Keep CAC current without rebuilding the sheet every week. Opera pulls spend and real customer events across platforms and computes CAC the way you define it — blended and per channel, in one pass.
CAC is the metric most likely to be silently wrong, because it has the most moving parts: spend from four platforms, a customer definition that isn't 'install', and a denominator that must be deduplicated. Automating it means automating the *inputs and the definition*, not just a formula cell.
Spend lives in four ad managers; customers live in the MMP. Stitch them weekly by hand and you get boundary mismatches, platform-claimed conversions double-counted against MMP events, and — the classic — CAC quietly computed on installs because that column was easier to find than purchase accounts.
Opera stores the definition once and applies it every run: CAC = spend ÷ new customers, where 'new customer' is the event you count — a first purchase, a purchase, a First Subscription commerce Succeeded — pulled event-level from the AppsFlyer Raw Data Pull API and deduplicated per user. Channel CAC and blended CAC come from the same pass, so the blend can't flatter a channel that's off.
"Refresh blended and channel-level CAC for last week and flag anything above target."
| Channel | Spend | New customers | CAC | vs target |
|---|---|---|---|---|
| Meta | $13,900 | 1,012 | $13.74 | ✓ |
| $17,800 | 998 | $17.84 | ✓ | |
| TikTok | $9,400 | 571 | $16.46 | ✓ |
| Snap | $7,100 | 376 | $18.88 | ⚠ |
| Blended | $48,200 | 2,957 | $16.30 | ✓ |
Same guarantees as every Opera report: schema re-validated, previewed append-only writes, duplicate periods refused, audit-logged. Start by locking the customer definition in writing, run one cycle in parallel with your manual number, then schedule it with a target threshold so breaches get flagged in the summary.
See this running on your own reports.A 45-minute workflow audit maps your current process and shows exactly what Opera automates — step by step.
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