Not all leads deserve the same follow-up speed
Point-based lead scoring models combining fit and intent signals to prioritise sales follow-up.
Lead scoring assigns a numeric value to each lead based on how closely it matches an ideal customer profile and how much genuine buying intent it has shown, so sales can prioritise the leads worth calling first instead of working every inbound form fill in the order it arrived. Without a scoring layer, a downloaded whitepaper from someone with no budget or authority gets the same follow-up urgency as a demo request from a director at a target account.
It becomes necessary once lead volume outpaces what a sales team can manually judge - past a certain point, treating every lead equally is functionally the same as treating none of them as a priority.
Lead scoring is a point-based model that ranks leads by fit and intent so sales follow-up is prioritised toward the leads most likely to close.
What we bring to this
ICP Fit Scoring
- Firmographic and demographic scoring criteria
- Weighting based on what actually predicts a close, not assumptions
- Disqualification rules for clear non-fits
Behavioural Intent Scoring
- Page visit and content engagement scoring
- Email and campaign interaction weighting
- High-intent action triggers - pricing page visits, demo requests
Threshold & Routing Rules
- Score thresholds that trigger sales handoff
- Tiered follow-up speed by score band
Score Decay & Calibration
- Decay rules for leads that go cold
- Ongoing recalibration against actual closed-won and closed-lost deals
Scope of work
| Area | What's included |
|---|---|
| Scoring Criteria | Defined fit and intent criteria specific to your ICP and buying signals |
| Model Build | Point values, weighting, and thresholds configured in your CRM or marketing platform |
| Decay Rules | Automatic score reduction for leads that go inactive |
| Calibration | Review cycle comparing scores against actual deal outcomes |
The engagement, step by step
Closed-Deal Analysis
We look at what your actually-closed deals had in common before assuming what should be scored highly.
Scoring Criteria Definition
Fit and intent criteria are defined and weighted based on that analysis, not a generic template.
Model Build
Point values and thresholds are configured directly in the CRM or marketing platform you already use.
Threshold & Routing Setup
Score bands are tied to specific follow-up actions and speeds, so a high score actually changes what happens next.
Live Testing
The model runs against real incoming leads before it fully replaces manual triage.
Ongoing Calibration
Scores are checked against actual closed deals on a regular cycle and adjusted as the model drifts.
Where this fits
- A B2B team is drowning in inbound leads and sales is following up with everyone in the order they arrived
- Marketing and sales disagree on what counts as a real lead, and scoring gives both sides a shared, defined threshold
- A company has grown past the point where a rep can judge lead quality on instinct alone
Who needs this
Teams with lead volume outpacing manual triage
Once inbound volume passes what one or two reps can judge by eye, a defined model replaces gut instinct with something consistent.
Teams stuck arguing about lead quality
A scoring model gives marketing and sales a shared definition of a sales-ready lead instead of a running disagreement.
What changes for you
- Sales time concentrates on leads that actually resemble past closed deals
- Marketing and sales share one definition of a qualified lead instead of two
- Stale leads stop cluttering active pipelines once decay rules are in place
Why work with EASI7 on this
- We build the model from your actual closed-deal data, not a generic fit and intent template
- We keep calibrating against real outcomes instead of treating the initial model as finished
Other services in this area
Your CRM should do the follow-up for you
CRM workflow automation that moves deals forward without manual data entry or reminders.
The right lead, to the right rep, immediately
Automated lead routing rules by territory, product, or rep capacity - no manual assignment queue.
Campaigns that run themselves once they're built
Multi-step campaign automation across email, ads, and CRM triggered by a single workflow build.
Fewer manual steps, fewer dropped handoffs
Internal marketing operations workflows automated end-to-end, from asset requests to reporting.
Common questions
Not fully - the first version is a hypothesis based on available data, and it needs a few months of real outcomes to calibrate properly. Treat the initial launch as a starting point, not a finished model.
No - scoring improves prioritisation and consistency, but it cannot fix a fundamentally weak offer or a sales process that mishandles good leads once they're flagged. What it reliably does is stop good leads from waiting behind bad ones.
Most modern CRMs and marketing platforms support point-based scoring natively - HubSpot, Zoho, and Salesforce all handle it. If yours doesn't, we will tell you before starting rather than after.
Quarterly is a reasonable default for most B2B sales cycles, though a business with a very short cycle can calibrate sooner because the closed-deal data to check against accumulates faster.
They don't disappear - they typically go into a lower-touch nurture track rather than direct sales follow-up, so they're not ignored, just not prioritised at the same speed.
It uses standard engagement data most marketing platforms already collect - page visits, email opens, form fills. We work within your existing consent and tracking setup rather than adding new collection.
Still following up on every lead in the order it arrived?
A scoring model built from your own closed deals usually sorts this out in a few weeks.
Ready to get started?
We usually reply within 24 hours.