Overview
A BigQuery attribution gap audit helps marketing, analytics, and revenue teams explain why campaign reports disagree. This playbook uses warehouse evidence to compare campaign touchpoints, conversion events, customer records, and revenue outcomes, then turns the messy differences into a tracker and source-of-truth summary.
It is useful when dashboard numbers do not line up, paid channel ROI is being challenged, or a planning meeting needs more than "the data looks weird." Instead of re-litigating every metric by hand, Juno narrows the problem to the joins, date logic, and missing records that matter.
Why you should resolve attribution gaps before planning
Attribution gaps are expensive because they create fake certainty. A campaign can look underfunded, overcredited, or impossible to evaluate when click, lead, order, and revenue records are stitched together differently across tools.
BigQuery is built for analyzing large warehouse datasets, and Google's BigQuery documentation describes it as a serverless data warehouse for analytics across managed data. That makes it a strong place to reconcile the full reporting chain, not just whichever dashboard is loudest.
The output gives marketers a practical decision record: what source to trust, what needs cleanup, and which reporting rules should be used the next time performance is debated.
Step-by-step
- 1Confirm the reporting dispute, the business question, and the BigQuery datasets that hold campaign, event, customer, order, or revenue data.
- 2Map how attribution is supposed to move from campaign touchpoint to conversion, customer identity, downstream purchase, and revenue recognition.
- 3Compare counts and values across the selected window, looking for missing joins, duplicated conversions, unattributed revenue, or inconsistent date logic.
- 4Diagnose whether each gap is a tracking problem, a data hygiene problem, a valid business rule, or a stakeholder decision that needs a clear owner.
- 5Produce a gap tracker and summary report with severity, evidence, recommended fixes, and source-of-truth rules for future reporting.
Frequently asked questions
What data do I need?
You need BigQuery access to the warehouse tables that connect marketing activity to conversions and revenue. Juno can start from likely campaign, event, customer, order, subscription, or deal tables and ask for clarification before drawing conclusions.
Is this the same as a channel performance report?
No. A channel performance report explains what happened. This audit checks whether the data behind that report is trustworthy enough to use for budget, forecasting, or planning decisions.
How often should I run it?
Run it when reporting disputes appear, after tracking changes, before quarterly planning, or monthly for acquisition programs where attribution rules are still shifting.
