Recommend to contacts

Recommend to contacts

Recommend to contacts

Netflix: New feature

Netflix: New feature

Netflix: New feature

Role

UX Researcher

UX Designer

UI Designer

Company

Company

Company

Academic project

Timeline

Timeline

Timeline

3 weeks

Teammates

Teammates

Teammates

Solo project

Netflix original share feature

Brief

In this academic project I faced the challenge of adding a new feature in an existing app. "Share recommendations to contacts" was the starting point.

Goal

  • Identify the behavior behind sharing content

  • Enhance user engagement

  • Emphasize recommendations through the platform.

Brief

In this academic project I faced the challenge of adding a new feature in an existing app. "Share recommendations to contacts" was the starting point.

Goal

  • Identify the behavior behind sharing content

  • Enhance user engagement

  • Emphasize recommendations through the platform.

Brief

In this academic project I faced the challenge of adding a new feature in an existing app. "Share recommendations to contacts" was the starting point.

Goal

  • Identify the behavior behind sharing content

  • Enhance user engagement

  • Emphasize recommendations through the platform.

Approach

Approach

Approach

I started by exploring the existing flow of the app to understand how can I share content. The existing share feature allow users to share the content's link and share it on social media.

Then, I launched a survey to understand how do people recommend content, who do they share with and how do they get recommendations from. Also, I needed to fit in an age range to go for the next step

Key findings of the survey (48 responses)

Based on the results, I could analyze the data and choose a target to go for the interviews. I chose the highlighted age range (18–24) because they seemed to be most active on streaming platforms, specially on Netflix.

Through these interviews, I gained valuable insights into a key differentiation between “sharing” and “recommending.”

Based on the results, I could analyze the data and choose a target to go for the interviews. I chose the highlighted age range (18–24) because they seemed to be most active on streaming platforms, specially on Netflix.

Through these interviews, I gained valuable insights into a key differentiation between “sharing” and “recommending.”

Based on the results, I could analyze the data and choose a target to go for the interviews. I chose the highlighted age range (18–24) because they seemed to be most active on streaming platforms, specially on Netflix.

Through these interviews, I gained valuable insights into a key differentiation between “sharing” and “recommending.”

Sharing was perceived as casual act while recommending carried an emotional weight,

users expected reactions and something to talk about during their conversations about their recommendations.

This crucial insight significantly influenced my decision to focus on personal connections for the new feature. 

This crucial insight significantly influenced my decision to focus on personal connections for the new feature. 

This crucial insight significantly influenced my decision to focus on personal connections for the new feature. 

Learnings

Learnings

Learnings

Based on the insights gathered from the research, survey and interviews, I faced the next mission, sintetize the learnings, so I defined a user journey map that helped me understand and show the sharing process and how emotions were involved.

As a result, the UJM showed me the two most important comments during the experience of a user that wants to recommend content. Leaving a comment and leaving the app to recommend content were key on the experience.

Key comments on the user journey map

The real question

The real question

The real question

How can we improve the user experience when they recommend content through the app?

Initial Idea

Initial Idea

Initial Idea

My initial idea was to introduce a commenting system similar to a social media platform. However, after getting feedback from my TA, I realized that including comments could directly affect Netflix through negative thoughts.

To maintain a positive and constructive atmosphere, I shifted to the next idea while retaining some initial concepts. 

Initial idea: Users leaving a comment on the content they like.

Idea Iteration

For this iteration, I kept some concepts of the previous idea but this time the entry point is different. As you know, the comments can be dangerous if they're public.

So, I decided to implement private comments like other social media apps. Users can leave a comment for an specific contact.

Flow 1

Flow 1: Connect your phone number to your Netflix account

For the first flow and based on the insights, I know that people go for the share button, so that's where I decided to put the entry point.

The user is going to be able to connect their phone numbers to their Netflix account, so Netflix can access to their contacts.

Now, they don't share content. They recommend content.

Flow 2

Flow 2: After getting a recommendation, recommend someone else.

On the other side, when a user gets a recommendation they'll get a notification of the recommended content and the message of their contact.

I included the notification in this feature based on the most important insight, the emotional weight. People want to know somehow what the other thinks about the recommendation.

User testing

User testing

User testing

I recruited five users to do usability testing based on Nielsens methodology.


“After the fifth user, you are wasting your time by observing the same findings repeatedly but not learning much new.” Jakob Nielsen on NN Group article

Things that worked well

  • Users could connect their phone numbers to their Netflix account.

  • Users could recommend content to their contacts.

  • Users could leave a comment when recommending.

Things to iterate

  • It was not clear an visible the "Select All" button.

At the end, users appreciated the fact that they could stay on the app and leave a comment to their friends resulted positive to them.

On the other hand, they needed a notification when a friend see a movie they've recommended through the app.

Final Thoughts

Final Thoughts

Final Thoughts

I introduced the ‘Recommend to Contacts’ feature, which revealed a crucial insight: the difference between sharing and recommending.

Based on the interviews, I can say that sharing is a simple act, like passing something along. 

Recommending, on the other hand, is more meaningful. It sparks conversations and hopes for reactions.

This discovery led us to focus on building personal connections. Now, users could suggest their favourite shows and movies to specific contacts, creating opportunities for engaging discussions.

“Recommend to Contacts” stands as a testament to how empathy in UX design can make the entertainment experience richer.

Prototype

Prototype

Prototype

Check the prototype! Don't forget to go full screen for a better experience 😃

If you liked this project

Check "InterBus Redesign". This Spanish bus company needed to rethink their user experience on the app.