See a lead move from inquiry to a clear next action.

Explore how qualification changes when each business defines success differently.

Demo mode — sample data. Scores and messages are pre-authored examples, not live AI predictions.

Operations cockpit

Lead qualification and follow-up

Professional services: Clinic group · reporting delays. Ready to run.

01

Incoming Lead

Choose a sample inquiry
02

Qualification

  1. 01CaptureWaiting
  2. 02EnrichWaiting
  3. 03ScoreWaiting
  4. 04RouteWaiting
  5. 05Follow upWaiting

Activity

Scoring rules used

Northstar Advisory

A four-person operations consultancy serving growing regional businesses.

Success event
A qualified 30-minute discovery appointment
Ideal customer
20–200 employees, Operations or finance decision-maker
Service area
Remote across the Philippines
Services offered
Process redesign, Operations systems advisory
Minimum value
₱180,000 engagement potential
Capacity
Three new discovery calls per week
Urgency signals
Named operational blocker, Decision needed within 60 days
Required fields
Company size, Problem, Timeline, Decision role
Disqualifiers
Student research, Recruitment solicitation
38%Appointment rate29%Close rate after appointment
03

Recommended Next Action

Run qualification to see the recommended next action.

How this connects

Illustrative and simulated integration loop — no live systems are connected.

Ads FormLead source CRMSystem of record QualificationCRM qualification fields Assigned ownerQualification queueCreate an owner task and prepare an email Outcome feedbackMeeting held and deal outcome return to the scoring review

Start with clear rules. Calibrate against real outcomes.

  1. Define the measurable success event.
  2. Connect lead attributes to real downstream outcomes.
  3. Identify predictive or correlated attributes and combinations.
  4. Create evidence-backed rules from business context and historical performance.
  5. Compare qualification against appointments, sales, and revenue.
  6. Recalibrate as business conditions change, including capacity, services, seasonality, and customer behavior.

The recommended production pattern is to save the raw lead first in the CRM or Google Sheet, then trigger qualification before a salesperson acts. The CRM or Sheet remains the system of record, so a qualification failure cannot erase the original inquiry.

Production safeguards include idempotent processing, duplicate detection, retries, audit history, manual review, consent-aware communication, and failure recovery. This demo simulates those controls and does not make live AI or integration calls.

Want this shaped around your sales process?

Deploy this workflow for my business