TruSQL™ Scoring
TruSQL is Rover Insights' proprietary 0–100 lead scoring system that combines ICP match quality, buyer intent signals, and real conversation sentiment into a single, explainable score. Your rep sees exactly why each lead scored high or low, with AI-generated next steps.
Five Steps to a Score You Can Trust
Your rep opens a new lead. She sees a score of 84. Below it, three sentences explain exactly why: ICP match, buying timeline under 6 months, and strong positive sentiment from last week's call. Here's how that score got there.
Define Your ICP
You tell Rover Insights what your ideal buyer looks like: target job titles, company sizes, industries, and product needs. This becomes the anchor for Match Quality scoring, the largest weight in TruSQL at 40%.
Conversation Happens
The Rover Insights CDR team conducts a 6–12 minute phone conversation with the prospect. They capture pain points, feature needs, buying timeline, budget availability, current solution satisfaction, and decision-maker role.
AI Analyzes the Call
An AI workflow processes the full call transcript. It extracts structured data: sentiment analysis, buying signals, competitive intelligence, and feature priorities categorized as High, Medium, or Low importance.
Score Generates
TruSQL combines three weighted components into a 0–100 composite: Match Quality (40%), Buyer Intent (35%), and Call Sentiment (25%). The score updates with each new conversation, so it reflects the latest reality.
Rep Gets Context
Your rep opens the lead and sees the score, a plain-English explanation of why it scored that way, and AI-generated recommended next steps. No guessing. No black box. They know exactly what to say on the first call.
Three Components.
Fully Transparent.
Match Quality
How closely the lead matches your defined Ideal Customer Profile. Job title, company size, industry, management level, product needs, and geography all factor in. A Director of HR at a 500-employee company looking at HRMS scores differently than a junior analyst at a 20-person firm.
What Feeds This Component
- •Job title and function alignment
- •Company size (11 tiers from 4 to 10,000+)
- •Industry match (primary and secondary)
- •Management level and buying authority
- •Product needs overlap with your verticals
Buyer Intent
Behavioral signals captured during the conversation. Not web clicks. Not whitepaper downloads. Real statements from the prospect about their buying timeline, budget availability, demo interest, and current solution satisfaction. A buyer who says "we need to switch by Q3" scores differently than "we might look next year."
What Feeds This Component
- •Buying timeframe (Immediately to 24+ months)
- •Budget availability
- •Demo interest expressed
- •Current solution satisfaction rating
- •Competitive evaluation status
Call Sentiment
AI-analyzed tone and engagement from the actual phone conversation. Strong Positive through Strong Negative, measured across the full call. Sentiment updates with each new conversation. A prospect who was neutral in January but frustrated in April reflects that shift in their score.
What Feeds This Component
- •Overall conversation tone (5-point scale)
- •Engagement level during call
- •Sentiment trend across multiple calls
- •Specific pain point intensity
- •Openness to next steps
What Your Rep Actually Sees
A number alone doesn't close deals. Context does.
TruSQL Score
Why This Score
“This lead scored 84 because they match your ICP (Director of HR, 800 employees, evaluating HRMS), expressed urgency during their call with a buying timeline under 6 months, and rated their current solution 2 out of 5.”
Recommended Next Steps
- →Lead with their top pain point: reporting limitations
- →Reference their 6-month timeline and budget readiness
- →Offer a focused demo on the analytics module they mentioned
Not a Black Box
Most lead scores are a single number with no explanation. TruSQL shows the full breakdown. Your rep knows this lead scored 84 because of ICP match, not just that they "seem interested." When reps trust the score, they act on it faster.
Dynamic, Not Static
TruSQL scores update with every new conversation. A prospect who was lukewarm in January but frustrated with their current vendor in April reflects that change. Static intent scores from three months ago miss the shift.
Built From Conversations
Intent data platforms score behavior: page views, downloads, ad clicks. TruSQL scores what buyers actually say during 6–12 minute phone calls. Pain points, budgets, timelines, competitor mentions. First-party data from real conversations, not third-party web behavior.
Actionable Next Steps
Every scored lead comes with AI-generated recommended next steps. Not generic "follow up soon." Specific guidance: lead with their top pain point, reference their timeline, offer the demo module they asked about. Your rep picks up the phone prepared.
What the Numbers Mean
Color-coded urgency so your team prioritizes the right conversations first. Every score comes with context your rep can act on.
High ICP match, strong buying signals, positive call sentiment. Your rep should prioritize these leads. Each one arrives with verified ICP fit, stated buying intent, and positive call engagement.
Recommended Action
Prioritize outreach within 24 hours
Partial ICP match or mixed signals. The prospect might fit your profile but has a longer timeline, or they are in-market but at a company slightly outside your sweet spot. Worth working, but not top priority.
Recommended Action
Add to nurture sequence, revisit after next call
Low ICP match, minimal buying signals, or negative sentiment. These leads either don't match your target profile or aren't in a buying cycle. Rover still delivers them with full context so you can make the call.
Recommended Action
Deprioritize or exclude from active outreach