Who Needs Sexy When You're Rich? SEO and Keyword Diversity

Ian Lurie
By Ian Lurie / June 1 2007

One of my clients is having his best year yet. He also just lost his #1 position for a really important keyphrase.

keywords
How can he have the former in spite of the latter? Diversity. He’s got top 5 rankings for dozens of phrases. While the Big Money phrase gets hundreds of searches per day, and slipping from #1 to #3 is depressing, he also has top-3 position for hundreds of phrases that get 1 or 2 searches per day.

And those longer, better targeted phrases generate better conversion rates.

That’s why I prattle endlessly about making your site crawlable, aiming for semantic spaces instead of phrases, blah blah blah. Trust me – ranking #3 for every phrase that includes “custom tableware” may not be as sexy as being #1 for “silverware”, but who needs sexy when you’re rich?

Ian Lurie

Ian Lurie

 Founder
Founder

Ian Lurie is founder of Portent. He's been a digital marketer since the days of AOL and Compuserve (25 years, if you're counting). Ian's recorded training for Lynda.com, writes regularly for the Portent Blog and has been published on AllThingsD, Smashing Magazine, and TechCrunch. Ian speaks at conferences around the world, including SearchLove, MozCon, Seattle Interactive Conference and ad:Tech. He has published several books about business and marketing: One Trick Ponies Get Shot, available on Kindle, The Web Marketing All-In-One Desk Reference for Dummies, and Conversation Marketing. Ian is now an independent consultant and continues to work with the Portent team- training the agency group on all things digital. You can find him at www.ianlurie.com

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Comments

  2. Hi Adam,
    Search engines are increasingly good at semantic analysis. For example, they might understand that ‘car’ and ‘auto’ often represent the same thing.
    ‘Semantic space’ is a topic area represented by many phrases but one concept. So ‘Schwinn’ might be a keyword, but ‘bicycle’ might be the semantic space that ‘Schwinn’ occupies.
    Hope this helps,
    Ian

  3. This whole concept is called LSI: latente semantic indexing. For instance, if you want to find out what is releated to the term Schwinn Roadster 12 Inch Trike, you take each word and search it into Google using the symbol ~. In other words, you go to Google and search for ~Schwinn, ~Roadster, ~inch, ~trike. The bolded keywords that appear in the SERPs are semantically related.

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