Confidence Scores
Every enriched field includes a confidence score (0-100) indicating how reliable the data is. Use these scores to automate workflows and prioritize data quality.
Understanding Scores
High Confidence
Multiple sources agree. Safe for automated CRM updates and outreach workflows. Typically 3+ sources with matching data.
Good Confidence
Strong data with some uncertainty. Good for enrichment, consider review for critical use cases. Typically 2+ sources with agreement.
Medium Confidence
Limited source agreement or stale data. Recommended for display only, with human verification before action.
Low Confidence
Single source or conflicting data. Manual verification required. May be inferred or AI-generated without corroboration.
How Confidence is Calculated
Confidence scores are computed using multiple factors:
Source Agreement
When multiple sources return the same value for a field, confidence increases. 3 sources agreeing = ~95 confidence. 1 source = ~60-75 confidence.
Source Reliability
Each source has historical accuracy ratings. LinkedIn data for job titles scores higher than web-scraped data.
Data Freshness
Recently verified data scores higher. Data from 30 days ago = full score. 6+ months old = reduced confidence.
Cross-Validation
Fields that validate each other increase confidence. Email domain matching company domain = higher email confidence.
Types of Confidence Scores
| Score Type | Scope | Description |
|---|---|---|
confidence_score | Overall | Average confidence across all enriched fields |
email_confidence | Field-specific | Confidence in email address accuracy and deliverability |
persona_confidence_score | AI-generated | Confidence in AI persona matching |
icp_fit_score | AI-generated | How well a company matches your Ideal Customer Profile |
Confidence in API Response
Enrichment responses include confidence data in multiple places:
// Enrichment response structure
{
"data": {
"person": {
"full_name": "Jane Smith",
"title": "VP of Engineering",
"email": "[email protected]"
}
},
// Per-field confidence scores
"confidence": {
"person.full_name": 95,
"person.title": 88,
"person.email": 92
},
// Overall metrics
"metadata": {
"confidence_score": 91, // Average across all fields
"completeness_score": 85, // % of fields populated
"success_rate": 100, // % of sources that succeeded
"sources_used": ["linkedin", "hunter", "perplexity"]
}
}Using Confidence in Automations
Set confidence thresholds to control automatic data updates:
// Only update CRM if confidence is high enough
const enrichmentResult = await abmdev.enrich({
email: "[email protected]"
});
// Check overall confidence before CRM sync
if (enrichmentResult.metadata.confidence_score >= 85) {
await hubspot.updateContact(contactId, enrichmentResult.data);
console.log("Contact updated automatically");
} else {
// Queue for human review
await reviewQueue.add({
contact: enrichmentResult.data,
confidence: enrichmentResult.metadata.confidence_score,
reason: "Below confidence threshold"
});
console.log("Queued for review");
}Recommended Thresholds
- 85+: Safe for automatic CRM updates
- 75+: Good for enrichment display, review before action
- 60+: Display only, human verification required
Improving Confidence Scores
Provide More Input Data
Include LinkedIn URLs, company domains, or full names in your requests. More input = more sources can verify data = higher confidence.
Enable More Sources
Connect LinkedIn via Browserbase for real-time profile data. More sources means more cross-validation opportunities.
Re-enrich Periodically
Data gets stale. Re-enriching contacts every 3-6 months maintains high confidence by catching job changes and updates.