OWOX gives your marketing team direct access to governed campaign data — attribution, spend vs. revenue, cross-channel performance — in Google Sheets. No analyst queue. No CSV exports. No conflicting numbers.

Every campaign launch generates a wave of data requests. Every board review needs fresh metrics. Your analysts are drowning in marketing tickets — and your team is still waiting.
Your marketing team shouldn’t need a ticket to see ROAS. And your analyst shouldn’t spend their career pulling it.
Get started free →Your data team joins ad platform data with revenue and CRM data, publishes it as a governed library. Your marketing team sees business-friendly names, not raw tables.



The OWOX sidebar puts the Data Mart library inside Google Sheets. Your campaign manager browses, joins, picks columns, and refreshes. No SQL. No analyst.

Insights turn your marketing Data Marts into recurring performance narratives delivered on schedule. AI writes the summary. Your analyst approved the SQL.


Send this page to your data team. They’ll build the marketing library. Your team self-serves in Sheets before Friday.
Your data team builds the marketing library. Your marketing team self-serves from it. AI delivers performance briefs. The ticket queue empties.
Connectors pull ad data into the warehouse. Your analyst joins it with revenue, publishes governed Data Marts.

Campaign managers open Sheets, browse the library, pick columns, filter by platform or region, refresh weekly.

Performance narrative — spend trends, ROAS changes, anomalies — to your Slack channel every Monday. Deterministic.




When your marketing team self-serves from governed Data Marts, everything shifts.
Cross-platform spend joined with actual revenue. When the CFO asks "is TikTok working?" – you answer with data.
Marketing and finance pull revenue from the same place. The board meeting goes smoothly because reconciliation doesn't happen at the meeting.
When the marketing team stops filing "pull this" tickets, your analyst finally has time for attribution modeling, incrementality testing, and media mix optimization.
Teams that gave their marketers direct access to governed data
The Google Sheets Extension is a column picker inside the tool your team already lives in. They browse a library of Data Marts with names like "Campaign Performance" and "Revenue by Channel," check the columns they want, apply a filter for the platform or date range, and hit refresh. There’s no SQL, no query language, no new tool to learn. Your data team sets up the library (that’s the technical part). Your marketing team uses it (that’s the point-and-click part).
The attribution problem isn’t a methodology problem — it’s a data problem. Facebook says it drove the conversion. Google says it did. Neither is lying; they just only see their own touchpoints. OWOX pulls all platform data into one warehouse, joins it with your actual CRM revenue, and lets your analyst define the attribution logic as a Data Mart. One source of truth, one definition, one number.
You keep your dashboards. OWOX doesn’t replace Looker Studio or Tableau — it sits behind them. OWOX adds a self-service layer: your team gets the same data in Google Sheets with a column picker, so they can explore, filter, and join without modifying the dashboard or filing a ticket. Same Data Mart feeds both — numbers reconcile because the source is the same.
Your data team can have the first marketing Data Marts live in a day — connect the warehouse, pull ad platform data via connectors, build the "Campaign Performance" and "Revenue by Channel" Data Marts, publish them. Your marketing team sees the library in Sheets immediately. The AI weekly brief can be delivering to your Slack channel by the following Monday. Full library buildout typically takes a week of analyst time.
When someone on your team asks ChatGPT "what’s our Facebook ROAS?", the LLM generates a SQL query on the fly. It might join the wrong tables, confuse cost columns, or hallucinate a metric that doesn’t exist. OWOX works the opposite way. Your analyst writes the SQL, tests it, publishes it as a Data Mart. When your campaign manager pulls ROAS in Sheets, the number comes from that pre-approved query — deterministic, identical every time. AI Insights narrate the trends but the numbers are computed by SQL, not guessed by AI. Patented technology.
Most marketing orgs burn 15–25 analyst hours/week on data extraction. At $60/hour, that’s $3,600–$6,000/month in analyst time spent pulling data, not analyzing it. OWOX Cloud Starter is $30/month. Team plans (with AI Insights and multi-destination delivery) are $875/month. Even the Team plan pays for itself if it saves your analyst 15 hours/month — which it will in the first week. The question isn’t "can we afford OWOX?" — it’s "can we afford to keep our analyst as a human CSV export?"
Get started free, invite your data team (or someone technical). They’ll build the data mart library for you. Your team self-serves in Sheets. The ticket queue empties.
See how your marketing data flows from ad platforms to warehouse to Sheets — with your actual campaigns in mind.