POAS Course Part #6: Reaktion Exclusive — POAS After Refunds
By now, you’ve learned what POAS is, how it differs from ROAS, why it matters in 2025, and the kind of results it can unlock.
Now it’s time to go one step deeper, into a metric that’s exclusive to Reaktion and essential for brands with meaningful return rates.
Introducing: POAS After Refunds.
The only metric that tells you the actual profit your ads generate after returns and refunds are accounted for.
What Is POAS After Refunds?
It works just like regular POAS, but instead of stopping at the initial sale, it continues tracking the order long after the purchase.
If a customer returns an item, Reaktion automatically syncs that data from your store backend and pushes it into your reporting and ad platforms.
That means your performance numbers reflect reality, not just the moment the order was placed.
With POAS After Refunds, you can measure:
- Return rates
- Returned revenue
- POAS after returns
- ROAS after returns
- Profit after refunds
Across campaigns, ad groups, ads, and even products.
And in Google Ads, you can even optimize directly for profit after returns, ensuring Smart Bidding bids on customers who keep their purchases, not those who send everything back.
Why It Matters More Than Ever
Returns and refunds are simply part of ecommerce — especially in categories like fashion, footwear, accessories, and home goods.
Customers often can’t try, test, or feel products until after they arrive. Naturally, some items come back.
But here’s the problem:
You can generate thousands in profits on paper, and lose all of it when those orders get returned.
If you only look at standard POAS or revenue-based metrics, the numbers look great, while your actual profit is zero.
POAS After Refunds fixes that.
It shows the truth behind your advertising results and ensures you’re not scaling campaigns that secretly bleed profitability.
What You Can Do With It
By tracking and optimizing for profit after returns, you can:
- Identify audiences with high return rates
- Cut wasted spend on non-returning customers
- Improve product strategy and merchandising
- Reduce operational costs from processing returns
- Train Google’s bidding algorithm on actual profit, not short-term revenue
This matters especially for industries where return rates reach 20–30% or more.
Ignoring refunds leads to inflated profit metrics and bad decisions.
Feeding accurate data back to the algorithm leads to better outcomes.
Once again — the algorithm is king.
And the quality of the data you feed it determines everything.
POAS After Refunds ensures you’re optimizing for profit that sticks, not orders that disappear.