Thursday, April 26, 2007

Data Driven Design: Using Web Analytics to Improve Information Architecture / Andrea Wiggins

Saturday, March 24, 2007

Web analytics= think WebTrends although there are other tools out there.

Web analytics can be used to:
  • quantify user experience audits
  • identify key performance indicators
  • compare over time with annual audits

Limitations:
Most tools are not designed to capture Rich Internet Applications (RIA); user may stay on one "page" while interacting with content.

Spiders ruin user data

  • block out with robots.txt—prevent from looking at logs
  • can also identify spiders by looking at speed of visits from single user

Types of Data:

Ratio of new to returning visitors

  • think about context
  • track over time and track with cross-channel marketing
  • consider the effect of timeouts

Median visit length

  • is closer to reality than an average visit length
  • can indicate depth and breadth of visit—are they digging deep or are they hopping around?

Clicktru rates for clickable graphics--requires additional programming (we've done this for our Featured Connections).

Response time--be sure to check at peak load time

Server errors

  • Monitor 500 server errors, which is where our server has the problem
  • Try to identify how the user got to the 404 server errors
  • Combined, hits to server errors should be < .5%

Action items:

  • Look at those dang 404 errors that show up in WebTrends more closely. Can we track where they are coming from?
  • Look at Crazy Egg analytics tool
  • Look at “leakage points”—where did users bail out of the website. Do they make sense?

Links for More Info:

Sunday, April 15, 2007

Using Search Analytics to Diagnose What’s Ailing Your IA / Rich Wiggins and Louis Rosenfeld

Saturday, March 24, 2007

Wiggins’ emphasis was best bets within search results. Rosenfeld spoke more generally about identifying problems from search logs.

Practicalities:

  • Zipf curve (long tail/short head) applies to search log—many users have unique needs
  • Look at top searches, and then dip down into the unique ones. Don’t treat all the searches as equal. Could look at top 50% of all searches, for instance.
  • Consider seasonality (by season, day, even hour). Some needs are higher by season. Could promote that content accordingly.
  • Capture search logs to SQL database to then process. Can dump relevant fields into Excel and then evaluate.
  • Use IP with time stamp to surmise single user.

Ways to Use Search Logs:

  • Look at most common unique queries; are there patterns?
  • Test common queries to see what results look like.
  • Look for null results.
  • Look for too large results.
  • Can grow content to satisfy searches (ex: Netflix did this in response to “yoga” searches)
  • Look at improving search entry, results, and/or algorithm
  • Combine with field study (ex: L.L.Bean saw users starting with catalog, then taking SKU to web—answered why users were searching for SKU)
  • Fixing a trend seen in long tail could help many.
  • Look for time variations; respond by positioning Best Bets or guides seasonally.
  • Add tools for results page (i.e. options for broadening/narrowing)—this moves advanced search options from search page to results page
  • Best bets as not the final answer; still should monkey with relevance ranking. (ex: rank company names higher if that’s what users search)
  • Consider a best bets index rather than/in addition to a site index. See MSU A-Z index as example of using common queries as a best bets index. Site index uis difficult to build. Do you make it comprehensive? Selective?
  • Look for the page the user is searching from to identify failure points.
  • Look at top pages found through search; how can these be easier to find in navigation?
  • When cleaning up site, start with what people want—rather than complete evaluation of content.
  • Look at “tone” in search (technical or popular; specificity; acronyms; plural) to help create labels.
  • Cluster queries to see parent/childs; look for possible metadata fields and contents for those.
  • Sample the long tail (tends to be more research oriented)
  • Compare spikes (proper names, companies) and compare with editorial content; identify future stories. (ex: Financial Times has done this)
Links for More Info:

Wednesday, April 11, 2007

The Lost Art of Productively Losing Control / Joshua Prince-Ramus

Saturday, March 24, 2007

This was the opening keynote.


Architect Prince-Ramus, spoke about a handful of projects on which he worked and, despite fairly radical end results, were designed for use rather than purely aesthetic. The expectation of the talk was that information architects would find parallels between information architecture and building architecture.

Project 1: Seattle Public LibraryResponded to challenge to create a space which would fulfill the varied expectations for a modern public library. Among the recognized conflicts is the growth of new technologies, on top of the existing, long-lived book technology. In parallel are increased expectations for an urban public library as community space. Both of these progressions are illustrated with the following graphs. In response, the architect attempted to designate a percentage to the “stable spaces” (book stacks, staff spaces, etc) and not allow the social spaces areas to encroach. In other words, both (or all) roles of the library…and all formats deserve a space.

One of the highlights of this building is that the book stacks are in one continuous spiral—much like a parking garage—within the building. This design provides a logical arrangement while also creating serendipity (users flow from one section to the next).

  • There is no down escalator, in fact, to encourage the user to browse down the stacks.
  • Call numbers are embedded in the floor at the end of each range.
  • Elevator buttons which normally indicate floor are instead labeled with call numbers.

Possible Application to L&ET:

  • Can make the same argument about stable versus unstable spaces in our environment? Our spaces seem to be in flux and our “stable” spaces (staffing, in particular) have encroached on social spaces, rather than the other way around.
  • How do we label our elevator buttons in the stacks? In public areas?
  • Embedded call numbers they way they did it don’t make sense for us (it looked somewhat permanent for them). I wonder about carpet squares with exchangable call numbers or an electronic display. Would the gain in navigation be worth the cost?

Project 2: CalTech Pasadena Information Sciences building
One of the early steps in this project was to chart out the different functions of the building spaces with colors—first, on a floor map and then stacked up into a bar graph. The end result looked much like a disk defrag graphic, and the conclusions may be somewhat similar.

In this building, as across the entire campus, the spaces were heavily intertwined. His point was that with everything all mixed up, users are less likely to visit that building because they can’t figure it out. Instead, they stay in a building that they’ve already learned, even though that building may be just as fragmented.

To clean it all up, the architect worked with the client to create clusters (research, factory, undergrads centers, Olympus were his labels). Like things were treated in like ways. For instance, staff office spaces ended up in a ring around the facility.

Possible Application to L&ET:

  • He promoted fishbowl conference rooms which spark conversation, even from outside a team, and promote innovation. The poster sessions offered a similar idea from AOL—not fishbowl, though.
  • The idea of defragging a space makes sense to me. Put like functions together and it seems like you’d get more efficiency.
  • I think we’ve been thinking too inside the box about staff work spaces. Should we start looking at vertical space like we did with the double-decker carrels?
  • An interesting observation from the architect…many architects (and the information architects I asked, too) work in large spaces where collaboration is easier. In fact, conversations from co-workers are seen less as distraction and more as a staying involved. He found that academics viewed collaborative space more as private offices with doors that could be opened.
  • Are too committed to the traditional work day. Do we have staff that would prefer to work different schedules and share spaces?

Links for more info: