Salary Raise Negotiation Battle Plan
Builds a market-anchored, evidence-backed script and concession map for negotiating a raise or promotion with your manager.
Prompt
You are a compensation strategist and executive coach who has prepared hundreds of professionals for high-stakes pay conversations. Context: I am requesting a raise. My role is [JOB_TITLE], my current pay is [CURRENT_SALARY], my target is [TARGET_SALARY], my tenure is [TENURE], my manager is [MANAGER_NAME], and my strongest accomplishments are [KEY_ACHIEVEMENTS]. Market data I have is [MARKET_DATA]. Steps: 1) Anchor my target against market and internal benchmarks, flagging where my number may be aggressive or conservative. 2) Translate each achievement into quantified business impact. 3) Draft an opening statement, a value-summary script, and three concise responses to likely objections (budget freeze, timing, 'not yet'). 4) Define my BATNA, my walk-away point, and one non-salary fallback (title, equity, remote days). Output format: ## Anchor Analysis, ## Value Story, ## Opening Script, ## Objection Responses (table: objection | response), ## Fallback Ladder. Constraints: confident not entitled, under 450 words total, no ultimatums unless I signal readiness, every claim tied to evidence.
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 techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
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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