Return On Ad Spend

Q: How do you calculate ROAS?

ROAS = Revenue from Ads / Ad Spend

The revenue generated for every dollar spent on advertising.

2 min readLast updated Apr 2026

Reviewed by Golden Digital·Operator-reviewed ecommerce reference·Benchmark source: Golden Digital field data

Formula

ROAS=Revenue from Ads/Ad Spend

Example: ROAS = $87,500 / $25,000 = 3.5x

The revenue generated for every dollar spent on advertising.

Use our free ROAS Calculator to calculate your true return on ad spend instantly.

Why It Matters

ROAS is the primary metric for evaluating paid advertising performance. It directly answers: 'For every $1 I spend on ads, how much revenue am I getting back?' Understanding your ROAS allows you to scale profitable campaigns, cut underperformers, and allocate budget efficiently across channels.

Formula

ROAS=Revenue from Ads/Ad Spend

Example: ROAS = $87,500 / $25,000 = 3.5x

Benchmarks

A good ROAS is 4–6×. Top performers achieve 6×+.

Good Performance

4–6×

Top Performers

6×+

Practical Example

Scenario

A jewelry brand spends $25,000 on Meta ads in March and attributes $87,500 in revenue to those campaigns.

Calculation

ROAS = $87,500 / $25,000 = 3.5x

Result

At 3.5x ROAS, they generate $3.50 for every $1 spent. If their target is 3x to maintain profitability, this campaign is exceeding expectations and could potentially receive more budget.

In-Depth Explanation

ROAS measures marketing efficiency at the channel or campaign level. A 3x ROAS means $3 revenue per $1 ad spend.

Pro Tips

1Set ROAS targets based on your margins, not industry averages. A 70% margin brand can be profitable at 2x ROAS; a 40% margin brand might need 4x+.
2Track ROAS by campaign type: prospecting (2-3x), retargeting (5-8x), and branded (10x+). Blending them hides real performance.
3Account for attribution window differences. 7-day click ROAS will be lower than 28-day—compare apples to apples.
4Don't chase maximum ROAS—you'll under-spend. Find the ROAS where you can profitably spend more while scaling.

Common Mistakes to Avoid

Treating ROAS as the only metric. High ROAS on small spend isn't as valuable as slightly lower ROAS on much larger spend.

Comparing platform-reported ROAS across different attribution models. Meta 7-day click vs Google 30-day aren't comparable.

Optimizing for ROAS without considering LTV. A 2x ROAS on customers with 3x LTV might be better than 4x ROAS on one-time buyers.

Frequently asked questions

Depends on your gross margin. Formula: Minimum ROAS = 1 / Gross Margin. At 50% margin, you need 2x ROAS to break even on first order. At 70% margin, 1.43x. Add buffer for overhead and profit—typically target 1.5-2x your break-even ROAS.

Different attribution models. Meta counts conversions that touched their ads; Shopify shows total revenue. If customers see a Meta ad but buy via email, Meta claims the sale while Shopify attributes to email. Neither is 'wrong'—they measure different things.

Not always. Consider: 1) Is it prospecting? (Lower ROAS is expected), 2) What's the customer LTV? (Low ROAS on high-LTV customers is fine), 3) How does it affect other channels? (Pausing top-of-funnel starves retargeting). Evaluate holistically.

Put it to work

Related Terms

Marketing Efficiency RatioMER

Total revenue divided by total marketing spend, providing a holistic view of marketing efficiency.

Cost Per AcquisitionCPA

The cost of acquiring a specific action through a particular campaign or channel—such as a purchase, sign-up, or lead.

Customer Acquisition CostCAC

The total cost of acquiring a new paying customer, including all marketing and sales expenses divided by the number of new customers acquired over a specific period.

Gross Margin

The percentage of revenue remaining after subtracting the cost of goods sold (COGS).

Multi-Touch AttributionMTA

Distributes credit for conversions across multiple touchpoints in the customer journey.

Calculate Yours

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7.7x blended return at scale — seven figures attributed, across five straight quarters · Modern Prairie · Apr 2025–Jun 2026 Read the Modern Prairie case study