DATA WAREHOUSE
One Source of Truth, Where Your Numbers Reconcile
For founders spending $30K+/mo across Google, Meta, and Microsoft whose numbers never reconcile. We build a marketing data warehouse, your ad spend, leads, calls and closed revenue in one BigQuery source of truth you own, so cost-per-lead and ROAS finally agree. Built by the team that runs your ads, not an enterprise project. Get clarity on how things stand.
Example, conversions over 30 days. Google Ads, Meta, Microsoft Ads, GA4, HubSpot and call tracking load rows into one BigQuery table. The warehouse removes duplicate claims and joins the missing sessions and leads, so Meta (1,284), Google Ads (1,107), GA4 (912) and the CRM (804) all reconcile to 1,002, the number that matches the bank.
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- 1source of truth you ownin your own cloud
- ReconciledCPL & ROAS to closed revenuethe wedge
- 10+ hrsmanual stitching saved / week
THE REAL PROBLEM
Your data is everywhere, and nothing adds up
Ad spend in three platforms, leads in the CRM, calls on the phone, sessions in GA4. None of it reconciles, so true cost-per-lead and ROAS are impossible to see.
Nothing reconciles
Each platform reports its own number, none matches the bank, and the CRM tells a third story. There’s no single source of truth.
Attribution is impossible
Leads and calls never tie back to the ad that drove them, so you allocate budget on gut, not on what actually closes.
Your data is expiring
Google, Meta and GA4 keep only a slice of history. What you don’t capture into a warehouse you own is gone for good.
The two bad options
A connector tool that lands rows and reconciles nothing, or an enterprise firm that quotes a five- to six-figure project and walks away.
OUR APPROACH
A warehouse modeled around your marketing, not a generic box
The Data Warehouse is the load-bearing middle rung of the analytics ladder the 3-Pillar Method™ governs: tracking sends clean signals in, the warehouse stores them as one source of truth, reporting reads out.
Clean Signals In
Pillar 1 Conversion Tracking feeds the warehouse: server-side, Enhanced Conversions, offline and CRM imports, so what lands is accurate, not platform-estimated.
Modeled for Marketing
A schema built around campaigns, leads, calls and deals, not a horizontal star schema for “the business”, so it answers cost-per-lead and ROAS by channel.
Read by the Whole Stack
Wired on day one to feed attribution, Intelligence Reporting and Analytics, so it’s a system, not a disconnected one-off box.
WHAT’S INCLUDED
You’re not buying a database. You’re buying the day your numbers agree.
- A unified BigQuery warehouse inside your own Google Cloud, you own every row
- Wired to feed attribution, Intelligence Reporting & Analytics on day one
- Google, Meta & Microsoft ad platforms + GA4 + CRM + offline/call data, consolidated
- Platform data captured before it expires and is lost
- Cost-per-lead & ROAS reconciled to closed revenue, not platform-reported estimates
- Event Map — every tracked conversion feeding the warehouse, documented
- A schema modeled around campaigns, leads, calls & deals
- Built and maintained as the live source of truth, not handed off and abandoned
- You own it
- Right-sized: enterprise-grade, scoped for a founder
- One team: ads, tracking & warehouse
- No vendor lock-in
- Request data-source audit
- Built in your own cloud
WHAT YOU GET
The day your numbers finally agree
Cost-per-lead that reconciles
Ad spend, leads, calls and closed revenue in one place, so CPL and ROAS finally agree across every channel.
A warehouse you own
In your own Google Cloud, every row yours. The asset stays with you, feeding the rest of the stack.
Attribution that’s possible
Leads and calls tied back to the ad that drove them, so budget follows what actually closes, not gut.
WHY A PARTNER
nn.partners vs the two options you’ve been quoted
Every founder shopping a warehouse has bounced off one of two camps: a self-serve connector that reconciles nothing, or an enterprise project that builds a generic box and walks away. Here’s the third option.
Purpose
nn.partners
✓ Built for marketing decisions (CPL, ROAS, by channel)
- Enterprise IT DWH consultancy
- ✗ Generic BI for “the business”
- Connector / data tool
- ✗ Just moves rows into storage
Reconciliation
nn.partners
✓ CPL & ROAS reconciled to closed revenue
- Enterprise IT DWH consultancy
- ✗ Not modeled for marketing
- Connector / data tool
- ✗ None, that’s your job
Who builds it
nn.partners
✓ The team that runs your ads & tracking
- Enterprise IT DWH consultancy
- ✗ A data team, then they walk away
- Connector / data tool
- ✗ Nobody, self-serve
Schema
nn.partners
✓ Campaigns, leads, calls & deals
- Enterprise IT DWH consultancy
- ✗ Horizontal star schema
- Connector / data tool
- ✗ Whatever the connector dumps
Ownership
nn.partners
✓ Your own cloud, you own every row
- Enterprise IT DWH consultancy
- ✗ Often, but enterprise-gated
- Connector / data tool
- ✗ Their hub unless you upgrade
Right-sized
nn.partners
✓ For a founder
- Enterprise IT DWH consultancy
- ✗ A five- to six-figure project
- Connector / data tool
- ✗ DIY, no strategy
Risk
nn.partners
✓ Request an audit; get clarity on how things stand
- Enterprise IT DWH consultancy
- ✗ “Free estimate” (a sales call)
- Connector / data tool
- ✗ “Free trial” (DIY)
WHO BUILDS YOUR WAREHOUSE
Built by the team that runs your ads, not a data team you’ll never speak to again
A faceless enterprise project hands your warehouse to your IT team and walks away. A self-serve tool leaves the modeling to you. Yours is built by Nik Vdovenko, founder, with 9 years and $10M+ in managed spend, founder-led for judgment. You work directly with the strategist who owns the ads, the tracking and the warehouse, so the schema is designed around the marketing questions.
A data-engineering firm will quote you a five- to six-figure project to build a generic warehouse. You get one built for marketing decisions, run by the team that runs your ads, for a fraction of an enterprise project.
- You own itYour cloud, every row, no lock-in
- Founder-ledSenior attention, no handoff
- Marketing-builtModeled for CPL & ROAS, not generic BI
- Request auditGet clarity before you commit
HOW IT WORKS
Get clarity before you commit
Request Data-Source Audit
We inventory every source, ad platforms, GA4, CRM, call tracking, offline, map what’s missing, what doesn’t reconcile, and what a warehouse would unlock. No obligation.
Architect & Build
We model a schema around your campaigns, leads, calls and deals, then build the BigQuery warehouse in your cloud with reconciliation logic. Request an audit; get clarity on how things stand and areas of growth.
Feed & Run
We wire it to attribution and reporting, reconcile CPL and ROAS to revenue, and maintain it as your live source of truth, not a one-off handoff.
Request a data audit; get clarity on how things stand.
CLIENT STORIES
Leaders whose numbers finally agree
“He’s been invaluable in not only running our ad campaigns, but also helping improve our overall reporting and business model.”
Martin OchwatPartner, Dundas Insurance
“Our business grew exponentially.”
Leo VorontsovFounder & CEO, Contractors Intelligence School
“They genuinely care about getting the best outcome for clients and go above and beyond.”
Matt WoodHead of Digital, Karman Digital
FAQ
Questions serious advertisers ask
A connector just pipes raw platform data into a database. It doesn’t model it, reconcile it, or make it answer business questions, so you end up with the same disagreeing numbers in a new place. We build the modeling layer on top so CPL and ROAS actually tie back to closed revenue. That’s the part worth paying for.
Enterprise firms build you a warehouse and hand you an invoice. We build it inside your stack, tie it to the ad accounts we’re already running, and you own every table. No six-figure project, no year-long timeline, and we don’t vanish once it’s live.
Completely. It lives in your own BigQuery project under your billing. If we ever part ways, everything stays with you: queries, models, dashboards. We don’t hold your data hostage.
Google Ads, Meta, Microsoft, GA4, your CRM, call tracking, and most things with an API or a clean export. The goal is one place where every number agrees, not ten tabs that don’t.
If your dashboards already pull from one trustworthy source, maybe not. If they pull straight from platform APIs, they’ll keep disagreeing with each other and with your bank. The warehouse is what makes a dashboard worth trusting.
Most builds are live in a few weeks, depending on how many sources you have and how messy the current setup is. We scope it during the request audit, so you know before we start.
It depends on how many sources and how much modeling you need, so we price it after the audit, not before.
LET’S GROW TOGETHER
The day your numbers finally agree.
Your ad spend, leads, calls and closed revenue in one BigQuery source of truth you own, built by the team that runs your ads, so cost-per-lead and ROAS finally reconcile.
- 1Source of truth
- YoursIn your own cloud
- 9 yrsPaid media & analytics
- RequestData-source audit