Consulting & implementation
Marketing & Business Reporting Systems
Connect marketing, ecommerce, subscription, and operational data so your team can answer business questions without rebuilding reports by hand.
For founders, marketing teams, agencies, and operators working across several business systems.
Discuss your reporting needsDoes this sound familiar?
- Marketing spend, orders, and subscriptions live in separate tools.
- Reports need manual exports and cleanup every week.
- Dashboards disagree, and metric definitions are unclear.
What you receive
- A defined set of metrics and reporting questions.
- Connected sources with scheduled refresh and visible data checks.
- A reporting dataset, dashboard, or API your team can use.
- Source reconciliation, documented limitations, and a practical handoff.
A focused first delivery
Start with a small set of questions, accessible sources, and one useful report. We agree what each metric means, how data refreshes, and what is outside the first version before building.
- Marketing spend and orders in one reporting view.
- Separate ecommerce and subscription reporting with clear customer definitions.
- An automated recurring report using your existing reporting tools.
- A dashboard and AI access using shared metric definitions.
Access and scope
Source accounts or exports, current reports, and the business definitions behind your questions. Connector coverage and historical availability are checked before scope is agreed.
Pricing and delivery timing follow agreed scope and source access. Refresh frequency and historical coverage depend on the systems involved.
When the work needs to go deeper
Expand into custom ingestion, historical recovery, attribution normalization, customer/revenue modeling, or a warehouse when the reporting need justifies it.
Reporting data can support both dashboards and questions in Claude or ChatGPT. We define the metrics once, prepare the reporting layer, and scope an authenticated connection to the selected AI client.
Tools chosen around the problem
BigQuery, advertising APIs, ecommerce/payment APIs, Sheets, and existing BI tools. Managed connectors are useful when they cover the required fields; custom extraction fills specific gaps.
Relevant work
Marketing Data & Campaign Analytics Platform →
Advertising APIs, BigQuery reporting layers, recovery workflows, and campaign analysis behind a marketing analytics product.
Marketing Ads Dashboard →
Google Ads, Meta Ads, and Sheet inputs connected to a reporting model and an authenticated marketing dashboard.
Commerce, Subscriptions & Acquisition Reporting Backend →
Payment and subscription workflows, acquisition metadata, and reporting APIs within the same connected-device product.
DV360 & Ads Data Hub Data Pipeline →
Production event-driven data platform for DV360 metadata, DV360 report normalization, Ads Data Hub match-rate workflows, BigQuery processing, and reliable AWS SQS delivery.
Practical reading
Use the prepared data through AI
The same reporting definitions or backend APIs can support questions in Claude or ChatGPT.
Find a useful starting point.
Share the problem and relevant systems. We can identify a manageable first output before agreeing a build.
Discuss your reporting needs