Lead Scoring Setup Guide
Build an effective lead scoring model using Scrapine enrichment data. Score leads by firmographic fit, engagement signals, and data quality for better prioritization.
Overview
Lead scoring helps your sales team focus on the prospects most likely to convert. This guide shows you how to build a scoring model using Scrapine’s enrichment data, combining firmographic fit, intent signals, and data quality into a single actionable score.
Step 1: Define Your Scoring Criteria
Start with the attributes that correlate most strongly with closed deals. Review your last 50 won opportunities and identify common patterns. Typical firmographic criteria include company size, industry, technology stack, funding stage, and geography. Intent criteria include hiring signals, technology adoption, and recent company growth.
Step 2: Assign Point Values
Create a points-based system where each attribute contributes to a total score. High-impact attributes like matching your target company size should carry more weight than nice-to-have attributes. A sample framework: company size match (20 points), industry match (15 points), title seniority match (15 points), technology stack match (10 points), hiring signal (10 points), verified email (10 points), verified phone (10 points), recent funding (10 points).
Step 3: Configure Scrapine Enrichment for Scoring
Ensure Scrapine enriches every lead with the fields your scoring model requires. Set up enrichment rules to capture company size, industry, technology stack, recent funding events, and hiring activity. Each enriched field feeds directly into your scoring calculation.
Step 4: Implement the Score in Your CRM
Map Scrapine’s enrichment fields to your CRM and configure a calculated field or workflow that computes the lead score. In Salesforce, use a formula field. In HubSpot, use a custom score property. Set thresholds for hot, warm, and cold leads based on score ranges.
Step 5: Route Based on Score
Configure your CRM or sales engagement tool to route leads based on their score. Hot leads get immediate SDR attention and fast-tracked sequences. Warm leads enter standard cadences. Cold leads are placed in nurture campaigns or deprioritized. This routing ensures your team’s energy goes to the highest-potential prospects.
Step 6: Calibrate and Iterate
Review your scoring model monthly. Compare scores against actual conversion data. If high-scoring leads are not converting, adjust the weights. If low-scoring leads are winning, investigate what attributes you are missing. Scoring models improve continuously with real outcome data.