Lead Qualification Tracker

Install a reviewable qualification table with fit, intent, disqualifiers, owner, and handoff decisions.

Overview

A lead qualification workflow helps revenue operations turn an MQL review sheet into a cleaner, repeatable decision process. This playbook installs a lead qualification tracker and a rules document so Juno can review fit, intent, disqualifiers, owner, handoff decision, evidence, and next action in one place.

It is built for teams that already receive leads from forms, webinars, events, paid campaigns, partner referrals, or sales notes, but still decide "is this actually ready for sales?" in a spreadsheet. Juno does not replace your CRM or route leads automatically. It gives the team a durable review surface before the handoff gets messy.

Why you should make MQL review explicit

MQLs and SQLs sound tidy in a funnel diagram, but the hard part is the middle: deciding which interested people deserve sales time now. HubSpot's guide to MQLs and SQLs frames the difference around readiness for direct sales engagement, which is exactly where a review sheet needs stricter rules.

Without a shared qualification workflow, good leads wait for an owner, poor-fit leads look busy because they clicked something, and disqualified records keep reappearing in campaign handoffs. That is not a data problem first. It is an operating-rhythm problem.

This playbook keeps the boundary practical. The tracker holds the recurring decision state, and the rules document keeps fit, intent, disqualifiers, and handoff expectations visible. Salesforce also describes MQL-to-SQL movement as a lead quality step in its lead qualification checklist, which makes this a useful workflow even before heavier automation is ready.

Step-by-step

  1. 1
    Confirm the brand, ideal customer profile, MQL sources, review window, owner rules, handoff expectations, and any known disqualifiers.
  2. 2
    Install the lead qualification tracker and qualification rules document so the workflow has a durable place to hold decisions before the first review begins.
  3. 3
    Add or update lead rows from supplied lists, pasted notes, exports, workspace tables, or manually reviewed sources, keeping duplicates and incomplete rows visible.
  4. 4
    Review fit separately from intent so Juno can distinguish a strong target account with weak timing from a poor-fit lead with noisy engagement.
  5. 5
    Mark disqualifiers, suppression concerns, owner gaps, missing evidence, and duplicate records instead of blending them into a generic score.
  6. 6
    Assign each row a handoff decision such as sales-ready, nurture, research, disqualified, duplicate, or needs owner review.
  7. 7
    Summarize the reviewed rows, sales-ready leads, nurture and research candidates, owner gaps, disputed rules, and next decisions for revenue operations.

Frequently asked questions

Does this replace a CRM?

No. It replaces an MQL review sheet: the table and rules document a team uses to decide what should happen before a lead moves forward. CRM sync, task creation, assignment automation, and outbound sending are separate workflows.

What inputs are needed?

Bring the ICP, lead sources, qualification rules, disqualifiers, owner or queue rules, and the review window. Existing lead rows make the first pass stronger, but the installed tracker is useful even before live leads are added.

How is this different from lead scoring?

Lead scoring can support the review, but this playbook is about the operational decision. Juno records the fit reason, intent evidence, blockers, owner, handoff decision, and next action so a human can challenge or approve the outcome.

How often should we run it?

Run it before an MQL review meeting, after a campaign batch lands, or on the optional weekday or weekly cadence. Repeat runs should reuse the same tracker so qualification decisions stay comparable over time.