# Design Principles of a Mixed-Reality Shopping Assistant System in Omnichannel Retail
## 8 Conclusions and Limitations  
MR devices have high potential for retail customers to enhance their shopping experience in terms of hedonic and utilitarian value. Prior studies suggest that MR can be deployed in shopping assistant systems, although there are not yet any design principles to develop such artifacts. As mentioned in the Introduction, the first aim of this study was to propose a novel MR-enabled shopping assistant system, using MS HoloLens as the archetype, by combining content elements from e-commerce with the particular characteristics of the MR device. We developed a system that leveraged the attributes of the MR technology. The system recognized the product of interest and imposed 3D digital objects into the user's field of view. Seven design features were incorporated (product information, reviews, recommendations, videos, availability, buy, and virtual shopping cart) which could be navigated using NUI techniques. We explored which design principles need to be considered in the design of an MR shopping assistant for omnichannel retail. A qualitative study was conducted to capture the user perceptions towards the use of the proposed system, where 35 participants experienced the MR shopping assistant in a simulated omnichannel retail environment. Based on this study, we derived seven design principles for the future development of MR shopping assistant systems which combine retailing aspects with MR-specific characteristics: rigor, informativeness, tangibility, summary, comparability, flexibility, and holism. These design principles conclude the aim of the study, although there are some limitations to the implications of the results. Novel technologies such as the MR shopping assistant can have different effects on individuals based on their attributes. Even though this study tried to minimize the effect by random sampling and recruiting diverse participants, it cannot be eliminated. Moreover, the study did not focus on specific elements, such as the effect of prior user experience or different product categories. This study did not include quantitative measurements such as the System Usability Scale (SUS). Additionally, \begin{table}
\begin{tabular}{c c} \hline \hline
**Design Principle** & **Description** \\ \hline Rigor & The system should be able to provide a seamless shopping experience by minimizing query failures and optimizing search processes. \\ \hline Informativeness & The system should integrate a diverse set of meta-information elements about the products. \\ \hline Tangibility & The systems should be able to communicate the tangible properties of a product. \\ \hline Summary & The system should provide the information in a concise form that can help customers to make faster shopping decisions. \\ \hline Comparability & The system should facilitate the comparison of similar products. \\ \hline Flexibility & The system should facilitate customizing the application. \\ \hline Holism & The system should provide a holistic experience by integrating hedonic elements and introducing natural interaction techniques. \\ \hline \hline \end{tabular}
\end{table} 
Table 6: MR shopping assistant system design principles. because the current study was only conducted with Hololens2, the effectiveness of the current design principles with other hardware could be a subject of future research. This study provides the design principles for an early stage of MR shopping assistant systems; therefore, future studies might address the following topics:  
1. The identification of design patterns of MR-enabled shopping applications that enhance the omnichannel experience;
2. Further exploration of the proposed design principles with other MR shopping applications;
3. The extension of the proposed design principles with further design features for MR-enabled HMDs in the retail context;
4. Adding more assisting elements in MR shopping systems, and quantitative evaluation of those systems;
5. Conducting similar studies with a different demographic.