WatchBuddy

Introduction

Have you been in a situation where after a long busy day you finally sit in front of the TV, thinking that you will unwind for some time; And instead of relaxing you end up frustrated with the decision fatigue of what to watch? Sounds relatable right? We all face this problem frequently.

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Problem

Number of paid streaming services, and number of unique titles have increased exponentially in recent years, making it difficult to select what to watch.

The frustration of choosing right content stems from two major factors

1. Unavailability of relevant content. 60% of the content users are paying for is not relevant to them. (source: accenture)

2. Time spent on browsing and selecting titles. The average viewer spends 10 ½ minutes searching for titles every time they decide to watch something. (source: cbsnews)

While this problem is age-agnostic, most time spent on streaming services are by Gen-Z and Millenials.

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Our Hypothesis

1. Viewers are overwhelmed & frustrated with the time and energy spent on browsing titles and streaming services when it comes to selecting what to watch.
2. Users primarily search for relevant titles on Google, IMDB, Rotten Tomatoes etc. that throw a long list of titles, adding to the decision fatigue.

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Problem Statement

We are aiming to make the process of choosing entertainment titles less frustrating and time consuming for millennials and GenZ so that they get more time to unwind and waste less time on searching for the titles.  

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Research Insights

We conducted initial user research (21 participants age 25-34 yo) to validate our hypothesis and gauge the severity of the problem. We found out that 

1. The process of choosing a relevant title is cumbersome! A significant majority of users (20 out of 21) find it at least somewhat difficult (rating 3 or above) to decide what to watch on a streaming service.

2. The problem is prevalent! 90.5% of users said “There are too many options and it's overwhelming to choose.

3. There exists a sizable market for a potential solution! 80.9% of users are interested in a tool to help them quickly and easily choose content to watch. 

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User Pain Points:

• Overwhelming Library of Content Selection: Users feel overwhelmed by the vast amount of content available, leading to decision fatigue and difficulty in making a choice.
• Reliability on Ratings: While users highly value ratings, they don't fully trust the streaming services ratings and often resort to external sources to validate. They wish for easier ways to access detailed information about titles without accidentally starting an episode.
• Limited Variety and Lack of Personalization in Recommendations: Users are dissatisfied with the lack of variety in recommendations and the limitations of preset categories, making it challenging to discover new content tailored to their preferences.

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User pain-points can be summarized as:

In their own words…..

❝ I think for me it's mostly the visual overload and overwhelmingness that ends up making me feel defeated when choosing a title ❞

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Landing on the solution: 

• To create a valuable product, we began by focusing on the user's pain points and behaviors. The goal was to empower users to choose content from their streaming services more efficiently– decreasing decision fatigue and balancing options available to choose from. We hypothesized that decreasing the number of choices given to a user and allowing their current mood to dictate what to watch will make their decision making process easier, compared to being presented hundreds of movies and shows on the service homepage.

• What stood out to us in our research was:
  • Users find browsing overwhelming due to choice overload and lack of personalization. They experience decision-making challenges and pain points such as choice paralysis and wasting time scrolling.
  • Users highly value ratings and reviews. We found that users often browse online before deciding on content to watch to extrapolate information about ratings, reviews, and synopses from external sources like IMDb and Rotten Tomatoes.

• With user pain points in mind, we decided to frame the problem into something actionable:
  • How might we (HMW) help users streamline their decision making process to reduce information overload?
  • HMW help users make informed decisions about what to watch so they feel it's worth their time?

Key Features:

• Simplicity is the backbone of this product. We designed a simple, one-stop web app that includes 2 key entry points to get movie recommendations:
  • Mood-Based Browsing: Users get tailored recommendations based on their current mood. To streamline the process further, a streaming service filter was implemented to provide recommendations accessible to the user based on what they subscribe to.
  • Similar Content Discovery: Users can find movies similar to what users have already enjoyed.
  • Concise Output: By providing 3 curated suggestions, we reduce the cognitive load and promote faster decision-making through a 'bite-sized' approach. With each recommendation, users can get quick, concise information about ratings, a more detailed plot, similarity scores between movies, and summary of audience reviews all in one place. 

Feedback & Achievement:

• We’ve received positive user feedback showing that WatchBuddy is a simple, but impactful tool that people have been seeking. 
• With the introduction of WatchBuddy as a tool to combat decision fatigue and doom scrolling, a 30% increase in confidence in being able to find content more quickly was achieved; and on a scale of 1-5 (1 unlikely, 5 very likely), users rated their likelihood to returning to our product a 4.75.

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Mid-Fi Wireframes:

Hi-Fi Wireframes

Implementation Details: 

• Tech stack used: 
  • The backend was built using Flask with Python and JavaScript. We chose Flask because our product is small and straightforward. Flask is light-weight and easily set up. Additionally, it interacts well with external APIs, and its built-in support for JSON simplifies parsing data.
  • For the frontend, this project leverages a modern web development stack to deliver a seamless user experience. Next.js, a powerful React framework, is used for building the front-end, providing server-side rendering and optimized performance. The design and UI components are styled with Chakra UI, ensuring a responsive and visually appealing interface. Vercel is employed for continuous deployment, enabling smooth integration with GitHub for automated updates. This tech stack combines the best of React's component-based architecture with Next.js's performance optimizations and Chakra UI's design system, resulting in a robust, scalable, and user-friendly application. 

• Where is it hosted?:
  • We used the free tier of Render to deploy the backend because it supports continuous deployment and requires minimal configuration.

• Technical Tradeoffs:
  • One of the significant technical tradeoffs involved building the backend from scratch. While using Flask allowed for flexibility and customization, it required a steep learning curve. As a result, I had to rely heavily on support from mentors and peers, which increased the initial development time but ultimately provided a tailored solution that met our specific need.

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