AI Interview Training App (AI Features)
A web app that offers a set of AI-based interview tools to help job seekers ace their interviews.
Role: Product Lead
Problem Statement
Job seekers want immediate feedback on how to improve their interview skills.
There is a lack of effective and tailored interview preparation tools. Existing resources often lack realism and personalized feedback, leading to suboptimal preparation experiences. Additionally, there is a need for comprehensive progress tracking and personalized recommendations to enhance interview skills.
Goal Statement
Develop an AI-powered interview preparation app that prioritizes two key features:
Create an immersive mock interview simulator with AI-generated instant feedback.
Implement robust learning analytics powered by AI to track user's progress and identify areas of improvement.
Offer customized roadmap based on each user's specific scenario, that maximizes user’s potential for success.
DISCOVER
User Research
To gain a profound understanding of the challenges faced by job seekers, we conducted customer development calls. These insightful conversations revealed three primary needs:
Instant feedback regarding their performance during interview preparation, allowing users to gauge their progress in real-time.
Immediate coaching guidance provided promptly to assist users in recognizing areas for improvement, fostering continuous and immediate refinement of their interview skills.
Personalized learning plans tailored to the unique needs and objectives of individual users.
These findings became the cornerstone of our mission to revolutionize the interview process.
IDEATE
User Scenarios
After conducting interviews, we extrapolated multiple user scenarios and defined key insights, which were then translated into specific user needs.
To effectively tackle these needs for each persona through the application of AI, we devised distinct features and solutions tailored to cater to the unique requirements of each individual.
This process ensured that our proposed features align seamlessly with the identified user needs, enhancing the overall user experience and addressing specific challenges encountered by each persona.
Based on the importance and number of times certain insights were repeated across the personas, we were able to prioritize the AI solutions we found.
Actionable Feedback Framework
Constructive feedback becomes truly valuable when it is presented in an actionable format that facilitates improvement. It’s a 4 step process of describing: the Situation, the Behavior, the Impact and the Next steps.
By following this framework, I was able to deliver immediate AI feedback on crucial aspects such as body language, eye contact, and verbal tics, that could unknowingly cost candidates the job.
Personalized AI Learning Plan
Our next step was to craft a personalized AI learning plan for each user, utilizing insights from onboarding responses, app usage, and performance results.
We incorporated the following gamification strategies:
Setup Challenge during Onboarding: Introducing personalized challenges right from the onboarding process to tailor the learning journey to individual user goals.
Keep Users Motivated Along the Way: Implementing motivational elements such as encouragement messages, timely notifications, and accessible help features to support users throughout their learning experience.
Visual Progress Feedback: Employing visual indicators such as progress bars, scores, and levels to provide users with a clear and engaging overview of their learning progress.
Rewards Upon Completing Sections: Offering instant AI feedback and personalized action plans as rewards for successfully completing sections, enhancing the learning experience.
DESIGN
Wireframes
My next step was to test the waters with wireframes, ensuring early user input.
By crafting these detailed screens, I aimed to meticulously define the visual elements and overall user interface, capturing the essence of the feature's functionality and providing stakeholders with a realistic preview of its appearance and behavior.
UI Design
I carefully crafted an interface that would provide a seamless and intuitive experience for users. By adopting a clean design aesthetic, I aimed to create a visually pleasing interface that would enhance usability and promote user engagement.
Design principles such as "Hierarchy," "Emphasis," "Repetition," and "White Space" guided the creation of an easily scannable AI report. Users found the color-coded feedback particularly helpful, enabling them to identify areas for improvement at a glance.
User Testing
In our efforts to gather user insights, we conducted a comprehensive feedback survey focusing on three critical aspects: Value Provided, User Experience and Results Accuracy.
The user feedback survey revealed a strong appreciation for the value and user experience of the AI feedback feature, coupled with constructive insights on potential refinements to further enhance the accuracy of the results. These findings provide a solid foundation for iterative improvements, ensuring the continued satisfaction and effectiveness of the tool for users.
Next Steps
To enhance the AI feature further, continuous improvement of results accuracy is a priority.
Additionally, user-driven criteria will be added based on valuable feedback received, ensuring the tool evolves to meet changing user needs.
The customized learning plan demands substantial work in personalization to ensuring it aligns precisely with each user's unique circumstances and aspirations.