Cayley Vos, Owner
Netpaths, Los Angeles Search Engine Optimization Company
We have seen dramatic increase in clicks through to long tail searches suggested by Google. It also allows other websites to capitalize on brand searches. We ranked for a keyword ‘brand discount’. An example search would be “Nike Discount” and this search greatly helped the smaller retailer with a 25% traffic increase.
Tom Critchlow, Head of Search
Distilled, an Internet Marketing Company in London
I’ve only done some testing around this subject so don’t have definitive answers but I’m a strong believer that the search suggest options are generated from Markov-chain type processes. Obviously on top of that if there is large search volume Google wants to add value by using CTR, volume of mentions etc etc.
But Google also wants to provide search suggest results for long tail queries and I believe they do this by document analysis, Markov-chaining and machine learning because I’ve seen numerous examples of search results where for example there is a “brand x sucks” search suggest but where this phrase appears nowhere online and is also not searched for therefore I believe this hints that Google are creating this from somewhere by knowing that “brand x” refers to a brand and that “brand x sucks” is a common search format (obviously this is a very basic example but demonstrates the concept). Remember that Google drove a car through a city for 100,000 miles without a driver. They know a thing or two about machine learning.
Ian Lurie, President
Conversation Marketing, CEO, Portent
I think trending is also really, really important. If a particular set of phrases around a topic are trending sharply, those phrases are more likely to end up in search suggest.
Search suggest is influenced primarily by click-through and trends. If increasing numbers of people are searching on phrases and clicking through at a steady rate, and those phrases are easily clustered around a topic, you can bet they’ll end up in Search Suggest.
Rand Fishkin, CEO
I suspect the formula for it is both more and less complex than we’d suspect – less complex in that the quantity of signals may be just a few (maybe amount of use/appearance on the web, search volume and usage/CTR) and more complex, e.g. machine learning against a sample set of queries and suggestions to analyze the usefulness/effectiveness of the algorithm producing them (and whether they’re working well for users).
Search suggest is likely one of Google’s best methods for helping those stuck on what to query and reducing the uncertainty of intent. I suspect it also positively influences number of searches per searcher, particularly the number of searches where ads appear.
Aaron Wall, SEOBook Founder
In my opinion, Google autocomplete predictions mainly come down to search volume. The more a phrase is searched, the more likely it will be to appear in the suggestions.
Tim Eschenauer, SEO/SEM Strategist
Austin & Williams, an Advertising Agency
My feeling is that Google Suggests terms that have high search volumes and perhaps are competitive on the PPC space. Google knows many searchers are influenced by what they suggest at least at the beginning stages of their search. You’d think they’d at least try to lead them to the paid results.
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About the Author
Steve Wiideman has been practicing the crafts of Search Engine Optimization and Search Engine Marketing for nearly a decade, working for corporations on paid, organic, local, and product search. He has authored several popular eBooks and is acclaimed for his ranking in Google for the term “SEO Expert”. Wiideman hosts weekly workshops at Creative Search Strategies and continues to work at an SEO Consultant for a handful of popular brands.