MacPaw Growth OS · From Product Insight to Scalable Growth
Good marketing doesn't scale content. It scales learning.
Explore how AI, experimentation, and growth analytics work together across MacPaw's product ecosystem.
Marketing spend
$908,710
90-day window
New trial users
113,190
Paid customers
23,295
Paid CAC
$39
Media spend / paid
ROAS
0.74×
Attributed 90-day revenue, 7-day click
Trial → paid
20.6%
Est. LTV
$130
Simplified: contribution / churn
CAC payback
5.5 mo
Portfolio comparison
Paid CAC and ROAS by product (same filters)
Revenue & conversion trend
Weekly attributed revenue and paid customers
Channel acquisition efficiency
Paid CAC by channel · bar label = share of spend
Funnel drop-off
Click → trial → activated (first meaningful action) → paid
Clicks
1.2M
entry
Trials
113.2K
9.3% of previous
Activated
70.7K
62.4% of previous
Paid
23.3K
33.0% of previous
Growth insights
Deterministic rules on the filtered data (Demo AI)
- Google Search shows the lowest paid CAC ($21) vs. LinkedIn at $292. Attribution is last-click; validate with a holdout before reallocating.
- Activated→paid (33.0%) trails activation (62.4%); test pricing page clarity and trial-end messaging.
- Blended LTV:CAC of 3.3× is above the 3× guideline under simplified LTV assumptions — room to test scale carefully.
Top three next experiments
Eney
- 1Productivity vs. proactivity vs. trust messagingActivated trials per $1k · Find which promise attracts users who actually activate.
- 2Guided first task in onboardingFirst meaningful task rate (D1) · Largest simulated drop-off sits between trial and activation.
- 3Permissions explainer before access promptPermission grant rate · Trust friction may block activation.