Trend Demand Forecaster

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name: trend-demand-forecaster description: Turn sales notes, trend signals, seasonal context, promo plans, and inventory constraints into a practical demand forecast brief with base, upside, and downside scenarios, leading indicators, and replenishment cues. Use when planners, ecommerce operators, founders, or consultants need forecasting support without live ERP, BI, ads, or marketplace APIs.

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Trend Demand Forecaster

Overview

Use this skill to convert rough demand signals into a practical forecast narrative. It is built for teams that need a fast planning layer for the next few weeks, quarter, or seasonal window.

This MVP is heuristic. It does not pull live sales, ads, weather, ERP, marketplace, or competitor data. It relies on the user's provided notes, exports, and planning context.

Trigger

Use this skill when the user wants to:

forecast demand for the next month, quarter, or seasonal event

estimate promo lift or post-promo normalization

plan replenishment against demand uncertainty

interpret whether demand is recovering, stabilizing, or softening

turn messy trend notes into a base, upside, downside planning brief

Example prompts

"Forecast next month's demand using these sales and inventory notes"

"Build a base, upside, downside demand view for our holiday campaign"

"Should we buy deeper inventory or stay cautious?"

"Help me interpret whether demand is rebounding or just promo noise"

Workflow

1. Clarify the planning question, decision horizon, and risk tolerance. 2. Normalize the strongest signals, such as traffic, orders, conversion, price, inventory, and seasonality. 3. Separate baseline demand from promo distortion, stockout distortion, or one-off events. 4. Build base, upside, and downside scenarios with trigger conditions. 5. Return a markdown brief with indicators, action cues, and assumptions.

Inputs

The user can provide any mix of:

weekly or monthly sales summaries

traffic, conversion, pricing, and promo notes

stockout periods, inventory cover, or inbound timing

launch, seasonal, holiday, or campaign context

return rate, customer service, or marketplace feedback

constraints such as cash, lead time, MOQ, or warehouse limits

Outputs

Return a markdown forecast brief with:

demand narrative and likely mode

planning horizon and key signals

base, upside, downside scenarios

leading indicators to monitor

inventory and commercial implications

risk watchlist and next-step actions

assumptions, confidence notes, and limits

Safety

Do not claim access to live systems or external trend feeds.

Treat all scenarios as planning heuristics, not guaranteed forecasts.

Do not auto-commit buys, budgets, or inventory transfers.

Downgrade confidence when the user only provides promo-distorted or stockout-distorted history.

Keep final purchasing and budget decisions human-approved.

Best-fit Scenarios

ecommerce teams planning 2 to 16 weeks ahead

operators working from rough exports instead of a forecasting platform

founders who need a quick demand-planning memo before placing inventory bets

consultants preparing scenario-based planning recommendations

Not Ideal For

formal statistical forecasting that requires model calibration and backtesting

highly granular store-SKU-day forecasting at enterprise scale

workflows that require automatic PO creation or system sync

regulated forecasts that need audited financial controls

Acceptance Criteria

Return markdown text.

Include scenario, indicator, implication, and risk sections.

Make the advisory and heuristic framing explicit.

Keep the output practical for planning and replenishment decisions.