Search Query Language vs. Search Query Intent

In conducting keyword research, it is important to determine the search query language as well as the search query intent of your online target market. Search query language encompasses every type of search query and reflects the query intent of the searcher; i.e. your prospective user.

One of David Ogilvy’s quotations speaks very well to the idea of focusing on search query language and utilizing it in your web site to answer search query intent:

“If you’re trying to persuade people to do something, or buy something, it seems to me you should use their language, the language in which they think.”

A quotation by John Ilhan identifies that in developing your offering, you need to answer the intent of your primary users, not provide them with information you think they might want:

“This may seem simple, but you need to give customers what they want, not what you think they want. And, if you do this, people will keep coming back.”

Encouraging the use of search query language to answer search query intent is often more of a battle than many might assume. We’ll illustrate this with a hypothetical example:

mrbeemer.jpg

He sells used cars, but will not have either term used on his website. Let’s think about a few terms he may be missing out on; ‘used BMW dealership Denver’, ‘luxury second hand cars Denver’, ‘used Audi car sales Denver’ and on and on. (Incidentally, most people looking for a car online, new or used, will refine their search with some geographical boundary).

For the sake of expedience, let’s just look at a few very generic terms and the number of times they were searched. We’ll use WordTracker for this portion of the illustration.

First we’ll look at ‘used car dealer’ query language based searches:

used-car-dealer1.jpg

Now let’s look at ‘preowned automobiles’ and ‘pre-owned automobiles’…

preowned-automobiles1.jpg

Hmm… puzzling that. What about just ‘preowned’ and ‘pre-owned’?

preowned-pre-owned1.jpg

Ah hah! So there we have ‘preowned cars’ at the top which outstrips our more focused ‘used car dealer’ from above 54 to 27. Let’s see what happens when we try for ‘preowned car dealer’…

preowned-car.jpg

*sigh*… OK.

And then just because we can, what happens if we just go for the generic ‘used cars’ and compare it to the 54 searches we got for ‘preowned cars’…

used-cars.jpg

Ahhh… and yet Mr. Beemer is not interested. His opinion on what people should be looking for when they want to find ‘his type of offering’ (which very few people know about as the rest of his marketing is just as oblivious) is outweighing the data. The result is that he is simply not going to rank for any term that might conceivably give him decent exposure in the SERPS apart from extremely focused searches by a very low volume of equally ‘carrot-up-the-ass’ type people.

Moving on now to Search Query Intent.

Andrei Broder identified three primary types of search query intent in his ‘A Taxonomy of Web Search’ including:

  • navigational intent
    • looking for a particular site which may result in further interaction;
      • e.g. ‘westjet’,
  • informational intent
    • broad investigative search requiring no further interaction;
      • e.g. ‘toddler weaning tips’, and
  • transactional intent
    • specific search to achieve a web-based objective that requires full website interaction;
      • e.g. ‘Yellow pages’.

During the initial stages of the web development project when SEO and IA (information architecture) get together to work on the site plan, part of the best practice approach is to sub-divide the identified and topically grouped search query language keywords into each of these primary search query intent categories. Not only will this facilitate a more logical and defined approach to the rest of the web project development team, it will make the site more appropriate and usable in terms of structure and navigation.

By categorizing your keyphrases in this manner and structuring the rest of your development based on these groupings, it is highly probable that both your relevant click through rates and conversions will also increase. The hypothesis behind this two-fold probability conjecture is based first on the fact that, by nature of the query language utilized, searchers will (hopefully) be presented with a page in the SERPS that speaks best to their actual intent. The more a page answers search query intent, the more likely the user is to click on it. The second part of the conjecture, the conversion, is yet more hypothetical in that it requires that the design, speed, content and imagery as well as path to conversion is clear, logical and easily facilitated.

The use of effective search query language in the onpage elements of your site structure will also facilitate the development of a high quality backlink network. The more usable and logical your site and the more your pages reflect both search query language and answer intent, the more likely you are to encourage self-propagating inlinks, and to gain requested backlinks especially for deeper pages.

While keyword research and the effective deciphering of intent is vital, neither will achieve very much in terms of conversions if the site design, content and usability are of poor quality.


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