LGM Financial Services Inc. developed a digital self-service tool enabling consumers to learn about F&I products suited to their individual needs before they even set foot in a dealership. Using decades of experience and consumer input, the tool leverages machine learning and a series of lifestyle questions to deliver relevant, personalized product recommendations.
Business Area: Automotive Insurance
Client: LGM Financial
Objectives: Developing an online tool to assist users in finding auto insurance products that are tailored to their specific needs
My Role: Conducting research and ideation, collaborating with field experts, presenting the design concept to stakeholders, and creating clickable prototypes for testing and refining the design. Managing the design process and work with the development team to implement the project, as well as the marketing team for post-launch support.
The challenge
Automotive protection products can be confusing. There are no shortage of options, making it difficult for drivers to know which products they need, and which products they don’t. In today's fast-paced society, it can be challenging to keep users engaged, especially when it comes to boring insurance-related topics. Assessing risks for drivers can be tedious and costly, and serves as a reminder of the potential drawbacks of vehicle ownership and operation.
The solution
Meeting with key stakeholders helped me to understand their business challenges. Together we identified risks and aligned on expectations and constructed a shared vision for the app. I then created an Experience Strategy outlining our incremental approach and direction for the needs assessment page.
The solution was to offer a set of questions that characterize driving habits, lifestyle and personal or family preferences. Based on that the algorithm will help to choose the most suitable insurance products to cover or prevent future problems, find the best offers and make a qualified decision according to your needs.
We approached the design of the tool as a step-by-step journey with the aim of simplifying the process of gathering the necessary information. One of the key questions we faced was whether to present all of the questions on a single page or to divide them up. After conducting research and testing the options in the field, we ultimately decided to use the "one question per page" approach, as it allowed us to focus on a specific topic and include interactive elements on each page.
Unlike most quizzes, this tool is designed to be both enjoyable and personalized. To set expectations and increase engagement, we added a progress indicator (1) and icons to represent each choice (2). These icons also help users make an emotional connection to the process. We wanted to ensure that our users understand the purpose behind the questions and how their answers may influence the products they see afterward (3).
Reach visual content can help create a friendly atmosphere and make a tedious process fun.
We used our own set of icons to simplify the interfaces and make it easier for users to understand what they can do. The icons portray the main characteristics of each user, such as gender, age, location, lifestyle etc. These are used in a way that makes it easy for users to distinguish them without having to give too much thought about it.
The tools
For my initial drafts and ideas, I chose Adobe Photoshop. Due to tight time constraints, we decided to develop a high-fidelity prototype in Axure RP. All icons were created in Adobe Illustrator, exported as SVG and converted to custom fonts via icomoon.io. This move helped speed up the process for developers.
The result
The UI is designed to show the user a set of products that are relevant to their driving style and habits. This intuitive interface works the way the user expects it to, keeping them engaged while they shop.
