# Design Principles of a Mixed-Reality Shopping Assistant System in Omnichannel Retail
## 6 Results
### Natural Interaction Techniques (R3)  
Twelve (34%) participants found the system particularly easy to use, although six (17%) participants criticized that the overall interaction was not easy and intuitive. An additional nine (26%) users had difficulties pressing the buttons or using the slider, which added items to the shopping cart (3/9%). Nine (26%) users would have liked to have a wider field of view or be able to minimize content. The same feedback applied to the size of videos (5/14%). In total, 12 (34%) participants reported unfamiliar interaction techniques with the MR shopping assistant, and that it required some time to become accustomed to it. One said: \"I think, in the beginning, you need some time. It works if you've got a feeling for it. And at the end, It's simple\" (#22, female, 26). Five users (5/14%) criticized the required head movement to see all the information displayed within the field of view. One participant stated: \"When I'm moving the head, the physical object is not always moving with me. It would be nice to zoom in or out\" (#20, female, 25 years). Other than this, 10 participants (28%) would have liked to redesign/customize the tool, mentioning features such as a selection of languages. As a result of the qualitative study, Table 4 provides recommendations for future iterations of the MR shopping assistant for MS HoloLens. Suggestions are categorized according to the content design elements and indicate whether it represents the original design feature of the prototype implemented in the research (O), improvement for an existing design feature (I), or an additional feature (A). The number and percentage of mentions in the case of improvements and additional features are also depicted. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**I/A/O**} & \multicolumn{2}{c}{**Design Features for Future**} & \multirow{2}{*}{**N**} & \multirow{2}{*}{**\%**} & \multirow{2}{*}{**Subcategory**} \\  & & & **Iterations** & & & \\ \hline \multicolumn{6}{c}{Recognizing the Product (R1)} \\ \hline Product & \multirow{2}{*}{O} & Recognizing the product using & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{PR} \\ Recognition & & & image recognition & & \\ \hline \multicolumn{6}{c}{Design Features (R2)} \\ \hline Product & \multirow{2}{*}{O} & \multirow{2}{*}{Text-based information} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{PI} \\ Information & & & & & \\ \hline \multicolumn{6}{c}{3D models of the products to} \\ \multicolumn{6}{c}{project in the real environment} \\ \hline \multicolumn{6}{c}{A} & Product pictures with 360\({}^{\circ}\) view & 8 & 23 & PIA \\ \hline \multicolumn{6}{c}{More detailed product} \\ \multicolumn{6}{c}{information for specific} \\ \multicolumn{6}{c}{products (e.g., calories and} \\ \multicolumn{6}{c}{expiration date for food)} \\ \hline \multicolumn{6}{c}{I} & Product variations (e.g., colors) & 5 & 14 & PII \\ \hline \multicolumn{6}{c}{Reviews} & \multirow{2}{*}{O} & Product reviews with star \\ \multicolumn{6}{c}{ratings} \\ \hline \multicolumn{6}{c}{I} & Average star rating of reviews & 4 & 11 & RI \\ \hline \multicolumn{6}{c}{Recommendations} & \multirow{2}{*}{O} & Recommendations based on the \\ \multicolumn{6}{c}{product of interest} \\ \hline \multicolumn{6}{c}{Comparison of similar products} \\ \multicolumn{6}{c}{(incl. description, price,} \\ \multicolumn{6}{c}{reviews)} \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Results from the qualitative interviews. The extracted features from the user suggestions are comparable to the present literature, as several authors have mentioned similar features and concepts in the case of shopping assistant systems. Considering the user suggestions, most of the suggestions are in line with earlier research towards deploying shopping assistant systems, but the present research validates these for MR systems. Three-dimensional models and 360\({}^{\circ}\) view pictures of retail products have been adopted previously in web-based shopping applications.