Why Your Best ROAS Campaigns Have the Worst Return Rates

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Quick poll, which campaign do you think is more profitable… 

Campaign A: 4.2x ROAS, Campaign B: 2.8x ROAS. 

Most brands would scale Campaign A without a second thought, but when you pull Shopify return data and match it to UTM parameters, the story changes. 

Campaign A has a 43% return rate… 

Campaign B sits at 18%.

After factoring in returns and restocking costs, Campaign A barely breaks even. 

Campaign B prints money. 

When 40% of your "conversions" get returned within 30 days, you're not running profitable campaigns. 

You're funding a reverse logistics operation. 

In this email, we're breaking down: 

• The return rate tracking gap most eCom brands miss 

• How campaign elements directly correlate to return rates 

• The Net Revenue Attribution Stack that shows true profitability after returns 

Let's dive in:

Picture this: 60 days until Black Friday/Cyber Monday, and you're watching competitors lock in their Q4 strategies while you're still figuring out where to start.

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A proven system ready to deploy.

Most brands waste precious weeks trying to piece together campaigns, testing what might work, and hoping they haven't missed critical opportunities. Meanwhile, the top performers are already executing battle-tested plays that will drive record revenue.

The BFCM Playbook Stack is your competitive advantage.

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Inside, you'll discover:

→ SMS sequences that convert automatically - Pre-built campaigns designed to capture sales you'd otherwise miss 

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→ Customer experience frameworks - Keep buyers coming back long after the holiday rush ends 

→ Checkout optimizations that rescue abandoned carts - Proven tactics to capture revenue at the finish line 

→ LTV maximization blueprints - Turn one-time Black Friday shoppers into lifetime customers 

→ Social selling plays - Leverage the platforms where your customers are already spending time 

→ Weekly BFCM intelligence - Fresh strategies delivered to your inbox as the season evolves

These are the exact plays that are going to drive millions in Q4 this year.

No guesswork. No wasted budget. Just a proven roadmap to your most profitable quarter ever.

Your record-breaking Black Friday starts here.

The Return Rate Tracking Gap

Most brands track ROAS at the campaign level and return rates at the business level. 

That gap is where profitability dies… 

Your Meta dashboard shows revenue, while your Shopify analytics show returns. 

But unless you're connecting ad campaign data to return behavior at the customer level, you have no idea which campaigns drive serial returners versus keepers.

UTM-Level Return Attribution 

Tag every Meta campaign with unique UTM parameters. 

When a customer returns an order, tie it back to the specific campaign, ad set, and creative that acquired them. 

Pull a report showing return rate by UTM source. 

Your highest ROAS campaigns likely have dramatically higher return rates than lower ROAS campaigns. 

How Campaign Elements Drive Returns 

• Discount Depth 

Campaigns offering 30%+ discounts show return rates 15-25% higher than full-price campaigns. 

Discount-driven buyers over-order with plans to return. 

A skincare brand running 40% off campaigns saw 4.8x ROAS with 51% return rate… 

At 15% off, ROAS dropped to 3.1x, but return rate fell to 22%. 

Net revenue was 40% higher. 

• Product Showcasing 

Ads using heavily edited product shots or lifestyle imagery that doesn't match reality see return rates spike. 

Brands using authentic photography with accurate lighting see 20-35% lower return rates. 

• Audience Targeting 

Broad audiences outperform on ROAS but underperform on retention. 

Retargeting campaigns and email list lookalikes show the lowest return rates because these audiences have brand familiarity before purchasing.

The Net Revenue Attribution Stack

Tracking true profitability requires connecting three data sources. 

Step 1: Campaign-Level Revenue Tracking 

Use UTM parameters on every Meta campaign. 

Track first-order revenue, repeat purchase rate, and CAC at the UTM level. 

Step 2: Return Data Integration 

Pull Shopify return data and match it to the original order UTMs. 

Calculate return rate, average return value, and time to return for each campaign. 

The average return costs brands 15-20% of product value beyond just the refund. 

Step 3: Net Revenue Calculation 

Subtract returns, restocking costs, and return-related expenses from gross campaign revenue. 

Compare campaigns on net ROAS rather than gross ROAS.

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Final Thoughts

ROAS is a vanity metric when 40% of your conversions get returned. 

The campaigns that look best in your Meta dashboard often perform worst when you factor in return behavior and wasted ad spend on serial returners. 

Start connecting ad data to return rates at the campaign level. 

Track which audiences, creative angles, and discount strategies drive keepers versus returners. 

Your "best" campaigns might be your worst. 

You won't know until you track what happens after the purchase.

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Disclaimer: Special thanks to Postscript & Superfiliate for sponsoring today’s newsletter.