Return Rates Should Dictate Your Bidding Strategy
A sale is not a sale until the customer keeps the product. If you are bidding the same for products with 5% and 50% return rates, your profitability maths is fundamentally broken.
The Returns Blind Spot
Google Ads reports revenue at purchase. Returns happen weeks later, often in different systems. This timing gap means most accounts optimise for revenue that never materialises.
The Return Rate Reality
Ecommerce return rates vary dramatically by category. Fashion runs 30-40%. Footwear can exceed 50% during size-finding periods. Electronics typically stays under 10%. Home goods land somewhere between.
Even within categories, return rates vary by product. Fitted items return more than basics. New styles return more than proven sellers. Gift purchases return more than self-purchases.
Yet most Google Ads accounts treat every product identically. The bidding algorithm sees a £100 sale and optimises accordingly, regardless of whether £40 of it will come back next week.
"When you bid £20 CPA for a product with 40% returns, your real CPA is £33.33. If you did not account for that, your target ROAS is a fiction."
Calculating Return-Adjusted Bids
The adjustment is straightforward. If a product has a 30% return rate, only 70% of attributed revenue is real. Your effective ROAS is 70% of reported ROAS.
Low Returns (10%)
- • Reported ROAS: 4.0
- • Return-adjusted: 3.6
- • CPA adjustment: +11%
- • Max bid: near standard
High Returns (40%)
- • Reported ROAS: 4.0
- • Return-adjusted: 2.4
- • CPA adjustment: +67%
- • Max bid: significantly lower
The Cost of Returns
Returns are not just lost revenue. They incur direct costs: shipping both directions, inspection and repackaging, potential markdowns for damaged or out-of-season items, customer service handling.
A £100 order that returns might cost £15-25 in processing. The customer paid nothing, the product is back in inventory, and you are down the CPA plus the returns handling cost.
For high-return products, this completely inverts the economics. A "profitable" CPA on paper becomes a loss once returns and processing are included.
Implementation Approaches
Three Ways to Incorporate Returns
- 1.Value Rules by Product Category
Assign different conversion values to different product groups based on historical return rates. Quick to implement, coarse-grained.
- 2.Feed-Based Value Adjustment
Include return-adjusted margin in your product feed. Each SKU carries its own true value for bidding. More accurate, requires feed infrastructure.
- 3.Offline Conversion Adjustment
Send return data back to Google as negative conversions after the return window closes. Most accurate, most complex to implement.
Audience Segments and Returns
Return rates also vary by customer type. New customers often have higher return rates than repeat buyers. Gift purchasers return more than self-purchasers. Mobile shoppers sometimes return more than desktop.
Understanding these patterns allows for smarter audience bid adjustments. Rather than chasing new customer acquisition with identical bids, factor in the higher return rate to find your true cost of acquisition.
The Seasonal Factor
Return rates spike during sale periods and post-Christmas. Customers buy more speculatively when prices are low. Gift purchases have inherently higher return risk. The January returns wave is predictable and substantial.
Yet Q4 bidding rarely accounts for this. Brands chase Black Friday revenue without adjusting for the 40% that will return in January. The "record sales" celebration often precedes a painful returns hangover.
Building the Data Loop
Effective return-adjusted bidding requires connecting systems that often live separately. Order data from your ecommerce platform, returns data from your warehouse or 3PL, Google Ads conversion data, and ideally offline conversion imports.
The infrastructure investment pays back quickly. Even a 10% improvement in bid accuracy on high-return products can transform marginal campaigns into profitable ones, or reveal that apparently profitable campaigns are losses.
The Bottom Line
If your return rates vary by more than 10 percentage points across your catalogue and you are not adjusting bids accordingly, you are systematically overspending on high-return products. That is not optimisation. That is hoping for the best with someone else's maths.
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