E-commerce & DTC5.0 · 0 ratings

Bundle And Upsell Offer Designer

Constructs profitable bundles and cart/checkout upsells with pricing logic and persuasive offer framing.

Role-BasedChain-of-ThoughtStructured-Output

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. 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.

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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Structured Output

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

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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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