Write B2B LinkedIn Posts for Your Tech Startup
This prompt helps generate optimized B2B LinkedIn posts for a tech startup, targeting decision-makers with concrete arguments.
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Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
You are a B2B marketing expert for a tech startup. Write a professional LinkedIn post for [COMPANY_NAME], a startup offering [PRODUCT_SERVICE] to [TARGET] (e.g., marketing directors, agencies, sales teams). The post must:
- Hook with a problem or opportunity specific to the tech sector (e.g., customer acquisition cost, long sales cycles, scalability).
- Use an authoritative yet accessible tone, with technical vocabulary but not too much jargon.
- Incorporate a specific B2B lever: social proof (e.g., client, revenue), value demonstration (e.g., ROI, time savings), or market insight.
- Include a clear call-to-action: download a whitepaper, request a demo, sign up for a webinar, etc.
- Be 150-250 words, with short paragraphs and discreet emojis.
Here is the post topic: [TOPIC].
Bonus: add 2-3 lines of (simulated) comments that credible prospects might leave, to boost engagement.
Write the post in English.
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Why this prompt works
<p>This prompt is designed for tech startups that want to publish engaging LinkedIn content without spending hours. It forces structuring the post around a real problem or opportunity in the sector, increasing relevance for B2B leaders.</p><p>To use it, fill in the variables <strong>[COMPANY_NAME]</strong>, <strong>[PRODUCT_SERVICE]</strong>, <strong>[TARGET]</strong>, and <strong>[TOPIC]</strong>. For example: [Acme Analytics], [a predictive scoring platform], [SaaS marketing directors], [How to reduce churn by 30% with AI].</p><p>The prompt includes precise instructions on tone, vocabulary, and B2B levers (social proof, ROI, insight). The call-to-action is mandatory to generate leads. Tip: vary topics to test engagement.</p>
Use Cases
Expected Output
A complete LinkedIn post, ready to publish, with hook, structured body, call-to-action, and optionally simulated comments.
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