Quantitative Research

For our chosen subject of ‘Movies @ Dundrum’, we had identified various goals. We firstly wished to obtain an overview of peoples movie-going experiences, where and how they purchased tickets, what extras they purchased, the types of tickets, was the trip to the cinema a special event or was it something more casual.

We felt this would give us an understanding of various demographics as well as motivations and a core point of the study.The most obvious quantitative research method, to begin with, was a survey. We kept the survey reasonably short with mainly closed questions, keeping one open so as to provide further avenues for investigation (Survey can be viewed here). Opening questions where mainly demographic with later questions focused on purchasing habits and reasons for attending the cinema. We obtained a completion rate of 100% of 75 respondents,  Survey completions on average are about 40% (‎Rogers et al. 2015), so it would appear we had an excellent completion rate. But this may have bee partially due to the fact that convenience sampling was used which may have affected the randomness of the survey.
(Survey can be view here)

Types of questions

We asked a total of 14 questions broken into three sections for ease of use.

  • Questions regarding general demographic information.
  • Questions relating to participants general cinema-going habits
  • Questions specifically related to booking tickets and usage of the participant’s cinema of choice website or app

As per established practice suggested by Preece, Sharp, Rogers, (2015) when creating surveys, the opening questions where mainly relevant demographic questions so as to provide context when analysing the responses later.

Due to time and location, we settled on ‘Movies @ Dundrum’ to focus our further research. We undertook a second shorter field survey which we carried out on site, in the hope of obtaining further data that was particular to the experience of Movies at Dundrum.

Key Findings from Initial Survey

The main overall findings as they relate to all cinema attending habits where as follows. These where later broken down into results solely relating to Dundrum. The total number of responses across all cinemas was 76.

Respondents fell primarily into the age group of 25-34, this information was later used to inform both our primary persona and its related scenario.

Fig 1: Age group

Cinema attendance was reasonably high with a large percentage going at least once a month. Which would also suggest participants where quite familiar with the online booking process this assumption was further supported by the device usage results in fig 5 and the activity breakdown results in fig 7

Fig 2: Cinema attendance

Familiarity with technology was also quite high with most identifying as either experienced or expert, with males identifying chiefly as an expert (fig 3). Booking of tickets was heavily weighted towards computers with 32.9% using computers, 35.7% phone and 30% using both (fig 4).

Fig 3: Technology comfort level
Fig 4: Device usage

We also looked at device usage for the booking of tickets. The data indicated that users booked cinema tickets on the website using an array of devices which leaned marginally towards bookings via a computer (fig 5).  The fact that people where booking online via the website using a  phone and not an actual dedicated phone app was further supported by participants awareness as to whether or not the cinema they frequented had a dedicated phone app (fig 6).

Fig 5: Device usage for website
Fig 6: App awareness

The ratio of website activity across male and female was reasonably similar with both groups either checking to see what was on or booking tickets (fig 7).

Fig 7: Website activity by gender

The purchasing of food at the cinema and online was of particular interest. Nearly all participants purchased food at the cinema as none of the cinemas besides Dundrum provided the ability to purchase food online (fig 7). Females were slightly more inclined to purchase food. Of those that bought food and were either classed as an expert or experienced in relation to technology use, 90% said they would consider purchasing food online. This data combined with our later user observational data was used to inform our decision to completely redesign the food booking process for “Movies @ Dundrum”.

Fig 7: Food buying by gender
Fig 8: Would consider buying food online


Dundrum Specific

Within the overall results a total of 10 participants responses related directly to “Movies @ Dundrum”. These were isolated and broken down to find any further revealing or useful data which could be used to inform our prototype. Demographic data was very similar to that which was found in the overall data with the key age group being 25-34 (fig 8) and cinema going attendance being quite regular (fig 9).

Fig 8: Age group
Fig 9: Cinema attendance

The data from technology use and preferences was again similar in its results to the overall survey. Most users preferred to book tickets via the cinema website (fig 10) with 60% of users doing so while using a computer (fig 11). While using  the website the majority of users would simply book tickets with half respondents using it to check for deals (fig 12)

Fig 10: Booking medium
Fig 11: Technology of choice
Fig 12: Activity breakdown

The data at this early stage was clearly pointing to users not using phone apps for booking movies. They were either unaware that one existed (fig 13), and in the case of “Movies @ Dundrum ” only one did, or quite possibly due to the fact that people where willing to travel for a particular type of experience did not see the benefit in installing a cinema specific app.

Fig 13: App Awareness

Responses regarding purchasing of food were even across all categories (fig 14), two-thirds indicated they would consider or would buy food. Combined with the overall response in (fig 8) we considered that looking at the overall food purchasing process would be beneficial. Not only from a user experience point of view but also from the perspective of increased revenue.

Fig 14: Purchasing food online

Findings from Field Survey

After reviewing the results from the questionnaire and interrogating the data in various ways, we felt it was necessary to obtain an understanding as to why people chose “Movies @ Dundrum”. It was agreed a field study at the Dundrum cinema should be undertaken to try and add to the data we had already gathered and possibly reveal any insights. This was also an area I personally had no previous experience of, and something I was in no rush to undertake, making it all the more worthwhile doing.  The study was conducted on a Sunday afternoon inside the cinema foyer and 9 customers were approached (more had been approached but refused to participate) and asked 6 questions, both quantitative and qualitative.

Dundrum field trip survey questions
  • How did you book your cinema tickets for today? (e.g. through the site, the app or at the cinema)
  • Did you plan the trip in advance or did you decide just today?
  • Why do you go to Movies @ Dundrum? (e.g. you live close by comfortable seats, choice of movies, good deals)
  • (depending on how they answered earlier) … If you use the site / app, out of 10, how would you rate your experience (1 being poor, 10 being excellent)
  • Is there anything you’d like to see improved on the cinema’s site / app?
  • Finally, what age range do you fall under? (e.g. prefer not to say 18-24, 25 – 34, 35 – 44, 45 – 54 etc)
  • If you buy food when going to the cinema, do you buy your food online when purchasing your tickets?

Table 1: Dundrum field trip survey questions

The time of day we carried out the survey appeared to have an affect on the data obtained with it differing from the previous data with 56% of respondents in the 35-44 age bracket.

Chose the cinema due to proximity to where they lived 78%
Chose the cinema due to its proximity to the nearby shopping centre 22%
 Indicated they would not buy food online 78%
Indicated they were not aware this was an option 22%
Booked their tickets through the website 89%
Planned their trip to the cinema 66%
Decided on the day to go to the cinema 34%

Table 1: Dundrum field trip survey questions, quantitative results

In hindsight, we did not pick the best time to carry out our field trip, with numbers being relatively low. Those that were there, had a number of children with them, which was not exactly conducive to answering survey questions, but they did partially inspire or secondary persona. If we had more time we would have returned for a second attempt but whether or not we have gained any more insightful data is unclear. Either way it was educational and worth carrying out.

Card sorting

One of the issues highlighted as part of later observational data was an issue with the overall navigation of the site. We felt that this would be worth addressing as part of the overall redesign and to this end created a card sorting exercise with the goal of documenting participant’s mental models of the information architecture of the cinema website and disrupted it by email and via slack. This part of the research although carried out later will be reviewed in this section of the blog.

A quantitative user-centred research method, card sorting is used to gain understanding of how users view content and information and where it should be located. The two approaches used are open and closed, both consisting of an array of cards with the main items written on them which users must sort into groupings. In the later, groupings are provided while in the former it is up to the individuals to identify groupings. It is mainly used for redesigning an existing website or application but can also be used for new endeavours.

As part of our own card sorting exercise, we used an open approach, results can be view in the similarity matrix in fig 15. Like other methods, it has its strong and weak points. It requires at least fifteen participants for results to be accurate (Nielsen, 2004a), more than this results in diminishing cost of returns. It is relatively easy to set up and administer, providing a good starting point for the structure of the navigation under investigation. It has been argued by Spencer & Warfel, 2004 that the results may identify only surface characteristics. It has also been suggested by Cooper et al. 2014 that in certain cases there is a need for organisational knowledge and an assumption that sorting will mirror how the system will be used, in our case this was not of concern.

A total 16 (59%) people completed our study out of a total of 27 participants with 11 abandoning the survey. The full results and various methods of categorisation can be viewed here we later used this information to redesign the core navigation of the site, this will be discussed in the iteration posts.

Fig 15: Card sorting similarity matrix





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