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Content Matchmaker

The right case study, deck, or one-pager for every deal — instantly

Your content library has hundreds of assets. Your reps use five. This skill matches the right content to each deal based on industry, stage, persona, and competitive situation — so the perfect case study surfaces when a prospect asks "do you have a customer like us?"

House RecipeWork10 min setup

INGREDIENTS

📄Google Docs🔎Web Search

PROMPT

Create a skill called "Content Matchmaker". Index my content library across [Google Drive, SharePoint, etc.]. Auto-tag each asset by: industry, persona, deal stage, company size, use case, and competitive context. When I ask "what should I send for [deal or prospect]?", recommend the top 3 most relevant assets with a one-line explanation of why each fits. Auto-recommend content when deals hit key stages (e.g., case study after demo, ROI calculator at proposal). Detect gaps: alert me when a deal's attributes have no matching content. Track: which assets get sent, which get opened, and which appear in closed-won deals. Monthly report: top performing content, biggest gaps, and stale assets needing updates.

How It Works

Index your entire content library and the skill builds a recommendation engine. For

any deal, it matches relevant content based on deal attributes. Ask "what should I

send this healthcare CFO after a demo?" and get specific answers, not a search results page.

What You Get

  • Semantic search across all content repositories (Google Drive, SharePoint, etc.)
  • Deal-context matching: industry, persona, stage, company size, competitive situation
  • Automatic recommendations when deals hit key stages
  • Content gap detection: "you have no case studies for healthcare mid-market"
  • Usage tracking: which content gets sent and which influences closed-won deals
  • Freshness alerts: flag content older than 6 months for review

Setup Steps

  1. Connect your content repositories or upload/export the assets you want indexed
  2. Tag or let AI auto-tag content by industry, persona, stage, and use case
  3. The skill indexes everything and builds a recommendation model
  4. Start asking: "what should I send for [deal]?"

Tips

  • Content that matches prospect's exact industry + company size converts better
  • Auto-recommend case studies when deals enter Proposal stage
  • Use gap detection to prioritize new content creation
  • Track which content appears in closed-won deals — double down on what works
Tags:#sales-enablement#content#deals#productivity

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