Healthtech
Company Profile
115,000+ healthcare providers using platform
Leading cloud-based EHR and practice management
5,000+ employees
The Challenge
Rule-based lead scoring lacked nuance and precision
High-potential Marketing Captured Leads (MCLs) deprioritized
Missing valuable signals of readiness before buying intent
Missed revenue opportunities from poor prioritization
The Solution
ML-based lead scoring model with intelligent prioritization
Evaluates firmographic data and engagement signals
Generates "Total Lead Score" for conversion probability
Identifies promising leads early in the cycle
Data Inputs
Firmographic Data
Engagement Signals
Historical Win Data
MarketNext ML Model
Multi-Domain Evaluation
Conversion Probability
Pattern Recognition
Outputs
Total Lead Score
Intelligent Prioritization
~2x Higher Win Rate
ML-Powered Lead Scoring Replacing Rule-Based Approach
The Full Context
The marketing and sales teams needed a more intelligent way to prioritize outreach by identifying which leads were most likely to convert, even before they explicitly showed buying intent for the flagship product. The existing rule-based approach lacked nuance, often overlooking valuable signals of readiness.
As a result, high-potential Marketing Captured Leads (MCLs) were either deprioritized or contacted late in the cycle, leading to missed revenue opportunities. An ML-based lead scoring model was deployed to improve prioritization accuracy and provide deeper visibility into lead behavior across multiple data domains.
The Approach
An ML-based lead scoring model was deployed to transform lead prioritization for the sales development team.
1
Multi Domain Evaluation
Analyzed leads across firmographic data (company size, industry, location) and engagement signals (website visits, content downloads, email interactions) to identify conversion likelihood.
2
Total Lead Score Generation
Calculated the probability that a given lead would result in a successful closed-won deal. This score surfaced promising opportunities early, helping sales reps focus on high-potential prospects.
3
Intelligent Prioritization
Enabled sales development representatives to systematically work the most valuable Marketing Captured Leads (MCLs) first. The MarketNext platform eliminated guesswork.
The Impact
The solution delivered approximately 2x improvement in lead-to-win conversion rate for high-priority leads.
The MarketNext offering eliminated the limitations of rule-based scoring. Sales development representatives gained intelligent prioritization based on actual conversion probability, not arbitrary rules. High-potential Marketing Captured Leads were identified early and engaged at the right time.
The company now operates with data-driven lead management. Sales teams can focus on prospects most likely to close while marketing teams can refine targeting based on what actually drives conversions.
Project Highlights
Solution
ML-based lead scoring
Firmographic + engagement analysis
Total Lead Score metric
Results
~2x lead-to-win rate
Intelligent prioritization
Early opportunity identification
Improved conversion efficiency