Blog 8: MIDTERM Presentation

April 2023 | Pho Vu, Nahye Kim, Jaeni Park, Jiwoo Jung, Jiwon Cha

Period: 2023.04.19. - 2023.04.24

https://docs.google.com/presentation/d/14V-fHFi4oosxscEla9lXq0SX0dPGUL8CFQEk_a27_3c/edit?usp=sharing

We had the opportunity to work with a few raw data sources including voice recordings and transcripts. We conducted four mini interviews with three visitors and a staff member at MegaBox on April 23rd. They were formatted as semi-structured interviews and alongside these mini-interviews, additional questions were asked to investigate the users’ response in depth. These screenshots below provides a comprehensive overview of all the data collected for the understanding of possible target users. They are organized in a clear manner so that readers can easily view and understand the scope and nature of the data. Original script in Korean:

1. 나이가 어떻게 되시나요?

2. 영화관에 얼마나 자주 오시나요?

3. 가장 좋아하는 장르는 무엇인가요?

4. 관람할 영화에 대한 정보를 주로 어디서 얻나요? (영화앱, 유튜브, 지인 등등)

5. 영화 관람을 결정하는 가장 중요한 요소는? 중요한 순서대로 3개 골라주세요. (1. 줄거리, 2. 배우, 3. 후기 4. 별점, 4. 스오피스 순위, 예매율 5. 영화관(위치, 접근성, 시설))

6. 모바일 어플로 영화 관람권을 구매하신 적 있으신가요? 무슨 앱을 써보셨나요? 불편했던 점이 있으신가요?

7. 영화 어플을 사용하지 않는다면, 주로 어떤 경로를 통해 영화 관람권을 구매하시나요? (현장구매, 서치엔진, 통신사 행사, 기타)

8. 추가됐으면 하는 기능이나 요청사항이 있나요?

9. 음성지원 앶 개선을 하면 사용하실 의향이 있나요

English translation:

1. How old are you?

2. How often do you visit a movie theater?

3. What is your favorite genre of movie?

4. Where do you usually get information about movies? For example, movie apps, Youtube, friends, etc.

5. What is the most essential factor when choosing a movie to watch? Choose three among plot, actors, reviews, ratings, movie ranking, location of movie theaters, amenities.

6. Have you used a mobile app to reserve movie tickets? If you have, which one? Was there any challenging experience with the app?

7. If you haven’t, what is your alternative option?

8. Do you have any request for the app?

9. If we were to include special features like movie theater navigation or speech to text, are you interested in using it?

We used these sources to gain a deep understanding of the needs and preferences of our target audience: new-senior moviegoers.To make sense of this data, we employed a coding process that involved open coding, axial coding, and selective coding. First, open coding allowed us to identify themes and patterns in the data. With the data from all our interviews we did with our parents or with the visitors at the cinema, we organized the contents into a table with the categories of what generation they belong to, whether they were a staff or a visitor, with who they visited the cinema, their overall experience rating of the existing applications, and also specified on some particular points, opinions, or reviews on their interaction with the existing cinema booking applications. Second, axial coding helped us to connect these themes to broader categories and subcategories. By focusing on the transcripts we have had from interviews with users, we paid attention to some common keywords like “too many ads” or “difficult log-in”. With the contents of the interviews organized into a table as mentioned above, we were able to get a clearer understanding of the variety of opinions that we had to put into consideration for our project goal and our future prototype interface. Finally, selective coding allowed us to hone in on the most important findings and draw conclusions about our target audience. We had reached the conclusion that, because their were frank interviewees who claimed the current app experience to suffice and recommended no changes to the current task flow, we thought the improved interface would have to follow a framework that is not too different from what we have now - something not too new from our environment model, as it would put our users at a place where they experience confusion. We thought that with new ‘changes’ and ‘advancements’ incorporated into our project, they would have to be subtle to an extent where the users are not confused with the task flow, but with any of the previous inconveniences gotten rid of. Based on the analysis we acquired from the coding stage above, we went on to develop several possible models and quantitative analyses to help us understand the behaviors and preferences of new-senior moviegoers. Out of the five models shown in class, we were most drawn to information flow model and social structure model because of their ability to help us highlight hierarchies of data in the movie industry. The social structure model is a way to understand the relationships between individuals and groups in a social system. In the context of the cine.zip’s project scope, we can use this model to analyze the social structure of the film industry and how it affects the distribution and consumption of movies. Here is how we will apply the social structure model to the project.

1. Identify the key players in the film industry, such as producers, distributors, theaters, and consumers.

2. Analyze the relationships between these players, including power dynamics and dependencies.

3. Identify any hierarchies or social groups within the film industry, such as major studios vs. independent producers.

4. Consider how social factors, such as gender, religion, marital status, and socioeconomic status (income level), may impact access to the film industry and opportunities within it.

5. Use the social structure model to identify potential areas for intervention or improvement in the film industry, such as addressing inequality or promoting diversity.

The information flow model is a way to understand how information moves through a system. We can use this model to analyze the flow of information related to movie distribution and consumption. Similar to the abovementioned model, there are a few steps we will take in the next weeks to complete the model.

1. Identify the types of information involved in the movie industry, such as movie titles, release dates, box office numbers, and consumer preferences.

2. Analyze how this information is generated, collected, and disseminated throughout the film industry.

3. Consider any bottlenecks or inefficiencies in the flow of information, such as delays in reporting box office numbers or limited access to consumer data.

4. Use the information flow model to identify potential areas for improvement, such as implementing more efficient data collection and analysis methods or improving communication channels between industry players.

5. Consider how emerging technologies, such as artificial intelligence and machine learning, may impact the flow of information in the film industry and how these technologies could be leveraged to improve the cine.zip project.

These models allowed us to identify key trends and patterns in their movie reservation behavior, as well as understand their motivations for using mobile movie reservation applications.Finally, in our future presentation, we look forward to presenting our findings and possible implications on the interface of the cinema ticket mobile application that has been being studied and designed to meet the specific needs of new-senior moviegoers.We believe that this application has the potential to revitalize mobile movie reservation for this demographic, and we are excited to continue exploring ways to improve accessibility and reduce difficulty for new-senior moviegoers.