Predictive Lead Scoring: How to Let Your CRM Decide Who You Call First
Stop treating every lead equally. Learn how to set up behavioral and demographic lead scoring so your sales team only talks to hot prospects.
If your sales team is treating a CEO who downloaded three whitepapers and visited your pricing page the same as a student who accidentally clicked a Facebook ad, you are losing money. It is time to implement lead scoring.
What is Lead Scoring?
Lead scoring is a methodology used to rank prospects against a scale that represents the perceived value each lead represents to the organization. The resulting score is used to determine which leads a receiving function (e.g. sales, partners, teleprospecting) will engage, in order of priority.
Implicit vs. Explicit Data
A robust lead scoring model uses two types of data:
- Explicit Data (Demographic/Firmographic): Information the lead gives you. Job title, company size, industry, revenue. (e.g., +15 points for "Director" title).
- Implicit Data (Behavioral): Information you track. Website visits, email opens, webinar attendance. (e.g., +10 points for visiting the pricing page, +5 points for opening an email).
Building Your Scoring Thresholds
Once points are assigned, you create thresholds. For example:
- 0-40 Points (Cold): Marketing continues to nurture via automated email sequences. Sales does not touch.
- 41-79 Points (Warm): Marketing Qualified Lead (MQL). A junior SDR might reach out via email or LinkedIn.
- 80+ Points (Hot): Sales Qualified Lead (SQL). The CRM instantly alerts a senior account executive to call immediately.
Don't forget negative scoring! Subtract points if a lead visits the "Careers" page (likely a job seeker) or if their email bounces.