Searching the best prompts from our community
Click to view expert tips
Copy to your AI tool
Works with ChatGPT, Claude, Gemini, and more
Fill in placeholders
Replace [brackets] with your specific details
Iterate for perfection
Refine based on output - AI gets better with feedback
You are a Senior Revenue Operations and Customer Insights Strategist. You specialize in conducting rigorous win-loss analysis to identify systemic barriers to growth, refine product-market fit, and optimize sales enablement strategies. Your goal is to synthesize qualitative interview data into actionable, high-impact business intelligence.
To drive sustainable revenue growth and product alignment, our organization is implementing a structured Win-Loss Interview program. The goal is to move beyond anecdotal feedback and uncover the "ground truth" of our buying process. Interviews are conducted 2–4 weeks post-decision by a neutral party (e.g., Product Manager) to ensure emotional neutrality and accurate recall.
Analyze the provided [INTERVIEW_TRANSCRIPTS] and perform the following actions:
Present your analysis in the following structured report:
A proven free prompt for Win-loss interview analysis template is: "Extract insights from won and lost deals. Interview timing: 2-4 weeks after decision (emotions settled, memory fresh). Conductor: neutral party (product manager, not account exec). Questions for wins:..." — You can copy it for free on PromptsVault AI and paste it directly into ChatGPT, Claude, or Gemini.
Click the 'Copy Prompt' button at the top of the page, then paste the text into ChatGPT, Claude, Gemini, or any AI model. You can customize any variables in [brackets] to fit your specific needs before submitting.
Yes — this SALES AI prompt is 100% free on PromptsVault AI. No sign-up or payment required. You can copy and use it for personal or commercial projects with no attribution needed.
This prompt works with all major AI tools — ChatGPT (GPT-4o), Claude 3 (Anthropic), Google Gemini, Grok (xAI), Microsoft Copilot, Perplexity, Mistral, and Llama. The prompt is written in plain language so it's compatible with any large language model.