Marketers increasingly think about consumers in complex ways. It is understood that in a changing digital landscape, the context in which they learn and shop influences what messages we deliver and how we deliver them. But we rarely define “context”. It is one thing to design a usable app that conforms to human factors and cognitive requirements, but it is quite another to design a stage in an environment when there are innumerable semi-autonomous devices mediating in a swirl of information.
Physical context refers to the notion of infusing devices with a sense of “place.” In other words, devices can distinguish the environments in which they “live” and react to them. But this is difficult. Mapping out longitude and latitude is one thing, but reacting to features (political, natural, social, etc.) is much more problematic. Getting beyond the boundaries of identifiable borders and structures, means coming to grips with “place”.
Think of a mall. There are hundreds of stores, each with hundreds of devices. The device now has to decode what information is relevant and how it will deliver information. What competing retailer apps get precedence over others? When you receive an offer, will the device “tell” other retailers in order to generate real-time counter offers? The digital landscape is continuous at all points throughout the day and getting design right means understanding the systems in which people operate.
Just as various kinds of sensory apparatus (GPS-receivers, proximity sensors, etc.) are the means by which mobile devices will become geographically aware, another class of sensors makes it possible for devices to become aware of each other. This presents a series of problems that are different than those of physical context.
Technology is on the verge of existing in a world with zero-infrastructure networks that can spring up anywhere, anytime. Devices will exist in a constant state of discovery. Returning to the mall, imagine that you are with a friend whose device is communicating with yours. In the mall are a couple of thousand devices, all of which are discovering each other. What happens now? Assuming we’ve dealt with the problem of one friend’s device communicating with the other friend’s device while blocking out the other 2000 devices, you still have several thousand potential “identities” that may have useful information. How is it decided what to manage without devoting significant time to setting up the hundreds of variables?
This is the realm of information architecture. Data no longer resides “in” our computers. Devices are extensions of the cloud and exist as something akin to perceptual prostheses. They exist to manipulate data in the same way a joy stick allows us to handle the arms of robot in a factory. This reflects a shift in how we use information because all information is transitory.
Storage issues are essentially removed from the equation. Content can leap from place to place and device to device in an instant. Content will be customizable and reflect the human-application interaction rather than shaping it. Devices will find themselves in the fourth kind of context of social interaction, with all its contingencies. Just as behavior is shaped by the moment, so too will the apps and information needed to adapt.
Each person is unique to contrasting cultures, tongues, traditions and world views. A cultural context may exist on levels as diverse as a workplace, a family, a building, a county, a continent, a hemisphere. Cultural context provides a framework for what “works” for each consumer in the world.
It is at this point where a better perspective is gained on what will and will not be accepted in the mobile universe. Take a beer pouring app that mimics the pouring of a beer when the device is tilted. It serves no direct function and yet it has been successful because of the cultural needs it to which it speaks – workplace breaks, male-to-male bonding, etc. But in another context, say Saudi Arabia, the context shifts. Success lies in understanding the reasons behind the consumers beliefs and actions in the symbolic exchanges, and the ability to code and decode those exchanges. Marketing mishaps come from a lack of comprehension.
Our great technological leaps forward have also produced more complexity, leading to a greater need to make sense of insights. Without a means to categorize context, marketers will miss identifying trends that matter most. What to do?
- Rethink the problem. Frequently, “the problem” is a facet of something else. For example, when researching an eBook the problem to be solved isn’t technology, it is understanding why people read different material in different contexts. It may be about displaying books as a means of gaining status. The point is the problem seen may not be the problem at all.
- Define the contexts. Defining the contexts helps articulate the range of possibilities for observation. For example, if the consumer behavior is drinking beer, all contexts in which beer is purchased and consumed need to be articulated.
- Think through the sample. Who is the marketing targeting? What are the social circles that will shape the event? It isn’t enough to define a demographic sample, you need to think in terms of cultural systems.
- Make a plan that involves experiential information gathering, not just statistics. Develop a guide to navigate the data collection and a method for managing the data (everything is data). Don’t just think about the questions to ask, but also include opportunities for observation and participation.
- Head into the field. This is the heart of the process. Meaningful insights and moments of “truth” are slow to get at. Low-hanging fruit will be easy to spot, but the goal should be to find those deeper meanings. Because everything is data, from attitudes to artifacts, it is important to capture as much as possible.
- Do the analysis. Analysis is the most difficult, but also the most rewarding. The goal is to bring a deep understanding of cultural behavior to the analysis process. This goes beyond casual observation and gets to the underlying structures of why people do what they do.
The process is more time consuming than traditional approaches, but it ultimately yields greater insight and reduces time and costs on the back end. The end result is that you create greater value for the client and for the company.