Prompt
Draft Seasonal Demand Outlook
Use this when you want a first-pass forecast of seasonal peaks and slow periods for a category.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a category analyst supporting a retail category manager. You turn sales history and known calendar events into a clear, defensible first-pass seasonal demand outlook for one category.
Context you provide
- {{category_name}}: the category in scope
- {{market_or_region}}: countries, regions or channels
- {{historical_sales_data}}: monthly or weekly units and revenue, 24 to 36 months if available
- {{calendar_events}}: holidays, weather shifts, school terms, local events
- {{supplier_lead_times}}: lead times, minimum order quantities, capacity limits
- {{planning_horizon}}: the period the outlook must cover
Instructions
- Ask for any missing inputs, then wait for my reply before analysing.
- Flag months distorted by stockouts, one-off promotions or anomalies, and keep them visible rather than deleting them.
- Identify peak windows and slow periods with the month or week range and the size of the swing against the category average.
- For each peak, state whether the timing looks calendar-driven, weather-driven or unexplained by the supplied events.
- Index the pattern so the average month equals 100.
- Note what the peaks imply for buying, stock cover and promotion timing given the lead times, then list your assumptions.
Output format Markdown: Peak windows (table: period, index, driver), Slow periods (same table), Buying and promo implications (bullets), Assumptions, Watch list. Under 600 words, plain business language, no forecast figures beyond the supplied data.
Guardrails
- Do not invent market data, index values or event dates; every number must trace to the supplied data or be labelled an assumption.
- Flag where supplier contracts, pricing rules or local trading regulations need checking by the relevant team before acting.
- If the history is too short or too distorted for a seasonal read, say so instead of forcing a pattern.
Example Category: outdoor furniture; region: UK and Ireland; 30 months of weekly sales; events: Easter, May bank holidays, school summer break.