Why this matters
Marketing Analysts use ROAS and MER to decide where to spend the next dollar and when to scale or pause campaigns. Teams rely on you to:
- Set channel efficiency targets and budgets.
- Diagnose performance swings after creative or bidding changes.
- Explain blended efficiency to non-technical stakeholders.
- Balance channel-level ROAS with business-wide MER so growth does not kill profitability.
Progress note: The quick test is available to everyone. Only logged-in learners will have their progress saved.
Concept explained simply
ROAS (Return On Ad Spend) tells you how much revenue you earned for every dollar of ad spend for a specific campaign or channel.
MER (Marketing Efficiency Ratio), also called blended ROAS, shows how much total revenue the business earned for every dollar of total marketing spend across all channels.
- ROAS = Channel Revenue / Channel Ad Spend
- MER = Total Revenue / Total Marketing Spend
Mental model: Zoom lens
Think of ROAS as a zoomed-in lens on a single channel. MER is the zoomed-out lens on the whole business. ROAS helps optimize within channels; MER ensures the overall business remains efficient while scaling.
What MER is not
- MER is not a channel metric. It cannot be used to judge a single campaign in isolation.
- MER is not a margin metric. It ignores cost of goods, shipping, and overhead unless you use contribution margin instead of revenue.
Targets and practical thresholds
- Typical eCommerce target MER: 2–5 depending on margins and scale.
- Typical channel ROAS: varies by channel and funnel stage. Prospecting is usually lower than remarketing.
Tip: If your business margin after variable costs is 50%, then a MER of 2.0 roughly breaks even on marketing before fixed costs. Adjust using your actual contribution margin.
Worked examples (step-by-step)
Example 1: Single-channel ROAS
- Spend: $10,000 on Paid Search
- Attributed revenue (same source-of-truth): $40,000
- ROAS = 40,000 / 10,000 = 4.0 (400%)
Interpretation: If your target ROAS is 3.0, this channel exceeds target and may be a candidate for more budget (capacity permitting).
Example 2: Blended MER across channels
- Spend: Search $15,000; Paid Social $25,000; Email $2,000
- Total Spend = 15,000 + 25,000 + 2,000 = $42,000
- Total Revenue (site-wide): $126,000
- MER = 126,000 / 42,000 = 3.0
Interpretation: As long as MER stays at/above target (e.g., 3.0), scaling top-of-funnel channels with lower ROAS can still be healthy.
Example 3: ROAS down, MER steady
- Before: Paid Social ROAS = 1.8; MER = 3.2
- After: Paid Social ROAS = 1.5; MER = 3.2
Interpretation: Although social ROAS declined, total efficiency stayed the same. Social likely assisted other channels. Consider keeping scale if MER is on target and growth matters.
How to analyze ROAS and MER (fast workflow)
Hands-on exercises
Do the exercise below, then check your work using the solutions. Mirror of Exercise ex1.
Exercise ex1: Compute ROAS and MER
Given one week of data:
- Search: Spend $12,000; Revenue $36,000
- Paid Social: Spend $18,000; Revenue $30,000
- Email: Spend $2,000; Revenue $28,000
Tasks:
- Compute ROAS for each channel.
- Compute MER for the week.
- Recommend: scale, hold, or reduce Paid Social if MER target is 2.8.
Show solution
Search ROAS = 36,000 / 12,000 = 3.0
Paid Social ROAS = 30,000 / 18,000 ≈ 1.67
Email ROAS = 28,000 / 2,000 = 14.0
Total Spend = 12,000 + 18,000 + 2,000 = 32,000
Total Revenue = 36,000 + 30,000 + 28,000 = 94,000
MER = 94,000 / 32,000 ≈ 2.94
Recommendation: Paid Social ROAS is low but MER is above the 2.8 target. Consider holding or cautiously scaling Paid Social if growth is the priority, while monitoring MER.
Self-check checklist
- I used the same time window for spend and revenue across channels.
- I computed both channel ROAS and overall MER.
- My recommendation references the MER target, not only channel ROAS.
- I noted any data caveats (attribution, refunds, margins).
Common mistakes and how to self-check
- Mixing attribution sources: Platform-reported revenue vs
- Ignoring returns, discounts, or taxes. Self-check: Use a consistent definition, ideally contribution margin when profitability matters.
- Judging a channel only by its ROAS when MER is on target. Self-check: If MER is healthy, low-ROAS prospecting may be fueling growth.
- Using MER to evaluate a single ad. Self-check: MER is blended; use ROAS (or experiments) for granular decisions.
- Time-lag blindness. Self-check: Compare equal windows and consider delayed conversions for upper-funnel channels.
Practical projects
- Build a weekly ROAS and MER tracker: one tab per channel plus a summary that flags when MER drops below target.
- Create a scenario model: If spend increases 10% on Paid Social, estimate new MER at a range of ROAS outcomes (1.2–2.0).
- Attribution sensitivity check: Compare MER when using Gross Revenue vs Contribution Margin to see impact on targets.
Mini challenge
Your company’s MER target is 3.0. This week:
- Total spend: $80,000
- Total revenue: $232,000
- Paid Social ROAS fell from 1.8 to 1.4 after scaling.
Questions:
- What is the new MER?
- Do you scale further, hold, or reduce Paid Social?
- What guardrail will you watch next week?
One possible approach
MER = 232,000 / 80,000 = 2.9, slightly under target 3.0. Hold or slightly reduce Paid Social to recover MER, and monitor MER daily plus new customer volume and CAC.
Who this is for
- Marketing Analysts and Growth Marketers needing channel and blended efficiency metrics.
- Performance marketers who plan budgets and scaling decisions.
- Founders who want a simple control metric for profitable growth.
Prerequisites
- Basic understanding of revenue, spend, and time windows.
- Comfort with ratios and percentages.
- Access to consistent revenue and spend data.
Learning path
- Learn ROAS and MER definitions and formulas.
- Build a simple sheet that calculates channel ROAS and weekly MER.
- Add targets and color-coded alerts for under/over-performance.
- Layer in contribution margin if profitability is the priority.
- Practice weekly post-mortems: what moved ROAS and MER?
Next steps
- Automate your ROAS/MER dashboard refresh.
- Add confidence bands using historical variability to avoid overreacting.
- Design a budget shift test and monitor MER as the guardrail.