Challenge
Develop a solution for displaying targeted ads to passengers in vehicles based on gender, age, and emotion.
Solution
An innovative app to showcase ads tailored to individual passengers, optimizing ad targeting, and boosting revenue while delivering a seamless user interface.
Tech stack
Swift, MVVM-C, Firebase, NetworkLayer, Vision, MLKit, Multithreading.
An established advertising firm with exclusive taxi in-car advertising contracts is Modsen’s longstanding client. They are focused on harnessing advanced technologies to enhance ad delivery, collect demographic insights, and create lucrative revenue opportunities for advertisers and taxi companies. As per the terms of the NDA, we are unable to disclose detailed client information.
Developing a cutting-edge in-taxi advertising solution that can accurately capture gender, age, and emotional data for ad targeting posed the primary challenge. Ensuring a seamless integration process into the vehicle infrastructure and implementing robust data security measures were crucial to realize improved passenger engagement and amplified advertising revenue.
1
Project Manager
1
Team Lead
2
Software Developers
3
QA Engineers
1
ML Engineer
1
UX/UI Designer
Given Modsen’s long-term partnership with the client, the initiation phase was smooth and streamlined. We promptly appointed a project manager, tech lead, and other key team members who had previously collaborated on successful projects. This allowed for quick team integration and effective communication. Defining deadlines and budget parameters was executed seamlessly, building on established working relationships.
Benefiting from our previous collaborations, the discovery phase progressed swiftly. With an in-depth understanding of the client’s preferences and requirements, we efficiently gathered specific project needs and conducted a thorough analysis of the target audience and market dynamics. Additionally, the team prepared detailed technical proposals, ensuring a cohesive and comprehensive project outline.
Drawing from our collective experience and expertise, we opted for an Agile development approach with 2-week sprints to enhance project efficiency and adaptability. By breaking down the development process into iterative cycles, the development team could continuously gather feedback from the client and make necessary adjustments to meet evolving requirements.
Developing a robust network layer was pivotal in handling network requests and facilitating seamless communication between the app and the server-side components. Our team employed Swift and NetworkLayer technologies to create a reliable and efficient network infrastructure for smooth data transmission and synchronization.
To ensure a scalable and maintainable codebase, our developers adopted the Model-View-ViewModel-Coordinator (MVVM-C) architectural pattern. This separation of concerns allowed us to manage complex data interactions, UI updates, and navigation flows efficiently. The architecture facilitated code modularity, making it easier to implement new features and perform updates without compromising the stability of the application.
We harnessed the power of Firebase as the backend platform for seamless data storage, synchronization, and management. The Firebase Realtime Database and Cloud Firestore were skillfully integrated to store the collected demographic and emotional data securely. Additionally, Firebase’s authentication and authorization features were employed to protect data and control access.
To enhance data processing and analysis capabilities while maintaining a responsive user experience, we strategically implemented multithreading techniques. Such an approach enabled us to efficiently distribute tasks across multiple threads, avoiding UI freezes and improving overall performance. Furthermore, rigorous performance optimization strategies were employed to maximize the application’s efficiency and resource utilization.
Crafting an intuitive and visually appealing user interface was paramount to delivering a seamless and engaging experience for both drivers and passengers. Our dedicated UX/UI designer meticulously followed industry best practices and brand guidelines to create an aesthetically pleasing design. The result was an interface that effortlessly guided users through the app’s functionalities and ensured a delightful user experience.
QA engineers at Modsen conducted thorough testing throughout the development process, encompassing both unit testing and integration testing. As a result of this rigorous approach, we were able to identify and resolve any issues or performance bottlenecks. We also ran acceptance testing with the client to verify that the final solution functioned reliably and accurately, meeting the highest standards of quality.
Throughout the development process, Modsen team provided regular demonstrations to the client, keeping them updated on the project’s progress and incorporating their valuable feedback to align the solution with their vision.
As part of ensuring the solution’s quality, the in-car advertising app underwent a comprehensive third-party audit by a reputable firm. The audit evaluated its architecture, codebase, network infrastructure, and data security. Successfully validating the application’s adherence to internationally recognized standards, including ISO 27001 for information security management and GDPR compliance for data privacy, relevant regional certificates were obtained, affirming the solution’s reliability, adherence to best practices, and commitment to safeguarding user data, thus instilling confidence in both the client and end-users.
Before the final delivery, we performed acceptance testing with the client to verify that the solution met all requirements and expectations. This step ensured the successful fulfillment of the client’s objectives and seamless integration into their existing ecosystem.
After thorough testing and successful acceptance by the client, Modsen proceeded to launch the AdTech solution into production. As a crucial step in our thorough handover process, we provided the client with the full source code and all relevant technical and business analyst documentation, facilitating a smooth transition to their internal teams for ongoing maintenance and further enhancements. To facilitate a smooth user experience, we prepared a detailed user guide that covered every aspect of the application, enabling both drivers and passengers to understand and utilize the app’s functionalities effortlessly. The user guide served as a valuable reference tool, empowering users to make the most of the in-vehicle targeted advertising solution.
The implemented taxi advertising platform enabled the client to display highly relevant ads based on passenger demographics and emotions. With efficient capture and analysis of gender, age, and emotional data, the application achieved precise ad targeting. Seamlessly integrating into the vehicle’s infrastructure, it delivered a seamless user experience for drivers and passengers:
Our team takes great pride in being part of this successful journey, working closely with the client to deliver exceptional results and driving forward their business objectives.
Surge in passenger response
Decrease in advertising waste
Boost in revenue generation