Example Inputs
Prospect
Ecommerce brand with rising CAC and falling repeat purchase rate
Offer
Email retention strategy and execution
Goal
Confirm urgency and scope of the retention problem
Prepare a discovery call plan with account context, hypotheses, questions, and likely objections.
This prompt helps sellers show up to discovery calls with a stronger point of view. It organizes what to ask, what to test, and what to listen for based on the account and offer context.
Copy-And-Paste Prompt
Works well in ChatGPT, Claude, Gemini. Replace any bracketed variables before you run it.
Variables to customize
Act as a sales strategist preparing high-quality discovery calls. Your task is to prepare a discovery call plan using the account context, offer, likely pain points, and meeting objective. Use these inputs when available: - [Prospect or Account Context] - [Offer] - [Likely Pain Points] - [Goal of the Call] Requirements: - Build a call structure, not only a question list. - Include discovery questions and likely follow-up questions. - Note what signal would indicate a strong fit or weak fit. - Keep the prep focused and easy to use live. Return the answer in this format: 1. Call objective and structure 2. Discovery questions 3. Hypotheses and likely objections 4. Next-step paths depending on the call outcome Tone and style: structured and commercially sharp Ask me concise follow-up questions only if a missing detail would materially change the quality of the final answer.
Prospect
Ecommerce brand with rising CAC and falling repeat purchase rate
Offer
Email retention strategy and execution
Goal
Confirm urgency and scope of the retention problem
Fit signal to listen for: the prospect can already name one or two lifecycle gaps that are clearly affecting repeat purchase behavior, which usually means the problem is concrete enough to solve rather than abstract.
This is a mock example only. Your result should change based on the variables, context, and constraints you provide.
The structure of this prompt is meant to make the AI do more than generate a loose first pass. It frames the model with a role, directs it toward a concrete goal, forces relevant inputs into the request, and asks for a usable output format instead of an open-ended answer.
That combination usually makes the result easier to review, edit, and reuse inside a real workflow. If the first output is still too generic, your best move is usually to add more context rather than abandon the prompt entirely.
These related calculators and guides add more depth when you want to connect this sales prompt to real numbers, strategy, or supporting tools.
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Straight answers to the questions readers usually have before using these prompts.
Replace the bracketed variables with your own context, then add any constraints that matter for your audience, offer, or workflow. The more specific you are about goals, tone, and output format, the stronger the result will usually be.
Yes. The prompt is written in plain English so it works well across major AI assistants. If one model gives an answer that is too short or generic, paste the same prompt back in with an extra sentence telling the model to be more specific.