Intelligent Lead Scoring System for Alkegen
Industry
B2B Manufacturing (Advanced Materials & Industrial Solutions)Focus: AI-Powered Predictive Lead Qualification in Microsoft Dynamics 365
Objective
To transform Alkegen’s global lead management process by introducing a machine learning–based Intelligent Lead Scoring System within Microsoft Dynamics 365, enabling the sales team to focus on high-intent, high-value prospects and streamline the conversion
The challenges
• Large volumes of inbound leads from multiple digital sources (website, campaigns, distributors, events).
• Manual lead scoring was inconsistent and dependent on subjective sales judgment.
• No predictive insight into which leads had the highest conversion or lifetime value potential.
• Sales follow-ups were delayed or misrouted due to lack of lead intent tracking.
• Difficulty aligning marketing-qualified leads (MQLs) with sales priorities.
Our Strategy
1 – Behavioral Pattern Recognition
- Integrated website analytics and campaign engagement data directly into Microsoft Dynamics 365 Customer Insights.
- Tracked behavioral patterns such as:
• Pages visited (e.g., specific product or industry pages).
• Content downloads (data sheets, technical brochures).
• Time spent on site and repeat visits. - Used these engagement metrics to train a machine learning model within Dynamics
365 to recognize behaviors strongly correlated with eventual sales conversions.
2 – Intent Signal Tracking
- Connected Dynamics 365 with LinkedIn Sales Navigator and email marketing
automation to capture buyer intent data. - Tracked early intent signals such as:
• Product inquiry form submissions.
• Repeated views of pricing or case study pages.
• Event registrations or webinar interactions. - Assigned intent-based weights in the scoring model to dynamically update lead
quality in real time.
3- Intent Signal Tracking
- Connected Dynamics 365 with LinkedIn Sales Navigator and email marketing
automation to capture buyer intent data. - Tracked early intent signals such as:
• Product inquiry form submissions.
• Repeated views of pricing or case study pages.
• Event registrations or webinar interactions. - Assigned intent-based weights in the scoring model to dynamically update lead
quality in real time.
4 – Predictive Lifetime Value (LTV) Calculation
- Leveraged historical customer and revenue data in Dynamics 365 Sales Insights to
build an AI model estimating potential LTV. - The model considered:
• Industry segment & company size.
• Deal volume and frequency.
• Historical purchasing patterns and contract renewals. - The LTV score was combined with lead score to prioritize high-revenue potential
accounts and inform marketing spend allocation
4 – Predictive Lifetime Value (LTV) Calculation
- Leveraged historical customer and revenue data in Dynamics 365 Sales Insights to
build an AI model estimating potential LTV. - The model considered:
• Industry segment & company size.
• Deal volume and frequency.
• Historical purchasing patterns and contract renewals. - The LTV score was combined with lead score to prioritize high-revenue potential
accounts and inform marketing spend allocation
The Results
• +42% improvement in Marketing Qualified Lead (MQL) to Sales Qualified Lead (SQL) conversion rate.
• 30% faster response time to high-intent leads through automated routing.
• 25% increase in average deal value due to predictive LTV prioritization.
• Unified lead visibility across marketing and sales teams through a centralized
Dynamics 365 dashboard.
• Significant reduction in manual lead scoring and routing errors.
Key Takeaways
The integration of AI-driven lead scoring within Microsoft Dynamics 365 empowered
Alkegen to convert data into sales intelligence.By aligning behavioral insights, intent data,
and predictive lifetime value in a unified CRM ecosystem, Alkegen achieved:
• Higher efficiency in lead management,
• Better sales forecasting accuracy, and
• Stronger marketing-sales alignment.
Technology Stack
• CRM & Sales Automation: Microsoft Dynamics 365 Sales
• AI & Insights: Dynamics 365 Sales Insights + Azure Machine Learning
• Automation: Power Automate + Power BI for dashboard visualization
• Data Enrichment: LinkedIn Sales Navigator + Web Analytics Integration
• Email Nurturing: Dynamics 365 Marketing
Core Intelligence Features Highlighted
- Behavioral pattern recognition
- Intent signal tracking.
- Automated lead routing.
- Predictive lifetime value modeling.
- Unified sales-marketing dashboard.
Ready to Achieve similar Results?
Available for consulting, full-time opportunities, and strategic partnerships