As an approved Burda IT supplier, we worked with the largest network and full-service provider for authentic micro and macro influencer marketing in Germany – tracdelight GmbH. Their platform connects publishers (bloggers, influencers, etc.) with fashion, beauty, home, food and sport brands and gives them the opportunity to earn money by sharing their products on social media and blog posts.
We did a full revamp and transfer of their outdated system onto a new, freshly build platform.
Our team worked on both the front-end and back-end part of the rebuilt publisher platform. The business logic of the system was kept untouched and in addition we implemented improved user interface.
We developed an automation tool, that helps publishers create a widget, which is filled automatically with a defined set of products. The users can choose between different layouts and product sets. All available products can be controlled by a set of filters (category, price, brand, etc.). Some of the filters feature an include/exclude switch.
One of the greatest advantages of the application is the precise statistics the system extracts with a detailed information about the bloggers' website visits and clicks. These data analytics help publishers improve their advertisement strategy. Infoleven took part in the adjustment and writing of the statistics back-end logic and entirely created the front-end part.
Another interesting feature we created is the tracking link generator extension, which can be used on Google Chrome, Firefox and Safari.
Our partners at tracdelight were particularly happy with the ability of the team to apply the agile methodology and cooperate with a product owner from the client's side. Our team successfully collaborated within a larger project team distributed on different locations. The online meetings were supported by planned on-site visits from both companies. Regular feedback rounds enhanced the positive progress and development of the team to ensure our long-term partnership.
Technologies Used:
- The front-end part was developed in React.JS
- For the back-end logic and server integration we used Node.JS and Python