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Google and Semantic Search Queries – A Suggestion to Google

Google and Semantic Search Queries – A Suggestion to Google

Google

A Problem that Google has created has been that it has forced companies to compete for a smallish range of keywords that have high search volumes.

This is problematic because the nuances of less common, but more specific, and high converting search phrases are lost and as such Google will produce lots of potential results for users that are not specific enough for their needs, which it then has to sort, as well as direct more irrelevant traffic to your site.

It also has made the job of ranking well for relevant users more difficult and pushed many smaller companies off the page even when they are the most relevant to more specific searches.

This isn’t just a problem for ‘organic’ SEO page rankings, but also paid search advertising, where Google’s AdWords deactivates targeted search queries that have small search volumes.

This makes it easier for them to run their servers on less power, (I read somewhere that Googles search technology uses half the electricity of it’s rivals) but it makes it harder for efficient targeting.

If you are a smaller business, the low search volumes on a few dozen search strings is not necessarily a problem, as long as these less common queries are likely to send relevant traffic and result in high conversions, so this approach is bad for this very sizeable sector. You might wish to compete on hundreds of similar combinations of longer keyword searches that are all more likely to be relevant to you, and so a small volume multiplied by hundreds of search possibilities that mean the same thing, actually could contribute a lot to your business.

It also is not intelligent from a search engine perspective. Allowing us to compete on ‘longer tail’ queries that are logically more relevant allows us to focus more effectively in tailoring performance to these users, and that means search results will be improved in their relevancy.

One solution I have thought of is to allow companies to rent the extra computing power required from Google so that if I were to plug in a thousand keyword combinations with low search volume into an Ad campaign, I can opt to be considered by Google when it interprets these longer or rarer queries that are more relevant to the business. The ‘rental fee’ is intended to cover the extra computing and memory requirements to process the increased volume of keyword combinations that would result. By renting in proportion to the number of these, I have an incentive to keep only those that convert and actually are relevant, following an experimental period.

Google is already however moving in this direction on its Organic Search. New algorithms (Hummingbird) have produced a stronger capacity to interpret longer tail queries, by adding a degree of intelligence into their interpretation at Googles end. Now we need them to integrate this with AdWords and the beauty of this is that we would hone the longer tail combinations automatically for them, learning which actually convert and are worth ‘renting’, so the combination of semantic search and increased bidding opportunities like this would be mutually enhancing. Given that much of the Google search-results page is now paid advertising, this will improve user experience as well.

Once longer-tail and semantic capabilities are developed, there will be an evolution by users to more complex search requests using formal rules of common spoken language, particularly with voice apps. This would in turn be expected to enhance the use of more human like search requests and encourage additional detail being entered into the search engine.

Another possibility is to change the bidding rules when a search query triggers both an organic and paid result on Page 1 of the SERP. If the organic result is nearer the bottom, or on page 2, then a rule could be invoked where we would increase bids on the paid ad so it was more likely to be at the top, increasing visibility. If the organic result ranks below a certain level, then we could reduce bids too. With semantic search aiming to improve relevancy of search results, this method would combine improved paid targeting with organic optimisation even if we can only bid on the more generic parts of a long tail query.

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