QA for marketing platforms: the numbers in the report match reality

A performance marketing platform sells trust in numbers. If impressions, clicks and conversions in its report diverge from the ad account, the client leaves even if the interface is flawless. So we test not only screens but data: where it came from, how it was computed, where it went.

What is special about martech testing

The main object of verification here is not a button but a data flow through third-party APIs. Ad platforms change versions, limits and response formats without warning; tokens expire; the same metric is computed differently in two sources. Defects accumulate quietly: the report keeps building, but its numbers are already wrong. We build QA to catch exactly that — discrepancies, not crashes.

• Integrations with ad platforms: authorization, token refresh, request limits, error handling and retries.
• Metric reconciliation: impressions, clicks, spend, conversions in the platform versus the ad account for the same period and the same attribution.
• Tracking and attribution: pixels, postbacks, UTM tagging, attribution windows, event deduplication.
• Reports and dashboards: filters, periods, time zones, currencies, rounding — the classic sources of discrepancy.
• Billing: commission calculation, budget limits, campaign stops on overspend.
• Roles and access: agency, client, manager — who sees and can change what.

Load before a peak campaign

Seasonal peaks and big launches raise not only site traffic but the volume of data the platform pulls from ad accounts and recomputes. Load tests here are about queues, the database and API limits, not pages. We take a profile from real logs, set thresholds for p95 response time and error rate, run peak scenarios with queue and database monitoring and hand the team reproducible scenarios.

Automation that removes manual reconciliation

Where a reconciliation repeats every day, a manual test becomes a workflow: on schedule we pull data from the ad accounts and the platform, compare, and post to the team chat when a discrepancy exceeds the threshold. At a performance marketing agency such a reconciliation covers every ad account to the cent: a top-up book with transaction hashes, panel balances matching it, and a failure of any scheduled job goes straight to the chat as an alert.

1. We map which reconciliations and reports the team does by hand and how often.
2. We build workflows on n8n and Python, connect ad accounts, the CRM and spreadsheets.
3. Two weeks of parallel runs alongside the manual process, comparing results.
4. Switch-over, documentation, workflow support.

Who it is for

• Ad management and analytics platforms that pull data from several ad accounts.
• Agencies with their own client dashboards.
• Affiliate and tracking services where postbacks and attribution are the basis of payouts.
• Spend control and auto-rule services where a data error becomes a money error.