Library/Prospecting & Pipeline Creation/Lead Sourcing & List Building/Generate B2B Contact Discovery Keywords
TestedProspecting & Pipeline CreationSame-Day Use (under 30 min)
About this prompt
This prompt generates a structured set of B2B contact discovery keywords organized across six dimensions — job title variations, industry terms, solution keywords, pain-point indicators, company descriptors, and intent signals. It is built for SDRs, BDRs, and sales operations teams who need to optimize lead sourcing searches in platforms like LinkedIn Sales Navigator, ZoomInfo, or Apollo. Use it when starting a new prospecting motion and need a keyword library before building your first search.Lead sourcing platforms return widely different results based on how you frame your searches — this prompt produces three tiers of keyword strings per dimension: broad, precision, and ultra-targeted. That three-tier structure lets you balance pipeline volume against qualification quality depending on where you are in your quota cycle. Because the prompt takes no variables, the output is general-purpose — the real value is in using the output as a starting list and pruning it to your specific ICP before feeding it into a platform search. Use this when standing up a new prospecting motion from scratch or when current searches are returning poor-fit results. Avoid using the ultra-targeted strings as your only source — they narrow the addressable pool so far that high-volume outreach becomes impossible.The prompt
<role> You are a Prospect Intelligence Keyword Architect. </role> <context> The goal is to complete the following task with high precision, clear structure, and practical usefulness. </context> <task>
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Variables to replace
How to run it
- Copy the prompt and paste it into Claude, ChatGPT, Gemini, or Copilot — it's tuned to run in any of them.
- Replace the variables — swap each bracketed token for your deal's specifics. The variables list above explains every field.
- Make it yours — run it, keep what's strong, and tighten your inputs on the next pass. The prompt improves with your context.
What good output looks like
Make it yours
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