The formula, the data sources, the pitfalls — and how to keep LTV current across platforms without rebuilding it every week.
Separate realized LTV (what a cohort has actually paid) from predicted LTV (a model). Both need the window stated.
LTV pulls from multiple platforms, each with its own definition and refresh lag. The moment you finish the report it's out of date — so it gets rebuilt next week. The fix is to automate the inputs and the write-back, not just the chart on top.
Illustrative. A 90-day cohort has generated $7.40 of revenue per user → LTV(90) = $7.40. Against a $15 CAC, that cohort hasn't paid back by day 90 — which is fine or alarming depending on your retention curve.
Comparing predicted LTV against realized CAC, or quoting LTV with no window — "LTV" without "over N days" is meaningless.
Opera pulls the inputs across AppsFlyer and your ad platforms, applies your lifetime value definition, reconciles the sources, and appends the result to your existing report — append-only, formulas preserved — then schedules it and posts a summary.
"Refresh the LTV report with this week's numbers by channel, and flag anything off target."
Skip automation while the lifetime value definition is still being argued about, while the report's structure changes weekly, or for one-off analyses. Automation pays on stable, recurring reports — lock the definition first, then put it on a schedule.
Opera is built to touch production reports and live ad accounts without breaking anything:
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.
Estimate the hours and fully-loaded labor cost your team spends on recurring reports — and what Opera gives back.