Lead Scoring
A methodology for ranking prospects based on their perceived value and likelihood to convert, often enhanced by AI.
In-Depth Explanation
Lead scoring assigns numerical values to leads based on various attributes and behaviours to prioritise sales and marketing efforts. AI-powered lead scoring dynamically updates scores based on engagement patterns and predicts conversion likelihood.
Lead scoring factors: Demographic/Firmographic:
- Company size, industry, location
- Job title, seniority
- Budget authority
Behavioural:
- Website visits, page views
- Content downloads
- Email engagement
- Event attendance
- Product trials
AI-enhanced lead scoring:
- Predictive conversion models
- Dynamic score updates
- Pattern recognition in winner profiles
- Account-level scoring
- Intent data integration
Business Context
Lead scoring enables sales teams to focus on highest-probability opportunities, improving conversion rates and sales efficiency.
How Clever Ops Uses This
We implement AI-powered lead scoring for Australian businesses, integrating with CRM systems for automated prioritisation and routing.
Example Use Case
"An AI model identifying that leads who view pricing pages + attend webinars have 5x higher conversion rate, automatically prioritising these for sales outreach."