Conversion Rate
Optimisation
Boosting eCommerce revenue through enhanced user experience.
The Approach
As a UX Designer in the CRO team, I collaborated with clients to enhance KPIs. I unearthed insights, devised concepts, oversaw execution, and held my breath during A/B tests. This systematic process was consistently repeated.
Moonmagic
Achieved a 6.9% ARPU growth by optimising the product page for a jewellery store.
Research
Analysing the user flow, I uncovered a pattern where 7% of transactions involved buying modifications of the same product. Notably, this user segment displayed the highest AOV and ARPU, suggesting potential for future experiments.
Hypothesis
Incorporating this behaviour pattern, I integrated the subject into the usability testing script. The revelation surfaced: users lacked the option to modify items and add them all to the cart.
Result
The new variation outperformed the control one in all key metrics:
6.9% ARPU growth・ 7.1% conversion rate growth・10.6% average order value growth・5.7% plus of the average number of units per transaction.
Somnifix
Enhanced the monthly revenue of the product landing page.
Research
Somnifix caters to individuals experiencing snoring issues. The landing page draws visitors from various sources. Examining user behaviour, I highlighted that approximately 30% of users failed to reach the product page at all.
Solution
The hypothesis tested aimed to present the product page without interrupting users seeking information. A quick view of the product is available through a slide-in overlay. This solution, combined with other optimizations, tripled the monthly revenue.
Very impressed by the speed and efficiency of the team's work. All the proposed changes and updates are always backed by data, not by assumptions. Since we've started working together in August 2019, the UX of our website has vastly improved and our monthly revenue has increased by 200 % (tripled).
Nich Michalak
Conclusions
Working with quantitative data was an incredible experience. Understanding real users and forecasting their behaviour while preparing and testing hypotheses for A/B tests was an interesting and highly useful part of the process.