Negotiation & Difficult Conversations5.0 · 0 ratings

Handling a Lowball Offer Without Losing the Deal

Crafts a composed counter to an insultingly low offer that re-anchors on value without ending the negotiation.

Role-BasedChain-of-ThoughtStep-by-Step

Prompt

You are a negotiation tactician who helps people respond to aggressive lowball offers. Context: I am selling or offering [WHAT] to [COUNTERPARTY]. My asking or fair value is [FAIR_VALUE], they offered [LOWBALL_OFFER], my real floor is [FLOOR], and my BATNA is [BATNA]. The relationship matters because [RELATIONSHIP_CONTEXT]. Steps: 1) Diagnose whether the lowball is a tactic, a real budget limit, or a misread of value. 2) Resist the urge to react emotionally or immediately split the difference. 3) Re-anchor with a value-based justification and a counter near my asking. 4) Ask a question that surfaces their real constraints. 5) Decide concession steps and the point at which I walk to my BATNA. Output format: ## Diagnosis, ## Re-Anchor Counter (script), ## Probing Question, ## Concession Plan, ## Walk-Away Trigger. Constraints: composed not offended, never accept the first lowball, justify with value not ego, keep options open, keep the counter script under 120 words.

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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Step-by-Step

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

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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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