pipeline

name	pipeline
description	Sales and recruiting pipelines with stages, deals, and stage transition history

Pipeline

Sales and recruiting pipelines with ordered stages, deals, and an append-only log of stage transitions. Deals track value, status, and expected close date. Stage history enables pipeline velocity analysis.

Tables

pipelines

Column	Type	Description
id	uuid	Primary key
org_id	uuid	FK to organizations
name	text	Pipeline name (e.g. Sales, Recruiting)
description	text	Pipeline description
is_default	boolean	Whether this is the default pipeline for the org
created_at	timestamptz	Row creation timestamp
updated_at	timestamptz	Last update timestamp (auto-set by trigger)
metadata	jsonb	Arbitrary JSON

pipeline_stages

Column	Type	Description
id	uuid	Primary key
org_id	uuid	FK to organizations
pipeline_id	uuid	FK to pipelines
name	text	Stage name (e.g. Qualification, Proposal)
position	integer	Display order within the pipeline
color	text	Hex color for UI rendering
is_terminal	boolean	Whether this stage is a final state (e.g. Closed Won, Rejected)
created_at	timestamptz	Row creation timestamp
updated_at	timestamptz	Last update timestamp (auto-set by trigger)
metadata	jsonb	Arbitrary JSON

Unique constraint on (pipeline_id, position).

deals

Column	Type	Description
id	uuid	Primary key
org_id	uuid	FK to organizations
pipeline_id	uuid	FK to pipelines
stage_id	uuid	FK to pipeline_stages. Current stage of the deal
owner_id	uuid	FK to users. Deal owner
contact_id	uuid	FK to contacts. Associated contact
company_id	uuid	FK to companies. Associated company
title	text	Deal title
value	numeric	Deal value in smallest currency unit (cents)
currency	text	Currency code, defaults to USD
status	deal_status	Current status: open, won, lost, or stale
expected_close_date	date	Forecasted close date
closed_at	timestamptz	When the deal was actually closed
lost_reason	text	Free-text explanation when status is lost
created_at	timestamptz	Row creation timestamp
updated_at	timestamptz	Last update timestamp (auto-set by trigger)
metadata	jsonb	Arbitrary JSON

deal_stage_history

Column	Type	Description
id	uuid	Primary key
org_id	uuid	FK to organizations
deal_id	uuid	FK to deals
from_stage_id	uuid	FK to pipeline_stages. Stage the deal moved from
to_stage_id	uuid	FK to pipeline_stages. Stage the deal moved to
changed_by	uuid	FK to users. Who triggered the transition
changed_at	timestamptz	When the transition happened
duration_seconds	integer	Time spent in the previous stage
created_at	timestamptz	Row creation timestamp
updated_at	timestamptz	Last update timestamp (auto-set by trigger)
metadata	jsonb	Arbitrary JSON

Enums

deal_status

Value	Description
open	Deal is active and in progress
won	Deal was closed successfully
lost	Deal was lost
stale	Deal has gone inactive with no recent updates

Row-Level Security

All tables have RLS enabled and are scoped to the current user's organization via get_user_org_id().

• pipelines: SELECT/INSERT/UPDATE for own org. DELETE requires admin.
• pipeline_stages: SELECT/INSERT/UPDATE for own org. DELETE requires admin.
• deals: SELECT/INSERT/UPDATE for own org. DELETE requires admin.
• deal_stage_history: SELECT/INSERT/UPDATE for own org. DELETE requires admin.

Dependencies

• crm -- contacts and companies referenced by deals

Example Queries

Get all deals in a specific stage:

SELECT
  d.title,
  d.value / 100.0 AS value_dollars,
  d.currency,
  u.full_name AS owner,
  c.first_name || ' ' || coalesce(c.last_name, '') AS contact
FROM deals d
LEFT JOIN users u ON u.id = d.owner_id
LEFT JOIN contacts c ON c.id = d.contact_id
WHERE d.stage_id = '<stage_id>'
  AND d.status = 'open'
ORDER BY d.value DESC;

Pipeline summary with deal counts and total value:

SELECT
  ps.name AS stage,
  ps.position,
  count(d.id) AS deal_count,
  coalesce(sum(d.value), 0) / 100.0 AS total_value
FROM pipeline_stages ps
LEFT JOIN deals d ON d.stage_id = ps.id AND d.status = 'open'
WHERE ps.pipeline_id = '<pipeline_id>'
GROUP BY ps.id, ps.name, ps.position
ORDER BY ps.position;

Average time in each stage (pipeline velocity):

SELECT
  ps.name AS stage,
  round(avg(dsh.duration_seconds) / 86400.0, 1) AS avg_days
FROM deal_stage_history dsh
JOIN pipeline_stages ps ON ps.id = dsh.from_stage_id
WHERE dsh.duration_seconds IS NOT NULL
GROUP BY ps.id, ps.name, ps.position
ORDER BY ps.position;

Deals expected to close this month:

SELECT
  d.title,
  d.value / 100.0 AS value_dollars,
  d.expected_close_date,
  ps.name AS stage,
  u.full_name AS owner
FROM deals d
JOIN pipeline_stages ps ON ps.id = d.stage_id
LEFT JOIN users u ON u.id = d.owner_id
WHERE d.status = 'open'
  AND d.expected_close_date >= date_trunc('month', current_date)
  AND d.expected_close_date < date_trunc('month', current_date) + interval '1 month'
ORDER BY d.expected_close_date;

Win/loss breakdown by owner:

SELECT
  u.full_name AS owner,
  count(*) FILTER (WHERE d.status = 'won') AS won,
  count(*) FILTER (WHERE d.status = 'lost') AS lost,
  round(
    100.0 * count(*) FILTER (WHERE d.status = 'won')
    / nullif(count(*) FILTER (WHERE d.status IN ('won', 'lost')), 0),
    1
  ) AS win_rate_pct
FROM deals d
JOIN users u ON u.id = d.owner_id
WHERE d.org_id = get_user_org_id()
  AND d.status IN ('won', 'lost')
GROUP BY u.id, u.full_name
ORDER BY win_rate_pct DESC;