Virtual Floorspace

After capturing all the data for the Millennials Apparel Ethnography, we needed to determine the strongest emerging concepts, to evaluate parameters that could drive the design strategy. First we reduced the transcipts to verbatims and observations that correspond directly to the codes, index terms, tags, etc. that we created from reviewing the complete data set. Then we placed the key sections of the transcript into an Excel table and assigned codes that represent their concepts. We then sorted by the codes and evaluated the strength of the concept for operationalizing as a variable to bring into quantitative research. An example coded transcript from the millennials apparel shopping project is shown below.

Uncategorized customer research, design strategy, e-commerce, e-retail, ethnography

My talk on Ethnography 101 at the Usability Professionals Association in Munich went well. The audience was very receptive and about 50% of them participated in the group exercise.

The feedback on my session was very good. It was about a 4.5 on a 5 point scale, including one person who seemed to not like me or the presentation at all.

The most relevant and informative presentation that I attended was by Andreas Hauser and Daniel Markwig of SAP. I took a lot of notes in that one. They discussed how they adapted a major UX initiative to fit within a Lean process, which is very similar to Agile.  The solution was thousands of screens in a complex ERP suite called Business By Design. They didn’t do the typical whining about how hard it is to be UX in an Agile world where documentation is antithetical to efficiency (?huh?). They explained how they used a pattern library combined with use cases and wireframes, to produce a recipe for UX that developers followed.

The overall atmosphere of the conference was very positive. People seemed very smart and focused, and spoke a common UX language, which was interesting to experience.

I really liked the shop windows in Munich. I posted a Flickr photostream:

http://www.flickr.com/photos/43883838@N02/sets/72157624030593401/show/with/4647416633/

Uncategorized e-commerce, e-commerce design strategy, e-retail, ethnography

The shop along is fun. I’ve done in-store apparel shopping with females before, and once again am confronted with a similar shopper decision framework, although the age group is very different. Body image is still critical in terms of time lapse of decision making. The more negative the self-assessment, the longer decisions take, and the more likely participants are to leave a given store without reaching the point of sale, and the more likely participants are, other factors equal, open to technology-based shopping aids. The more positive the self-assessment, the less the focus is on basic assortment factors like color, material, etc. and the more the focus is on less tangible attributes like body area draping and emotional lift. Technology interventions are different for the self-assessment dimension as well, with technology for negative self-assessments focused on shopping options, and for positive self-assessments on social confirmation of having hit the mark.

The above are basic in-process ethnographic study observations; we haven’t started coding the transcripts.

Uncategorized customer research, design strategy, e-commerce, ethnography, qualitative research

Web sites and other technology-based information systems satisfy needs related to a particular task, goal, or need. There is an activity context that is larger than the system’s role in customer satisfaction. That context is usually tied to a location, and that location is where the ethnographic study should take place. It is usually a simple matter to determine the best location.

For example, suppose you are responsible for a web site that sells women’s shoes. An ethnographic approach to researching the needs of women buying shoes online could be to visit the shoe closets of a sample of women in the target demographic, asking them about their current shoes, why and how they purchased the shoes they have, their total spend, their tendencies in terms of style, materials, cost, etc. If there are retail stores associated with the web site, you would probably want to conduct observation and shop-alongs in stores. This research could be conducted more easily in a lab or meeting room setting, but the data captured on site is likely to be much richer in terms of emotions, decision-making criteria, and purchase case histories, giving the work contextual authenticity that is difficult to generate from interview data alone.

It is usually a straightforward process to determine the best location for ethnographic research. Admittedly, it is not always easy or financially feasible to set up a study in that location.

Copyright 2010, Paul Bryan, Usography Corporation (http://www.usography.com)

Linked In: http://www.linkedin.com/in/uxexperts

Uncategorized design strategy, e-commerce, ethnography, methodology, qualitative research

Ethnography is a field research method developed by anthropologists to understand cultures other than their own. At one time, anthropologists theorized about other cultures from the comfort of their own life context. Ethnography was developed as a method to study the culture from within, as a participant, and at the same time as an observer. Ethnography is by definition and in practice a systematic approach for understanding cultural impacts on behaviors, attitudes, beliefs and rituals.

In recent years, ethnographic studies have gained favor across a wide range of commercial design situations. In the world of web design, the term ethnography can be used rather loosely to mean any research that is conducted on location, or in context of the activity for which a web-based system is being designed. Ethnography is most often used as a data gathering tool when the cost of research is significantly outweighed by the potential revenue of creating an innovative product. Ethnography is especially applicable to projects that are multi-cultural in nature, but is not limited to those types of projects. In design-related ethnographic research, the “culture” being studied may be a segment of a population that shares a set of common characteristics or goals.

Some of the methods associated with ethnographic research are: participant observation, in-depth interviews, participant diaries, informant debriefs, and context mapping. My presentation at UPA 2010 in Munich will focus on the application and adaptation of ethnographic research methods to the field of web design and usability, rather than a rigorous definition of anthropology research methods.

Copyright 2009, Paul Bryan, Usography Corporation (http://www.usography.com)

Linked In: http://www.linkedin.com/in/uxexperts

Uncategorized design research, design strategy, e-commerce, ethnographic research, ethnography, research methods, ux strategy

Users are not designers, but design without user input frequently misses the mark and suffers from poor usability and lack of adoption by users. Therefore, designers and engineers should give users a role in designing new or improved systems. One way to do that is to ask participants in research sessions to draw their concept of the ideal web page or application screen. You shouldn’t feed them answers that they then capture and write down, because that defeats the purpose. You can, however, ask them how they expect to do certain tasks they’ve already said they want to do on the site. In this way, you are prompting their recall without giving them biased or predetermined answers.

Conducting participatory design exercises is much easier than getting stakeholders to agree to the sessions in the first place. In participatory design exercises I’ve conducted, results showed a surprising consistency. Using the results of other research exercises I’ve described previously in this blog, I was able to pull the participants’ concepts together into a coherent screen design that emphasized the consensus elements. This doesn’t mean that we took the participants’ design consensus as our final solution, but it was compelling to the project sponsors, and our resulting design had substantial anchors to customer mental models that made it difficult for non-substantiated design “arguments” to pull us off track.

In the next post, I’ll give an example script for a participatory design exercise for a resort user experience.

Copyright 2009, Paul Bryan, Usography Corporation (http://www.usography.com)

Linked In: http://www.linkedin.com/in/uxexperts

Uncategorized customer interviews, e-commerce, e-commerce design strategy, participatory design, qualitative research

A LinkedIn question got me thinking this morning about m-commerce, and where the strategic focus should be. I think the future of m-commerce in terms of business strategy involves establishing a credible social voice relative to a given category or product/service domain.

M-commerce offers a tremendous advantage to the consumer who is in any given retail context and can find best options instantly in terms of product selection, pricing, brand, service, repair records, availability, etc. If a product or service provider wants to speak to that audience of one (a million times a day) it will require an established voice at the point of inquiry (since any location can be a point of sale).

The amount of customer-generated content related to any given product is increasing to the point where vendors are losing the verbal platform they once dominated. Fellow consumers are the virtual associates who, for the most part, have no vested interest other than to share what they know about a given product, service, or vendor. To present and manage that voice in context of your own offering gives you a seat at the table.

With respect to presenting an m-commerce offering that consumers can consult anywhere, that is a very basic extension of e-commerce that all e-retailers probably have in the works. The differentiator is being present when consumers are in a given shopping or product discussion context and are seeking their best options.

Copyright 2009, Paul Bryan, Usography Corporation (http://www.usography.com)

Linked In: http://www.linkedin.com/in/uxexperts

Uncategorized business strategy, e-commerce, m-commerce

Another exercise that helps discover attributes that pull retailers into the consideration set for a given product type involves filling out a table with a list of the attributes most likely to differentiate retailers in that category and ask customers to rate several retailers on these attributes. As a simple example, you could ask customers to fill out an evaluation of retailer attributes using the following worksheet. (SA: Strongly agree; A: Agree; N: Neutral; D: Disagree; SD: Strongly disagree)

• Convenient
• Simple
• Cost saving
• Easy to find products/services
• Easy to check out
• Easy to get details
• Provides help when needed
• Has the products or services I’m looking for
• Great customer service
• Great online experience

Based on these ratings, the user experience design strategy should include guidance about how to achieve differentiation for a given user type using design components. Most retailers have much more detailed quantitative data about differentiators, but they are usually aggregated such that its difficult to target these findings to a given type of customer or persona. This kind of module helps bridge that gap, although a follow-up quantitative exercise may be needed to drive out more comprehensive findings that are representative or validated to the extent needed to guide user experience design of a high-traffic web site.

Copyright 2009, Paul Bryan, Usography Corporation (http://www.usography.com)

Linked In: http://www.linkedin.com/in/uxexperts

Uncategorized customer interviews, e-commerce, e-retail, selection set, user research

Lisa Pecunia posted an entry about User Ratings and their credibility to her blog (http://making.grouvia.com/2009/10/22/ratings-are-overrated/#comment-25) and to the User Experience group of Linked In. I think she has a point that is worth some reflection. As an overall system, I think that the ratings disparity will correct itself. Here’s why.

Two complex variables implicit in the ratings system are Trust and Authenticity. They are not independent. Trust is a characteristic of the people viewing the ratings. Authenticity is a characteristic of the people responsible for the ratings.

In user research sessions, I have met some people who tend to trust a source until it is proven untrustworthy. I have met others tend to distrust a source until it is proven trustworthy, particularly when the source has a vested interest in a positive rating (ok, I’m in the latter group). Both groups will lower their trust for a given source when they have an experience that belies that trust. For example, you trusted the rating that your VA had received in the rating system, and were disappointed with the results you experienced. There could be many reasons for this disparity. But in the end, you put less trust in that system because it had betrayed your initial trust level. You may try to correct that system by assigning a slightly lower rating, but in the future you will definitely have less trust in that system’s ratings.

On the other side of the ratings system, the people supplying the ratings practice a certain level of authenticity (the quality or condition of being trustworthy or genuine). Some companies supply the ratings as they are submitted. Amazon doesn’t need to care if people don’t like the book. They can find another one. An online shoe retailer, on the other hand, has to care if somebody says a certain shoe brand is crap. That may affect a lot of purchases, particularly if the customer repeats this assertion in a number of places online. The shoe retailer has to decide to what degree they should “adjust” the ratings by omitting negative outliers. Rating by rating, they are building the perceptions of their authenticity.

The authenticity of a given source of ratings is not known until an experience reveals it. You had expected a degree of authenticity from the VA ratings, because a lack of authenticity defeats the purpose of the system. The people supplying the ratings were (apparently) not authentic. Their lack of authenticity was discovered through experience and you adjusted your trust level. Others probably have had the same experience. Together, a large group is lowering its trust, and the perception of authenticity is decreasing overall.

Companies used to be able to control the conversation that impacted the perception of authenticity, thus engendering trust by spending large amounts of advertising dollars. But not anymore. That conversation is out of their hands. In aggregate people will continually adjust their trust level, and communicate those adjustments to others, which will cause harm to the reputation of authenticity of a given source. In user research sessions I have found that lack of trust is one of the most difficult barriers to overcome in a transaction-based web site, so a decrease in aggregate trust will be felt in the bottom line.

This bottom line impact will take a while to surface. It will eventually be recognized as a problem by the companies that lack authenticity in their ratings. But by then it will be as difficult to recover trust in the ratings system as it is in every other context.

Copyright 2009, Paul Bryan, Usography Corporation (http://www.usography.com)

Linked In: http://www.linkedin.com/in/uxexperts

Copyright 2009, Paul Bryan, Usography Corporation (http://www.usography.com)

Linked In: http://www.linkedin.com/in/uxexperts

Uncategorized authenticity, design strategy, e-commerce, trust, user experience, user ratings

To understand the competitive set of each participant, ask them to list the competitive sources of products or information related to the topic you are researching. Ask them to describe:

• The relative value of each source
• Likes and dislikes of each source
• Successful and unsuccessful interactions with competitive sources
• Experience using similar or competitive web sites
• Rating of your site vs. competitive sites based on specific criteria

As a result of the competitive set module, you should have obtained:

• List of competitive sites
• Positive and negative aspects of competition
• Ratings to compare across participants
• Competitive benchmark in terms of design and/or functionality
• Opportunities to reach parity or superiority

Sample script:

• When did you first start planning your last stay in a vacation resort?
• When you started planning, which companies were you considering staying with?
• Why did you include each of these?
• Which companies did you leave out of this list? Why?
• Are there any companies that you wish you would have included in this process? If yes, which one(s)?
• Are there any companies you wish you would have left out of this process? If yes, which one(s)?
• Which web sites did you visit?
• Which web sites did you know about but not visit? Why?

Copyright 2009, Paul Bryan, Usography Corporation (http://www.usography.com)

Linked In: http://www.linkedin.com/in/uxexperts

Uncategorized customer interviews, e-commerce, e-retail design strategy, selection set, user research