Lead Magnet Offer Fit

Lead Magnet Offer Fit

Use the shared quality bar in ../references/output-standard.md and ../references/skill-design-principles.md when those files are available.

Use this skill when

• the user shares lead source, CRM stage, sales note, form, landing page or campaign data tied to lead magnet offer fit.
• the next decision could change targeting, qualification, scoring, follow-up, sales handoff or budget.
• lead volume looks acceptable but SQL, opportunity, closed-won, rejection or response-speed data raises doubt.

Do not use this skill for broad lead-generation advice without source, CRM, sales or qualification evidence. Use it when a real B2B lead quality decision is on the table.

Required input

• business model, ICP, offer, ACV or deal value range, sales cycle and main conversion goal.
• ad, landing page, lead form, CRM, call note, email or campaign data relevant to this diagnostic.
• time window, traffic source, lead volume and downstream outcomes where available.
• what decision the user is trying to make next: create, fix, scale, pause, brief sales or investigate.
• If an input is missing, continue with a clearly marked assumption instead of inventing data.

Analysis workflow

1. Classify the asset by buyer stage: problem-aware, solution-aware, vendor-aware or implementation-ready.
2. Compare the promised outcome with ICP pain intensity, buying urgency and the next commercial step.
3. Check whether the asset attracts budget owners, operators, researchers, students or low-intent downloaders.
4. Review the asset title, landing page, form, thank-you step and follow-up for one coherent promise.
5. Score qualification strength using specificity, business pain, implementation effort, proof and follow-up relevance.
6. Recommend keep, sharpen, reposition, gate differently, pair with a stronger CTA or retire.

Decision rules

• If the data does not connect to revenue, pipeline, qualified leads or conversion quality, label the recommendation as a hypothesis.
• If platform metrics and downstream data disagree, trust the downstream source for business quality and platform data for delivery mechanics.
• If the issue could be tracking, offer, audience, page or follow-up, do not collapse it into one cause without evidence.
• Do not recommend more budget until lead quality, follow-up and tracking confidence are separated.

Output format

| Finding | Evidence | Lead quality impact | Recommended action | Confidence | |---|---|---|---|---| | Specific diagnostic claim | Data, screenshot, report, note or missing-data marker | Business or signal consequence | Smallest useful next step and owner | High / Medium / Low |

End with:

• Decision: fix / test / monitor / ask for data / do not act yet
• Approval needed: yes/no and what would change if approved
• Missing data: only the inputs that would materially change the recommendation

Practical example

User: "Here are CRM stages, source data and sales notes for lead magnet offer fit. What should we change before the next campaign move?"

Assistant should: score the magnet on buyer stage, pain relevance, qualification strength and follow-up value, and stop at keep, rework or drop.

Guardrails

• Do not make changes to live campaigns, pages, tags, containers, CRM fields or customer messages.
• Do not claim performance impact without evidence.
• Mark missing data clearly.
• Keep recommendations practical for a performance operator, founder or owner with a real advertising problem.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: mardab96
• Source: mardab96/b2b-lead-generation-claude-skills
• License: MIT

Install and usage instructions live in the source repository linked above.