---
name: lead-source-conversion-analysis
description: Compares lead sources by volume, qualification, conversion, cycle time, revenue, and data quality to show which sources create useful pipeline. Use for lead-source analysis, marketing-to-sales reporting, funnel review, channel performance, or budget planning.
license: Apache-2.0
metadata:
  adlass.categories: "sales-crm/lead-qualification, sales-crm/pipeline"
  adlass.industries: ""
  adlass.tags: "lead-source, conversion, funnel, pipeline, attribution, sales-analytics"
  adlass.adaptation: "mapping"
  adlass.source: "original"
  adlass.version: "1"
---

# Lead source conversion analysis

## Purpose

Measure how lead sources progress through the sales funnel and revenue outcomes, while exposing attribution and data-quality limitations. Support channel decisions with comparable denominators rather than volume alone.

## Scope

Source, cohort date, lead status, qualification, opportunity, outcome, amount, cycle time, segment, owner, and attribution fields.

**Excluded:** changing attribution, reallocating budget automatically, and claiming source causation from incomplete records.

## Data basis

- Lead, opportunity, and outcome tables.
- Funnel definitions and source taxonomy in scope.
- Historical cohorts for comparison.

## Result

A source-funnel sheet and analysis memo with patterns, caveats, and decision questions.

## Quality criteria

- Funnel stages and cohort windows are explicit.
- Every rate shows numerator and denominator.
- Duplicate and unattributed records are counted.
- Revenue is reconciled to opportunity outcomes.
- Recommendations distinguish evidence from hypothesis.

## Instructions

Use source taxonomy and stage definitions exactly. Compare equivalent cohorts and allow for cycle length. Separate first-touch, last-touch, and multi-touch fields when present. Do not rank a source with insufficient sample or immature cohort as final performance.

## Adapt before use
Keep a clear audit trail throughout the run. Use the source wording and field values that support each material conclusion, and retain uncertainty when the evidence does not decide the issue. Separate a missing record from a negative result and a contradictory record from an exception. Prefer a short, prioritised result over unsupported completeness. Check that counts, identifiers, dates, and labels agree across the written result and the structured output. When a rule, source, or mapping is unavailable, name the limitation and explain how it affects interpretation. Do not silently infer ownership, approval, timing, or business intent.

- Map lead, opportunity, source, stage, outcome, and amount fields.
- Define cohorts, funnel stages, attribution model, and minimum sample.
- Set currency and reporting-period conventions.