Boxes And Arrows : The Design Behind the Design

Methodology, a tool, AND a creative parallel in one article? I liked your last article, too, so this idea definitely gets my vote.

I’m a big fan of Andrea’s earlier two articles. I think this new one would be great.

This is interesting. Is a persona really a persona if it’s only based on web analytic data? I would think it doesn’t truly become a persona until you bring in the other data you collected from interviews, surveys and testing. I’d be curious to read more about your thoughts on this.

In the past, I’ve created what I call an “Assumptions-Based Persona”. I like to do this with clients that have a hard time understanding the value of user research. After I get the buy-in we put together personas based off of their assumptions and other “data” they may have. After conducting the research we create new/real personas and compare them with the ones based on the assumptions. It’s usually pretty interesting for the client to see the difference and realize what they did/didn’t know about their users.

In high pressure, high constraint environments personas are a key tool to bridge the gap between user requirements and management decisions. Integrating real user data to inform the development of these (often)mythical beasts has to be a good thing, doesn’t it?

Right on. Either do a two-part article, one focused on Google Analytics and one on “other sources,” or cover both in one article. Similar to Kyle, above, I talk about “Evidence-Based IA,” data-based personas being one arrow in the quiver as it were. In training and consulting I encourage clients to gather various sources of user data on which to base personas. For public sites – market research, competitive analysis, customer service data (call stats, knowledge base), usability testing, etc. For intranets, usability testing plus personnel demographics (M/F, age, degrees, job roles, tenure at job) and IT demographics (computing environment, platform, browser, security roles, etc.). Also sometimes you can segment employees according to whether they support customers (engineering, sales, cust. supp, service providers) or support the organization (IT, HR, desktop supp, etc.)

I think this article would not only be informative for the B&A community but also for key product stakeholders, too. I find in an enterprise setting that this first phase of any project, the definition and documentation of the project which includes, IMO, this persona building step, is often the most difficult to sell to the C-level. Instead, most companies think they know their constituents better than anyone so why waste time and money on this part of project, just pull out the same old tired demo information and get started on the app. I’d like to read this article.

Thanks for the feedback, folks – I can only hope the “real thing” lives up to the hype! My perspective on this practice is to give a jumping-off point for developing personas using available user data, as opposed to solely from assumption or imagination. For more and more people, Google Analytics is one of few sources of user data, and while it can only get you started, it can lend structure and credibility, much like Elizabeth’s “Evidence-Based IA”. I’d love to see Elizabeth write an article or two about this topic – it sounds great!