It’s Written All Over Your Face! Or Is it? – Facial Response Analysis

Facial response analysis of the Mona Lisa

Facial Response Analysis has provided companies and researchers with a unique look into how exactly their users are feeling, allowing them to gather a large amount of data and provide a better user experience. However, this method may not always pick up on specific or unique emotional expressions, causing inaccuracy amongst evaluation.

 

     One element of great user experience design is a product that ignites positive emotions and engagement. This concept is called Emotional Design. Emotional Design is centered around the belief of users having a positive experience when engaging with a product. People should connect to a product/design on a personal level causing it to be relatable. But, how can researchers decipher what their users enjoy or dislike? By measuring emotions and engagements. Measuring the emotional reactions of users, allows researchers to view first-hand how their product is being received. One example of a tool used to measure emotion is facial response analysis, which is a software that can be used to detect emotion based on facial expressions such as a grin, furrowing of the eyebrow or a frown. Facial Response Analysis has provided companies and researchers with a unique look into how exactly their users are feeling, allowing them to gather a large amount of data and provide a better user experience.

     Facial Response Analysis examines the emotions of users by studying the movements of the face from a video recording. The system uses computer algorithms to break down the video from a webcam and provide emotion measurements. The first step in analyzing the data is locating the face and then extracting the key facial expressions that are used to classify each emotional characteristic. The software distinguishes between facial movements such as the widening of the eyes or a large upward mouth. The results generated by the software produces an “engagement score” that signifies whether the user is, for example, focused on the given task (face looking at the screen) or expressing joy (smiling) (Schall).

   Facial Response Analysis is one of the easiest methods to collect data and analyze. It does not require much interaction between researchers and users because it is more about the relationship between the user and the product/design. It is a less intrusive method, allowing users to exhibit more genuine notions about their experience. Data on any user satisfaction or frustrations can easily be noted because the user is engaging with the product. Companies are now working with emotional analysis software providers to understand what their users want. Facial analysis software providers include KAIROS who has work with companies like Ikea, Capital One, and IBM. AFFECTIVA, who has provided services to CBS and Kellogg’s and EMOTIENT which was recently bought by Apple in 2016 (Foster). Brands realize the importance of emotion design and want to achieve it.

   However, research shows, it is also the least accurate. Results can be very accurate for highly expressive emotions such as a large smile, but they are not consistent for complex or subtle emotions such as a smirk or a “slight rise of the eyebrow” (Ying Ki). Inaccuracy or lack of measurements in facial analyzation may cause data to be imprecise. Facial Response Analysis has been proven to be more successful when combined with other methods of user testing. When paired with a survey, open-ended questions or eye-tracking, researchers can better understand the specific emotional experience of the user.  

References:

Foster, T. (2016, June). Ready or Not, Companies Will Soon be Tracking Your Emotions. Retrieved from https://www.inc.com/magazine/201607/tom-foster/lightwave-monitor-customer-emotions.html/.

Schall, A. (2015, April). The future of UX research: Uncovering the true emotions of our users. In UX User Experience. Retrieved from http://uxpamagazine.org/the-future-of-ux-research/.

Ying Ki, S&J. (2015, December) Emotional UX-Techniques for Measuring User’s Emotions. Retrieved from https://eyetracking.com.sg/2015/12/15/emotional-ux-techniques-for-measuring-users-emotions/.

Design Critique: OpenTable (Mobile App)

Founded in 1998, OpenTable is a web service that allows users to book restaurant reservations online. Through their website and mobile app, users can view restaurant menus, reviews, photos and earn reward points through using the platform to make reservations. Based in San Francisco, this free service has expanded to include restaurants throughout the United States and now offers its services globally in countries such as Canada, Mexico, Japan and the United Kingdom. This post will critique the design of OpenTable’s mobile application.

Home Screen:

When the user opens OpenTable’s mobile app, they are taken to the home screen, to a greeting message and multiple signifiers providing discoverability.  The four buttons at the bottom are each labeled with text and images providing the user with two signifiers for each icon. The decision to only have four icons to navigate allows for easy usability. These selections are easy for the user to memorize, allowing effective navigation through the app. If the user is on a specific screen the color of the navigation icon changes from grey to red. This signifier provides the users with feedback that illustrates what page is being viewed.

On the home screen, the option to search is placed in two locations: at the top of the screen and at the bottom, as one of the main navigation icons. This leads to more discoverability for the user. The bar is labeled “search” and has an image. The user is aware that they can perform an action within the search box to get a form of feedback. Once the user taps inside the search box, the app automatically redirects them to a page where the user can search by food type or restaurant name.

OpenTable also provides buttons labeled “Recommended for You” and “Near Me Now” where they provide compilation lists of restaurants fitting these specific descriptions. By doing this OpenTable reduces the time the user would spend searching for a restaurant with these characteristics. This design feature is an example of great user experience. It provide discoverability while engaging the user in a fun, exciting way. Designing a feature that provides recommendations leads to an emotional connection with the user.

The home screen does contain one design issue. There are no signifiers informing the user that the page can scroll up and down, leading to other features such as searching by other compilation lists, cuisines, and neighborhoods. Other pages of the app include signifiers for scrolling. I would add this feature to the home screen as well.

Searching for a Restaurant:

OpenTable design provides multiple ways for the user to search for a restaurant. Once the user clicks on the search bar, the design provides feedback, taking the user to the search page. On the mobile app, the design automatically provides restaurants in the local area of the user. This can be seen as a problem. Users may perform an action slip where they are only searching local restaurants without realizing. I would change this feature by giving the user the option of typing in the location they desire from the beginning.

At the top of the search page, the user can modify the number of people, date and time of the reservation by clicking on the red arrow. This signifier is very small and can be easily missed by the user. However, the contrast in color between the arrow button and the rest of the screen page is an affordance for the user to know that this icon provides feedback. Once the user taps the red arrow, a scrolling menu drops down giving the user the option to modify their reservation details. The natural mapping of this scrolling menu is straightforward. As the user changes the number of people, date and time of the reservation, the information above the scrolling menu changes as well.

Booking a Reservation:

Once it is time to book a reservation, the user navigates to the restaurant page to reserve an available time. The affordance of the time options allows easy gulf of execution and feedback. Once the user selects the desired reservation time, they are automatically taken to the final step where they complete the reservation process. OpenTable provides a small gulf of evaluation through its reservation screen. The information for the user’s reservation is displayed, allowing for easy interpretation. Overall, the OpenTable app offers a good user experience through its design.