Elastic lists - a great interface for faceted browsing

Have a look at this neato interface for 'faceted browsing' - Elastic lists

And if you want some Friday afternoon mind bending...

Card Sorts

Some quick resources to get the low down on doing a Card Sort. Remember it is as easy as it seems!

• www.boxesandarrows.com/view/card_sorting_a_definitive_guide
• www.usability.gov/design/cardsort.html
• www.markboulton.co.uk/articles/detail/card_sorting_part_1

This article offers a critique of some of the pitfalls with card sorts

• www.uxmatters.com/mt/archives/2008/10/extending-card-sorting-techniques-to-inform-the-design-of-web-site-hierarchies.php

For me what’s interesting that card sorts are single tool used in part of a larger design process. Also interesting are the alternative activities esp. the findablity testing. These might be a better fit in situation where IA is constrained by other factors such as dealing with the inevitable politics of ‘my business area must have spot on the homepage’ or the existing IA is heavily entrenched.

What to do with search logs

This is a great on article covering how you should be monitoring search logs – Interpreting Your Search Activity Reports

Also like that it points out the connections between search logs and more general usage logs.

How much should an organisation invest improving the intranet search?

Last week I began grappling with the following question:

“How much should the organisation invest improving the intranet search and will this be recouped in timed saved finding information on the internal web channel?”

There is general agreement that poor search cost organisations money in lost time. Quantifying this is tends to be based around simplistic extrapolation. For example: X Staff spending Y seconds each on searching for information equals ten zillion dollars in lost productivity. Therefore we should invest money in a new search application. Sort of fails to discuss the complexity of finding information or recognise that there are plenty of possible approaches in addition to just focusing on improving the search application.

As I ponder this within the context of where I work some thoughts have begun to emerge including:

• Quantifying the performance of an internal search engine is difficult and will probably be based around fuzzy qualities measures


• Without these it could be difficult to establish a benchmark in which to measure the effectiveness of various enhancements or optimisations


• Building a search based around lots of high quality metadata is resource intensive. It could end up costing the organisation more then it returns in productivity improvements.


• Is it more cost effective to rely on the built in power of a good search application and put the resources into improving content, fixing the IA, archiving out of date pages etc?

I’ve found a couple of interesting articles and I'm sure I’ll be posting more on this topic.

• Metadata Schmetadata, Relevance and Reality


• How to Measure Findability in Enterprise Search Solutions