Grovana.ch: higher revenue through targeted conversion optimisation
Background
Swiss watchmaker Grovana stands for high-quality “Swiss Made” timepieces. Since 1924, the family-run company from Tenniken has been crafting precise, durable wristwatches for women and men. In its official online shop, watch lovers find classic automatic watches, elegant quartz models and exclusive personalisation options.
Client statement
“Adisfaction-Annex spotted the many conversion opportunities in our online shop straight away and turned them into a clean concept. We were pleasantly surprised by how much impact the optimisations had, and it motivates us to keep developing the shop.”
Christopher Bitterli (Managing Director, Grovana Uhrenfabrik AG)

Starting point
In 2024, the grovana.ch online shop already had clear navigation, plenty of filter options and product pages with attractive images and feature descriptions. Yet the conversion rate stayed well below expectations. Generating strong revenue therefore meant buying a lot of traffic.
What we did
We used MS Clarity to analyse heatmaps and click maps. This alone revealed a long list of UX issues, such as searches that returned no results and dead links, which were then fixed.
To give shoppers more guidance and confidence, we added labels such as “Bestseller” to products at category level, made the zoom on product pages much larger and displayed product availability. The checkout was given stronger contrast, and popular payment options were highlighted.
At the end of 2025, new features followed: elegant gift wrapping and watch engraving, which cater perfectly to customers buying a gift.
Results
Once the first UX improvements went live in May 2025, the positive results came quickly. Within just a few weeks, the conversion rate had doubled. Further refinements lifted it by another 50% in 2026.
Grovana.ch is a good example of a common pattern: standard shop software works fine technically, but lasting e-commerce success only comes from a deeper look at UX and continuous conversion rate optimisation.

For reasons of confidentiality, we do not disclose exact details of the time period, baseline or data source.
