Forum Moderators: Robert Charlton & goodroi
The more content you have and the bigger you as a business appear to be, the more you will climb the SERP ladder.
The more content you have and the bigger you as a business appear to be, the more you will climb the SERP ladder.i don't know. i am up against some pretty heavy hitters (my main site included) but i still manage to beat them for first page placement with 5 sites that each have less than 10 pages, next to zero content, less than 5 links, and iframes that keep viewers on a page for very long periods of time.
The more content you have and the bigger you as a business appear to be, the more you will climb the SERP ladder.
Search for a red widget however and you will see nothing but amazon, regardless of how fresh, unique or superior your product or content is.
The more content you have and the bigger you as a business appear to be, the more you will climb the SERP ladder. I think you all agree with this notion and there are more than enough examples to back it up.
[edited by: martinibuster at 1:06 pm (utc) on Apr 23, 2015]
you are given a free ride
... and to help determine what users in aggregate want to see in the SERPs.
Machines are quality raters now. Google and Bing do not depend on human quality raters. Did you know that? Human quality raters make conflicting judgments. Machines do not. Human quality raters cannot scale. Machines can scale.
Are you saying it's not working that way (roughly) any more?
...you look for signals that recreate that same intuition, that same experience that you have as an engineer and that users have....we actually came up with a classifier to say, okay, IRS or Wikipedia or New York Times is over on this side, and the low-quality sites are over on this side. And you can really see mathematical reasons...
A new trend has recently arisen in document retrieval, particularly in web search, that is, to employ machine learning techniques to automatically construct the ranking model... In web search engines, a large amount of search log data, such as click through data, is accumulated. This makes it possible to derive training data from search log data and automatically create the ranking model. In fact, learning to rank has become one of the key technologies for modern web search.
Those who continue to promote the idea that Google prefers brands do a disservice to themselves and to those who listen to them
For example, there are many documented cases of companies with connections getting manual penalties lifted...
That's a rhetorical trick.
I'll give you the benefit of the doubt that you're simply repeating what someone else wrote.
doesn't happen with SMB websites, ever.
It happens to SMBs who hire Virante, InternetMarketingNinjas, and BruceClay...
Two different topics.
I wrote an article in SEMPost that completely demolishes the idea.
To me, it does nothing to change the idea that he feels that brands are how you "sort out the cesspool". How can you read that in any way other than "brands == quality"?
...this is still relevant to my notion of "artifact of machine learning" . It`s not that Google wants brand bias - its the way machine learning interacts with certain sites to create one, unwillingly.
We show that incorporating user behavior data can significantly improve ordering of top results in real web search setting. We examine alternatives for incorporating feedback into the ranking process and explore the contributions of user feedback compared to other common web search features. We report results of a large scale evaluation over 3,000 queries and 12 million user interactions with a popular web search engine. We show that incorporating implicit feedback can augment other features, improving the accuracy of a competitive web search ranking algorithms by as much as 31% relative to the original performance.
Machine learning is not about homogenizing the SERPs with brand type sites. To the contrary, it's the opposite.
but the machine learning algorithms kick in to measure user satisfaction and they will actually suggest dismantling ranking factors if they are leading to user dissatisfaction
What you see in the SERPs can be said to be what users have generally voted up the SERPs with their clicks.