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Lead Scoring 2.0: From Static Models to Dynamic Buyer Intentby@olgaukr
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Lead Scoring 2.0: From Static Models to Dynamic Buyer Intent

by Olga UkrainskayaFebruary 16th, 2025
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Traditional lead scoring systems are based on the assumption that buyers go on a simple, linear journey. Dynamic scoring updates in real-time based on actual buyer behaviour, providing more relevant and actionable insights.
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You have a lead scoring model in your CRM that just simply is not working?


The harsh truth is that your lead scoring system as it stands, is probably broken. You are assigning points for job titles, for the number of times people visit your website, or open your emails, but when your sales team goes to these so-called “hot leads,” a lot of these people are not even interested. Sound familiar?


The problem is that traditional lead scoring systems are based on the assumption that buyers go on a simple, linear journey. The reality is that today’s buyers are much more complex.


By the time a buyer needs a solution, the decision is often already made.


  • They do their homework long before you can even pronounce their name—glossing over reviews, measuring competitors, exploring industry blogs.


  • Their engagement is inconsistent — they may view a lot of content one week and none the next.


  • They may not respond to your emails, but engage with your product often — a clear sign of intent missed by static scoring models.


If you're still relying on static lead scoring, you might be missing out on valuable opportunities.


This is where Dynamic Lead Scoring comes in - a more innovative, real-time approach that prioritizes leads based on what buyers do and intent signals.


This guide will give you some ideas for how to create a dynamic lead-scoring model in your CRM. Then, by using AI, behavioral data, and automation, you can make sure your sales team is spending its time on the leads that are most likely to convert.


Ready to get started? Let’s dive in. 🚀

Static and Dynamic Lead Scoring: What’s the Difference?

Feature

Static Lead Scoring

Dynamic Lead Scoring

Data Sources

Demographics, firmographics, past actions

Real-time engagement, behavioral patterns, AI insights

Updates

Manual, periodic

Continuous, automated

Intent Signals

Clicks, form fills

Product usage, time-sensitive actions, in-market signals

Sales Alignment

Often misaligned

Predictive and relevant


Static models make fixed point assignments (i.e., “10 points for an email open”), whereas dynamic scoring updates in real-time based on actual buyer behavior, providing more relevant and actionable insights.

Step 1: Identify Your Dynamic Lead Scoring Model

When creating a dynamic scoring model, there are three main types of data that you need to focus on:


  1. Fit Score (Who They Are)


    Industry

    Company size

    Job title

    Company Revenue


👉 CRM Setup Tip: If your CRM is missing company data, identify gaps and use enrichment tools to fill them. Next, build workflows to move this data into contacts and create baseline scores and segments against your ICP (Ideal Customer Profile).


  1. Engagement Score (How They Interact With You)


    Visits to your website (e.g. product or pricing pages = high intent)

    Content downloads

    Webinar attendance

    Email interactions

    Social media engagement


👉 CRM Setup Strategy: Use a marketing automation tool like HubSpot, Marketo, Pardot, etc., to track engagement, and automatically update scores dynamically.


  1. Intent Score (How Ready they are to Buy)


    Engagement on the product (especially for SaaS companies)

    Frequent website visits

    Competitor comparisons (activity on G2 or Capterra, etc.)

    High engagement with sales materials (case studies, ROI calculators, etc.)

    More web searches aligning with your product


👉 CRM Setup Hack: Link intent data solutions, such as HubSpot Breeze, 6sense, Bombora, or others to your CRM.

Step 2: Add Scoring Automation in Your CRM

Option 1: HubSpot


  • 3rd Party Data Enrichment: Use ZoomInfo, HubSpot Breeze, Bombora, etc. to track buyer intent outside of your own channels.

  • Establish Scoring Models – Fit, Engagement, and Intent scores should each have their own models.

  • Sales Alerts: Automatically alert SDRs when a lead’s score crosses a threshold.


Option 2: Salesforce


  • Step 1: Turn on Einstein Lead Scoring – Use AI score to score leads.
  • Use Flow Automation: Set up rules to assess leads according to their behaviors.
  • Add Product Analytics: If relevant for SaaS companies, integrate Amplitude or Mixpanel, so product usage can be tracked, thus updating the scores.
  • Set Dynamic Segments: Organize your leads based on their behavior and auto-enter them into nurturing tracks.

Step 3: Move to Adaptive Lead Scoring

Lead scores almost never stay static and decay over time. To keep your model effective:


  • Decay Stale Leads: Subtract points from leads that haven’t acted in over 30 days (change based on longer sales processes).
  • Use Action-Weighted Points: High-intent actions (like demo requests or product searches) are worth much more than email opens.
  • Monitor and Optimize Monthly: Run CRM reports to ensure high-scoring leads are converting.

Step 4: Align Sales & Marketing With Dynamic Scoring

Your lead scoring model must work seamlessly with your sales team’s workflow. Here’s how:


  • Define a “Marketing Qualified” Score (i.e., leads above 80 points trigger a follow-up).
  • Personalized Outreach: Sales should include recent high-intent actions in e-mails (e.g., “I noticed you read our enterprise security case); Let's chat!").
  • Feedback Loop: If sales report back that high-scoring leads are not converting, revise scoring weights accordingly.

Conclusion

If your lead scoring model is failing to deliver the results your sales team needs, it’s probably too rigid for today’s buyers.


Today’s buyers don’t take a linear path — they research on their own, engage in bursts, and decide quickly. Traditional scoring models simply can’t keep pace with that kind of activity.


Choose dynamic, intent-based lead scoring so your sales team only focuses on those most likely to convert. It moves past clunky lead scoring and instead into the realm of real-time engagement and behavioral signals.


So, where do you start?


Assess your existing model: What’s working, and what’s not?


🔝 Target intent signals: Look to buyers with clear readiness signals.

✅ Maintain updated scores: Keep your CRM up to mark with the latest information.

✅ Always iterate: Refine the model with feedback from your sales team.


The shift will not, of course, happen overnight, but even small tweaks can dramatically impact both conversions and pipeline velocity. A well-implemented lead scoring model can thus work for you, not against you.


It’s time to have a look at lead scoring and get it to work for your business in a smarter way.


Would you like to take a stab at answering some of these questions? The link for the template is HERE. Interested in reading the content from all of our writing prompts? Click HERE.