Lead scoring
Prioritize leads with directional AI scoring
FEIJIALE AI scores leads from your uploaded data, configured fit rules, and available context. The score helps route attention; it does not replace rep judgment.
Signals
Six categories shape each score
The scoring model is designed to make reasoning visible enough for reps and managers to audit.
Role fit
Job title and function alignment with your target buyer.
Industry
Company category and vertical tags from provided lead fields.
Region
Territory grouping for coverage and routing.
Intent notes
Signals present in the uploaded record or compliant public context.
Data quality
Completeness, duplicate checks, and missing field flags.
Rep context
Notes, status, previous outreach, and manual adjustments.
Score bands
Simple bands for daily sales workflow
High
Review first
Strong fit or intent signals. Recommended for prompt human review and personalized follow-up.
Medium
Queue with context
Some fit signals are present. Reps can enrich or route based on territory and workload.
Low
Hold or nurture
Limited fit or incomplete data. Keep for later review, enrichment, or suppression rules.
After scoring
Move from signal to next action
High-priority leads can flow into follow-up suggestions, task queues, owner routing, and pipeline updates. Managers can review score rationale and adjust workflow rules as data quality improves.
AI-generated recommendations remain drafts until a rep reviews them.