How FUXBAU uses exit-intent and post-purchase surveys to learn why shoppers leave and where new customers come from
FUXBAU is a German Shopify brand that sells clothing made from natural fibers and manufactured in Europe. Together with their customers, they are committed to a sustainable future, and their fair fashion community is a big part of how the brand grows.
We spoke with Kenny from the FUXBAU team about how they use Zigpoll to:
- Keep attribution running after Shopify's checkout changes broke their previous post-purchase survey
- Find out exactly why shoppers leave without buying, with percentages for each reason
- Turn those answers into pricing and product page changes, then measure whether the objection shrank
Why FUXBAU switched to Zigpoll when Shopify dropped additional checkout scripts
Survey Type: Post purchase
Survey Question:
"How did you discover us?"
FUXBAU's first goal was simple: understand how customers discovered the shop. They had been running a "how did you hear about us" survey with a different tool, but that tool relied on Shopify's additional scripts in the checkout. When Shopify discontinued support for those scripts, the survey stopped working and the tool offered no replacement.
"We wanted to use a post-purchase survey to understand how our customers discovered us. We previously integrated a survey using a different tool, but when Shopify discontinued support for additional scripts in the checkout process, that tool no longer offered a way to do this."
Zigpoll's post purchase survey runs on Shopify's checkout extensibility, so FUXBAU could keep asking the same question on the order confirmation page without any custom scripts.
What the exit-intent survey revealed about lost sales
Survey Type: Exit intent
Survey Question:
Why shoppers are leaving without buying
Alongside attribution, FUXBAU runs an exit-intent survey that asks shoppers who are about to leave what stopped them from ordering. Because the answers are multiple choice, the team gets a clean ranking of objections rather than a pile of open-ended comments to sort through.
Here is how the responses break down:
| Reason for not buying | Share of responses |
|---|---|
| Prices are too high | 30.0% |
| Uncertainty about size or fit | 26.3% |
| Desired product not available | 10.7% |
| Uncertainty about quality or material | 7.9% |
| Something else | 5.8% |
| Shipping costs are too high | 4.9% |
| Missing product information | 4.9% |
| Missing payment method | 4.5% |
| Technical issues | 4.4% |
Two objections, price and size or fit, account for more than half of all lost sales. Everything else is in single digits. For a brand that makes clothing from natural fibers in Europe, neither result is a surprise, but seeing the proportions gave the team a clear order in which to act.
What FUXBAU changed: prices where possible, size charts in the gallery
The team addressed the top two objections directly. For price, they reviewed their range and adjusted prices on the products where there was room to do so. For size and fit, they moved the size chart out of a separate tab and into the product image gallery, where shoppers actually look.
"Based on the results, we adjusted our prices where there was room to do so, and for the size and fit question we added size charts to our image galleries."
What happened next: fewer shoppers citing size and fit
Because the exit-intent survey kept running after the changes, FUXBAU could measure the effect with the same question they used to find the problem. After the size charts went into the galleries, the share of leaving shoppers who chose "uncertainty about size or fit" fell from 31.8% to 29.5% in the comparison period, a drop of 2.3 points.
"Following the integration of the size chart into the image gallery, the size and fit answer in the exit-intent survey was selected noticeably less frequently."
The price adjustments are harder to score. They rolled out product by product with no single cutoff date, so the team is careful not to claim a number for them. That honesty is part of why the sizing result is credible: it comes from one change, one date, and one survey question measured before and after.
Takeaway: an exit-intent survey is both the diagnosis and the measurement. Leave it running after you ship a fix and the objection rate tells you whether the fix worked.
Using post-purchase attribution to vet new channels quickly
On the attribution side, Zigpoll's results closely matched what FUXBAU's previous survey had shown, which confirmed the data was trustworthy and gave the team a reliable baseline for where new customers come from.
The biggest ongoing value is speed. Whenever FUXBAU tries a new marketing channel, the post-purchase survey shows within weeks whether that channel is actually bringing in new customers, without waiting on platform reporting or modeled attribution.
"We currently have a solid foundation and know where our new customers come from. It is always interesting when we begin using a new channel; the survey allows us to quickly determine whether that new channel is successfully attracting new customers."
How FUXBAU would describe Zigpoll to another Shopify brand
"Zigpoll is a very useful tool for gaining a better understanding of customer behavior, provided, of course, that you ask the right questions."
