Reel Talk

Overview

What is Reel Talk?

Reel Talk is an online movie/TV-show community that is a combination of IMDB and Reddit, for movie/TV enthusiasts.

It provides a platform for users to:

Read movie/TV-show listings, ratings, and reviews
Discuss their favorite content

Features highlights

Onboarding

We use the onboarding process to understand users' content preferences.

Community

Users can join a community that matches their interests.

Discussion

Users can share content relevant to the community's topic to spark discussions.

Final deliverables

Established design system

Discovery

How did the team come up with the idea of creating a community for movie and TV show enthusiasts?

Initial exploration

The founder of Reel Talk, who is a Movie/TV-show enthusiast himself, found that the existing platforms such as IMDB or Rotten Tomato cannot fully satisfy his needs. He believes that there is a gap in the market for a platform that caters to the needs of movie/TV-show enthusiasts. To validate his hypothesis and uncover specific pain points, surveys were conducted.

Survey setup

108 respondents: 71 females & 37 males
Watch movie more than once per week/watch TV shows more than twice per week
94% of the respondents are between 18 to 54

Key insights

The respondents primary needs on the existing platforms are:

Read ratings and reviews
Discuss the content they’ve watched

For their discussion needs, Youtube and Reddit are their go-to platforms.

Since they're general-purpose platforms, they also express lack of confidence in existing communities (since they're are pro users), and want more features dedicated to content discussions.

Here is a common scenario:

Based on the survey results, our team concluded that:

The movie/TV-show enthusiasts only have general-purpose platforms to discuss content, and these platforms don’t have features to cater to their specific needs.

This insight presents an opportunity to create a platform tailored to their needs.

However, before moving forward, we need a deeper understanding of the pain points they have on current platforms and their specific expectations for a new one.

Prospective user interviews

"What has your experience been like with movie and TV show discussions on existing platforms?"

Interview setup

1. Recruitment

We recruited our interviewees from a survey
Participants are movie/TV-show enthusiasts who watch at least 2 movie/5 episodes every week

2. Process

35 minutes remote sessions
6 initial questions + probing

3. Insights

Conducted affinity diagram to distill interview insights

Key pain points from interviews

Movie/TV show enthusiasts struggle to find:

Quality discussions

On current social platforms, most conversations stem from reviews and take place in the comment sections. It does not facilitate in-depth discussions effectively. Some interviewees also expressed a desire for specialized features.

Peers who share their passion

Movie and TV-show enthusiasts is relatively smaller compared to general viewers, and current social platforms lack effective ways for them to identify and connect with one another.

Design challenge

HWM Statement

How might we help movie/TV enthusiasts (1) find each other and (2) have quality discussions?

Challenge 1

"find each other"

Solution 1

Finding out user's taste

By identifying users' taste, the platform can recommend groups and content they might enjoy, fostering engaging conversations.
Additionally, if we could incorporate users' tastes into their profiles, it would allow them to learn more about each other without direct interaction.

Challenge 2

"have quality discussions"

Solution 2

Foster a great discussion environment

I can employ various design techniques to create a discussion environment that encourages in-depth and friendly conversations.

Let's take a closer look at how I crafted these solutions to respond to the specific needs and insights gathered during our research.

Solution 1: Finding out user's taste

Noticing that shared interests often spark meaningful conversations, we started looking into ways to understand users' tastes.

Understanding a user's taste: Key indicators to consider

Through brainstorming and interviews, we identified few potential ways to find out user's taste.

Selected indicators

Most liked content

Top genres
Top movies
Top TV-shows

Age

Although it's not directly related to taste, we thought it's a good indicator of the user's preference.

Excluded indicators

Most hated content

We initially thought this would be equivalent to "most liked content", but then we realized that while people might enjoy different things, they often dislike the same ones. A bad movie or TV show often shares common weaknesses, such as a weak plot or poor acting.

We also checked with our engineers to determine if this would improve our algorithm's accuracy, and they confirmed the effect is minimal.

Content released year

ex. user indicates that he/she doesn't watch anything before 1990.

Release year is excluded as a taste indicator because a viewer's aversion to content from certain time periods often stems from technical factors like dated special effects or unfamiliarity rather than the actual storytelling quality, potentially causing them to miss timeless narratives that they would genuinely enjoy if presented in a modern format.

With a clear understanding of what indicate a user's taste, I shifted focus to exploring effective ways to gather this information.

Gathering taste information on the platform

Through brainstorming, I developed three integration plans.

1. From user's watch history and ratings

It leverages user's viewing record and ratings to understand preferences.

2. Answer few questions during the onboarding process

Users select their interests and preferences when first signing up.

3. Feed-side quick surveys

The platform would presents quick preference questions while users browse content.

Proposal evaluation: effort-impact matrix

Design review

We also carried out internal design reviews and feasibility assessments for the three approaches.

After considering all factors, including user scores and internal evaluations, we believe approach #2 is the clear winner.
Regarding the cons listed from internal evaluation, we believe that with thoughtful design, we can make the process more enjoyable, ultimately reducing the drop-off rate.

Validation: Usability testing and follow-up interviews

After finalizing the direction with approach #2, I proceeded to design the high-fidelity version and conducted a usability test.

Test setup

Task: get an account on the Reel Talk platform
5 Movie/TV-show enthusiasts identified by how frequently they watch content
45 mins remote sessions
Thematic analysis

Usability testing and follow-up interviews

Findings & Iteration

1. Preference questions

Positive: Our users love these questions!

Prior to testing, there were concerns about the onboarding's length. However, none of the tested users raised this issue, indicating their strong interest in preference questions.

Negative: Users struggle with decision-making

Some users find it challenging to identify their top movies/TV shows when asked because they can't decide immediately.

I changed the word used in the title from "top" to "favorite." This removes the need for users to rank their choices.

I also adjusted the quantity restriction from a mandatory 5 choices to "up to 10," allowing greater flexibility.

Additionally, it also includes more options to choose from (trending content)

My decision-making process

1. Wording

I deliberated over the wording and recognized that using "top" might burden users with the task of mentally ranking items, thus increasing cognitive load. I then brainstormed several alternatives such as "Preferred," "Beloved," and "Highly rated." After team discussions, we concluded that "Favorite" best suited our needs in this context.

2. Quantity constraints

The adjustment from "top 5" to "up to 10" adeptly accommodates two scenarios:

If users can only think of a few items (less than 5)
If users have more items in mind than the previous limit allowed (more than 5)

2. Birth date -> Age range

Through the validation process, we found that users had privacy concerns to provide birth date, even though I made some efforts to explain why these inputs were necessary and tried to make the process more enjoyable (see on the right).

I then decided to address these privacy concerns by updating the interface from requiring users to enter their birthday to simply selecting their age range (e.g., Under 18, 18–29, 30–39, etc.).

My decision-making process

I explored 2 additional solutions to address the privacy concerns:

1. Instead of asking for the full date of birth, I considered only requesting for the birth year.
However, this approach was rejected because it's uncertain if users are over 18 based solely on their birth year.

2. Another option was simply selecting their age.
This idea was also rejected because users would face an overwhelming number of choices.

Final design

Solution 2: Foster a great discussion environment

How did we approach designing a discussion environment that fosters in-depth conversations?

For our users, what constitutes a good environment for discussions?

I distilled insights from our research with prospective users and developed three key design principles.

Effortless connection with like-minded individuals

Effortless connections with like-minded peers

With the information users provide, we can create an environment that makes it easy for them to connect with one another.

Format that facilitate in-depth discussions

A discussion format for deeper engagement

Users should be able to engage in meaningful and in-depth discussions with ease.

Control

Users have the option to choose whom they want to talk to.

Discussion formats

Following these principles of good discussion, I developed three distinct formats for conducting conversations.

Episode- or movie-specific chat rooms

Provide chat rooms dedicated to each movie, TV show, or specific episode. Users can join in on discussions with others who've watched the same content.

"Discussion circles"

Enable users to create public or private groups where they can chat about a specific show or movie together. These groups can be small or large. The environment allows users to share thoughts in a more intimate, real-time environment.

Community with topic-based discussion posts

Set up a community where users can post about specific themes or genres (e.g., "Top Psychological Thrillers" or "Everything Batman"). Users can engage by commenting or reacting to posts and tagging specific movies or shows.