How Lead Scoring Works
OrbiLattice uses AI to automatically score leads from 0-100, helping you prioritize your time and focus on the hottest opportunities.What is Lead Scoring?
Lead scoring assigns a numerical value (0-100) to each contact based on their likelihood to convert. Higher scores indicate hotter leads that deserve immediate attention.
0-40: Cold
41-70: Warm
71-85: Hot
86-100: Very Hot
Factors in Lead Scoring
Our AI considers multiple signals to calculate lead scores:
- Engagement HistoryEmail opens, clicks, property views, and response rates
- Behavioral SignalsSearch frequency, saved properties, time on site, and viewing patterns
- Profile CompletenessBudget stated, pre-qualification status, timeline clarity
- Activity RecencyRecent interactions weighted more heavily than old ones
- Historical PatternsSimilar leads that converted in the past
Understanding Confidence Levels
Each lead score comes with a confidence percentage showing how certain the AI is about the score:
- High Confidence (90%+)Sufficient data points, clear patterns. Trust this score.
- Medium Confidence (70-89%)Good data but some uncertainty. Monitor for changes.
- Low Confidence (<70%)Limited data or mixed signals. Gather more information.
Why Scores Change
Lead scores are dynamic and update automatically when:
- • Contact interacts with your emails or messages
- • They view properties or save searches
- • Profile information is updated (budget, timeline, etc.)
- • Time passes without engagement (decay)
- • AI learns from similar leads that converted
Best Practices
- Focus on 85+ scores firstThese are your hottest leads with highest conversion probability
- Review 70-84 scores regularlyGood opportunities that need nurturing
- Use automation for <70 scoresSet up drip campaigns to warm them up automatically
- Check 'Why This Score' explanationsAI shows reasoning for transparency and learning
- Override when you have insider knowledgeYour expertise trumps AI—manual overrides are respected
AI Learning & Improvement
The scoring model learns from your outcomes:
• When leads convert, AI identifies patterns that preceded the conversion
• When you manually adjust scores, AI learns your preferences
• Scores become more accurate over time as the system learns your market
• Historical patterns unique to YOUR business inform future scores
Have questions about lead scoring? Contact Support