Free Lead Scoring Model Builder
Build a lead scoring model that separates high-intent buyers from tyre-kickers. Define demographic and behavioral criteria, set your MQL threshold, and test sample leads -- so your sales team focuses on the prospects most likely to close.
Custom Criteria
Define demographic and behavioral scoring criteria with customisable point values from 1 to 10
Test Sample Leads
Score sample leads against your model and see instant MQL qualification results
Export Rubric
Copy your complete scoring rubric to clipboard and implement it in your CRM or marketing automation
How it works
Demographic Scoring
Score leads based on who they are -- job title, company size, industry, and revenue
Add Demographic Criterion
Behavioral Scoring
Score leads based on what they do -- page visits, content downloads, event attendance, and demo requests
Add Behavioral Criterion
MQL Threshold
Set the minimum total score a lead must reach to qualify as a Marketing Qualified Lead (MQL)
Your Scoring Rubric
Full lead scoring model summary
Demographic Criteria
Behavioral Criteria
Score Ranges
Test a Sample Lead
Select which criteria a sample lead matches and see their total score and MQL status
Demographic Matches
Behavioral Matches
Need Help Building a Lead Scoring System?
Our GTM experts can help you implement lead scoring in your CRM, set up automated MQL routing, and optimise your sales-marketing handoff.
Frequently Asked Questions
Everything you need to know about building and implementing a lead scoring model
What is lead scoring and why does it matter for B2B SaaS?
Lead scoring is a methodology for ranking leads based on their likelihood to convert into paying customers. It assigns numerical values to leads based on two dimensions: demographic fit (who they are) and behavioral engagement (what they do). For B2B SaaS companies, lead scoring matters because it helps sales teams prioritise high-intent leads, reduces time wasted on unqualified prospects, and improves conversion rates by ensuring the right leads get the right follow-up at the right time. Our outbound sales system setup includes lead scoring implementation.
What is the difference between demographic and behavioral lead scoring?
Demographic scoring evaluates who a lead is -- their job title, company size, industry, annual revenue, and geography. It measures fit with your ideal customer profile (ICP). Behavioral scoring evaluates what a lead does -- visiting your pricing page, downloading content, attending webinars, or requesting demos. It measures intent and engagement. The most effective lead scoring models combine both dimensions, because a perfect-fit prospect who shows no engagement is just as unlikely to convert as a highly engaged lead who does not match your ICP.
What is an MQL threshold and how do you set one?
An MQL (Marketing Qualified Lead) threshold is the minimum score a lead must reach before being passed to sales for follow-up. Setting the right threshold requires balancing quality and volume. Too high, and sales does not get enough leads. Too low, and sales wastes time on unqualified prospects. Most B2B SaaS companies start by setting the MQL threshold at 40-60% of the maximum possible score, then adjust based on sales feedback and conversion data. Our SDR as a Service team can help calibrate your thresholds.
Which lead scoring criteria should I use for B2B SaaS?
For demographic scoring, the most impactful criteria are job title and seniority (decision-makers score highest), company size (matching your ICP sweet spot), industry vertical, and annual revenue. For behavioral scoring, high-intent actions like requesting a demo, visiting pricing pages, and starting a free trial should receive the highest points. Medium-intent actions like downloading whitepapers and attending webinars score moderately. Low-intent actions like opening emails or visiting blog posts score lowest. Weight your criteria based on historical conversion data whenever possible. Read our guide on lead generation strategies for B2B SaaS for more detail.
How many points should each lead scoring criterion be worth?
Most lead scoring models use a 1-10 point scale per criterion. High-intent signals like demo requests and pricing page visits should score 8-10 points. Strong ICP fit indicators like matching job title and company size should score 7-9 points. Medium-intent signals like content downloads and webinar attendance score 5-7 points. Low-intent signals like email opens and social media engagement score 1-3 points. The key is relative weighting -- ensure your strongest buying signals score significantly higher than passive engagement signals.
How do I implement lead scoring in my CRM?
Most modern CRMs (HubSpot, Salesforce, Pipedrive) and marketing automation platforms (Marketo, Pardot, ActiveCampaign) have built-in lead scoring features. Start by defining your scoring criteria and point values using a tool like this builder. Then configure the scoring rules in your CRM, mapping each criterion to the relevant data fields and tracking events. Set up automated workflows to flag leads when they cross the MQL threshold and route them to sales. Our outbound sales system setup service handles the full CRM configuration.
Should lead scores decay over time?
Yes, implementing score decay is a best practice. A lead who downloaded a whitepaper six months ago but has shown no engagement since is less likely to convert than one who downloaded it last week. Common decay rules include reducing behavioral scores by 10-20% per month of inactivity, resetting specific action scores after 90 days, and applying a blanket decay after 180 days of no engagement. Demographic scores typically do not decay unless the lead's company or role changes. Score decay ensures your MQL pipeline stays fresh and reflects current buying intent.
How often should I review and update my lead scoring model?
Review your lead scoring model quarterly at minimum. Track key metrics including MQL-to-SQL conversion rate (target 30-50%), MQL-to-opportunity rate, and average sales cycle length for MQLs versus non-MQLs. If MQL-to-SQL conversion drops below 20%, your threshold is too low or your criteria need recalibrating. If sales complains about lead quality, increase the weight of high-intent behavioral signals. If marketing cannot generate enough MQLs, consider lowering the threshold or adding new engagement criteria.
Related Resources
Deepen your lead scoring and GTM strategy knowledge
Outbound Sales System Setup
Get your CRM, lead scoring, and outbound sequences configured by GTM experts for predictable pipeline.
Learn More →SDR as a Service
Outsource lead qualification and prospecting to trained SDRs who follow your scoring model.
Learn More →Lead Generation Strategies for B2B SaaS
Proven strategies for generating high-quality leads that score well and convert to revenue.
Read Article →Lead Gen Cost Calculator
Calculate your cost per lead across channels and optimise your lead generation budget.
Use Calculator →Pipeline Velocity Calculator
Measure how fast qualified leads move through your pipeline to closed-won.
Use Calculator →Get Custom Lead Scoring Help
Book a consultation for personalised lead scoring implementation and CRM configuration.
Book Call →Need Help Implementing Lead Scoring in Your CRM?
Our GTM experts have built lead scoring models for hundreds of B2B SaaS companies. Get a free 30-minute consultation to review your scoring criteria, MQL thresholds, and sales-marketing handoff process.
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