How can I manually measure the return rate reduction myself?

If you wish to measure return rates and the reduction of it, we recommend you to follow the following guidelines.

While in our value reports we are tracking for you your return rates and how much the Size Advisor reduces them, sometimes it can be required to conduct a manual analysis on return rates.

  • We recommend to set up an A/B test and compare on A side Size Chart Users and B side Size Advisor User to get a complete picture


  • If you wish to analysis without an A/B test: A possible but not ideal way is to look size advisor user vs. non-size advisor users, however, there are different phenomena that influence the return rate. In an isolated comparison of Size Advisor users to Normal Visitors, the Size Advisor User Return Rate does not necessarily have to be smaller, because
  1. Individuals who are uncertain in terms of size have inherently a much higher return rate (i.e., orders with size recommendations or with any other size guide (e.g., table) showing higher returns rates)
  2. The comparison group (no size recommendation / size help required) can behave randomly depending on the shop, i. e.g. in countries or shops with very high returns rates (over 50-60%), then such a simple comparison happens to be good. But that has no statistical significance.
  3. Individuals who are uncertain in terms of size are also individuals who order a lot of choices and are therefore more likely to return. This becomes apparent from our analysis which concluded that Size Advisor users have a statistically significant higher return rate for non-size-related returns.

The comparison of Net Revenues, however, takes these phenomena better into account as it implicitly summarizes all of them. Furthermore, you can measure with the Net Revenue: "How much more EUR Size Advisor users keep on average compared to normal visitors. The Comparison of Net Revenues is what we do in our customer reporting.


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