The scope of the project was to develop an OTT (Over-the-top) movie recommender application that provides Personalized Movie Recommendations based on User Mood, Behavior, and Preferences.

The app's primary goal is to help users quickly and easily find movies on various platforms that match their interests, trends and mood, while minimizing the time and effort required to search for movies manually.

Scope of the project includes UX Research and Design of the FlixGenie application, based on the implementation of AI and ML algorithms to generate personalized movie recommendations.

• The need to balance simplicity and ease of use with the need to provide enough options and customization for users to find movies that match their preferences and mood.

• Limited access to comprehensive movie databases and APIs that provide accurate and up-to-date information on movie titles, genres, ratings, and user reviews.

• The need to comply with legal and ethical considerations, such as data privacy laws and avoiding biased or discriminatory recommendations.

• Conducted User Research:
  Conducted user research to understand user behavior, preferences, and pain points related 
to movie recommendations.

• Created User Personas:
  Based on user research, I was able to create user personas to represent different types of users 
and their needs.

• Designed Wireframes and Prototypes:
  Created wireframes and prototypes that reflect the app's features and functionality.

I am confused what to watch
I’m trying to search and select a movie
But unable to decide
Because overwhelmed with the vast amount of options
Which makes me feel angry as i waste most of the time browsing the content.

Create an application with rich UI which will give you recommended options based on Users Mood, Choice, Ratings & Reviews, Trends, with an option to watch it directly to different streaming platforms.

With the abundance of TV shows, movies, and streaming platforms available, choosing what to watch can be an unsettling task. We are often overwhelmed with the vast amount of options, leading to indecision and wasted time browsing through content. Additionally, many individuals have different tastes and preferences, making it difficult to find a show or movie that will satisfy everyone in a group. As a result, there is a need for a solution that can help consumers efficiently navigate through the endless choices and select the most appropriate content based on their individual preferences.

Netflix, Disney+, Amazon Prime Video are dominant players in the OTT streaming industry with a wide range of movie recommendations based on user history and preferences. However, they lack a dedicated mood-based recommendation system like FlixGenie, making it difficult for users to quickly find movies based on their current mood.

FlixGenie stands out in the OTT streaming industry with its precise AI and ML algorithm and dedicated mood-based recommendation system, making it easier for users to quickly find movies based on their current mood.

As part of the UX research for the FlixGenie project, a comprehensive user survey was conducted to gain valuable insights into users' movie-watching preferences, habits, and pain points. The purpose of this survey was to better understand the challenges users face when selecting movies from various OTT platforms and to inform the design of FlixGenie's personalized movie recommendation app.

• Explore users' movie-watching habits, including frequency, genres, and favorite movies.

• Understand the factors that influence users' movie selection process.

• Identify pain points related to content discovery and decision-making on OTT platforms.

• Gather feedback on users' expectations for a movie recommendation app.

The survey was designed as an online questionnaire, accessible to a diverse group of users. Participants were recruited through social media, email invitations, and online forums. The survey consisted of both multiple-choice questions and open-ended questions to encourage detailed responses.

The survey responses were carefully analyzed to uncover patterns and trends among users. Key insights included users' preference for specific OTT platforms, their desire for personalized recommendations, and the common pain points related to content discovery. The open-ended questions provided qualitative data on users' frustrations, desires, and expectations from a movie recommendation app.

Impact
The user survey played a crucial role in shaping the design and features of FlixGenie. The insights gathered directly informed the personalized recommendation logic, the implementation of the Mood Station feature, and the focus on a simplified and precise searching process. By understanding users' movie-watching preferences and pain points, FlixGenie was tailored to meet their needs effectively.

Conclusion
The user survey was a pivotal part of the FlixGenie project, providing invaluable feedback from users and helping to create a user-centric movie recommendation app. The insights gained through the survey ensured that FlixGenie addressed real user challenges, ultimately leading to a more delightful and satisfying movie-watching experience for users.

Affinity mapping is a powerful tool that enables us to better understand our users' needs and preferences, and ultimately provide them with the best movie-watching experience possible.

After collecting the feedback, we group them into common themes using affinity mapping. This helped me to identify the most critical issues faced by our users and prioritize them for future development. By analyzing the affinity mapping results, we can create a better user experience and provide more accurate movie recommendations that cater to our users' preferences..

Empathy mapping helped to gain insights into the user’s experiences with watching movies and TV shows. By understanding their emotions and motivations, I was able to design a better user experience that caters to their needs and preferences.
Empathy mapping can also help to identify opportunities for new features and improvements to existing ones. Overall, empathy mapping was a valuable tool for FlixGenie to create a more user-centered product.
Empathy mapping helped to understand users on a more personal level, and to identify pain points and opportunities for improvement.

I believe that people often experience decision paralysis when trying to choose what to watch on television or streaming services, due to the overwhelming number of options available.
By understanding more about people's viewing habits and preferences, we can develop tools and features that help people make decisions more easily and efficiently.

Final hypothesizes that by providing a simplified and precise user experience that takes into consideration the user's mood, behavior, and preferences, it will effectively solve the problem of users being overwhelmed with too many options and not knowing what to watch. By providing a quick and limited option and understanding user preferences, aiming to design FlixGenie to provide a personalized and enjoyable movie-watching experience for all users.

“When I am trying to choose what to watch on television or streaming services, I want to easily and efficiently make a decision, so that I can enjoy my viewing experience without feeling overwhelmed by the number of options available."

Katie is a mid 40’s year-old working professional woman who loves watching TV shows and movies during weekends. She's been feeling frustrated lately, as she finds herself spending more time scrolling through endless options on her multiple subscribed streaming services which includes Netflix, Prime Video, Hulu; than actually watching anything. She often ends up giving up and turning off the TV altogether.
She wants to be able to watch something she enjoys without spending so much time searching. She's heard about a new streaming app that offers simplified and personalized recommendations based on her mood, viewing history, and she's interested in giving it a try. She signs up for the service and is impressed by how simple and accurate the recommendations are. She's able to easily find a new show to watch and is excited to start binging. Thanks to the simple and personalized recommendations, she's spending less time browsing and more time enjoying her favorite movies and shows.

It's the weekend and Olivia is feeling bored. She wants to watch a TV show to pass the time, but she doesn't know what to watch. She starts scrolling through her options on Netflix, Disney+, Prime Video but the endless list of shows is overwhelming.
She spends 30 minutes scrolling through the different categories and still can't decide what to watch. She feels frustrated and wants to give up, but then remembers that she saw a Web/Mobile App with a survey about TV watching habits earlier in the week. She decides to try that to see if it can recommend something that fits her mood.
After answering the questions and connecting to her streaming account in the app, she is given a personalized recommendation based on her mood and viewing habits. She decides to watch the recommended show and ends up enjoying it. She feels relieved that she didn't waste her weekend just browsing through endless options and is happy with the App’s recommendation.

This project highlights the significance of UX/UI learning in creating a successful and user-centric movie recommendation app like FlixGenie.

The emphasis on UX/UI learning has empowered me, as the designer, to understand users' needs, preferences, and behaviors, resulting in a streamlined and intuitive user interface. The Mood Station feature, limited searching options, and user feedback loop are the direct outcomes of this learning process, proving the value of user-centric design.

FlixGenie's impressive features and positive user feedback reaffirm the impact of UX/UI learning in creating exceptional digital experiences. By prioritizing user satisfaction, this project showcases how effective UX/UI design can make a substantial difference in the competitive landscape of OTT streaming platforms.

As a UX/UI designer, this project has reinforced the importance of continuous learning and the power of design in shaping user interactions and enhancing overall app performance.