5
Awards
13.2%
Lead reactions
10%
Configurator entries
2.6%
Test drive requests
150,000+
Users/month
Finding the right vehicle isn’t easy: With dozens of model variants and billions of possible combinations, prospective buyers often feel overwhelmed. Mercedes-Benz recognized this user pain early on. Essentially, people are looking for a vehicle that fits their lifestyle. That' s why we jointly developed the first lifestyle-based recommendation engine, which represents a radical simplification compared to complex configuration processes. The
engine delivers matching vehicle recommendations based on personal preferences. This playful introduction to the portfolio is particularly helpful for new customers with no prior product knowledge. Artificial intelligence forms the basis of this approach and achieves great results: on an above-average basis, customers use the suggested vehicle for further customization.
Picking the personal favorite from millions of possible combinations of vehicle models and equipment types can be a tedious and laborious task. But with the help of a learning AI, however, this becomes a playful pleasure that only takes a few minutes. The basic concept: Tell us about your lifestyle and we'll show you the vehicle that suits you. In this way, customers who do not want to delve deeply into technical facts are given exploratory access to the portfolio along with full freedom of choice. Thanks to filter and configuration functions for exterior and interior, the Lifestyle Configurator's recommendation quickly becomes the personal vehicle of your dreams—equipped entirely according to your own taste.
In addition to its smart technical foundation, the Lifestyle Configurator also excels in terms of look-and-feel and usability. Three Red Dot Awards, an OttoCar Award and an Automotive Brand Contest Award confirm this view. The natural, dialog-based design sets new standards. The results of the AI recommendation are visualized in real time so that each vehicle can be experienced individually. Intuitive, seamless, and fluid—this is how product exploration is turned into a truly inspiring and convincing experience.
With the Lifestyle Configurator, we set ambitious goals for the user experience on the front end. The current JS application frameworks could not keep up. So without skipping a beat, we decided to develop our own, higher-performing libraries, which we have successfully used in other projects as well.
We developed the recommendation engine based on machine learning and artificial intelligence in close cooperation with the Fraunhofer Institute for Intelligent Analysis and Information Systems as well as Berylls Strategy Advisors. Thanks in part to this cooperation, we were able to deploy the first version of the machine learning system within just 3.5 months. For the touch table version, we also oversaw the provision of its corresponding hardware solution. At the IAA 2015, visitors were able to try out the Lifestyle Configurator on our large-scale touch interface. Based on the user feedback, we further optimized and developed a web version within just 3 months.
For the recommendation engine’s frontend, we fully leveraged the app-like capabilities of AngularJS: What may appear playful, relies in fact on the extensive interplay of conversational UI elements, complex sequential animations, and next-best-action targeting. The existing JS application frameworks were quickly pushed to their limits, so we implemented our own performance improvements and completely replaced parts of the frameworks. The libraries we developed for sequential animations, among other things, have proven their long-term effectiveness.
To make complex products with many configuration options easily accessible, we address one central question: How do people go about searching for the products that are perfectly tailored to their needs? With this as our focus, we guide users directly to the product they want.
Only the best are able to deliver outstanding solutions. That's why we complement our experience in product strategy, UX/UI design and development with the expertise of qualified partners who are leaders in their respective fields—such as machine learning and artificial intelligence.
Above all, a good solution must prove itself in practice. That's why we do everything we can to get a Minimum Viable Product (MVP) up and running as quickly as possible. This allows us to monitor performance and target the areas where optimization is most needed.