Following a suggestion at the Enterprise SEO session of PubCon, I’ve been using Wordle.net to create a tag cloud from inbound search terms.

Will this actually help me evangelize SEO to the rest of the team? This remains to be seen. Perhaps the real value comes in comparing clouds from multiple data points over time, to visualize the change.

Included here is a sample tag cloud, generated for an old personal blog, just to illustrate the result. Read on for tips and a special tool for Omniture users.

There are a couple tricks to using Wordle to graph search terms effectively:

1. Replace spaces in multi-term phrases with tilde characters (because Wordle expects space-delimited lists)
2. For enterprise use, divide term frequency by something between 2 and the minimum count represented in your sample, unless you really want to wait while Wordle’s browser-hosted Java applet tries to process your 3MB list of search terms
3. And maybe just strip all the branding terms entirely. (I would hope you’re getting a ton of search traffic for your domain name.)

The other trick for enterprise use is getting the search terms in the first place. It isn’t practical to process tens of millions of lines of CLF (webserver log) data frequently. If you have Omniture, try the “Natural Search Keywords Report;” you can request a CSV file of the top 500 items. The CSV data looks like this:

474.,,no on prop 8 petition,1010,0.3%
475.,,acne diet,374,0.1%
476.,,puffy under eyes,215,0.0%
477.,,mac izle,167,0.0%

(Note: contrived data.)

Converting this CSV data into something you can drop into Wordle is as easy as submitting it to this tool. This is a PHP script I put together to optionally strip branding terms, add tildes, expand term counts, and so on.

If you don’t use Omniture, and it is reasonable to process Apache log files directly, you can simply extract the search terms from the log files. This requires a bit of processing too, and I have a tool that as well. But it will have to wait for another day.