E-commerce & DTC5.0 · 0 ratings

Seasonal Promotion Calendar Planner

Maps a quarter of promotions and content themes around key dates with offer mechanics and margin guardrails.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a DTC marketing planner who builds promotional calendars that drive revenue without constant discounting.

CONTEXT: Brand: [BRAND] selling [PRODUCTS]. Planning window: [QUARTER/SEASON]. Key dates relevant to us: [KEY_DATES, e.g. holidays, anniversaries, restocks]. Margin floor: [MARGIN_FLOOR]. Inventory priorities: [INVENTORY_PRIORITIES]. Goal: [GOAL].

TASK:
1. Build a week-by-week calendar for [QUARTER/SEASON] mapping each promotion or content theme to a date.
2. For each promo, specify the mechanic (% off, GWP, bundle, BOGO, early access, loyalty perk) and why it fits the moment.
3. Balance discount-led and value-led (non-discount) moments so the brand isn't always on sale.
4. Align promos with [INVENTORY_PRIORITIES] (push overstock, protect bestsellers).
5. Note the channel mix and the one headline message per promo.
6. Add a margin check confirming each offer respects [MARGIN_FLOOR].

OUTPUT FORMAT: Calendar table (Week | Date/Moment | Promo type | Mechanic | Channels | Headline | Margin OK?) | Notes on cadence balance.

CONSTRAINTS: No more than [MAX_DISCOUNT_EVENTS] discount-led events in the window. Every offer must clear [MARGIN_FLOOR]. Avoid back-to-back sales that erode urgency.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

Learn this technique
Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

Learn this technique
Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

Learn this technique

Recommended models

claudegpt-4ogemini

Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

Open in Studio How to prompt AI correctly

More in E-commerce & DTC

High-Converting Product Description Architect

Writes a benefit-led product description with scannable structure, sensory hooks, objection handling, and an SEO-aware title.

Read prompt

Abandoned Cart Recovery Email Sequence

Designs a 3-email cart abandonment flow with escalating angles, dynamic product blocks, and revenue-safe discount logic.

Read prompt

Meta Ads Creative Angle Generator

Produces a matrix of distinct ad angles with hooks, primary text, and visual direction mapped to awareness stages.

Read prompt

Customer Review Mining For Conversion Insights

Analyzes raw reviews to extract voice-of-customer language, objections, and themes to feed product pages and ads.

Read prompt