
ecatch is an online auction platform by Mindnow and Cornèrcard: interested buyers propose their personal maximum price for various products, get grouped by bid amount, and the group with the highest bids wins the product at the lowest suggested price within that group.
ecatch launched as an externally built MVP that we took over after go-live. There was no suitable overview for monitoring KPIs, and many end users did not understand the auction principle, failing to pay after winning their bid.

After the externally built MVP went live, we took over the project under tight time constraints. There was no KPI overview, and many end users misunderstood the auction principle and failed to pay for the products they won.


We built clear dashboards for suppliers, partners, and admins and made the "win first, then pay" concept understandable through automated messages. A progressive onboarding process was designed to encourage new users to explore, bid, and pay.

Onboarding paired with a triggered bid-reminder campaign doubled bets per user and sharply reduced non-payment. 1500 products sold within the first weeks and a very satisfied partner in Cornèrcard speak for themselves.
Starting from Cornèrcard's business requirements, we reworked the auction flow and made the "win first, then pay" principle clear through automated messages.
A step-by-step onboarding process eases new users into the platform and motivates them to discover products, place bids, and pay for the items they win.
A comprehensive dashboard displays all the important figures in a clear format, keeping platform operators well-informed at all times.
Automated bid reminders keep the auction running in the background, split bidders into groups, and increase the number of bids per user.
We improved the auction's user flow with a step-by-step onboarding and automated messages that explain the payment process. In parallel, we built a comprehensive dashboard that clearly surfaces every key KPI for suppliers, partners, and admins.
Mindnow was involved in these pages from BSI