Marketing-to-Sales Lead Quality Auditor
Audit lead quality and handoff failures to fix poor-fit patterns and improve conversion rates with evidence-based diagnostics.
Customise & copy
Add the context you have. The prompt updates as you work.
Describe the campaign context and targeting parameters.
Provide lead information and demographic/firmographic data.
Detail the qualification data and scoring models used by marketing.
Include sales acceptance or rejection reasons with notes.
Provide downstream opportunity outcomes and conversion data.
Live prompt
5 fieldsAnalyze the provided marketing and sales data to audit lead quality and campaign handoffs. Identify information gaps, poor-fit patterns, and handoff failures between marketing and sales based strictly on the provided evidence. Campaign Context & Targeting: {{campaign_context}} Lead Information & Firmographics: {{lead_data}} Marketing Qualification Criteria & Scoring: {{qualification_criteria}} Sales Feedback & Rejection Reasons: {{sales_feedback}} Downstream Opportunity Outcomes: {{downstream_outcomes}} Provide a structured diagnostic report following this format: 1. Lead Quality Issues: Categorize recurring patterns of unqualified leads reaching sales. 2. Qualification & Handoff Failures: Identify ambiguous criteria driving false positives and specific information gaps during handoffs. 3. Evidence-Backed Recommendations: Provide concrete, actionable changes for marketing qualification rules, lead routing logic, and required handoff fields derived solely from the provided data.
Proof before you use it
A real example
Tested on gemini-3.1-flash-lite on 2026-09-06
{
"lead_data": "45 demo requests. 40% from hospitals with over 1,000 beds. Rest from student researchers or IT helpdesk technicians.",
"sales_feedback": "Account Executives noted a lack of technical requirements context and no indication of current compliance framework in the handoff notes.",
"campaign_context": "Google Search PPC campaign targeting 'cloud security compliance software' aimed at CISOs and IT Directors in Healthcare.",
"downstream_outcomes": "45 demos booked; 18 disqualified immediately due to lack of cloud infrastructure; 27 active pipeline but stalled due to unverified security budgets.",
"qualification_criteria": "Scoring model assigns 100 points for demo form submission regardless of company type or verification of buyer persona."
}A small ritual that works
How to use it
- 01Gather your campaign context, lead data, and sales rejection notes.
- 02Paste the data into the corresponding prompt variables.
- 03Run the prompt to generate the diagnostic report.
- 04Implement the recommended changes to your qualification scoring and routing logic.
Why it works
The prompt structures an analytical audit by breaking down lead quality, qualification/handoff failures, and evidence-backed recommendations based on explicit data inputs (campaign context, lead data, scoring criteria, sales feedback, and downstream outcomes). This forces a systematic diagnosis of misalignment between marketing outputs and sales requirements without relying on generic assumptions.
Where it fails
INSUFFICIENT_EVIDENCE
Customisation tips
Adapt the diagnostic report categories and required handoff fields to match your specific CRM schema, product category, and pipeline stages. Ensure that the recommendations section strictly references the exact metrics, feedback notes, and conversion data supplied in your variables.
Watch-outs
- Do not invent percentages, personas, firmographic thresholds, or rejection reasons not present in the input variables.
- Ensure all recommendations are strictly derived from the provided evidence rather than standard industry best practices.
- Avoid making assumptions about target account size or budget limits unless explicitly stated in the campaign context or lead data.
Works in
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