OpenTable AI Assistant
Transforming the dining experience with intelligent, personalized booking solutions that account for users’ itineraries.
Problem Space
Problem Statement
How might we enhance the reservation process on OpenTable to offer instant, personalized booking options, and improve the management of group reservations and long-term dining plans?
Problem Background
Since the rapid growth of digital booking platforms, OpenTable has faced increasing demand for more efficient and personalized services. Our users need quicker, more intuitive booking options that cater to their individual and group dining needs.
Research Insights
User Pain Points
From our comprehensive analysis in the Research Synthesis, it became evident that users of OpenTable often face challenges with:
- Instant Booking: Users frequently encounter difficulties when trying to secure reservations at peak times, leading to frustration and a decrease in platform usage.
- Group Reservations: Organizing group dining experiences is particularly cumbersome due to the need to manage multiple preferences and schedules, which the current system does not adequately support.
Supporting Data
Our surveys highlighted critical statistics that reinforce the need for AI enhancements:
- 78% of surveyed users expressed dissatisfaction with the time it takes to find and book a reservation that meets their criteria.
- 65% of event planners noted the lack of efficient tools for managing group bookings as a major barrier to using OpenTable more frequently.
Feedback
Feedback from users who participated in surveys indicated:
- A strong appreciation for AI-driven features that could predict and suggest dining options based on past behaviors and preferences.
- Enthusiasm for features that allow for dynamic adjustments to bookings, which would be particularly useful for last-minute changes.
Landing on the Solution
Based on user feedback and pain points, we focused on developing AI-driven solutions like instant booking recommendations and group management tools that adapt to user preferences.
Explanation of Solution
After introducing the AI prototype to users, we refined our approach to focus more on personalization, leveraging data to enhance the accuracy of our dining recommendations.
User Flows
Future Steps
Continuing to gather user data will help us further refine the AI capabilities, possibly extending to more predictive capabilities based on user dining habits.
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Learnings
Product Manager Learnings:
Emmanuel Ojesekhoba
Application and Refinement of Skills
Participating in the Co.Lab program was an amazing experience. Throughout my time working on the OpenTable project, I was able to effectively apply and enhance my skills in user research, project management, and AI technology application. It was particularly enlightening to see how directly user feedback could drive product innovation in real-time.
Problem-Solving Approach
One significant learning was the importance of decomposing a large problem into manageable segments. My approach involved:
- Establishing a solid background understanding,
- Defining a clear and concise problem statement,
- Detailing specific goals, user stories, and scenarios to articulate the problem effectively.
This methodical breakdown prevented the common pitfall of rushing towards solutions without fully understanding the problem—ensuring that each aspect was thoroughly addressed without bias or assumptions influencing the research.
Growth in Confidence and Collaboration
Participating in Co.Lab not only enhanced my technical skills but also bolstered my confidence in navigating complex problem spaces. I learned to immerse myself in the problem, understand its roots, and develop solutions grounded in real user needs. The collaborative environment at Co.Lab provided a supportive community that was instrumental in this growth, offering perspectives that enriched the development process and ultimately led to a more refined product strategy for OpenTable.
Engagement in Co.Lab Initiatives
- Product Sprint: This program provided hands-on experiences that were critical to my learning, offering real-world applications of theoretical knowledge.
Mentorship: Engaging with my mentor enriched my understanding and ability to guide others through similar learning processes.
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.