demand Forecaster

Problem

When demand signals arrive as scattered exports, ops notes, promo retros, or stockout gaps, teams often still need a practical answer for the next month, quarter, or seasonal window. trend-demand-forecaster targets this planning layer where there is no formal forecasting platform, but the team needs a defensible demand narrative instead of a false-precision point estimate.

How It Works

The skill is heuristic and does not connect to live sales, ads, weather, ERP, marketplace, or competitor data. It works from user-provided context:

• Planning question: define the decision horizon, risk tolerance, and constraints such as cash, MOQ, and lead time.
• Signal normalization: organize signals like traffic, orders, conversion, price, inventory, and seasonality.
• Noise separation: distinguish baseline demand from promo lift, stockout distortion, and one-off events.
• Scenario output: produce base, upside, and downside scenarios with trigger conditions, indicators, inventory and commercial implications, and a risk watchlist.

The output is a Markdown brief with demand narrative, likely mode, planning horizon, key signals, leading indicators, assumptions, confidence notes, and limits.

Boundaries

It fits ecommerce teams planning 2 to 16 weeks ahead, operators working from rough exports, founders who need a quick demand memo, or consultants preparing scenario-based recommendations. It is not ideal for formal statistical forecasting that requires model calibration and backtesting, highly granular store-SKU-day enterprise forecasting, automatic PO creation, or system sync. Treat all scenarios as planning heuristics, and keep purchase, budget, and inventory-transfer decisions human-approved.