One of the most enjoyable aspects of user experience design is the opportunity to observe human behavior and interactions directly within the user’s environment. I like to picture user experience designers on reconnaissance missions, quietly gathering user behavior intel while covertly recording the interactive patterns and dialogs we observe. Melodramatic? Sure. Romantic? Possibly. Intriguing? Most definitely.

Working on these skills is like brain pilates. Observational exercises are great avenues to recharge our professional spirit, but honing our skills in observation requires training. It demands we slow down and reflect—it requires patience, passivity, and a willingness to table our personal bias. This type of empathic design will help you produce more innovative solutions and create a strong communal association with the behavior of users. It's a gentle reminder that our role is one of advocacy, trust, and facilitation.

Considering the need for this kind of professional development, our UX team has actively created “training” exercises that specifically focus on refining our observational skills. One recent opportunity we created took place at the Virginia Museum of Fine Art in conjunction with a team offsite event in Richmond, Virginia.

Image courtesy of VMFA. Photography by Bilyana Dimitrova.

Our goal was simple—create an engaging team exercise to challenge our ability to observe and record behaviors, usability patterns, or interactions. The museum provided a great setting for this type of exercise since it contains visitors of all ages, interactive exhibits, wayfinding/traffic flows, and wasn’t too large or too small.

We determined that a digital scavenger hunt would provide a recognizable game structure for teams to understand. Using our smartphones as a recording device, teams were given an hour to photograph examples of interactive-related behaviors. We created 11 categories modeled after a hunt created by the Computer-Human Interaction Forum of Oregon (CHIFOO). Each category included instructions to capture both a good and bad example of each category. These included tasks such as:

• Capture an arrangement of controls that make it easy to perform a task
• Capture physical feedback that interferes with a user’s ability to use a system
• Capture an interactive sequence with an intuitive user flow
• Capture an example of an agent that negatively affects the user’s behavior
• Capture an example where color is successfully used to convey meaning
• Capture an experience that users enjoy.

We also wanted to have a shared online repository where every team could record the observations they captured within each category. Our smartphones were an efficient and unobtrusive way to record our observations, and we discovered that the Pinterest app’s interface suited our requirements better than many applications specifically built for scavenger hunts. Pinterest allowed us to create shared pinboards for each usability category and pin our images to the appropriate board immediately after they were captured. Our boards could then be used for any future exercises, morphing into a long-term collection of good and bad usability examples.

One final aspect that was particularly interesting to the team was how observations or notations around spatial properties in the physical world reflect similar usability concerns in online environments. Could the observation of a flow or sequence in an environment such as a museum influence any future interactive patterns we develop for our clients? I’ve listed a few of our observations below.

The transition from the balcony to stairs was further cued in a floor texture change from tile to carpet. While this decision likely served a practical material purpose, the subtle reinforcement of the upcoming transition prepared visitors for their descent down the stairs.

Matching the background of the exhibit description labels to the wall paint color allowed the boards to be legible when in the immediate vicinity of the object, but not distracting (and fairly invisible) when panning or surveying the entire exhibit. This allowed the art, rather than the supportive objects to be the primary focus of sight.

Image courtesy of VMFA. Photography by Bilyana Dimitrova.

The success of pushing the elevator button is further reinforced by a visual cue of highlighting the button's outline.

Poor user flows and navigation were not typical of the museum except in this one example where the visitor encounters a dead-end and must retrace their steps back out of the exhibit. The physical experience of dissatisfaction and confusion is not dissimilar to user flows which provide little evidence of further interactions.

Listing the upcoming exhibits at this scale and location on this 3rd floor wall removed any ambiguity or confusion around the exhibits in this distant space, even for a user 2 floors below.

Example of a perspective where key pieces of art are visible from various points during your progression. Besides providing a sense of anticipation and wonder, the pattern of using art to mark the beginning or end of a path was established. This navigation strategy became a useful mental model for a visitor to understand progression through the museum.

A few challenges we noted were not being able to capture video for time-based observations like sequences and not having an efficient means to provide context or descriptions around the captured images. Given the limitations around mobile typing, the static image and subsequent label did not always adequately reflect the context for the observation.

Overall, the exercise was a success and provided a good opportunity for the team to practice our observational-based skills. The game-like mechanics and competition of the scavenger hunt made the exercise enjoyable while providing some categorical structure and focus to the behaviors we were looking to capture. It was also beneficial to pin our observations to a central location so all the groups could reference the images after completing the exercise .

We’d love to hear if other teams have found success in any observational exercises. In the meantime, check out our Pinterest boards or download the list of categories and tasks we used in our hunt.

Recently, I took on the task of updating our Viget Facebook account to the new Timeline layout. Now, I don’t just mean clicking the “Get Timeline Now” button, but actually using it to its fullest potential by updating it with various facts, photos, and videos from our company’s history. What I initially expected to be a tedious, content-gathering chore turned out to be quite an informative and even enjoyable little project.

Over the past couple of weeks, I’ve been consulting with various folks across the company from co-founders, Brian and Andy, to Cindy, our first employee (whom I’ve now classified as our Resident Historian since she either remembers or has access to information about almost anything from Viget’s past), to Jason, who more recently helped start our Boulder office. I stumbled upon hilarious photos from TTT events going way back, heard stories about previous employees, and got a chance to flip through binders of our old internal weekly Lab Reports (updates on projects, sales, and other Viget info).

A challenge that has always plagued the web industry is understanding users. Whether it’s their habits, assumptions, interests, tendencies, or expectations, it all affects how any user will interact with and respond to a website. Since no group of users or customers is the same, it takes more than just a general knowledge of what users want in order to design something effective.

Traditional UX research practices include user interviews, focus groups, and usability testing to answer some of these questions. These tools are great for being able to dive deeper into questions, asking why, probing where needed, and developing empathy for how certain people think. However, there’s a potential gap if we rely solely on these tools. These exercises are anecdotal, and thus only tell a piece of the story.

What if the five users you interviewed are not representative of the entire customer population? There needs to be some way to verify conclusions across a larger sample, substantiating your findings with real, hard data.

Recently I was troubleshooting why ?fb_xd_fragment= was getting appended to the end of a bunch of URLs in Google Analytics. With a little bit of googling, the source of the problem wasn’t tough to find--it happens when a visitor using Internet Explorer clicks a Facebook ‘Like’ button on your page.

Surprisingly, though, all of the highly ranking results in Google give a GA solution that’s flat-out wrong. Here’s why:

In April of this year, Google began updating their search algorithms with something called "Panda." These effects have been more fully integrated throughout the year. In the world of SEO, this update represents a greater movement towards human accessibility and usability and away from machine oriented language (such as meta tags, keywords, etc.).

Panda utilizes thousands of ratings from human quality raters that provide answers to simple questions on the quality of the websites they visit. These questions include anything from "Would you trust this website to prescribe pharmaceutical drugs to your children?" and "Were you engaged by the content on this site?" to "Would you ever revisit this site?" These questions focus on visual design, user experience, and original content, more so than any other algorithms have previously measured. Based on the quality raters' answers to these questions, Google determined trends that re-ranked thousands of websites. These re-rankings hurt thousands of "content and link farms" which used traditional SEO tricks to boost rankings. Specifically, these sites suffered due to the following qualities:

1. Template footprint leaving a low ratio of original content 
2. Empty content pages which exist simply to link to other pages 
3. Overlapping and redundant articles 
4. High advertisement ratio 
5. Affiliate links and auto generated content

On the flipside, these re-rankings benefited well-designed and usable sites that decreased user confusion and were designed from a human point of view.

A practical example is Google's new functionality to block all results from a certain site. This allows them to track the meaning of bounces off search results. They can then use public users' own "quality ratings" by taking into account the amount of blocks any site has received, relevant to certain keywords.

As Panda becomes more sophisticated and robust, SEO is becoming less focused on writing and designing for machines, and more focused on writing and designing for humans. Viget fully believes this is a great change for the web community and embraces the ways in which new algorithms will rank websites.

Bottom line: make sure your users are having great experiences, or it'll come back to bite you in search rankings.