Powering your unique return data and refining your product pages, we effectively reduce your return rate.
In fashion, around 50% of returns happens because of sizing inconsistencies. With yayloh, you no longer need to guess which product is sizing small or large nor adjust your sizing guides manually.
We analyze your unique return data, your customer feedback and your product attributes to pinpoint where your product pages need improvement—automatically.
Only by continuously analyzing your return data, recurring product issues can be detected.
In our platform, you set your own filtering criteria to flag products needing an update—whether it’s return rate, return volume or a specific reason contribution to return volumes.
This customizable filtering ensures that you're focusing on the products that matter most for your brand, so you can take timely action to reduce returns and improve customer satisfaction.
Based on patterns in return data and your customized criteria, the system recommends targeted sizing nudges for specific products.
These nudges guide customers toward better-fit choices, helping to reduce the likelihood of returns. Once you approve the recommendations, product descriptions are automatically updated on your website.
This eliminates the need for manual intervention, ensuring that your product pages stay accurate and up-to-date with minimal effort on your part.
Every change made to a product page is automatically logged in the system, ensuring full transparency and accountability.
As updates are implemented, yayloh tracks their impact on return rates, providing you with real-time data on how each adjustment affects customer behavior. Over time, this allows you to see the cumulative effect of your changes, helping you identify what works best in reducing returns.
With this data-driven approach, you can continuously refine your product pages and make informed decisions that further decrease return rates and improve customer satisfaction.
Make a well-thought-out choice.