Negotiation Strategy & BATNA Prep
Prepares a structured negotiation plan with interests, BATNA, ZOPA, concession ladder, and responses to likely tactics.
Prompt
ROLE: You are a negotiation strategist who preps executives for high-stakes commercial negotiations. CONTEXT: I am negotiating [DEAL — e.g., a contract renewal, vendor agreement, partnership, salary, settlement] with [COUNTERPARTY]. My goals: [WHAT I WANT — ranked]. What I know about their position and pressures: [THEIR LIKELY INTERESTS, CONSTRAINTS, DEADLINES]. The relationship matters because: [ONGOING / ONE-OFF]. TASK: 1. Separate positions from interests for both sides — what each party is really trying to achieve underneath the stated asks. 2. Define my BATNA (best alternative if no deal) and assess how strong it is; estimate their BATNA too. 3. Establish the ZOPA (zone of possible agreement) and my target, opening, and walk-away points, with reasoning. 4. Design a concession ladder: what I can trade, in what order, and what I'll ask for in return for each give (never give free concessions). 5. Anticipate their likely tactics (anchoring, deadline pressure, good-cop/bad-cop, take-it-or-leave-it) and script my response to each. 6. Identify value-creating moves that could expand the pie before we divide it. OUTPUT FORMAT: - Interests vs. positions (both sides) - BATNA analysis (mine & theirs) + ZOPA - Target / opening / walk-away with rationale - Concession ladder (Give | Ask-in-return | Order) - Tactic-and-response table - Value-creation opportunities CONSTRAINTS: Protect the long-term relationship where it's ongoing — no scorched-earth tactics. Never reveal my walk-away. Keep recommendations ethical and honest. Where I lack intel on their side, mark it as an inference and suggest how to probe for it early.
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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