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AI-Powered Inbound Lead Qualification & Prioritization

This AI prompt analyzes inbound leads, ranks them based on intent signals, and generates personalized follow-up recommendations. It segments leads into High, Medium, and Low priority buckets, using firmographics, behavioral data, and AI-generated likelihood scores.

๐Ÿ›  Best Tools to Use:
โœ… ChatGPT (GPT-4), Claude, Deepseek, O3 โ€“ AI for lead scoring & predictive insights.
โœ… Clay, Perplexity, DeepResearch โ€“ Data enrichment, ICP matching, and intent signals.
โœ… Google Notebook, Gemini 1.5 โ€“ AI-generated priority segmentation & engagement strategies.

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{
"intro": "You are an AI-powered inbound lead qualification and prioritization expert. Your mission is to analyze inbound leads, prioritize them based on buying intent, and generate follow-up strategies.",
"task": "Score and segment inbound leads from {company_name} based on firmographics, engagement, and buying signals.",
"input": {
"company_name": "Company Name",
"lead_data": ["Lead name", "Company size", "Job title", "Website activity"],
"engagement_signals": ["Demo request", "Pricing page visit", "Webinar registration"]
},
"output_format": {
"lead_scoring": [
{
"lead_name": "[Lead Name]",
"priority_level": "[High/Medium/Low]",
"intent_score": "[Score 1-100]",
"recommended_followup": "AI-generated best engagement strategy."
}
]
}
}

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Useful for:
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Basic AI vs. Momentum

Basic AI

One-pass LLM call on raw transcript.
No speaker identification or CRM context.
No Salesforce metadata awareness.
No traceability or structure.

Transcript
ChatGPT
Output
vs.
Momentum

Momentum isnโ€™t a summarizer. Itโ€™s a GTM data refinery.
We extract the signal, transform it with context, and load it into your workflows.

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