---
title: Qualification Flows
subtitle: Define how OrcaPulse decides lead quality and next steps
slug: documentation/qualification-flows
---

# Qualification Flows

This page documents how qualification works in the current OrcaPulse project: prompt-driven discovery, intent capture, review logic, lead success evaluation, call scoring, and the operator surfaces used to inspect outcomes.

## What qualification means in this project

Qualification in OrcaPulse is the logic used to decide whether an inbound lead is worth advancing, what information is still missing, and which workflow action should happen next.

The project already expresses qualification in multiple places:

- qualification prompts described in workflow and quickstart docs
- social lead AI analysis with intent and follow-up signals
- lead and call success evaluation fields
- call scoring for successful conversations
- operator review surfaces such as Lead Hub and Review Lead

## Core qualification signals

Current qualification signals in the project include:

- lead intent on social leads such as `interested`, `inquiry`, `spam`, and `unknown`
- sentiment and follow-up need flags on captured social conversations
- success evaluation on leads and calls
- call score from 1-10 for successful conversations
- operational statuses like `NEW`, `QUALIFIED`, `CONVERTED`, `FAILED`, and `STOPPED`

## Prompt-driven qualification

The docs and setup flow already treat qualification as prompt-driven discovery. Teams are expected to define the key questions that capture intent, fit, urgency, budget, timeline, location, or use case before launch.

In practice, the first qualification flow should stay short and explicit:

- ask only decision-making questions
- phrase prompts like a natural follow-up, not a rigid form
- define what counts as qualified, unqualified, incomplete, or review-required
- connect each answer path to a downstream action

## Review and scoring

Qualification continues after the first conversation. Calls can be marked with `successEvaluation` and scored from 1-10 based on transcript quality and goal achievement. The scoring service uses transcript analysis plus summary context to judge how well the conversation met its goals.

This means qualification is not only “what the lead said first.” It also includes whether the AI or operator actually moved the lead toward the intended outcome.

## Operator visibility

Operators already have review surfaces that support qualification work:

- `Review Lead` shows lead status, execution state, recall state, call outcome, and success evaluation
- `Lead Hub` gives a broader list view across workflows
- timeline events on the main lead record show what happened after qualification and routing

## How to design the first flow

A strong first qualification flow in this project usually follows this pattern:

1. capture inbound intent
2. collect the minimum missing business details
3. decide whether the lead is qualified, incomplete, or low priority
4. route the qualified lead into CRM sync, webhook sync, messaging, AI call, or human review

## Next steps

After qualification logic is clear, continue into routing rules, follow-up automation, and workflow execution so qualified leads move into the right downstream path.