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Goal: Minimize cost per signup, trial, and activation — see how each paid channel performs and track the trend over time to catch regressions early.

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Cost per Outcome — Evolution (Combined paid)

Cost per Outcome — by Period & Channel

Cost per Outcome — Full Period Summary

Ad Spend — Meta + Google Ads ▼

Signups per Period — by Source ▼

Campaigns — Meta & Google Ads ▼

Attribution: Meta = 7d click + 1d view  ·  Google Ads = last click  ·  Signups/Funnel = Metabase (facebook utm → Meta; google utm or _gcl_aw → Google Ads; youtube/trustpilot/etc utm → shown by name; no utm → Organic)

Goal: Find leaking buckets — which steps lose the most users, and does the drop vary by acquisition channel? Compare new (V2) vs legacy onboarding performance.

Onboarding v2 Funnel — 8 steps, unique by email

Source
Device

Onboarding v2 — Leaking Buckets by Channel ▼

Onboarding v2 — Leaking Buckets by Device ▼

Onboarding v2 — Channel Breakdown Table

Onboarding v2 — Trial Behaviour

Legacy Onboarding Funnel — 9 steps, unique by email

Source
Device

Legacy — Leaking Buckets by Channel

Legacy — Leaking Buckets by Device

Legacy — Channel Breakdown Table

Trial Behaviour — 14-day window

Legacy vs Onboarding v2 — Signups · Trialing · Active

Goal: Track revenue health and retention — use MRR, ARPU, and LTV to set acquisition spend targets and evaluate channel ROI.

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Paying Customers ▼

Churn — subscription_status ≠ active, newest first ▼

Current Trials — V2, ordered by trial end date ▼

Goal: Understand how user behaviour varies by language — identify where each language drops off in the funnel and which languages have higher churn after activation.

All-time data  ·  Signups up to 14 days ago (recent cohorts excluded — they haven't had enough time to complete the trial cycle)  ·  Language = account owner's preferred locale set in Overloop

Funnel by Language

Conversion Rates — Visual Comparison

Cohort Analysis

Granularity
Metric

Annotation

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