Fave App — Emerging Media Capstone

Find the Best From People You Trust

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Project Summary

Everybody is on the hunt to find the very best but this search comes at a cost. People spend countless hours crawling the web and reading reviews from complete strangers in the hopes that they will find a new favorite. They bounce around from site to site to research entertainment, restaurants, travel destinations and more, all the while losing efficiency and building stress.

Fave is a social recommendation and list-making app that lets users rank their top ten favorites in a variety of genres, read recommendations from their friends and instantly try these recommendations for themselves. Fave is a one-stop shop app for finding the best things that are approved by people you trust.

The Problem

Scroll through Twitter or Facebook and you’ll see it. People are asking their friends and followers for advice and recommendations more and more these days. Hours are wasted searching through Amazon, Goodreads, Netflix, and Yelp for a 5-star lead that will live up to the hype. Ranking and review sites are so segmented that 59% of participants in a recent survey said that they rely on 2–3 different sites to read reviews before making a decision. Everybody wants to find the next best thing but nobody wants to spend all their time getting there or relying on a complete stranger’s opinion.

The following scene may be a familiar struggle:

Fave eliminates this time consuming and exhausting task by bringing rankings and reviews for books, movies, music, restaurants and travel all in one simple app. Users no longer have to bounce around from site to site to find reliable reviews. The app lets people track and share their top ten favorites within these categories and includes short reviews from the people they trust the most: their friends.

Project Features

Fave is currently in the prototype stage. The prototype includes a number of essential features that set it apart from other review sites and apps.

Top Ten Lists

Each user has their own profile page within the app. On this profile page they can list their top ten favorites (called Faves) within pre-designated categories (books, movies, music & TV, restaurants and travel) along with any categories they want to add. Fave lists are limited to ten so that users share only their true favorites and best recommendations for each category. The ranked Faves are displayed in a gallery that slides horizontally so users can view the entirety of the list by swiping left and right.

Short Reviews

When a user taps into a Fave item, the app displays a pop-up window that provides extra details such as authors, directors, locations and photos. This window also includes a short review from the individual that added the Fave. These succinct reviews (approximately 40 words or less) encourage users to get straight to the point when offering their recommendation to further improve task efficiency.

Direct Links

Fave is all about helping people find the best things. Part of this process is letting users actually try the Fave right away. Fave offers direct links to websites where people can take action or learn more about an item their friend has added. Examples of these links connect users to Amazon, Netflix, Spotify, iTunes, restaurant menus and tourism websites.

Add a Fave

The app is driven by crowdsourcing. Therefore it was important that users find the process of adding a fave to be simple and enjoyable. Fave lets you add a fave to your own lists in two ways. If you find something on a friend’s fave list you also consider a favorite you can click the “Fave” button on the details page to begin the process. Additionally, users can click the plus button on the bottom menu to add a Fave. The app takes users through six easy steps that take only seconds to move through. These steps include picking a category, selecting a sublist (if applicable), naming the Fave, ranking the Fave, adding a review and uploading a photo.

Fave Feed

Whenever a user adds a new Fave, their friends will see the ranking and review on their Fave Feed. The feed orders the posts with the most recent appearing at the top of the home page. This feed is great for discovering new things from friends and inspiring further exploration within profile pages and categories.

Search Engine

To help users find what they are looking for faster, the app offers a search engine feature. Users can filter their Fave Feed by entering keywords such as book genres, locations, people, etc. to pull up relevant Faves.

Future Features

In later iterations of the app, Fave will incorporate more features to improve the app experience.

  • Commenting/Liking: users can interact with one another by liking and adding comments to their friends’ Faves
  • Direct messaging: users can message friends to ask questions about Faves or seek recommendations in the app
  • Friend matching: users can choose to be matched with others that have similar favorites
  • Geo-notifications: the app will send push notifications when a user is near a business or landmark that has been Faved by their friends
  • Public profiles: users can follow people they are not direct friends with, such as celebrities and other public personas

Prototype & App Technology

Fave is a prototype created with the Justinmind software. Justinmind is a tool that can be downloaded and used to develop the user interface and design of websites and mobile apps. Justinmind was chosen to develop the Fave prototype because it allows for rich interactions, such as filtering contentm and came with prepared layout features and icons. Justinmind can be downloaded and used for free. A paid pro version is also available that offers deeper tools and interactions.

The fully developed app will require integration with a user’s social network, such as Facebook. Facebook Login for Apps is commonly used to help people create accounts and connect with their friends within apps. Examples of the Facebook Login in apps include games, music platforms like Spotify and more. Facebook Login will help Fave build a user base by automatically filling a user’s friend list and encouraging them to share the app with their friends.

Potential Impact

Fave has the potential to change how people search for reviews and how trends spread in the entertainment and restaurant industry. People will no longer have to search on different websites to find effective reviews. The app brings all of this information to one place and directly to the user’s pocket. Industries will be able to see how they are performing in the market by analyzing their presence on Fave lists across the app.

Fave will also have a great impact on the individual’s personal life. Users will be able to enjoy the best entertainment and share their own expertise with their friends. People will be able to connect over shared interests and experiences and learn more about their friends that, without Fave, they may have never discovered.

Lessons Learned (Research, Design, Development)

Initial Research: Before creating the Fave solution, a round of knowledge gathering was conducted. This included a Google Forms survey which was distributed online through Reddit forums. The survey asked a number of questions about how people search for reviews and find new things to try. The survey received responses from 75 participants and learned that people use multiple sites to read reviews, trust their friends and family most for recommendations and are open to sharing and reading top ten lists from people they know well.

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Based on this data, an initial prototype for Fave was created using Marvel in Fall 2016. This version of the app was tested among potential users to discover user flow preferences, potential usability issues and changes for design and layout. This research implemented the think aloud method as well as textual feedback from participants to gather their questions, opinions and suggestions related to the app. Input from this first round of user testing powered decision-making for the second iteration.

The second iteration of the Fave prototype was developed with the tool Justinmind to offer richer interactions and quick development. Once the minimum viable product was finalized, Fave was tested a second time among potential users.

Two tests were conducted in the second round of research. The first used card sorting to determine the best categories to include in the app. The study was created with Optimal Sort and participants were recruited via online forums. Participants were asked to sort 16 items into one of two groups (1. I have clear favorites in this genre or 2. I do not have clear favorites in this genre).

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This method revealed that the participants are most likely to have clear favorites in categories like songs, things to do, books, hobbies, music artists, websites, restaurant and movies. Participants are less likely to have clear favorite bars, concerts, events, magazines, podcasts, albums, cities and shopping.

This falls mostly in line with the categories selected for the app. However, this study relied on responses from just 7 participants. A larger-scale study is required to fully confirm these results and drive future decisions about the categories.

The second user study focused on actual interactions with the prototype. Five participants explored the app as they completed pre-determined tasks and questions in a Google Form.

Results from this study found that users are divided on how the ranks should be ordered. One participant suggested that the app allow users to decide what order they prefer in a settings option

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Additional comments and ideas that have since been implemented in the prototype include:

  • add a skip option for some steps in the “Add a Fave” process (add a photo, add a review)
  • reconsider the icon bank for adding a new category — the current icons are confusing and do not fill all category needs
  • use icons consistently across the platform
  • make the category filter on profile pages more obvious

Other recommendations for the future include:

  • rename “friends” to “Favers” to further brand the app
  • let users give preference to a certain friend’s Fave list
  • determine how to “bump” Faves in a list when a new one is added (add a prompt letting users know that the added Fave will move items in their list).

Creating Fave made it clear that app users appreciate simple and flat designs. Transparent objects, gesture interactions and quick processes are key for users and can determine whether they will use an app or not. It is also essential to completely understand user needs. The app can look and work perfectly but if it does not fit a need or add value to the user’s everyday life, the app will struggle to find popularity.

Finally, the most important lesson learned throughout this process was how to develop digital solutions efficiently. Feedback from users was considered while developing both iterations of Fave and the app was tested twice to reveal issues before moving forward. Implementing this Sprint-like mindset in the prototype development process allowed issues to be resolved quickly. This user-centered design and development prevented the pratfall of going too far in prototyping before realizing a major UI or UX issue that would take the project backwards. It is also helpful to keep in mind that just because an element or action makes sense to the team does not mean that this will translate to users.

It is important to continually think: “WWUD?” What would users do?

Visit the official Fave website for more information about the app and how it was created. Thank you to everyone who helped make this project possible including the Emerging Media program and UGA-Grady faculty and staff.

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Fave Website

Justinmind Website

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