How Many Facets is Too Many?

Recently on the Taxonomy Community of Practice, a member asked the following question on faceted taxonomy design:

“I’m researching about Faceted Navigation and Information Retrieval. I’ve been looking over the Internet for some articles/books/white papers about which is the best number of facets to use on a classification.”

Interesting question, especially given the popularity of faceted search and taxonomy. The community discussed the topic, and a a few answers were provided by members. Continue reading

Faceted Search Design – Ordering Facets

I’ve been lurking on the IAI’s mailing list for some time now, but recently someone posted a question that I just couldn’t resist answering:

We are getting ready to roll out a new faceted search option and I’ve been asked to make recommendations regarding the order of the facets and their characteristics.  I am having a hard time finding specific information about standards or best practices.  I repeatedly come across Stephanie Lemieux’s recent article, Designing for Faceted Search, stating that both facets and values should be based on importance.  While this is great, can anyone point me toward supporting information or is this something that is just understood?  Are there general guidelines for when to list characteristics alphabetically versus when to list them in descending order?

Ok, good call on the poster’s part – I had been vague in my article (Designing for Faceted Search, originally published in KM World), mainly because I had a broad audience and a word count limit. But I supposed that I should clarify a bit…  Here’s my response: Continue reading

Can’t it just be like Google?

I often get frustrated by those who think Google is the greatest search engine that ever parsed. Don’t get me wrong – I like Google, I use Google, I employ it as a verb. But if I hit the search button and get wonky results, I recognize that they are wonky and am not afraid to blame Google. (Full disclosure: I have a library science background which I’d like to think has made me into a pretty good searcher, so I will usually try a few different queries before I point the finger at the machine.)

On most of our consulting engagements, at least one person will say “I want our search to be more like Google.” I have a few problems with this kind of statement. Partly it’s that most folks aren’t terribly critical when it comes to evaluating the relevance of Google results. It’s what we know, it’s what we’re used to. We don’t mind that Wikipedia is almost always the first result on any query – many might find that a “feature”.  We’re generally happy to take whatever shows up in those top 10 results and roll with it regardless of what it is, mostly because we can’t know everything that is out there so we trust Google to filter it for us. We satisfice (yes, it’s Wikipedia, joke intended)

Take these same folks and plunk them in front of their enterprise search and ask whether the top ten results are usually “good enough”… Most will answer no. Why? Because we have a better idea of what information is out there and what would make for a good result. Continue reading

Taxonomy & SEO – Integrating Perspectives

My last few blog posts on keyword research tips have generated interest from our readers regarding the relationship between the SEO task of keyword research and taxonomy. The purpose of today’s post is to examine the intersection between the two and offer a little advice for reconciling the internal perspective of taxonomy with external internet search.

We can harmonize these perspectives using a data-driven approach to understand the “mental model” of the external searcher.

Taxonomies Drive Information Organization

The purpose of a taxonomy is to define consistent organizing principles for information based on language people use to achieve their goals. (Whether finding a product, executing a task, solving a problem, etc)

Taxonomy terms can standard industry vocabularies, language unique to the organization or even general marketing speak.

Regardless of the context, taxonomies define the preferred terminology along with its synonyms, word stems, variants and relationships to other concepts. These classification schemes are intended to help users locate specifc documents and content as they go about their business.

Continue reading

Tips for Conducting Keyword Research – Part 2

In my last post I discussed a process for putting together a broad list of keywords intended to act as the starting point for our keyword research. The purpose of this step was to give us the ability to cast as wide a net as possible in an effort to uncover as much of the language being used by our potential customers when searching for our content, products and/or services online. Doing so not only gives us the opportunity to wisely target the correct keywords, but also lets us craft our content in such a way as to tap into as much into the long tail as possible.

To illustrate, I’ll use the following Top Content report from Google Analytics. As you can see this particular page, although targeted toward a specific set of keywords, generated traffic from an amazing 5,766 unique keyword combinations! This alone demonstrates the power of the long tail in driving significant amounts of traffic to your website.

Google Analytics Top Content Report

Google Analytics Top Content Report

Keep in mind that you don’t want to generate traffic just for traffic’s sake; you want these visitors to do something while on the site, whether it’s to buy your product, fill out a form or contact your company. Web analytics aside, now that we’ve done all the groundwork and assembled our master list of terms, we’re ready to tackle the research part of our keyword research. Continue reading

Good Facets Gone Bad

I recently met with a client who said “no one uses facets for searching…”  I expressed surprise at this comment and probed a bit as to why they thought so.  We opened their home page and I soon surmised why.  The facets they had did not seem to be very useful.  No one had tested them and I had not yet spent any time in analysis, but at first glance, they did not provide context for their content.  I recall one facet was “content type” and contained terms like “pdf”, “doc” and “jpg”.  There were also ambiguous terms like “article”, “white paper” and “research”.  I am not necessarily saying these were not useful, but I did not understand the difference between “white paper” and “research”.  (Perhaps a frequent user would).

The point here is that faceted search is incredibly powerful but only if the facets make sense to users and the terms are clear, concise and meaningful.  Terms have to help users locate what they want and not frustrate them in the process. 

In support of that goal, I wanted to point out some examples of bad facets – the facets that don’t help anyone and that sully the good name of faceted search. 

Here is an example from the Verizon Wireless site:  "Wireless" as a facet on the wireless site is not terribly useful

None of these terms are really useful – I have a business, it is a coporation, I work from my residence and yes, my cell phone is wireless. 

Do you have some good examples of bad facets?  I’d love to hear about them.  Send a note to me: seth@earley.com and I’ll post them here.

The Popularity Contest: Taxonomy Development in the Petabyte Era

Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.” (1)

Recently Chris Anderson wrote an article for Wired magazine called the The End of Theory. The thesis of the article in a nutshell is that the impending petabyte era of data storage signals the end of the traditional scientific method of discovery. No longer are we bound to the outdated model of observation, hypothesis and measurement. Computers (developed by Google & IBM) “can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.”

Continue reading