Predictive Lead Scoring
Quick definition
AI models that automatically score leads based on conversion probability, trained on your historical data.
Detailed explanation
Traditional lead scoring uses manual rules (CEO = 20 points, viewed pricing = 15 points, etc). Predictive lead scoring uses machine learning to find patterns in thousands of deals: which combination of attributes (job title, company size, behavior, timing) lead to conversion? The model learns from your won and lost deals and predicts for new leads their probability of converting. This is more accurate than manual scoring because ML finds subtle patterns that humans miss. Tools like HubSpot, Salesforce Einstein, or 6sense have predictive scoring. The advantage is that your SDRs automatically focus on leads most likely to convert, which dramatically increases efficiency. Companies using predictive lead scoring see 30-50% higher conversion rates because effort goes to the right leads.
Synonyms
Examples
A lead has medium job title (VP = 15 pts) and small company (50 employees = 10 pts). Manual score: 25/100 = low priority. But predictive model sees this combo + recent funding + tech stack = 85% conversion probability. Lead gets high score and SDR calls immediately → closed deal.
After 6 months, the model sees that webinar attendees with @gmail addresses convert poorly (5%) despite high engagement scores. Model downweights these leads, so SDRs focus on corporate email addresses with 40% conversion → 3x better efficiency.
When to use this?
Implement predictive lead scoring once you have 500+ historical leads (AI needs data to learn). Use it alongside manual scoring first, validate accuracy, then switch fully. Review quarterly if the model still fits - your ICP can evolve.
Match-day approach
Match-day implements predictive lead scoring in your CRM and ensures it's actually used. We first ensure clean data (garbage in = garbage out), train the model on your won/lost deals, and integrate scores into your SDR workflow. Crucial: we make it actionable - high-score leads go directly to SDR queue with context on why they scored high. We also monitor model performance and retrain quarterly with new data.
Related terms
Marketing Qualified Lead (MQL)(MQL)
A prospect who has shown interest in your marketing but is not yet ready for a sales conversation.
Sales Qualified Lead (SQL)(SQL)
A prospect who has been qualified by sales and is ready for an active sales process.
Predictive Analytics
AI-driven analyses that predict which leads, deals, or actions have the highest chance of success.
Learn more
Wil je weten hoe je predictive lead scoring effectief inzet in jouw organisatie? Neem contact op met Match-day.
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