Marketing reporting automation for fintech apps

Fintech UA is attribution-heavy and AppsFlyer-centric, with blended CAC spread across Meta, Google, TikTok and Snapchat. Reporting has to tie spend to purchases and first transactions, not just installs.

The fintech funnel you're optimizing

Front-end clicks and installs are the top of a longer funnel — and for fintech, the metrics that decide profitability live further down it:

impression → install → registration → checkout / verification → purchase → first transaction

What a good fintech report shows

Spend, installs and cost per purchase by channel and market; blended and per-channel CAC against purchases; verification and first-transaction rates; cohort LTV.

The measurement nuance that trips teams up

A run you could schedule today

"Update the weekly acquisition report with spend by channel and purchases from AppsFlyer, and flag any market where cost per purchase rose more than 15%."

Opera pulls spend from each ad platform, counts the purchase event from the AppsFlyer Raw Data Pull API per market, computes cost per purchase against your definition, appends the week, and posts the flags to Slack — compliance-friendly, append-only, fully logged.

How Opera automates fintech reporting

Opera reads your existing report, pulls fresh data across platforms, appends it safely (formulas preserved), reconciles spend against attribution, and posts a summary to Slack or email — on the cadence you set.

"Update this week's report with spend and new customers by channel and market, and flag anything off target."

Safe enough for production

Opera is built to touch production reports and live ad accounts without breaking anything:

• No destructive writes. Updates are append-only by default — your existing data and formulas are never overwritten.
• Preview before execution. You see exactly what Opera will change before a single cell is written.
• Campaigns paused by default. New campaigns are created paused, with approvals required before any spend.
• Full audit logs and client-level isolation. Every action is logged, and each client's data and rules stay separate.