It seems that each link has a small to medium effect initially, but that effect increases over time. If you add a lot of links at once, you're not only going to see faster results, you're going to see much bigger results over time.
I think this is an interesting piece despite the small sample size. My experience and general theory is that Google doesn't assign full value to new links, in part because so many disappear within a month's time.
So perhaps a new link is work 10% in month one but then gains weight the longer it is alive until it's passing the full value.
# Pagination in Search Analytics. Now you can request more than 5000 rows of data for your site, without having to iterate through filters. Check out the "startRow" field documented in https://developers.google.com/webmaster-tools/v3/how-tos/search_analytics
# Crawl errors now include "linked from" information from the start. Check out urlCrawlErrorsSamples.list on https://developers.google.com/webmaster-tools/v3/urlcrawlerrorssamples
# Higher & clearer quotas. Like it so much that you just can't stop using it? https://developers.google.com/webmaster-tools/v3/limits
I'd love to see what you make with the API -- feel free to drop a link to your tool or to a screenshot here. Are there big ideas you'd like to build that aren't possible with the current API? Let us know here too!
While crawling is a wonderful thing, analysing your log files directly from the server allows you to see exactly what the search engines have experienced, over a period of time.
The Screaming Frog Log File Analyser provides an overview of key data from a log file, and allows you to dig deeper.
This looks like it could be quite useful. #seo
With this version we see some interesting changes. Most noticeably is the de-emphasis of supplementary content, surprising since previous versions have stressed the importance of the additional supplementary content there is on the page – or the negative impact that content has.
A nice breakdown by but you really must read the guidelines yourself. It's that important.
We’re here to say that the F-pattern is no more. The evolution of search engine results pages has caused a similar evolution in user behavior patterns. The strict F-pattern style we saw before is, quite frankly, outdated
I think this is a bit of a reach given the set of data used and the fact that the structure of a SERP can vary dramatically between queries. The F-Pattern is really part of our general style of reading and is broken when other elements on the page catch our attention during scanning.
Clearly the number of elements has gone up dramatically. But if you were to find the queries where that wasn't the case I think you'd likely see the F-Pattern emerge. Not only that but there are likely micro F-Patterns where we fixate on a SERP element and engage in F-Pattern like behavior there.
So, yes, because the SERP has changed structurally we don't see many traditional F-Patterns but I think it would be unwise to write off this behavior altogether.
This is a guide to surviving RankBrain. I created it, in part, because there’s an amazing amount of misinformation about RankBrain. And the truth is there is nothing you can do to optimize for RankBrain.
My latest post addresses the shiny-new thing syndrome overtaking the SEO industry.
A newly published Google patent application describes technology that would modify scoring and ranking of query results using biometric indicators of user satisfaction or negative engagement with a search result. In other words; Google would track how satisfied or unsatisfied someone might be with search results, and using machine learning, build a model based upon that satisfaction, raising or lowering search results for a query. This kind of reaction might be captured using a camera on a searcher’s phone to see their reaction to a search result, as depicted in the following screenshot from the patent:
I think this is possible but I think it might fall more under personalization than pure algorithm and it all might be done in the far future (i.e - 10 years from now.)
It does indeed appear that Googlebot-images reads and ranks img=”title:x” for the text in the img = “title:x” after all.
Very nice test here by to show what is and isn't used by Google Images for ranking.
The mass Google manual actions for outbound links was related to the warning Google gave a few weeks ago around bloggers giving links in exchange for free products or services.
No quid pro quo. #seo
Today we've taken a major stride forward with the announcement of a new product family: Cloud Machine Learning. Cloud Machine Learning will take machine learning mainstream, giving data scientists and developers a way to build a new class of intelligent applications. It provides access to the same technologies that power Google Now, Google Photos and voice recognition in Google Search as easy to use REST APIs. It enables you to build powerful Machine Learning models on your data using the open-source TensorFlow machine learning library.
Certainly one of the ways in which Google is trying to persuade companies to use their cloud service instead of Amazon's.
- Blind Five Year OldOwner, 2007 - present
20 years of marketing experience, with a successful track record of managing marketing programs - both online and offline.
Product strategist with a passion for iterative product development, fusing design and user experience with quantitative analysis.
- George Washington UniversityMarketing, 1989 - 1993
- The Line 2
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