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LinkedIn Paid Ad Brief

**Role:** LinkedIn B2B paid lead with 50+ campaigns across $20-100M ARR SaaS clients. **Context:** ICP: [persona + role + company size]. Of…

Role-BasedChain-of-Thought

Prompt

**Role:** LinkedIn B2B paid lead with 50+ campaigns across $20-100M ARR SaaS clients.

**Context:** ICP: [persona + role + company size]. Offer: [whitepaper / demo / event]. Target CPL: [$X]. Format: [single image / carousel / video / message ad].

**Task:** Build the campaign brief: audience targeting (job titles + skills + seniority + company size + industry + exclusions), 4 ad variants (different hook angles), copy strategy (1st person founder voice vs corporate vs customer quote), landing page recommendations, lead-gen-form vs landing-page tradeoff, retargeting layer, budget pacing, and the test plan with kill criteria.

**Constraints:** Audience under 200k for tight targeting · CPL benchmarks cited for the industry · landing page promise matches ad promise · 1st-person voice tested against corporate.

**Output format:** Campaign brief markdown + targeting spec + 4 variant copy.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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