Score every lead, route it to the right rep

Rule-based scoring model

Compose scoring from positive and negative rules. Identical inputs always produce the same score, so the model is predictable and easy to audit.

Intent-signal scoring

Score behavioral signals like pricing-page visits, demo views, return visits, and email clicks so engaged leads rise above cold ones.

Firmographic scoring

Add points for ideal-fit traits like company size and job-title keywords to surface leads that match your target buyer.

Custom-field rules

Score on any field you track on a lead with equals, contains, or in-list conditions, so the model fits how your team actually qualifies.

Transparent point breakdown

Open any lead to see every rule that matched, the points it contributed, and the signal behind it. No black-box scores.

Priority-ordered routing

Routing rules evaluate in priority order; the first match wins and assigns the owner, so overlapping rules behave predictably.

Round-robin assignment

Rotate matching leads evenly through a pool of reps for fair distribution, or pin a rule to one fixed owner when you need it.

Default-owner fallback

A workspace-level fallback owner catches any lead no rule matched, guaranteeing every inbound lead has someone responsible.

Territory routing

Build a territory hierarchy with effective dates, priorities, and managers, then route leads — plus companies and deals — to the right team, with a full assignment-history audit.

Live re-scoring

Edit a scoring rule and the whole base re-grades in one coalesced pass, so a model change is reflected everywhere immediately — no manual recalculation.

Lifecycle stages

Move each record through lead → MQL → SQL with a server-enforced map of legal transitions, so the marketing-to-sales hand-off is an explicit stage on the record.