The goal of the thesis was to answer the questions of this research, which were:
• What is the user engagement levels and user experiences with current ordering channels in restaurant industry?
• What are the challenges, gaps, and opportunities for restaurant industry in ordering systems design?
• What is a good AR concept for restaurant menu design?
From the results of the research about the user engagement level with current ordering channels, it is clearly visible (figure 1 & figure 2) that there has been a significant change.
Before the Covid-19, users were visiting restaurants more, while the sales through deliv-ery channels have increased after Covid-19. It was also found that the percentage of uses using the self-service has increased after the pandemic (figure 1 & figure 2). On the other hand, self-service is a quicker medium than ordering from front-counter. A user (Fe-male,17) has explained this benefit of self-ordering "If there are some self-services, I use them because of quicker and convenient. I don’t need to wait. If there is no such system, then I use help of others.” So, the trend is towards self-service order processing which in-cludes a kiosk in the place or using mobile applications.
From the qualitative interviews with managers of “Taco bell Finland”, it was found that customer feels poor user experience due to lack of knowledge about the product. Due to lack of information access, users tend to expect more and at times turns out disappointed with the product. So, it brings opportunity for the restaurant owners to improve the design of self-ordering mediums. Thus, the research answers question about the status of current user engagement and user experience in current ordering channels.
Furthermore, it was found from the semi-structured interview that most of the user feels excited about the prospect of an AR menu where user can see a 3D image of the product.
The opportunity to learn more about the product before the order was appreciated by al-most every user. For example, user (Male, 26) commented, “The 3D image part is a good way to get an idea about the portion size, what it contains, and you get better idea of the product in general” Or another user (Female, 17) said “It is very convenient. It is very im-portant to have such apps. Sometimes I don’t know what to order, what a product has in it, I don’t like to buy something that I don’t know about”.
From the qualitative analysis, it was found that before buying a product every user wants to see the image of the product, the ingredients list, and the price of the product (table 2).
So, these are the fundamental information that a restaurant menu design should have.
This was considered while designing the low-fi prototype (figure 5). In low-fi prototype, all the fundamental aspects were covered for an AR based 3D restaurant menu. There were other suggestions from the users about few other dimensions. User recommendation was one of them. One user (Male, 27) commented about this, “Customer reviews are also of my interest as I can make orders based on those recommendations” or another user (Fe-male, 17) “I also use friend’s recommendations. Reviews should be also valuable”. This idea was later transformed into a review bar which let the users know about the ratings that their friends provided about a product (figure 9). The consciousness about the nutri-tional values of food items was also found from the interviews (table 2). Almost half of the interviewee sees it as valuable to know about these values. So, this aspect was also brought into the design to let users know what the values of their eating are (figure 9).
A good AR design concept should also follow different design principles, theories such as Nielsen heuristics (Nielsen Norman group, 2020), Shneiderman’s golden rules (Shneider-man 2018, 95-97), Galitz’s theory (Galitz 2007, Chapter 2), and Nor(Shneider-man’s suggestions (Norman 2004, 21) were considered and used to make the design intuitive and user friendly. While standards such as ISO 9241-210:2019, were also considered while design-ing the Hi-fidelity prototype of the concept. The results were quite successful, which could be found from the results of the usability test (table 4). Every user was able to complete all the given tasks and the time of completion was quite similar, between 01:23-01:49 s. This justifies the usability, user friendliness and intuitiveness of the design. Further clarification can be seen from the user comments, for example one user (Female, 18) commented about the look and feel of the design- “It is quite user friendly. I really liked the design.
Hoping to see the real app” while another user (Female, 20) commented about the tradi-tionality of the texts and icons, “They are quite common. It was easy to understand. Liked the design and it felt easy & comfortable” (table 4).
It was found that after the usability test, the AR concept brough a lot of interest and enthu-siasm about the prospect of having such an app which can be used for augmentation and using a single app users can order from any restaurants. Some of their suggestions were quite encouraging, (Female, 30) “The possibility of visually evaluate the ingredients would be something I would ask for. I mean that I would like to know what the product contains by being able to move different part of the product in 3D augmentation” (table 4).
The fact that a part of the research was done using the real sales data of a real company with data from 10 different branches of Taco Bell, it justifies the research reliability. While the qualitative interviews were done with real users who were random people and different
in nationality, gender, and age. This provides results that are free of participant error or participation biases. The research was done with sufficient time and interviews were rec-orded either by recording or writing and data were collected from them leaving the
chances of research error or research biases. So, the reliability of the research can be jus-tified from the above arguments.
On the other hand, the research considered real sales data to evaluate the user engage-ment levels and interviews with people who work and deal with user experience as every-day work. It was the basis to realize the user experience levels. While qualitative research about the user expectation and preferences from a diverse group of users who had differ-ent level of knowledge about AR provides a valid ground to provide quality data. Similarly, for the usability the user selection was also diverse and random, the location was a real restaurant which again justifies the validity of the research.
The research was about conceptualization of an AR restaurant menu, the results were quite satisfactory and encouraging for further study about the topic. A 3D prototype de-sign would be a next viable product to evaluate and further research about the concept.
9 Conclusion
Covid-19 has made a significant impact in usage behavior (figure 2). Through analyzing the sales channels of Taco bell Finland before and after Covid-19, a significant change was observed in terms of how people changed their attitude in choosing ordering medi-ums in restaurants. Based on the research, it was found that currently users are more in-clined to use the ordering mediums or service channels that are more remote and in less physical contact with humans. While a big rise in home delivery concept means less phys-ical communication between the buyer and the seller. Which in turns brings in poor user experience. In terms of experience, there are large number of negative or poor experience from home delivery medium where the expectation does not meet the reality. So, the pro-spect of an AR menu to solve the lack of product information issue is very optimistic.
Upon learning about the scope of AR and possibilities, some great imaginations came out of users’ mind which are futuristic but very viable. Manipulation of 3D product to modify a product sounds very exciting prospect. While among the most popular choices-
knowledge about ingredients, price of product and a descriptive image were primary re-quirements. While some views a catchy description, nutritional values and friends reviews about products to be important factors in better buying decisions and improved user expe-rience.
While different analytical methods helped the research find various data about the topic of interest, knowledges from literature reviews were also very valuable. Information about User Centered Design (UCD) methods, User Interface (UI) design, or User Experience (UX) design were valuable to design a suitable prototype that helped to evaluate the con-cept.
In restaurant industry, A 3D menu based on AR can provide visitors with a superior expe-rience where user will be able to learn more about the products and make a better buying decision. The concept could be a great business plan for a food ordering application which can be a single app for users to order any food from anywhere. But further study about the concept should be made before that. A more in-depth study about the concept with a 3D design and testing will be valuable for further understanding.
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