Glassdoor AI Interview SmartPrep
An AI-driven interview preparation tool that helps job seekers get ready for interviews by providing personalized question predictions, company-specific insights, and answer tips.
Problem Statement
How can we utilize AI to transform interview preparation on Glassdoor, leveraging real user-generated data to create a comprehensive resource that empowers job seekers to confidently succeed in their interviews?
Problem Background
The job market is currently very competitive and difficult to navigate. To stand out and secure a job offer, job seekers must be well-prepared and confident during their interviews. Glassdoor is already one of the most widely used platforms for job seekers researching companies and interview experiences. By integrating this AI-powered interview prep assistant seamlessly into the interview section of company profiles, we can increase awareness of this feature enabling user to seamlessly practice for an interview with greater confidence and ease
Research Insights
User Pain Points
Users reported difficulties in finding and preparing for role-specific questions and lacked confidence in interviews due to uncertainty about potential questions. Additionally, job seekers found the disorganized interview content on Glassdoor to be a drawback, leading to lower engagement with this feature compared to others, such as salary insights. These pain points were identified through user interviews and further validated through surveys to gather quantitative data.
Supporting Data
- Approx. 83% of respondents struggles to prepare for role-specific behavioural or technical interview questions.
- Approx. 40% of respondents cited poor organization of interview content on Glassdoor as a challenge.
- Approx. 40% of users found mock interview practice to be highly impactful.
- Approx. 75% of respondents found company insights on Glassdoor highly valuable for interview
Landing on the Solution
Based on user’s pain points and their usage habits of Glassdoor we wanted to create an AI-driven interview prep solution called ‘Interview SmartPrep’ that would be very engaging, user-friendly and not disruptive to their user experience. Job seekers preparing for an interview will see a Call-To-Action (CTA) button directly on the company’s profile interview page with a compelling text such as the following: “Try *NEW* AI Interview SmartPrep”
Explanation of Solution
An AI-driven interview preparation tool that helps job seekers get ready for interviews by providing personalized question predictions, company-specific insights, and answer tips. Interview SmartPrep leverages existing data from real interview experiences shared on Glassdoor to generate relevant practice questions, interview insights, and tips. Data is collected from past and current Glassdoor users, who are encouraged to leave interview review/feedback when engaging with any of the three (3) SmartPrep modules: ‘Commonly Asked Questions,’ ‘AI-Powered Insights,’ or ‘Mock Interview’ to increase our SmartPrep AI knowledgebase. Using this tool, users can practice interview questions, conduct mock interviews, refine their responses with AI-powered feedback, improving their chances of success in interviews.
User flow
Wireframe
Mock-up/Low fidelity Prototype
Commonly Asked Interview Questions
Interview SmartPrep AI Chatbot
Interview Insights
Interview Tips
Next Steps
Mock Interview
Future Steps
Looking ahead, we plan to refine the current MVP and introduce additional features to enhance the SmartPrep experience. The current MVP success will be measured based on the following criteria:
- Active Users - Number of users who have interacted will SmartPrep in some way or the other in the first 90 days of it going live.
- Frequency of interaction - Which out of the three (3) modules: ‘Commonly Asked Questions’, ‘AI-Powered Insights’, and ‘Mock Interviews’, are users interacting most with. *This will guide us on what we need to focus on building/iterating on. *
- Time Spent - Average time spent using the SmartPrep tool.
- User Satisfaction & Experience - User satisfaction scores and ratings on their experience with SmartPrep. Additionally, we can assess how users perceive the relevance and accuracy of our AI in predicting interview questions that closely align with real interview scenarios.
Marketing Images & Marketing Strategies
Marketing campaign image sample
Marketing Strategies for Glassdoor Interview SmartPrep
- Content Marketing - Write articles on interview preparation tips, insights and career advice, linking back to SmartPrep's features.
- Social Media Marketing - Use social media sites like Instagram and Tiktok where Glassdoor already has a presence/profile to advertise and promote SmartPrep. Host Q&A and live info sessions about the tool.
- Booth or Kiosk Presence - Set up a booth or kiosk at tech events, networking events, workshops, etc. where attendees can experience SmartPrep firsthand. Offer live demonstrations of the platform’s features, such as the mock interviews or AI-powered insights.
Glassdoor AI SmartPrep PowerPoint Presentation
Glassdoor AI Interview SmartPrep.pptx
Recorded Pitch Presentation
Pitch - Glassdoor AI Interview SmartPrep
Learnings
Product Manager Learnings:
Chioma Olisekwe
Joining Colab, I had a broad understanding of Product Management and Artificial Intelligence (AI). However, through this program I gained a much deeper grasp of both.
I learned the foundations of AI, including machine learning, Large Language Models (LLMs), and the difference between supervised and unsupervised models for example. I was also exposed to new tools such as bolt.new, Figma, Microsoft Copilot and of course ChatGPT.
I also came to understand the importance of continuously testing models with the right inputs to avoid issues such as ‘overfitting’ or ‘algorithmic bias’ due to a limited dataset for models to train on.
On the product management side, my biggest takeaway is that a PM’s primary focus should be to try to thoroughly understand the problem before jumping into solutions. It is crucial to back proposed solutions with data and user research to truly address user needs.
Designer Learnings:
Designer Learnings:
Jo Sturdivant
- Adapting to an Established Team: Joining the team in week 6 of 8 was challenging, as I had to quickly adapt to existing workflows, dynamics, and goals. This mirrors real-world situations where you often integrate into teams mid-project, and flexibility is essential.
- Work-Blocking for Efficiency: With only two weeks to complete the project, I learned the importance of a structured work-blocking system. This approach allowed me to manage my time effectively and meet deadlines under pressure.
- Making Data-Driven Design Decisions: Unlike my past projects, I had to rely on research conducted by others. This was a valuable experience in using pre-existing data to guide design decisions, helping me focus on the core insights without starting from scratch.
Developer Learnings:
Developer Learnings:
Vanady Beard
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As the back-end developer, I learned how important it is to create efficient and reliable systems that support the entire application. This experience also taught me the importance of optimising the database and ensuring the backend is scalable and easy to maintain.
Developer Learnings:
Stephen Asiedu
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As a back-end developer, I've come to understand the importance of being familiar with various database systems and modules. This knowledge enables me to build diverse applications and maintain versatility in my work. I've also learned that the responsibility for making the right choices rests on my shoulders, guided by my best judgement.
Developer Learnings:
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Developer Learnings:
Maurquise Williams
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- Process of Creating an MVP: Developing a Minimum Viable Product (MVP) taught me how to focus on delivering core functionalities balancing between essential features and avoiding scope creep.
- Collaboration in a Real-World Tech Setting: This experience taught me how to collaborate efficiently in a fast-paced tech environment, keeping the team aligned and productive, even while working remotely across time zones.
- Sharpening Critical Thinking and Problem-Solving Skills: This experience honed my ability to think critically and solve problems efficiently. By tackling challenges and finding quick solutions, I sharpened my decision-making and troubleshooting skills in a dynamic, real-world setting.
Developer Learnings:
Jeremiah Williams
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All in all this experience was very awesome I learned that in coding with others being transparent is key
Developers Learnings:
Justin Farley
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I learned how important communication is when working with a team. Communication provides understanding, advice, ideas, and much more. While working with the product team, I’ve found that communication keeps everything flowing smoothly. Working with a team also showed me that every member brings something different to the table and we all have to work together in order to align and meet our end goal.