Testing social media is difficult. We are not testing micro interactions, but macro, or global, behaviors. These can be extremely hard to observe—either by using qualitative methods to assess the commentary of individuals or groups or by tracking clicks. When testing social media, we are assessing social influence and motivation, which are much more elusive.
Understanding these types of behaviors won’t let you determine things like the perfect placement of your shopping basket icon. However, it can be invaluable when determining the right timing for providing choices such as content or action buttons. The monitoring of macro behaviors is quantitative in nature, and the data represents broad trends—what people do en masse, not individually. Nevertheless, it is the sum of many people’s behavior that is important rather than the behavior of individuals. Studying societal behaviors requires a different way of thinking—macro thinking—rather than the micro thinking that is characteristic of studying the behaviors of individuals.
Examples of Macro Thinking
In one example of macro thinking, Figure 1 depicts an aggregate view of half a billion Foursquare check-ins.
A great example of a social-media platform’s potential for applying a macro perspective is the way Foursquare has used their data to predict the day on which everyone’s New Year’s resolutions would come to an abrupt end—also known as Fatty Solstice. By looking at their users’ exercise habits and visits to fast-food restaurants, Foursquare predicted that, on February 2nd, 2017, visits to the gym would drop, as trips to fast-food restaurants rose. The infographic in Figure 2 shows this reversal in user behaviors, as users exercised less and ate more.
How can businesses apply a macro perspective and look more holistically at the data their customers’ social networks are generating? How can businesses apply such insights to shape a better customer experience?
Unfortunately, dealing with broad data sets is not something that usually sits well with UX professionals. Historically, businesses have mainly used social media as communications tools—then, more recently, as monitoring tools. Very few businesses are using social media to understand and design better digital experiences. If you were monitoring the sentiment of discussions about a business over the course of a month and saw a significant increase in negative commentary, how could that help UX designers to do their job?
Using Health Monitoring as a Model
Monitoring people’s health is not a new concept. In fact, it is a very well-established practice. How can we apply the concepts and practices of health monitoring to social media? Then, how can monitoring social-media data help us better understand digital behavior and how we can apply that data to the design of customer experiences?
Anyone who has visited someone in a hospital will have seen the range of monitoring devices that measure different aspects of a person’s health, including heart rate, oxygenation levels, and blood pressure, as shown in Figure 3.
Measuring human health is no mean feat. The over 100 trillion cells that make up the human body must work in a coordinated way, within incredibly tight tolerances, to achieve a healthy state. Interestingly, we can consider monitoring of the social-media ecosphere in the same way—with each person acting both independently and in various groups.
Doctors use health-monitoring data to localize health problems, so they can investigate them further and prescribe a treatment. In the same way, UX professionals can delve more deeply into social-media monitoring data—looking beyond the noise that thousands of broad observations generate into the realm of deep, precise learnings. Similar to usability testing in a lab, social-media monitoring helps UX professionals observe what people are actually doing rather than what they say they are doing.
Next, we’ll look into how effective social-media monitoring can produce insights that help us to design better experiences, as well as insights that deepen our understanding of social media and people’s associated behaviors.
Digital Trails: A Day Out at LegoLand
As we go about our days, most people leave behind a trail of data, consisting of clicks, pushes, swipes, likes, and shares. We can turn this data into behavioral information that reveals a rich history about who we are, where we have been, what we have done, and who we are doing it with. Figure 4 shows the use of social media in researching, traveling, experiencing, and sharing a day out at LegoLand.
The experiences of other people influenced one Dad’s decision to take his family to LegoLand for the day. A broad range of digital systems and services supported this experience. The Dad initially carried out a search to find something that would entertain his children, then made a decision to go to LegoLand. He based his decision on Aunt Sarah’s Facebook posts—a strong tie—and after discussing LegoLand with another parent at school—a weak tie.
Figure 5 shows Paul Adams’s model of influence. He suggests that the level of influence we exert over others—and that which they, in turn, exert over us—correlates to the strength of the relationships between people.
Among other things, this Dad’s digital experience provided travel options, information about on-site food outlets, reviews from complete strangers about the best things to do at LegoLand, and tips on how to beat the queues. Finally, because both parents own smartphones, digital social-media platforms let the family upload photos and share their thoughts and observations about LegoLand—before, during, and after their visit. The posts the Dad made on Twitter throughout the day influenced two other families to visit LegoLand later that summer.
The Bigger Picture
Applying the health-monitoring metaphor, we know: just as one heartbeat does not provide enough information for a clinician to make an accurate diagnosis, one tweet does not provide enough data to make a compelling case for redesigning an online customer journey. But, with social-media monitoring tools, we can build dashboards that let us see what social-media trends are unfolding in real time. By analyzing a broader social dataset, we can understand whether many people have had a similar experience and, therefore, whether a redesign may be necessary.
Figure 6 shows a social dashboard monitoring LegoLand. The data comprises publicly available tweets. In the upper-left corner of the dashboard, you’ll find data showing the volume of social discussions for the month. To the right, the graph under Mentions Timeline shows peaks and troughs of activity throughout the month. Under Reach & Spread, you can see the primary reach of these conversations—the 8 million timelines that received these posts—then their secondary spread—the additional 2.7 million social connections who also saw them. Under Sentiment, you can see the sentiment of people’s language regarding these messages—47% positive, in green; 8% negative, in red.
How Far Can a Tweet Travel?
It is possible to track how far and where a shared tweet travels. In Figure 6, Adam Hills’s tweet to his 500K followers, shown in Figure 7, drove the spike in the middle of the Sentiment graph in Figure 6.
T analysis is a systematic approach to defending against disruption by focusing attention on driving sustainable value from the social Web—rather than chasing meaningless metrics. Figure 8 shows Nomensa’s T-Analysis Framework, which contrasts broad versus deep social-media monitoring. Taking a broad perspective provides an overview and helps you to identify areas to explore further through deep analysis—which then lets your organization benchmark and track specific areas and business systems.
This form of analysis lets you move away from Show me everything people are discussing about LegoLand to the much more valuable: The customer has a problem. What is it, and what can we do about it? Some other questions this approach addresses include the following:
Why are people increasingly expressing dissatisfaction?
Are trends or patterns emerging?
Is the Customer Support team dealing with more calls and messages as a result?
Is this issue impacting sales?
What part should User Experience play in this situation?
Is there something we must do to improve the situation?
Figure 9 depicts just such a situation: A customer has had problems buying tickets on the LegoLand Web site. Seeing different prices at different points in the purchase process has led to mismatched expectations and a poor user experience, so the customer has shared her experience on Twitter.
When other people came across this tweet in their Twitter timeline, it influenced their perception of the brand. This is not just a problem for LegoLand’s reputation, but also indicates broader issues that need addressing. Effective monitoring is a question of viewing social-media data at the right altitude. So, just as one heartbeat is not enough for a doctor to diagnose heart disease, one tweet is definitely not enough to justify a complete redesign of LegoLand’s user interface for purchasing tickets.
But this situation does pose the question: Are others having the same problem? How many others have been put off from buying tickets or called the Customer Support desk because of similar experiences? We need to monitor and understand such situations more deeply.
The Social Web: A Business Tool at Everyone’s Fingertips
One of the biggest challenges for the use of social media in a business context is that businesses have historically perceived social media narrowly—as a marketing channel to help reach the masses. For example, an influencer-marketing approach to social media might cause Social Media Managers to chase their own Adam Hills moment—doing everything they can to deliver a momentary spike in activity and drive the visibility of their brand. This is a very one-dimensional way of thinking about social media that ignores the cumulative effect of everyone posting online. Many organizations will, in time, become aware of the broader potential of social-media monitoring to inform them about their customers’ social behavior. But, for some, it will be a lesson they learn too late.
The Social-Media Health Check
“By monitoring the social-media conversation, a company can keep abreast of what people are saying about its brand and even its competitors. It lets a company determine what kind of response its marketing team should give and which one would be most effective, before they are caught off guard.”—Jason Falls and Erik Decker, from No Bullshit Social Media
Just as monitoring the heart rhythm of a critically ill patient helps doctors prevent heart attacks, the T-Analysis Framework gives organizations an early-warning system, providing rich feedback that supports the ongoing design and delivery of better experiences.
Competitor analysis helps organizations to see how they compare objectively to their competitors or other markets. For example, LegoLand could explore how healthy their social media was in comparison to Alton Towers. Or, alternatively, they could use broad monitoring to understand where they sit in the What to do with my kids this summer market.
Moving from broad to deep analysis sharpens yours lens and allows your organization to benchmark and track specific areas or business systems. An example of this would be looking for posts that convey user frustration about not being able to find specific information, as Figure 10 demonstrates.
We can learn a lot from social-media data—about peoples’ motivations, expectations, and attitudes toward a business, as well as the value they place on its customer experiences. Using the T-Analysis Framework gives companies a competitive edge because it lets them do the following:
Identify and track opportunities and risks within their market.
Identify and track opportunities and risks within the delivery of their services.
Identify and track opportunities and risks within the delivery of their digital estate.
Correlate observable social activity against organizational impacts.
Focus redesigns—in response to customer feedback—on the areas where they’ll have the most impact
Deliver improved experiences.
Digital disruption is raising the stakes for many businesses. Our digital lifestyles represent the social fabric that connects all of us, so we must consider the part social media can play in the success of any digital experience. Leaders of 21st-century businesses could take a lesson from the medical community, which takes monitoring and managing health very seriously. Doctors and nurses rely on a broad range of diagnostic techniques, including health-monitoring devices, to provide them with the data they need to make informed, evidence-based decisions. Businesses need to achieve the same rigor in relation to social-media monitoring.
In 2001, Simon founded Nomensa, a UX design company. He coined the phrase Humanising Technology to reinforce Nomensa’s belief that digital technology should be usable, accessible, and engaging. With an academic background in Human Psychology, Human Biology, and Cognitive Science, Simon has turned the traditional view of Web design on its head, focusing on people’s emotions and experiences and enabling organizations to engage with their customers more deeply, meaningfully, and ultimately, more profitably. In his role as CEO, Simon is responsible for the growth and strategic development of Nomensa. He also leads UX strategy and vision for many corporate clients, integrating and refining human centered–design techniques for them. Some of the world’s largest companies have asked Simon to create their corporate UX strategy and digital transformation programs. Read More
With his background in intensive-care nursing, Peter brings a unique perspective to social media. His nurse training in sociology, psychology, and their practical application in acute medical settings informs and guides his work. Peter has advised companies and organizations across a broad range of sectors, helping them to devise their social-media strategy and understand the impact of their social-media communications. After working for ten years in nursing, about ten years ago, he shifted his focus to social media. Read More