Project goals

The main task was to build a platform that would support the international development of the brand and eliminate the performance issues of the previous system. We focused on solutions that really support sales and build a premium image:

Building a stable architecture ready for heavy traffic, especially during periods such as Black Friday.
Shortening the customer’s path to the product. Search should be intuitive and return accurate results in a fraction of a second.
Personalization of purchases. The system should respond to user behavior and present them with tailored recommendations in real time.
Complete freedom in managing the content and aesthetics of the store so that the DRYKORN team can independently and efficiently conduct marketing activities.
Launching the entire project in four months, while maintaining the highest technical and visual standards.

Strategy and approach

We carried out the project in three-week sprints with an international team. This allowed us to maintain the right pace and respond to business needs on an ongoing basis. The foundation was laid at joint workshops, during which we learned about the DNA of the DRYKORN brand and precisely defined the goals to be achieved by the new store.

The business-first principle guided us, and technology was primarily intended to serve sales. Our priority was to launch the platform before Black Friday, which necessitated a strong focus on architectural stability during periods of high traffic.

We did not base our decisions on assumptions and verified each new feature or product presentation method in A/B tests. Thanks to this approach, listings and recommendations adapt to customer behavior in real time, which translates into better results.

Challenges and our solutions

We were working under time pressure. We had four months for the entire project, and the launch date was set for the upcoming Black Friday. The main challenge was to faithfully transfer the “pixel-perfect” vision to the online store.

DRYKORN is a brand for which every detail matters, so instead of using standard Shopware solutions, we designed and built mobile navigation from scratch. We also had to deal with the limitations of the old system, which hindered sales on international markets and couldn’t handle high traffic.

Algolia implementation

The search engine is one of the most important elements of this project, so we chose the Algolia system to enable customers to find specific products instantly. The tool responds immediately and, thanks to intelligent filters, can even handle imprecise queries.

The system works in search-as-you-type mode. The results on the screen change dynamically after each character entered, without the need to confirm the query or refresh the page. Algolia has an advanced typo-tolerance feature, so it finds clothes without error even if the customer makes a typo in the collection name or enters a word with a mistake.

We combined it with the Advanced Commerce solution, which turned static product lists into dynamic compilations. Now, the system itself suggests items that may interest customers based on their previous choices.

Implemented solutions

We chose a set of tools that guarantee stability and enable rapid growth in new markets:

Shopware 6: We opted for the latest version because it has the best performance mechanisms and natively supports international sales. This allows the system to run smoothly even under heavy load, which was crucial before Black Friday.
TYPO3 CMS: The brand needed space for extensive content. TYPO3 gives the marketing team complete freedom to build pages without involving developers, which speeds up the publication of new campaigns and makes them independent of the IT department.
Algolia: Standard search mechanisms did not meet the high requirements of a premium brand. Algolia works in real time and handles query errors very well, which directly facilitates shopping and shortens the path to the shopping cart.
Advanced Commerce: This module turns ordinary product lists into smart compilations. The system learns customer preferences and suggests clothes they are actually looking for, which increases the effectiveness of each visit to the store.
Google Analytics: It collects detailed data about every step the customer takes. This allows us and the DRYKORN team to make decisions based on facts, not hunches, which is essential when conducting A/B testing.

Results of the project

The platform reflects the DRYKORN premium identity and simplifies mobile shopping through custom navigation. By using Algolia for search and personalizing content, we made finding products faster and results more accurate. This keeps customers engaged and has led to an increase in sales and better use of every site visit.

The architecture handled heavy Black Friday traffic without any technical delays or downtime right after the launch. With detailed analytics, the DRYKORN team has moved away from assumptions. They now use hard data to tailor the store and the offer to actual user behavior.