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Lead Scoring and Routing for B2B SaaS: A Worked Example

Separate account fit from buying intent, then define what happens next. Build a scoring model your sales team can inspect, test and change.

Goal: Separate account fit from buying intent, then define what happens next. Build a scoring model your sales team can inspect, test and change.

Complexity

High

Tools

3

Context

The Problem

A single score can hide the difference between a good-fit account with little activity and an unsuitable account clicking every page. Scoring only helps when the reasons are visible and ownership is clear.

Resolution

The Solution

Get the editable worksheet (.md)

Start with two scores

Use separate tables for account fit and recent intent. All weights and thresholds are illustrative starting assumptions, not validated defaults. Agree your ICP and exclusions with sales before implementing them.

Fit signalMaximum points
Industry match25
Employee range15
Product dependency15
Relevant technology10
Geography10
Revenue or funding stage10
Decision-making role10
Relevant regulatory requirement5
Intent observationExample pointsExample expiry
Demo or trial request307 days
Pricing visit207 days
Activation milestone2514 days
Comparison research257 days
Return visit157 days
Case study read1014 days
Teammate invited207 days
Email reply257 days

Keep timestamps and source records. In this example, count each event type once within its window, expire it afterwards and cap intent at 100. Repeated page refreshes must not inflate a score. Missing enrichment is unknown, not evidence of poor fit.

Three worked records

Fictional accounts; the sums demonstrate the model, not client results.

AccountFit calculationIntent calculationAction
Cedar, 120 employeesIndustry 25 + size 15 + dependency 15 + geography 10 + role 10 = 75Case study 10Nurture; high fit alone does not establish urgency
Birch, 20 employeesGeography 10 + role 10 = 20Demo 30 + pricing 20 + return 15 + reply 25 = 90Manual qualification; activity does not override poor fit
Elm, existing customerIndustry 25 + size 15 + technology 10 + geography 10 = 60Activation 25 + invite 20 = 45Account owner reviews adoption; exclude from new-lead routing

Route in a defined order

First deduplicate against the stable CRM record. Respect suppression and consent settings. Existing customers go to their account owner; existing opportunities stay with the opportunity owner. Missing ownership or required data goes to a named exception queue.

For remaining new leads in this illustrative model:

  1. Fit below 60: manual qualification if a demo was requested; otherwise appropriate nurture.
  2. Fit at least 60 but intent below 60: nurture until a relevant change.
  3. Fit and intent at least 60: route by territory, then size. More than 1,000 employees goes to the enterprise priority queue; 501-1,000 to enterprise; 50-500 to mid-market; fewer than 50 to the small-business queue.
  4. If size or territory is unknown, or the owner is unavailable, use the exception queue and record the reason. Assign its owner and response expectation before launch.

Test before activating

The worksheet includes boundary cases at 49/50, 500/501 and 1,000/1,001 employees, stale events, duplicate requests and unavailable owners. Run historical records through the rules without sending alerts or changing owners first.

Freeze each record's inputs at the scoring date. Compare later qualification and retention across score bands, showing the cohort size and observation window. Do not use future revenue to construct a historical score. Log false positives and sales overrides; revise weights when evidence supports a change.

What to measure

Higher qualification in the top bands

Qualification by score band

Falling as exception causes get fixed

Routing exceptions

Faster for high fit, high intent leads

Time to first response

Routing Logic Example

FitIntentActionOwnerSLA
A-fitHighRoute to SDRSDR<5 min
A-fitLowNurture + alert on spikesMarketing Ops24 hrs
B-fitHighRoute to AEAE24 hrs
Bad fitAnyAuto-DQ with reasonRevOpsInstant

At Peakon we identified anonymous /pricing visitors and wired Clearbit into Marketo and Salesforce, five years before Clay existed. Read the Peakon case study, the signal-driven GTM system behind a $700M Workday exit.

Team Responsibilities

RoleResponsibility
GTM ownerAgree the objective, definitions and review decisions.
RevOps / GTM engineerImplement data checks, document rules and manage exceptions.

When NOT to Use

  • •When required data is missing or cannot be used for this purpose
  • •When the team cannot review exceptions or act on the output

Tools & Tech

Your CRM
Spreadsheet or data workspace
Clay / enrichment, if needed
Take the GTM Readiness Score

Put this playbook to work

Need help adapting this workflow to your team? Explore the relevant implementation services.