Customer Scoring
When your lead pool grows, the key problem is not finding more accounts. It is deciding which ones deserve rep time first. AlineGPT combines rules and AI scoring to solve that.
Best For
- Sales leaders
- BD teams
- Growth teams managing lead routing
Use Cases
- Lead segmentation
- Rep assignment
- Opportunity prioritization
Why It Stands Out
- Looks at both static fit and dynamic behavior
- Supports customizable scoring logic by business model
- Turns scores directly into rep routing and cadence choices
Inputs and Outputs
Inputs
- Industry fit
- Job seniority
- Market priority
- Behavior signals
Outputs
- Lead scores
- Priority tiers
- Follow-up suggestions
- Routing rules
How It Works
Define score dimensions
Set weights for fit, seniority, market, and behavior.
Calculate scores
Apply rules and AI signals to each lead.
Create priority tiers
Group leads into high, medium, and nurture categories.
Trigger next actions
Use tiers to route, sequence, and prioritize outbound.
Reusable Assets
Scoring Template
Field template for fit, title weight, and buyer intent.
Role Mapping
Priority guidance for decision-makers, champions, and users.
Action Matrix
Recommended actions by score band.
Frequently Asked Questions
What does customer scoring use?
Typical inputs include industry fit, job seniority, market priority, engagement signals, and historic interactions.
Can the scoring model be customized?
Yes. You can adjust weights based on deal size, cycle length, and team strategy.
How do teams act on scores?
High-score leads go to reps first, while lower-score leads can enter nurture or re-qualification flows.