Here's a blogpost by Gretchen Anderson called Making use of user research, on the role of ethnographic field research as part of user research, drawing insights from observations of software users. Some excerpts ... 

"User research can be roughly broken down into two types: usability testing and ethnographic field research. Many people are already familiar with usability testing, and many companies make use of it during development. However, ethnographic field research can yield valuable results for improving products that can't be easily measured by usability testing......"

"Beginning a product development cycle with ethnographic research helps generate ideas for the product offering. It also helps product developers understand users' "mental model" of what they want to achieve so that the software can better reflect how people actually work."

The portion that resonated most with me - we have been following just this practice on a couple of ethnographic studies recently. 

"Ethnographic research can point out opportunities to serve user needs that are currently unmet, which can help you keep or create a competitive edge. Observing real customers using an actual product can provide information about the overall product offering and how it can be extended. These observations will not only reveal problem areas to product designers, but will often provide clues about how problems can be addressed.  Things that are especially effective to observe:

- Blind spots: Are features going unused? Why? Are people unaware of the tool, or do they just not need it?

- Toolboxes: What tools do people use frequently? How do people think about them? How are they being used? What frequent or repetitive activities are people performing that might be better served by creating a special tool?

- Software crutches: People in the real world will develop ways to make up for shortcomings in software in order to achieve their goals. Look for places where people leave your product and turn to Post-Its, printouts, or other solutions to get the job done.

- Missteps: Users who perform tasks "incorrectly" are a great source of constructive data. Look for where people go when they make mistakes and whyóit may be a good hint at how to better organize the application.

- Audio cues: Many people, especially while being observed, will provide a running soundtrack of what they are thinking while using software. This is invaluable when trying to understand how a person relates to the product. Listen for frustration, mnemonic chants ("F4, shift, then enter. . . "), and indecision ("Do I want to revert to temp.bak?").

- Goals: Operating software is not the end goal for any user. Pay attention to what users are trying to achieve. Is it an object (creating a file)? Or a process (telling Mr. Smith the status of his account)?"

[thanks James at Column Two for the link.]

3:31:48 PM    comment []  trackback []

Michael Higgins and Vikram Arumilli have interesting thoughts on popularity of blogs. Michael defines popularity in a neat way :

"However, I would define popularity in a slightly different way than just, "I like to read his/her blog." I would define popularity as, "I really like that person."

while Vikram does an analysis of a few Indian blogs using Google PageRanks as a measure to define popularity.

It was nice to learn that my blog has a PageRank of 7 - I remember when I started blogging, I used to watch it.  But haven't for months.  These posts evoked questions in my mind on what is 'popularity'. Rajesh Jain and I have a Google PageRank of 7 -  and we don't really attract the volumes of comments that so many other Indian blogs do and yet have higher ranks than those that do. Neither am I linked to by as many Indian blogs but some of the 'popular' blogs in the world link to posts I write, or my blog - would that not skew this measure of popularity? Where is the 'wisdom of crowds' :)?

I also revisited Blogstreet - while my blog is ranked 513 in the world rankings, Blogstreet India has me much lower at 45 than many Indian blogs with lower Google PageRanks than mine. Then there is Technorati and Bloglines subscriptions and Alexa and TTLB and Popdex and Daypop.  Robin Good has a neat list of measuring of indicators and tools that measure popularity, authority and credibility.  

It is all a little confusing.  I enjoy using some of these to benchmark and track my own blogging patterns and readership. And for a few blogs that I really enjoy.  For instance, I have no interest in what my ranking on Technorati is, but I do visit it daily to see who is linking to me and how they might have progressed a thought. Yet, I'm not so happy when these get transformed into lists, ratings and rankings. Are you merely well-known, or well-read?  

How would you define and measure popularity in the blogworld?  Can there be a robust quantitative measure?  Does the blog software you use matter? Are links and comments and page visits and clicks good measures?  How is stickiness measured?  

I'd rather look at more qualitative measures (disclaimer : I am a practitioner of qualitative research) like relevance, integrity and credibility when you engage readers in your areas of interest, empathy generated, stretch in teasing boundaries, intimacy with your audience. A combination of respect and amicability.  There was a good discussion about some of these issues at the opening session at BlogHer.

UPDATE :

Wow.  Mary Hodder has done some very solid thinking on a new open source algorithm that balances the weighted value of social gestures against large data sets in a post called Link Love Lost or How Social Gestures within Topic Groups are More Interesting Than Link Counts   

".... For many bloggers the relevant sphere of influence is not overall popularity, as those indexes express. It's influence and connection within a community. And the relevant measure of connection isn't the number of connections -- it's the depth and impact of those connections. This is about celebrating the niche, and measuring engagement over time."

".... Part of what we want is a rich user generated ontology resulting in topic groups that is constantly adjusting to find what's delightful, useful, interesting across blogs. And a more complex metric for understanding those topic groups and individual users as they blog memes and interact with each other, with some context around those bloggers, would help quite a bit."

More Dimensions :

danah boyd adds another dimension by examining patterns in the network structure of blogs and linking behaviour.  From her post, the biases of links :

"After reminding folks at Blogher that there are gender differences in networking habits, i decided to do some investigation into the network structures of blogs. Kevin Marks of Technorati kindly gave me a random sample of 500 blogs to play with. I began coding them based on gender (which is surprisingly easy to do given the amount of personal information people put about themselves) and looking for patterns in links and blogrolls.

I decided to do the same for non-group blogs in the Technorati Top 100. I hadn't looked at the Top 100 in a while and was floored to realize that most of those blogs are group blogs and/or professional blogs (with "editors" and clear financial backing). Most are covered in advertisements and other things meant to make them money. It's very clear that their creators have worked hard to reach many eyes (for fame, power or money?)."

And Stowe Boyd says :

"I personally want something completely different, as I outlined earlier today in my RankOut piece (see Mary Hodder on The Paris Index, And Why RankOut Would Be Better): a means where everyone can generate their own top 100 list, or a whole bunch of lists, depending on the topic, the community of interest, or the purpose for rank ordering blogs."

3:11:31 PM    comment []  trackback []