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The pipeline trust gap

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[temp] The reporting backlog

Your pipeline numbers don’t match. And everyone knows it.

Sales, marketing, and finance each have their own version of pipeline, attribution, and revenue. Your forecast lives in a spreadsheet nobody can audit. And when the board asks "are we going to hit the number?" — you’re not sure which pipeline to believe.

How sales data works today

Three systems, three truths

CRM says $4.2M. Marketing says $3.1M. Finance says $2.6M. Which is the board number?
Marketing delivered 500 MQLs. Sales says 200 were junk. Nobody can prove it.
Forecast lives in a spreadsheet someone built 18 months ago — formulas broken
RevOps spends 20 hours/week on pipeline snapshots and reconciliation
Board asks "confidence on Q3?" — you answer on gut, not governed data
With OWOX

One pipeline. One forecast. One truth.

CRM + marketing + revenue joined in one governed Data Mart
MQL-to-revenue tracing — see which efforts actually drove closed deals
Forecast built on governed data with deterministic SQL — auditable, owned
Sales team self-serves in Sheets — filter by rep, region, or stage
AI weekly brief — deal velocity, conversion, forecast confidence — to Slack

Pipeline numbers reconcile because CRM, marketing, and revenue data pull from the same governed source.

Get started free →
Joined pipeline data

CRM, marketing, and revenue — in one governed library

Your RevOps team joins CRM, marketing, and revenue data in the warehouse and publishes it as a governed library. One definition per metric. One source of truth.

CRM pipeline + marketing spend + actual revenue — joined with analyst-defined keys
One definition of "pipeline" across sales, marketing, and finance — no more reconciliation
Technical and Business Owner on every Data Mart — clear accountability on every metric
CRM, marketing, and revenue — in one governed library
CRM, marketing, and revenue — in one governed library
Your sales team filters by rep, region, or stage — without RevOps
Self-serve pipeline

Your sales team filters by rep, region, or stage — without RevOps

The OWOX sidebar puts the pipeline library inside Google Sheets. Your sales managers browse, join, filter by region, and refresh. No RevOps in the loop.

Column picker shows "Deal Value," "Stage," "Days in Pipeline," "Marketing Source" — business-friendly names
Joins follow analyst-defined keys — combine pipeline with attribution or revenue without SQL
Every cell is deterministic — same number for sales, marketing, and finance. Patented technology.
Your sales team filters by rep, region, or stage — without RevOps
Pipeline intelligence

Weekly pipeline brief in Slack. Deal velocity. Forecast confidence. Zero hallucinations.

Insights turn your pipeline Data Marts into recurring sales narratives delivered on schedule. AI writes the summary. Every metric is deterministic SQL.

Pipeline health — stage conversion, velocity trends, slippage alerts — auto-generated weekly
Forecast confidence scored from governed data, not gut feel
Patented technology — AI narrates pipeline trends, never invents the numbers
One Data Mart. Every report. Every channel.
Build a gold layer you actually trust

Get pipeline numbers that everyone trusts

Send this to your RevOps lead. They’ll join CRM, marketing, and revenue data. Monday pipeline reviews finally use numbers everyone agrees on.

How it works

From pipeline chaos to governed forecast — in three steps

Your RevOps team builds the library. Your sales org self-serves. AI delivers pipeline intelligence. The reconciliation meetings end.

RevOps joins the data

CRM, marketing, and revenue data joined and published as governed Data Marts. One definition per metric.

CRM, marketing, and revenue data joined and published as governed Data Marts. One definition per metric.

Sales team self-serves

Sales managers open Sheets, browse the pipeline library, filter by rep or region, refresh. No RevOps bottleneck.

Sales managers open Sheets, browse the pipeline library, filter by rep or region, refresh. No RevOps bottleneck.

AI delivers the weekly brief

Pipeline narrative — conversion rates, velocity, forecast confidence — to Slack every Monday. Deterministic.

Pipeline narrative — conversion rates, velocity, forecast confidence — to Slack every Monday. Deterministic.
CRM, marketing, and revenue data joined and published as governed Data Marts. One definition per metric.
Sales managers open Sheets, browse the pipeline library, filter by rep or region, refresh. No RevOps bottleneck.
Pipeline narrative — conversion rates, velocity, forecast confidence — to Slack every Monday. Deterministic.
What changes for your sales org

Answer "are we going to hit the number?" with data, not gut

When pipeline, attribution, and revenue pull from the same governed source, the sales org transforms.

Marketing and sales finally agree

MQL-to-close tracing in one view. Marketing sees which leads converted. Sales sees which efforts mattered. No more "your MQLs were junk" arguments.

Forecast you can defend

Pipeline data is governed, versioned, deterministic. Your forecast has a foundation, not a formula you inherited.

RevOps works on operations, not exports

When the sales team self-serves pipeline data, your RevOps lead stops spending 20 hours/week on snapshots and starts optimizing the process.

What sales leaders say

Customer stories

Sales orgs that unified their pipeline data

Teams that ended the pipeline reconciliation problem

All case studies →
Questions sales leaders ask

[temp] Questions data analysts ask

Can OWOX pull data from our CRM?
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How does OWOX solve the marketing-sales attribution argument?
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Can my sales team really use this without training?
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How reliable is the AI forecast brief?
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What does this cost?
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We already have CRM dashboards. Why do we need this?
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RECOMMENDED

Get pipeline numbers everyone trusts

Send this to your RevOps lead. They’ll join CRM, marketing, and revenue data. Your sales org self-serves. Monday reviews finally work.

From $30/month — saves 20+ RevOps hours/week
CRM + marketing + revenue joined in one library
Get a rollout plan for your RevOps and sales teams
NEED HELP?

Book a demo with our team

See how your CRM data joins with marketing attribution and revenue — with your actual pipeline in mind.

30-minute walkthrough focused on sales pipeline
See MQL-to-close attribution in action
AI pipeline briefs with deterministic forecast data