Blended CAC, Paid CAC & MER Marketing Efficiency Calculator

Growth Strategy: Why iOS Privacy and Attribution Require 'Blended CAC' and MER

Following Apple's ATT iOS 14.5+ privacy updates and cookie deprecation, single-channel in-platform attribution (e.g. Facebook Ads Manager) has become fragmented.

Why Modern CMOs Rely on MER and Blended CAC

• Marketing Efficiency Ratio (MER): Also known as Blended ROAS, MER looks at total business revenue divided by total ad spend, giving a holistic view of company performance without attribution guesswork.

• The Halo Effect: Paid ads drive searches on Google and word-of-mouth referrals that convert as 'organic' traffic; Blended CAC accurately captures this combined synergy.

How to Use This Calculator

Enter your Paid Advertising Spend ( / month) (e.g. 30000 (Meta, Google, TikTok, LinkedIn)), Sales/Marketing Payroll, Agencies & Tools ( / month) (e.g. 18000 (salaries, HubSpot, agencies)), New Customers Acquired via Paid Ads (e.g. 120), New Customers Acquired via Organic / SEO / Word-of-Mouth (e.g. 80 (Unpaid acquisition)), Total Company Gross Revenue ( / month) [for MER] (e.g. 140000), and Monthly ARPU ( / customer / month) (e.g. 150.0). Results update instantly as you type — adjust any value to compare scenarios.

The Formula

Omnichannel customer acquisition cost & MER equations: Marketing Spend = Paid Ad Spend + Sales/Marketing Salaries, Tools \& Agencies CAC = (Total Marketing Spend) / (Total New Customers (Paid + Organic)) CAC = (Paid Ad Spend) / (New Paid Channel Customers) Acquisition Share (\%) = ((Organic Customers) / (Total New Customers)) × 100\% Efficiency Ratio (MER) = (Total Company Gross Revenue) / (Total Paid Ad Spend)

Worked Example

For example, spending 30,000 on ads and 18,000 on team payroll/tools (48,000 total spend) to acquire 120 paid and 80 organic customers (200 total) with 140,000 in monthly revenue: . Paid CAC is . The organic customer share is 40.0%, yielding a Marketing Efficiency Ratio (MER) of \.

Understanding Your Result

Marketing metrics are most useful as trends over time rather than isolated snapshots. Benchmark your result against your own historical performance first, then against industry averages. Attribution models (last-click vs. multi-touch) can produce dramatically different channel ROI figures — ensure consistent attribution methodology before making channel budget decisions. Statistical significance requires sufficient sample size: most A/B test decisions need a minimum of 1,000 conversions per variant for reliable results.