Returnless x Tweakwise
Learn how to integrate Returnless return data with Tweakwise to optimize merchandising strategies based on return rates rather than just sales volume.
In current merchandising strategies, we often focus on popularity or sales volumes. This works in many cases, but it doesn't account for returns.
A product that sells frequently but is returned just as often damages profitability, logistical efficiency and sustainability.
By linking return data through Returnless, we can actively influence these products within the ranking for the first time.
How does it work?
Even when your overall catalog has a low return rate, our integration highlights specific outliers at the individual item level. It does this by calculating the return-to-conversion ratio for each individual product.
Here are the most effective ways you can use this attribute:
- Sorting: You can add the ratio to the recommended sorting option, so that products with a high return rate are scored lower.
You could potentially do this in combination with an A/B test. - Boosting: Products with a low rate are your true runners. Give these a subtle boost. Or vice versa: give products with a high rate a subtle bury.
- Recommendations: Make sure that cross-sell and upsell blocks (for example on the product detail page or in the shopping cart) do not recommend products with high return risk. You can do this by adding the returnless_segment to the sorting rule used in recommendations.
Instructions
- Implement Tweakwise Event Tag, see Event Tag introduction on your platform.
- Create a Returnless API key:
- Log in to your Returnless Panel.
- Create a new API key.
- For detailed instructions on managing keys, refer to the Returnless API Support Doc.
- Send the API key to your CSM.
- Tweakwise will calculate the return percentage (contact your CSM), the
returnpercentagewill be made available in your instance.
Usage
For the return percentage data to really be useful in boosting & sorting, the percentages should be flipped or turned into a segment. For example, create a range attribute to categorize/segmentize the percentages.
Example: range attribute that turns a low return percentage into a higher group value:

If you apply this attribute as boost, the products that have a low return ratio, will be boosted.
Updated 6 days ago