AI Summary
AI Sales Assistant Prompt Documentation
AI Summary (Functionality Breakdown)
1. Lead Quality Score
Quantifies lead’s potential value (0–100).
Based on:
Platform/source trustworthiness
Engagement metrics (time to response, interaction depth)
Keyword relevance
Similar conversion behavior
2. Conversion Probability (%)
Predicts the chance of the lead converting into a sale.
Uses:
Historical campaign and CRM data
Frequency and type of communication
Persona alignment
3. Lead Summary & Journey
100-word overview including:
Source (e.g., Instagram ad)
Timeline of actions (form submitted, chat started, etc.)
Interaction details (missed calls, WhatsApp replies)
Engagement flags (budget range, signals of disinterest)
4. Ideal Persona Mapping
Matches the lead to successful past clients.
Highlights:
Common traits (age, location, interest)
Red flags or mismatch points (budget gap, wrong product category)
5. Next Best Communication Step
Recommends:
Channel (WhatsApp, Call, Email)
Time (e.g., weekday mornings)
Messaging tone (e.g., empathetic, urgent)
CTA (action-oriented message)
6. Conversion Playbook
Custom tactics to improve conversion odds:
Name-based personalization
Targeted offers
Multichannel outreach plans
7. Learn from Similar Conversions
Uses deal closure data from similar cases to:
Identify potential objections
Recommend the best-fit plan
Predict deal value
Use Cases
Sales agents analyzing inbound leads.
CRM systems automating follow-up strategies.
Marketing teams designing retargeting flows.
Business owners monitoring campaign ROI by lead quality.
Benefits
Reduces manual qualification effort.
Speeds up response with optimal channel and timing.
Helps improve conversion through personalization and smart targeting.
Learns continuously from past successes.
Last updated