CRM Lead scoring
Lead scoring setup for HubSpot and Salesforce
Optimize SDR output using criteria queues.
Prioritizing leads based on firmographic and behavioral signals.
Not every lead deserves the same response. Lead scoring ranks leads by how well they fit your ideal customer and how strongly they have shown interest, so sales works the best opportunities first and marketing nurtures the rest. Done well, it shortens response times on the leads that matter and gives ad platforms a better signal of quality.
We build lead scoring in HubSpot, Salesforce and other CRMs from your own won and lost deals: fit criteria such as company size, industry, role and budget; engagement signals such as pricing-page visits and demo requests; and quality checks at the form itself — valid phone numbers, business email domains and suspicious submissions.
The problem
Sales teams manually prioritize leads, causing them to miss hot opportunities while calling cold accounts.
What we do
- Define lead grading rules
- Configure lead score calculators in CRM
- Build behavioral scoring rules
- Train SDRs
What you get
- Lead grading worksheets
- CRM calculator setups
- Lead routing alerts
- Team training guides
Automatic lead scoring in the CRM that prioritizes hot buyers for immediate calls.
How it runs
- Identify Signals. We research customer logs to find actions (e.g. viewing pricing) that predict won deals.
- Configure CRM. We build calculated fields in the CRM to score leads automatically.
- Setup Alerts. We build notifications to alert reps when a lead score crosses target thresholds.
- Review Quotas. We monitor lead conversion rates to update and refine scoring rules.
Who this is for
- B2B and high-value B2C teams receiving more leads than sales can handle well
- Companies where sales distrusts marketing's MQLs
- Teams sending lead quality signals back to Meta, Google or LinkedIn
- Businesses struggling with spam, fake or junk form submissions
What's included
- Analysis of won and lost deals to identify predictive fit and engagement signals
- Fit and engagement scoring models with negative scoring
- Form-level quality checks and spam filtering
- MQL and SQL definitions and thresholds agreed with sales
- Routing and SLA rules by score
- Score-based audiences and conversion signals for ad platforms
Fit and engagement are different questions
A lead can be a perfect fit and not yet interested, or very engaged and a poor fit. Combining both into one number hides that distinction. We score fit and engagement separately — often as a grade and a score — so a well-fitting but quiet lead goes to nurture, a highly engaged poor fit is handled efficiently, and the leads strong on both go to sales immediately.
The criteria come from your data, not a template: which attributes and behaviours actually appear more often in won deals than lost ones. Our B2B lead scoring playbook shows the analysis.
Scoring quality at the form
Some low-quality leads can be caught before they reach the CRM: invalid or disposable emails, fake phone numbers, implausible answers, repeated submissions and bot patterns. Filtering those at the form protects sales time and, just as importantly, stops junk leads from being reported to ad platforms as conversions — which would teach the platforms to find more of them.
Scoring lead quality at the form
Automatic scoring rules mapped directly in HubSpot or Salesforce.
Ad platforms optimize for raw lead volume rather than lead quality, driving up spends on unqualified signups.
- Map CRM deals back to ad platforms
- Feed quality signals to ad networks
- Configure offline conversion syncs
- Build lead score rules
Frequently asked questions
What is lead scoring?
A method of ranking leads by how well they fit your ideal customer and how much interest they have shown, so sales can prioritise the best opportunities.
Can HubSpot and Salesforce do lead scoring?
Yes. Both offer lead scoring tools — HubSpot through its lead scoring features and Salesforce through Account Engagement scoring and grading or Einstein — with capabilities that vary by plan.
What is the difference between an MQL and an SQL?
A marketing-qualified lead meets marketing's criteria for fit and interest; a sales-qualified lead has been accepted by sales as worth active pursuit. Clear, agreed definitions prevent disputes between teams.
Should we use predictive lead scoring?
Predictive scoring can help when you have enough historical won and lost deals to train on. With limited data, a well-designed rules-based model is usually more reliable and easier to explain.
Can lead scores improve our ad campaigns?
Yes. Sending qualified-lead events based on scores to Meta, Google and LinkedIn helps those platforms optimise for leads that progress rather than all form fills.
What parameters are scored?
Job titles, industries, page visits, email opens, form details, and ad clicks.
Does lead scoring work in HubSpot?
Yes, we build scoring calculators inside HubSpot and Salesforce.
How do we prevent sales from ignoring scores?
By setting up automated alerts and deal routing queues that prioritize high scores.
Pricing: monthly retainers by region
Every engagement is a monthly retainer priced on scope — never a percentage of ad spend. The range depends on the number of channels, markets and the depth of tracking and CRM work involved.
| Region | Monthly retainer |
|---|---|
| United States | $2,500–$6,000 per month |
| India | ₹1,00,000–₹5,00,000 per month |
| United Kingdom | £2,200–£5,000 per month |
| United Arab Emirates | AED 4,000–AED 10,000 per month |
| Australia | A$3,000–A$7,000 per month |
| Canada | C$3,000–C$7,000 per month |
| Singapore | S$3,000–S$7,000 per month |
| Europe | €2,500–€5,000 per month |