What to Watch? — A UI/UX Case Study on OTT platforms
In this era of Netflix and chill, OTT platforms are one of the main sources of entertainment for many. But deciding what to watch has become a hassle.😪 This case study aims to analyze the gravity of this issue, how it is affecting people and businesses, and hopefully come up with solutions in favour of all.
THE AGENDA:
- Understanding the problem statements
- Framing the 5W’s and 1H questions
- Secondary Research
- Primary Research
- Analyzing the data
- defining problems
- Ideating solutions
- Wireframing
- UI design
- Usability Testing
1. UNDERSTANDING THE PROBLEM STATEMENTS
To get a basic layout of the situation, a business and research problem statement were defined.
BUSINESS PROBLEM STATEMENT:
With the Pandemic and the Lockdown, there has been an increase in audience watching shows and movies on OTT platforms. People tend to get very confused with the large number of options available. An OTT app wants to make it easier for people to decide what to watch.
What did I understand from this?
THE TOPIC:
OTT platforms for movies and TV shows
THE PROBLEM:
Confusion in deciding amongst the variety of options available.
THE TRIGGER:
The Covid-19 pandemic that lead to the lockdown and therefore an increase in audience
RESEARCH PROBLEM STATEMENT:
Making the decision of what to watch on an OTT platform has become very confusing for the audience. As a UX designer you first want to understand the behavior of people trying to choose what they want to watch and the different factors that influence the decision. Plan a research to identify the behavioral patterns to help the business cater to users in an efficient way.
What did I understand from this?
GENERAL PURPOSE:
Understand the audience:-
- Their behaviours
- Their problems
- The factors that influence their decisions
END GOAL:
- Help the business improve
- Help the users in an efficient way
2. FRAMING THE 5W’s AND 1H QUESTIONS
To get a better understanding of the problem statement I framed questions to help me figure out the various areas pertaining to this topic that needed further research.
- WHAT is the problem that we need to solve?
What are OTT apps? I need to figure out what exactly the users are struggling with while using OTT apps. What is their current user experience and what can be improved?
- WHAT is the purpose of the business?
I have to understand why it is important for the business to solve the problem of the users. How will it benefit them?
- WHEN did this problem arise? WHEN did the users start using these platforms?
Need to understand the factors that led to usage of these platforms. Did the pandemic have anything to do with the surge in users? If yes, then how?
- WHO are the users?
Research is required on the demographic using OTT platforms. And analysis is required as to what factors affect the said demographic. (type of platform, options, time period affecting the gender, age, location, the number of people using at a time)
- HOW often do the users use OTT apps?
The frequency of app usage must be looked into. What time of the day are they utilizing the resource and what affects that decision. What triggers the usage of these apps?
- WHAT factors affect the decision of the users?
While choosing the movie or tv show that they want to watch, what is their mindset? What reasons do they consider? Does age, gender, the group, genre or timing come into play? If not, what else does?
- WHAT features do users currently find useful and what do they dislike?
Understand their current usual user experience. What do they enjoy, what annoys them and what do they find is lacking?
- WHY do users prefer OTT apps over traditional television?
Understand how the change occurred and what are the reasons for this trend.
- HOW difficult is it to decide what to watch?
Understanding user patterns while interacting with the app. Do they struggle to make a decision? If yes, in what ways does it affect their experience?
3. SECONDARY RESEARCH
Also known as desk research; this stage involves a lot of research and googling to get an overall understanding of the topic we are dealing with. This stage may look easy, but trust me it’s like finding a needle in a haystack.😅 With the earlier questions are a base line, I dove deep into the internet.
Disclaimer: Data collected is mostly within the realm of India to avoid inconsistencies in the later stages.
REASONS FOR SUCCESS OF OTT :
- Availability of low-cost mobile data
- Affordable smartphones
- The availability of the internet in rural areas of the country has been growing rapidly. While internet penetration in these areas was 13% in 2015, it nearly doubled to 24% in 2018.
Since the outbreak of COVID-19 and consequent national lockdown in March 2020, India witnessed a significant growth in the usage of OTT and emerged as a threat to the Television industry.
Until then, the popularity of OTT platforms were limited to urban area and above middle class.
source:https://en.wikipedia.org/wiki/Over-the-top_media_service_in_India
REASONS FOR RISE OF OTT :
- People were restricted to their homes and didn’t have many options for entertainment.
- Film theatres were closed.
- Entertainment programs on Television were not that interesting for the educated middle class.
CHALLENGES AFFECTING THE USERS:
- There are highly heterogeneous customer demands and tastes that streaming providers need to adapt to.
- There exist multiple languages in India which makes it difficult for movie producers to target a vast majority of the country.
- CONTENT DISCOVERY: Viewers no longer have the patience to browse through hundreds of channels to find something they may like watching. The modern consumer wants to find the required content after browsing through no more than a couple of pages.
This makes it important for OTT platforms to enhance their content discovery functionality. A unique aspect is that viewers tend to stick with a service that provides personalized content suggestions, which is simpler to use and faster to find the content of interest.
CURRENT OTT STATISTICS IN INDIA:
- In 2021, the internet penetration went up by 45 percent, which resulted in an overall increase of 75 percent viewership in OTT app subscriptions during the lockdown.
- NASSCOM stated “while OTT platforms were making a mark for themselves in the Indian market, COVID-19 crisis accelerated the process. From just two OTT platform providers in 2012 to about 40 players now, the OTT revolution has come a long way.”
- 30% rise in the number of paid subscribers, from 22.2 million to 29 million, between March and July 2020 alone.
- Overall, India stood second highest with 8.43 hours of video consumption per week after the United States at 8.55 hours per week.
- Over 90 percent of video views came through mobile devices, indicating behavioural shifts in media consumption.
source: https://yourstory.com/weekender/one-year-of-lockdown-indian-ott-industry-trends/amp
I would like to bring in the PARETO principle at this point to get into more significant data.
The Pareto principle states that for many outcomes, roughly 80% of consequences come from 20% of causes.
Therefore, I wanted to focus on the factors/causes that affected the decision making process on OTT platforms.
According to PwC Consumer Intelligence Series 2021 video survey percentage of people interested in content based on the following:
74% — mood
66% — length of content
65% — who you are with
64% — what your family / friends are watching
29% of respondents said they were often “frustrated” or “overwhelmed” by the array of choices on offer.
There was an interesting piece of conflicting information that I discovered online.🤔 More quantity is desirable but causes difficulty in content discovery. This was something I definitely wanted to look into in the further stages.
Another source that I referred was the ORMAX report to understand the different types of OTT users in India.
4. PRIMARY RESEARCH
The next stage involves collection of data firsthand without relying on any other resource. It includes in-depth analysis of a problem by direct interaction with users. It involves defining the user, preparing a session guide and user interviews.
WHY IS PRIMARY RESEARCH IMPORTANT?
It is important to conduct primary research in order to ensure that real data taken directly from users are considered. Cross-questioning is possible in primary research. It helps avoid dilution of data as we have control over how the data is collected and used. There is more involvement of the researcher, ensuring the data collected meets the needs of the designer and it will help avoid assumptions from being made.
DEFINING TARGET USERS:
Defining users helps us get insight into the type of audience (target group) that utilizes the product. It gives us a basic understanding of the way the product is used in terms of the frequency, duration, location, etc. It helps us design a solution that corresponds to the needs and wants of the users as well as the business.
PREPARING A SESSION GUIDE:
A session guide is a brief questionnaire made to be prepared for the user interview.
Disclaimer: It must be noted though that it is not necessary to follow the session guide during the interview. This only serves as a guide. One must listen and reciprocate according to the conversation.
USER INTERVIEWS:
There are a few things to keep in mind before interviewing a user. I made a list of Do’s and Don’ts to help keep track.
Now it was finally time to interview users. Finding users whom I don’t know personally and who fit the profile was definitely a task. 🙃 After that convincing the users that this interview was not a big deal (just to collect some data) and getting them on call was another hurdle.
I was eventually able talk users of different ages and lifestyles. Here are some insights from the interaction:-
STATEMENTS FROM USERS:
“My family gets really annoyed when I keep switching what we are watching.” (translated)
As a busy woman, this user doesn’t mind changing the content she is watching if it does not interest her. But this proves to be an inconvenience for everyone she is watching with as well as a waste of her time.
“ I did not enjoy using Zee5 at all. I was unable to look for shows due to the lack in organisation.”
“As a regular user, cluttered content is really annoying while deciding what to watch.”
As a user, findability plays a big role while interacting with the platform and deciding what to watch.
“One issue that I come across a lot is that I cannot recognize if I have already watched something just from the poster of the show.”
Recognition is better than recall. When we are making the user rely on their memory, it displays the lack in efficiency of the design of the platform. And it makes the user feel like it’s their fault when the problem is in the design.
“I spend way too much time finding what to watch. I could have watched something within that duration.”
Efficiency based on time plays another significant role in the effectiveness of the design as it is a valuable factor for all. ⌚
“ The search filter is not properly implemented yet on Amazon, I feel.”
This user accounted his experience while using the platform and expressed his difficulty while looking for particular content.
🚩 KEY LEARNINGS AT THIS STAGE:
1. Listen to the user carefully and avoid unintentional interruption
2. Don’t think ahead while the user is answering, be in the moment. (Even if you aren’t confident in that language)
3. RECORD THE CALL
5. ANALYSE THE DATA
We need to analyse the data collected because raw data is difficult to understand. It is useful at the beginning of a design process to understand the learnings of the interview.
WHAT IS ANALYSIS OF DATA?
- Analysis of research data is a process of examination, organization and comprehension of the data collected from the user interviews.
- It includes understanding the non-verbal cues, attitudes and behavioural patterns of the user.
- Taking a note of the reasons for the actions taken by the user in various formats.
- Condensation of the data into points that help make sense of the load to data collected.
USER SETS:
To get a better understanding of the users’ behaviours I will be classifying the users into sets. I contemplated on the grounds of classification. But in the end based on my interactions with the users, I felt it would be best to do so on the basis of ‘frequency’.
The type of user and their priorities are understood during this analysis. It will guide me into examining what problems they are facing and the importance of those features to those users.
EMPATHY MAPPING:
Empathy maps are visual representations of acquired qualitative data in terms of what the user says, does, thinks and feels. It maps insights into personas. It helps empathize with the user.
After a lot of understanding of the data collected, these are the maps I made.
USER PERSONAS:
This stage is used to organize the data analyzed into a format that can be easily interpreted using personas (characters) that represent each user set.
6. DEFINING PROBLEMS
At this stage I will be pin pointing the areas that need to be improved and frame HMW (How Might We) questions to address them.
7. IDEATING SOLUTIONS
The following are the various ideas I came up with for the HMW questions that were framed.
8. WIREFRAMING
A wireframe is basically a blueprint of the screens that will be designed in the next stage. To start the process, I made a brief mental model of the screens I wanted to include.
After that, I went ahead and sketched out my ideas on paper. This is called a paper wireframing.
Next, I headed to Figma to get my ideas flowing into a digital medium. I started out by making a list of the components I will be using.
After that I tried replicating what I jotted down on the paper into screens on Figma. And trust me this took way too long to figure out. These are high fidelity wireframes.
NOTE: For the purpose of focusing on the problem statement, I took a base application to avoid unnecessary creation of an app from scratch. The one I chose was ‘Amazon Prime’.
🚩 KEY LEARNING AT THIS STAGE:
Make the wireframes more iterative and to keep all iterations to avoid wasting time for perfection at this stage.
The fear of getting the designs right hinders the development of designs.
9. UI DESIGN
At this stage I focused on making the prototype to look like an actual application while ensuring the solutions I ideated are appropriately incorporated.
- How to ensure the user selects the right content?
Solution- User ratings for each content at first glance.
2. How to prevent unnecessary scrolling?
Solution- Categorize by genre, language and celebrity at the top of the page.
3. How might we enable users to quickly realize if the content was already watched?
Solution- With the help of a tick mark on the top right corner. So, the tick mark acts as a signal (knowing that something is to be remembered) and it conveys a message (remembering the information) that the content has already been consumed earlier.
4. How to ensure the user is able to look into all the factors that affect the user’s decision?
Solution- Giving all relevant information on the content in an organized format. This was done by keeping Gestalt’s principles in mind while designing the Detail1 and 2 screens.
All the cast members are put in the same circular shape using similarity and placed close to each other showing proximity. The watch button and the episode list is placed with an equal distance from the borders following symmetry.
5. How to speed up the search process?
Solution- An organized search filter with questions for the user to answer when unable to find suitable content and to prevent cognitive overload.
6. How to ensure that watchlist content isn’t just an unorganized dump?
Solution- A folder system to store content with personalised titles.
NOTE:
Something I learnt later on in my case study from my mentor is to only put effort into what matters. Which means designing things that directly correspond to solutioning the problems at hand or the research that was performed. Therefore, if I were to redo, I would have avoided designing the Downloads screen.
Also, I learnt to use a defined standard and consistencies (according to material design) instead of defining my own.
10. USABILITY TESTING
This has to be the most important stage because until now all the solutions are based on my interpretations of the researches done. Now, I will be able to get feedback from actual users.
WHAT IS THE PURPOSE OF THE USABILITY TEST?
- Understand what features are aiding the users in the decision-making process
- Notice if their navigation has become faster
- Learn if particular changes that I’ve made is not useful or slowing down the process
- Figure out if there are loopholes in my solutions
- Study if there are more factors that wasn’t taken into consideration the first time
- And finally improve the design to better user experience
WHOM TO TEST WITH?
- Frequent OTT platform users
- Occasional users
(of various ages)
HOW TO EXECUTE THE USABILITY TESTS?
- Give a brief idea of what the UI is about without revealing the exact problems and solutions
- Show each screen and ask the user to think out loud (their opinions on the screen)
- If not mentioned, ask what differences they notice and how it affects the UX compared to the base app
- Ask users what they would do if a certain task was assigned and observe where they tap.
- Guide the users to the next screen if they aren’t able to but analyse why they couldn’t.
- In the end have an interaction on what their whole experience looked like, what they expected and what changes/improvements they would prefer (with the help of open ended questions without pushing the user in a particular direction)
Here are few of the questions that I prepared myself to ask the users that were specific to the screens. I tried my best to involve past based probing.
The following are some general questions:
- The last time you used this platform, what was your next move?
- Do you feel like there are any changes from the base app?
- If yes, what are they? Do you feel they make any difference in your decision making process? If not, do you feel the need for one?
- In your opinion how does this change impact your overall experience?
- Tell me more about the reason you would click that?
- What other factors affect your decision making personally?
- What changes were you expecting?
- In your opinion what causes your decision process to slow down?
- What other aspects from your past experiences would you hope to see changed in OTT platforms?
To ensure the users had a more realistic feel to the app; I prototyped it and presented it to them on a phone so that I could analyse their interaction with the design.
Here are the insights I gathered from the users:
WHAT ABOUT THE SOLUTION WORKED OVERALL?
- The addition of features without complicating the familiarity of the base app (Jakob’s law)
- Incorporating features that directly correspond to factors that affect the user’s decision on what to watch.
- User centric changes
WHAT SPECIFIC FEATURES HELPED AND HOW?
- The search filter based on various factors helped narrow down what to watch
- User ratings aided decision process
- Categorization aided discoverability
- Organised information about the content which would usually be googled.
- Faster navigation and quicker elimination based on additional features that are factors that she considered.
NOW… THE ACTUAL FEEDBACK TO HELP IMPROVE THE DESIGN🙈
Firstly, one common behavioral insight that I discovered from all users was their natural instinct to go to the ‘Find’ page when prompted to look for TV shows.
This made me realize the importance of this page and I decided it would be a good idea to improve the usability of this page in particular.
As a user, their end goal is to enjoy the content. They don’t want to waste time trying to figure out what to watch. While all the users were impressed by the search filter idea; nothing beats content directly in front of you. Therefore, I added a Frequently Searched list as soon as they open the Find page.
Apart from that I incorporated ‘recently searched’ and ‘trending searches’ (inspired from google searches) including a prompt on the search bar to ease the process.
WHY?
Search option should be able to recognize content from related information and not only exact titles.
Knowledge in the world and knowledge in the head needs to work simultaneously for better results (what the user remembers and related results on the screen to find what the user wants)
Further, I included a search by Actor category as this factor was mentioned by most users.
Secondly, I was disproved by applying the genre and language categories above the trending section. The users explained to me how they’d prefer trending content that is directly discoverable over categorization in terms of genre and language even if it included scrolling. Trending content is an important factor for frequent as well as occasional users. Therefore, I moved this section to the top.
At this point I realized that more quantity on OTT platforms is better but the organization of the content is what affects the discoverability. This finally answered my question from my secondary research.😄
Furthermore, a common UI feedback I received was the visibility of the tick mark on the corner of the poster of the content. They weren’t able to locate the tick mark, once located were able to understand the meaning (already watched).
Signifier worked but discoverability didn’t.
So, I attempted to change the transparent look into a coloured one.
Another minute realization I had during the testing was that; not everyone knows the standard representation of age rating. Therefore, I changed it into a format that everyone can understand.
I would like to mention that all the steps I used to perform this project utilised the double diamond design process.
The Discover stage took place from understanding the problem statement to analyzing all the data from the research, therefore diverging.
The Define stage defined the problems in detail and converging.
The Develop stage involved ideating solutions for the defined problems where I diverged again.
In Deliver stage the ideas where put into existence with the help of the Interface designs and testing with users, converging finally.
Future Scope:
- Being able to change the recommendations based on the users’ daily activities and moods
- Incorporating songs as a medium to aid user’s decision on what to watch
🚩 KEY LEARNINGS:
1. We need to design for people. The technology should fit the people and not the other way around.
2. Do not wait to be perfect. Embrace your imperfections and create something unique.
3. Always have a ‘Student for Life’ attitude. Don’t be afraid of being disproved and having to relearn.
4. Do not give up, even when it seems like the goal is unattainable.
I would like to thank Anudeep Ayyagari for his constant support and guidance.
UX Case Study by Sanjana Somanath Sannamari
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