Lead Scoring Model (Sales-Led) - Project Details / Task List
Tag: lead-scoring
Total Hours: 40h
Structure: Single Milestone (<=50h)
Milestone: Lead Scoring Model (Sales-Led)
Description: A strategic and technical implementation project that designs, builds, and deploys a systematic lead scoring model in the CRM/marketing automation platform to prioritize leads based on fit and engagement for a sales-led GTM motion.
Task List: (Lead Scoring) 1. Discovery & Model Build
Contains: Parts 1-2
| Task | Est | Description |
|---|---|---|
| 1. Audit Current Lead Data and Processes | 2.5h | Assess the current state of lead data quality, existing scoring (if any), and the lead handoff process between marketing and sales. End state: Gap analysis document showing what data exists, what's missing, and current pain points. • Pull sample of 50-100 recent leads from CRM to assess data completeness • Inventory available data fields: demographic (title, company size, industry), firmographic (revenue, employee count), and behavioral (page views, email engagement, form fills) • Interview 2-3 sales reps on current lead quality issues and what signals they use to prioritize • Document current MQL definition and handoff process (if any exists) • Identify data gaps that will need enrichment or new tracking |
| 2. Define Ideal Customer Profile (ICP) Criteria | 3h | Establish the firmographic and demographic attributes that define an ideal customer for scoring purposes. End state: Documented ICP criteria with weighted importance for each attribute. • Analyze closed-won deals from past 12 months to identify common attributes • Define primary ICP attributes: industry, company size, revenue range, geography • Define secondary attributes: tech stack, growth signals, funding stage • Create tiered scoring for each attribute (e.g., exact match = 20 pts, adjacent = 10 pts, poor fit = 0 pts) • Validate ICP criteria with sales leadership to ensure alignment |
| 3. Map Behavioral Engagement Signals | 3h | Identify and weight the behavioral actions that indicate buying intent. End state: Documented list of engagement signals with point values assigned. • Catalog all trackable behaviors: website visits, specific page views (pricing, demo, case studies), email opens/clicks, form submissions, content downloads • Classify behaviors by intent level: high-intent (demo request, pricing page), medium-intent (case study download, webinar attendance), low-intent (blog visit, email open) • Assign point values based on intent correlation (e.g., demo request = 50 pts, pricing page = 30 pts, blog visit = 5 pts) • Define negative scoring triggers: competitor company, student email, unsubscribe, bounced emails • Establish time decay rules (e.g., subtract 10 pts for every 30 days of no engagement) |
| 4. Design Scoring Model Architecture | 3.5h | Create the complete scoring model framework combining fit and engagement scores with defined thresholds. End state: Documented scoring model with all criteria, point values, and threshold definitions. • Create combined scoring model: Fit Score (0-100) + Engagement Score (0-100) = Total Score • Define MQL threshold (e.g., Fit Score >= 50 AND Engagement Score >= 25) • Define SQL threshold (e.g., Total Score >= 75 with recent high-intent action) • Document score calculation logic for all attributes and behaviors • Build scoring matrix showing how different lead profiles would score |
| 5. Configure Lead Scoring in CRM/Marketing Automation | 4.5h | Implement the scoring model in HubSpot, Marketo, or Salesforce with all criteria and automation rules. End state: Working scoring system calculating scores for all leads in real-time. • Create custom score fields in CRM (Fit Score, Engagement Score, Total Score, Score Date) • Build scoring rules for demographic/firmographic criteria in marketing automation platform • Configure behavioral scoring triggers for website, email, and form engagement • Set up negative scoring automation (competitor domains, disqualifying titles, time decay) • Create automation to recalculate scores on relevant events |
| 6. Build MQL Threshold Automation and Notifications | 3.5h | Configure automated workflows that trigger when leads cross MQL threshold. End state: Leads automatically flagged as MQL and routed to sales with appropriate notifications. • Build workflow to update lead status to MQL when threshold is met • Configure sales notification (email/Slack) when new MQLs are created • Create lead assignment rules or integration with routing system • Set up re-MQL logic for leads that drop below and return above threshold • Document automation logic for ongoing maintenance |
Task List: (Lead Scoring) 2. Validation & Enablement
Contains: Parts 3-4
| Task | Est | Description |
|---|---|---|
| 7. Validate Scoring Model with Historical Data | 3h | Test the scoring model against historical lead and opportunity data to validate predictive accuracy. End state: Validation report showing correlation between scores and conversion outcomes. • Score a sample of 200+ historical leads (mix of won, lost, and disqualified) • Analyze score distribution: Do won deals cluster at higher scores? • Calculate conversion rates by score band (0-25, 26-50, 51-75, 76-100) • Identify any criteria that are over-weighted or under-weighted • Adjust point values based on analysis findings |
| 8. Conduct Pilot Test with Sales Team | 3.5h | Run a 2-week pilot with a subset of the sales team using the new scoring model. End state: Pilot feedback collected and model adjustments identified. • Select 3-5 reps for pilot program • Brief pilot reps on scoring methodology and how to interpret scores • Have reps work scored leads for 2 weeks and track outcomes • Collect feedback via survey and 1:1 interviews on score accuracy • Document model adjustments needed based on pilot learnings |
| 9. Refine Model Based on Feedback | 2.5h | Make final adjustments to scoring criteria and thresholds based on validation and pilot feedback. End state: Production-ready scoring model with stakeholder approval. • Adjust point values for criteria that pilot identified as over/under-valued • Fine-tune MQL/SQL thresholds if conversion rates are too high or low • Update time decay rules if needed based on actual sales cycle length • Get sign-off from sales and marketing leadership on final model • Document final scoring model configuration for ongoing reference |
| 10. Train Sales Team on Lead Scoring System | 2.5h | Enable the full sales team to understand and effectively use the new lead scoring system. End state: Sales team trained with documentation and able to leverage scores in daily workflow. • Schedule training session (45-60 min) for full sales team • Explain scoring methodology: what fit and engagement scores mean • Demonstrate how to view and filter leads by score in CRM • Provide quick-reference guide showing score interpretation and recommended actions • Address questions and common scenarios (e.g., high fit / low engagement leads) |
| 11. Create Monitoring Dashboards and Reports | 4h | Build dashboards to monitor scoring model performance and lead quality metrics. End state: Live dashboards showing scoring distribution, MQL volume, and conversion rates by score band. • Create lead score distribution dashboard (histogram of current scores) • Build MQL-to-SQL conversion tracking by score band • Set up weekly/monthly report on scoring model health metrics • Configure alerts for anomalies (sudden score inflation, MQL volume spikes) • Document dashboard locations and metrics definitions |
| 12. Document and Hand Off to Client | 4h | Transfer ownership and complete documentation to client RevOps/Marketing Ops team. End state: Client team self-sufficient with admin access, runbooks, and optimization playbook. • Create scoring model documentation: all criteria, point values, thresholds • Document automation workflows and where they live in the platform • Build troubleshooting guide for common issues (score not updating, wrong MQL status) • Provide optimization playbook: how to review and adjust scores quarterly • Transfer admin access and schedule 30-day check-in call |
Summary
- Total Task Lists: 2 (consolidated from 4 Parts)
- Total Tasks: 12 (one per Step)
- Total Hours: 40h
- Generated from: playbook_lead-scoring-model-sales-led.md
- Generated on: 2025-12-31