A few years ago, I was working for a client who had the word “trust” in their tagline. This company had been around for a while, as had their tagline, so no one really thought about it outside of the annual “does our logo need to be updated” discussion.
But they wanted to do a major redesign of their site. Their initial requirements were pretty broad, so I began to dive into their product experience to narrow them down. I also started the conversation about brand pillars, design guideposts, and manifestos. As a highly regarded brand that had been around for a while, there was plenty of big-picture brand surveys and analysis to do, but it was interesting to look at the mark itself (which had been around for almost 100 years), and the tagline, and ask ourselves what the words really meant. If working for Hugh Dubberly (a RISD-, Yale-, Apple-, and Netscape-alum that AIGA President David Brown called, “a professional shiner of light into the murk and ambiguity of life.”) taught me anything, it taught me not to take the basics for granted. Often a deep understanding of the basics can be precisely what guides us to a breakthrough user experience. So what exactly was trust, anyway? What did we mean by it, and did it have any implications for the user experience?
We’re big fans of creating concept maps to understand a topic that is new to us but that we need to understand well, or which we might know slightly but need to have a rigorous understanding of. It helps us to ensure a user experience that’s consistent with an accurate mental model of the space. Over the years, much of it under Hugh’s guidance, we’ve created concept maps for topics as diverse as heart attacks, TCP/IP packets, and Java. As Hugh says on his site:
We create concept maps, a type of model, to explore and learn about complex information spaces. By showing everything—the forest and the trees—in a single view, concept maps help people create mental models and clarify thoughts.
We create concept maps to share understanding—with our clients, peers, and others interested in the subjects. http://www.dubberly.com/concept-maps
0. A Brief Definition
Concept maps came into use by educators after the publication of Joseph Novak and Bob Gowin’s book, Learning How to Learn. The basic idea is that you draw all the objects or concepts related to a particular idea, and then you draw and label all the connections between those concepts. Because of the non-linear nature of a concept map, it can much more succinctly describe a complex network of concepts and their relationships. The maps’ visual nature lend them to sharing and conversation, which often leads to deeper understanding (more concepts, and more connections).
1. In Which I Adjust My Approach
Armed with a healthy (read: naïve) dose of “How complicated can it be?” I planned to use my normal approach to concept mapping. Normally my process goes like this:
- Collect all the concepts I can think of or find
- Organize the nouns into buckets
- Label the buckets
- Organize the bucket labels into a sentence or two (if two, they must intersect—this becomes the “armature”)
- Add the rest of the concepts with their relationships
- Fill in the missing relationships and add concepts
- Share, revise, repeat
So for example, to make a simple map of “martinis”, it might go this way:
In this case, I really had two uber-buckets: cocktail and sophisticated. With a few experiments, I decided to try this perpendicular two-sentence armature, which allows for easier connections, which you’ll see later. Sometimes you have to try lots of variations of the armature to find something that works.
You can see here that plenty of revision is called for—ice is missing entirely, as are the concepts of “wet” and “dry”, but you get the idea.
In the case of the “trust” concept map, I began my first search and found, to my horror, nearly 2 million articles on trust via Google Scholar. It was impossible to imagine collecting a meaningful set of concepts from so many articles.
A search for a model or definition of trust helpfully narrowed things down a bit. I decided to use an entirely different approach, and to essentially work from the inside out, looking for a good working definition of trust to use as my armature, and then I planned to build around that.
2. Find a Candidate for an Armature
As I read papers focused exclusively on the definition of trust, I came to realize that many of them hinge on an important article written in 1995 by Lewicki and Bunker. I’d read that article, but now decided to use it as my touchstone, and to use their definition as my armature. I reread it more carefully, following up more fastidiously on its references, finding criticisms of their definition and investigating papers the authors had written since. I revised their definition, now my armature, to support important objects and relationships. Simply finding my first set of articles, zeroing in on my “touchstone”, and following the strong leads from there took two weeks. As I read I mapped, starting off with lots of concepts but few connections. As I went on, I added fewer and fewer concepts (at some point I’d found most of them), but more and more connections because my understanding of the nuances of how the terms related became more developed.
3. Stop Mapping at Some Point
Eventually I’d followed my primary paths of inquiry full circle, running into references to papers and authors I already knew, and for the purposes of this exercise felt I had enough solid material to work with. To riff on da Vinci, research is never done, just abandoned. Because I’d worked “from the inside out” (from a good definition first), it was relatively simple to organize my concepts, add missing connections, and then remove everything that didn’t seem to be of primary importance. Because my audience for this map was internal, not academics, it was important to make sure I kept the final version of the map contained. I love geeking out on this stuff but not everyone has the same tolerance for it.
So what, if anything, was useful about this map?
Broadly, I was interested to read, and finally decided to use, Lewicki and Bunker’s tiered classification for trust: Calculus-Based Trust sounds just like what it is: people make a calculation about whether there are penalties and rewards in place sufficient that they can trust another person. Starting there, people can move up to (or, depending on the circumstances, start at) Knowledge-Based Trust. The idea here is that you know something about, you have some experiences with, another person or entity. Finally, the ultimate trust is Identification-Based Trust, where we believe another person knows us well enough, and has our best interests at heart so much that our interests are aligned, and I can trust them entirely.
My definition of trust in the map is a modification of several others’, but nearly everyone’s definition includes the idea that trust involves an expectation. For this map, I specifically called out the generally agreed-to-be-critical expectations about goals, competence and integrity that are guided by experience, reputation, and of particular interest to this audience, brand. (See Hugh Dubberly’s Brand Map if you really want to blow your mind.)
…and So What?
It is important somewhere in here to make the point that not all models are gems of insight or even useful. Designers and their bosses, clients and colleagues need to allow for a little bit of “follow your nose” time, for a few models that don’t go anywhere, and for time with those that seem to show hope.
It’s also worth answering the question that comes up occasionally: How do we know this is right? Because it’s clearly subjective — I used good sources, but I also chose the definition to use, I chose what to leave out, and personally acted as both author and editor. But I maintain that subjectivity is not a reflection of accuracy. There are seven different ways to organize the coins in your pocket. The fact that you organize yours by amount and I do it by size doesn’t mean that either of us is wrong. If the map leads us to some new understanding, or even fosters conversation, then it’s done its job.
Having said that, the trust model surfaced some ideas that are worth considering.
For example, I’ve always been baffled about why people look for “the little lock” when conducting usability studies of ecommerce sites. Sure, secure http is important, but many of them think https when they see the icon. They don’t know what it is or whether it’s actually in play. And even if it is, there are nefarious employees, hackers, etc. But these people had some good experiences with a recognized and repeatable construct, and had developed some knowledge-based trust of it. (It’s worth noting that trust only exists in a situation of perceived risk – if users know everything about how a site works, who is running it, and everything in between, there’s no point in or need for trust. The flip side is that the very fact that usability participants don’t understand what https is or how to know when it’s actually being employed creates a risk state that requires trust.)
It’s also suddenly crystal clear that for even the most basic level of trust, Calculus-based trust, as site owners we must provide some essentials to users, things like: How does our company make money? What happens if something goes wrong? Why is our company helping them in the first place?
Similarly, being explicit about goals (We make money the old-fashioned way—we earn it.), competence (50 million served!) and integrity can support an expectation of trustworthiness, sometimes long beyond the time that actual experiences belie that expectation (Don’t be evil!).
There are certainly many more examples of how this trust map specifically can have implications for user experiences; we’ve just pointed out a few of them. Happily, with topics like trust, we can continue to learn and leverage what we learn across projects and over years.
Bainbridge 1997 - Who Wins the National Trust?, Marketing, October 23th, 21-23.
Barney and Hansen, 1994 - Trustworthiness as a Source of Competitive Advantage, Strategic Management Journal, 15, 175-190.
Bhattacharya, Devinny and Pillutla, 1998 - A Formal Model of Trust based on Outcomes, The Academy of Management Review, 23 (3), 459-472.
Bhattacherjee, 2002 - Individual Trust in Online Firms: Scale Development and Initial Test, Journal of Management Information Systems, Volume 19 Issue 1, Number 1/Summer 2002
Fournier, 1998 - Toward the Development of Relationship Theory at the Level of the Product and Brand, in Advances in Consumer Research, Vol. 23, ed. Kim P. Corfman and John G. Lynch, Jr., Provo, UT: Association for Consumer Research, 661-662.
Delgado-Ballester, 2003 - Development and Validation of a Brand Trust Scale, Revista: International Journal of Market Research
Dubberly, 2005 - Models of Models
Gefen, 2000 - E-commerce: the role of familiarity and trust, Omega, The International Journal of Management Science, 28 (2000) 725-737
Glaeser, Laibson, Scheinkman, and Soutter, 2000 - Measuring Trust, Quarterly Journal of Economics 115(3): 811-846.
S. L. Jarvenpaa, M. Tractinsky, and M. Vitale, “Consumer trust in an Internet store,” Information Technology and Management Special Issue on Electronic Commerce, vol. 1, no. 1–2, pp. 45–71, 2000
Lewicki and Bunker, 1995 - Trust in Relationships: A Model of Trust Development and Decline, in Conflict, Cooperation and Justice, ed. B. Bunker and J. Rubin, San Francisco: Jossey-Bass, 133-173.
Lewicki, R.J., & B.B. Bunker. (1996) “Developing and Maintaining Trust in Work Relationships.” In Trust in Organizations: Frontiers of Theory and Research, eds. R.M. Kramer & T.R. Tyler, 114–139. Thousand Oaks, CA: Sage Publications.
Mayer, Roger, David James, and F. David Schoorman (1995), An Integrative Model of Organizational Trust, Academy of Management Review, 20 (3), 709- 734.
McAllister, Lewicki and Chaturvedi, 2006 - Trust in Develop Relationships: From Theory to Measurement
Oakes, 1990 - The Sales Process and the Paradoxes of Trust
Oxford English Dictionary, 2005
Sheth, Jagdish N. and Atul Parvatiyar (1995), Relationship Marketing in Consumer Markets: Antecedents and Consequences, Journal of the Academy of Marketing Science, 23 (4), 225-271.