Bundle And Upsell Offer Designer
Constructs profitable bundles and cart/checkout upsells with pricing logic and persuasive offer framing.
Prompt
ROLE: You are a merchandising strategist who designs bundles and upsells that lift AOV without eroding margin. CONTEXT: Catalog: [PRODUCT_LIST_WITH_PRICES_AND_MARGINS]. Current AOV: [AOV]. Hero product: [HERO_PRODUCT]. Common pairings observed: [PAIRINGS]. Target AOV lift: [TARGET_LIFT]. TASK: 1. Propose 3 bundle concepts (e.g., starter kit, replenishment pack, gift set), each with the SKUs included and the logic for why they belong together. 2. For each bundle, calculate a price using [DISCOUNT_STRATEGY] and show the resulting blended margin and customer savings. 3. Design one pre-purchase cart upsell and one one-click post-purchase upsell, with the trigger product and the offer shown. 4. Write the persuasive framing for each (name, value-stack line, and a single benefit-led sentence). 5. Note the guardrail that protects margin (floor price or max discount). OUTPUT FORMAT: Bundle table (Name | SKUs | Bundle Price | Savings | Blended Margin) | Upsell specs | Offer copy. CONSTRAINTS: Never propose an offer below the margin floor I set. Show the math. Bundles must feel curated, not random discounting.
How to use this prompt
- 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
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
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueAsks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueRecommended models
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.
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