Panda 3.3 Update and 40 Google Search Algorithm Changes
Google works on changing and improving their search algorithm almost everyday, and with 500 plus changes happening over the course of the year, this month’s changes are of little surprise. The king of search has just announced on their Google Official Inside Search Blog, the latest Google Panda 3.3 update.
With this new panda update there are also 40 other search algorithm changes that will impact the search results.
All of the changes and updates in the algorithm started and affected the search result since the beginning of February and some change results are still in the making. Vab media would like to provide some insight into what this means for Search Engine Optimization and business owners.
We chose to highlight a few of the most important changes below.
“Panda Update: Launch refreshes data in the Panda system, making it more accurate and more sensitive to recent changes on the web.”
What this means– The moment Panda is mentioned, webmasters freak out and the SEO industry pays full attention hoping their clients’ rankings don’t suddenly drop. This brief announcement shows less of an importance as is it being buried in the list of 39 other changes. One can draw conclusions that the algorithm implemented during the original Panda update is heading toward socially shared links, and in all likelihood, Google will be pulling the social data from their Google+ network.
“Link Evaluation: We often use characteristics of links to help us figure out the topic of a linked page. We have changed the way in which we evaluate links; in particular, we are turning off a method of link analysis that we used for several years. We often re-architect or turn off parts of our scoring in order to keep our system maintainable, clean and understandable.”
What this means– Some link building practices have been abused over the last few years by Black Hat SEO companies. Google seems to putting more emphasis on social sharing and re-sharing data of a page than on their traditional link evaluation, which may have previously taken into account the of number of anchor text links pointing to a page. Google does not say whether this is a permanent change of a particular algorithm characteristic of the way they assess links or an just an experiment to see if the accumulated data they collect will be sufficient to maintain or increase relevancy of people’s search results, while getting rid of spam and abuse.
“Spam Update: In the process of investigating some potential spam, we found and fixed some weaknesses in our spam protections.”
What this means– You should be focused on putting out high-quality, share-worthy content as much as ever. Just because Google is focusingon combining social media with search results, do not think that its spam filters are not being refined.
“Improvements to Ranking for Local Search Results: [launch codename “Venice”] This improvement improves the triggering of Local Universal results by relying more on the ranking of our main search results as a signal.”
What this means– The ranking of your website in the local search results is now influenced by the ranking of your web pages in Universal search. This means you need to be optimizing all aspects of Universal search which includes videos, images, and maps in order to dominate Google’s first page results for local search. You need to take actions. Optimize your website and make sure it is done professionally and is optimized correctly to get you ranked on the first page for search queries related to your industry.
“More locally relevant predictions in YouTube. [project codename “Suggest”] We’ve improved the ranking for predictions in YouTube to provide more locally relevant queries. For example, for the query [lady gaga in ] performed on the US version of YouTube, we might predict [lady gaga in times square], but for the same search performed on the Indian version of YouTube, we might predict [lady gaga in India].”
What this means– YouTube is the second largest search engine surpassing Yahoo since last year. Google has been constantly refining this, as it will play an ever-increasing role in visual-media content. If you are adding video to your marketing efforts to drive potential customers to your business website, now the titles, description and tags you use are an even more important part of your SEO strategies.
“Improved local results. We launched a new system to find results from a user’s city more reliably. Now we’re better able to detect when both queries and documents are local to the user.”
What this means– Google’s local SEO vertical is ramping up. Now the search engine knows where you are in an area and what’s around you. For the small business owner, now is the time.to start using local SEO best practices, and geo-tagging to help your business get found locally by your local customers.
This most recent Google Panda 3.3 update talks about the refinement of the data and promises accurate and sensitive results for the queries, so we can hope the impact on websites will be far less extreme than the first Panda update. However, one of these updates that may bother some SEOs are the changes that Google talks about with their link evaluation. By shutting down their old method of evaluating links that has been used for several years, indicates a huge shift which will surely change and evolve the strategies of link-building in the future. It certainly looks like the importance of social sharing and Google+ will play a much larger part of the web going forward.[button link=”http://www.vabulous.com/contact-us/” type=”big” color=”purple”]Get Started On An SEO Strategy Today[/button]
Here is the official blog written by Amit Singhal, Senior VP and Google Fellow
Search quality highlights: 40 changes for February
“This month we have many improvements to celebrate. With 40 changes reported, that marks a new record for our monthly series on search quality. Most of the updates rolled out earlier this month, and a handful are actually rolling out today and tomorrow. We continue to improve many of our systems, including related searches, sitelinks, autocomplete, UI elements, indexing, synonyms, SafeSearch and more. Each individual change is subtle and important, and over time they add up to a radically improved search engine.
Here’s the list for February:
- More coverage for related searches. [launch codename “Fuzhou”] This launch brings in a new data source to help generate the “Searches related to” section, increasing coverage significantly so the feature will appear for more queries. This section contains search queries that can help you refine what you’re searching for.
- Tweak to categorizer for expanded sitelinks. [launch codename “Snippy”, project codename “Megasitelinks”] This improvement adjusts a signal we use to try and identify duplicate snippets. We were applying a categorizer that wasn’t performing well for our expanded sitelinks, so we’ve stopped applying the categorizer in those cases. The result is more relevant sitelinks.
- Less duplication in expanded sitelinks. [launch codename “thanksgiving”, project codename “Megasitelinks”] We’ve adjusted signals to reduce duplication in the snippets for expanded sitelinks. Now we generate relevant snippets based more on the page content and less on the query.
- More consistent thumbnail sizes on results page. We’ve adjusted the thumbnail size for most image content appearing on the results page, providing a more consistent experience across result types, and also across mobile and tablet. The new sizes apply to rich snippet results for recipes and applications, movie posters, shopping results, book results, news results and more.
- More locally relevant predictions in YouTube. [project codename “Suggest”] We’ve improved the ranking for predictions in YouTube to provide more locally relevant queries. For example, for the query [lady gaga in ] performed on the US version of YouTube, we might predict [lady gaga in times square], but for the same search performed on the Indian version of YouTube, we might predict [lady gaga in India].
- More accurate detection of official pages. [launch codename “WRE”] We’ve made an adjustment to how we detect official pages to make more accurate identifications. The result is that many pages that were previously misidentified as official will no longer be.
- Refreshed per-URL country information. [Launch codename “longdew”, project codename “country-id data refresh”] We updated the country associations for URLs to use more recent data.
- Expand the size of our images index in Universal Search. [launch codename “terra”, project codename “Images Universal”] We launched a change to expand the corpus of results for which we show images in Universal Search. This is especially helpful to give more relevant images on a larger set of searches.
- Minor tuning of autocomplete policy algorithms. [project codename “Suggest”] We have a narrow set of policies for autocomplete for offensive and inappropriate terms. This improvement continues to refine the algorithms we use to implement these policies.
- “Site:” query update [launch codename “Semicolon”, project codename “Dice”] This change improves the ranking for queries using the “site:” operator by increasing the diversity of results.
- Improved detection for SafeSearch in Image Search. [launch codename “Michandro”, project codename “SafeSearch”] This change improves our signals for detecting adult content in Image Search, aligning the signals more closely with the signals we use for our other search results.
- Interval based history tracking for indexing. [project codename “Intervals”] This improvement changes the signals we use in document tracking algorithms.
- Improvements to foreign language synonyms. [launch codename “floating context synonyms”, project codename “Synonyms”] This change applies an improvement we previously launched for English to all other languages. The net impact is that you’ll more often find relevant pages that include synonyms for your query terms.
- Disabling two old fresh query classifiers. [launch codename “Mango”, project codename “Freshness”] As search evolves and new signals and classifiers are applied to rank search results, sometimes old algorithms get outdated. This improvement disables two old classifiers related to query freshness.
- More organized search results for Google Korea. [launch codename “smoothieking”, project codename “Sokoban4”] This significant improvement to search in Korea better organizes the search results into sections for news, blogs and homepages.
- Fresher images. [launch codename “tumeric”] We’ve adjusted our signals for surfacing fresh images. Now we can more often surface fresh images when they appear on the web.
- Update to the Google bar. [project codename “Kennedy”] We continue to iterate in our efforts to deliver a beautifully simple experience across Google products, and as part of that this month we made further adjustments to the Google bar. The biggest change is that we’ve replaced the drop-down Google menu in the November redesign with a consistent and expanded set of links running across the top of the page.
- Adding three new languages to classifier related to error pages. [launch codename “PNI”, project codename “Soft404”] We have signals designed to detect crypto 404 pages (also known as “soft 404s”), pages that return valid text to a browser but the text only contain error messages, such as “Page not found.” It’s rare that a user will be looking for such a page, so it’s important we be able to detect them. This change extends a particular classifier to Portuguese, Dutch and Italian.
- Improvements to travel-related searches. [launch codename “nesehorn”] We’ve made improvements to triggering for a variety of flight-related search queries. These changes improve the user experience for our Flight Search feature with users getting more accurate flight results.
- Data refresh for related searches signal. [launch codename “Chicago”, project codename “Related Search”] One of the many signals we look at to generate the “Searches related to” section is the queries users type in succession. If users very often search for [apple] right after [banana], that’s a sign the two might be related. This update refreshes the model we use to generate these refinements, leading to more relevant queries to try.
- International launch of shopping rich snippets. [project codename “rich snippets”]Shopping rich snippets help you more quickly identify which sites are likely to have the most relevant product for your needs, highlighting product prices, availability, ratings and review counts. This month we expanded shopping rich snippets globally (they were previously only available in the US, Japan and Germany).
- Improvements to Korean spelling. This launch improves spelling corrections when the user performs a Korean query in the wrong keyboard mode (also known as an “IME”, or input method editor). Specifically, this change helps users who mistakenly enter Hangul queries in Latin mode or vice-versa.
- Improvements to freshness. [launch codename “iotfreshweb”, project codename “Freshness”] We’ve applied new signals which help us surface fresh content in our results even more quickly than before.
- Web History in 20 new countries. With Web History, you can browse and search over your search history and webpages you’ve visited. You will also get personalized search results that are more relevant to you, based on what you’ve searched for and which sites you’ve visited in the past. In order to deliver more relevant and personalized search results, we’ve launched Web History in Malaysia, Pakistan, Philippines, Morocco, Belarus, Kazakhstan, Estonia, Kuwait, Iraq, Sri Lanka, Tunisia, Nigeria, Lebanon, Luxembourg, Bosnia and Herzegowina, Azerbaijan, Jamaica, Trinidad and Tobago, Republic of Moldova, and Ghana. Web History is turned on only for people who have a Google Account and previously enabled Web History.
- Improved snippets for video channels. Some search results are links to channels with many different videos, whether on mtv.com, Hulu or YouTube. We’ve had a feature for a while now that displays snippets for these results including direct links to the videos in the channel, and this improvement increases quality and expands coverage of these rich “decorated” snippets. We’ve also made some improvements to our backends used to generate the snippets.
- Improvements to ranking for local search results. [launch codename “Venice”] This improvement improves the triggering of Local Universal results by relying more on the ranking of our main search results as a signal.
- Improvements to English spell correction. [launch codename “Kamehameha”] This change improves spelling correction quality in English, especially for rare queries, by making one of our scoring functions more accurate.
- Improvements to coverage of News Universal. [launch codename “final destination”] We’ve fixed a bug that caused News Universal results not to appear in cases when our testing indicates they’d be very useful.
- Consolidation of signals for spiking topics. [launch codename “news deserving score”, project codename “Freshness”] We use a number of signals to detect when a new topic is spiking in popularity. This change consolidates some of the signals so we can rely on signals we can compute in realtime, rather than signals that need to be processed offline. This eliminates redundancy in our systems and helps to ensure we can continue to detect spiking topics as quickly as possible.
- Better triggering for Turkish weather search feature. [launch codename “hava”] We’ve tuned the signals we use to decide when to present Turkish users with the weather search feature. The result is that we’re able to provide our users with the weather forecast right on the results page with more frequency and accuracy.”
- Visual refresh to account settings page. We completed a visual refresh of the account settings page, making the page more consistent with the rest of our constantly evolving design.
- Panda update. This launch refreshes data in the Panda system, making it more accurate and more sensitive to recent changes on the web.
- Link evaluation. We often use characteristics of links to help us figure out the topic of a linked page. We have changed the way in which we evaluate links; in particular, we are turning off a method of link analysis that we used for several years. We often rearchitect or turn off parts of our scoring in order to keep our system maintainable, clean and understandable.
- SafeSearch update. We have updated how we deal with adult content, making it more accurate and robust. Now, irrelevant adult content is less likely to show up for many queries.
- Spam update. In the process of investigating some potential spam, we found and fixed some weaknesses in our spam protections.
- Improved local results. We launched a new system to find results from a user’s city more reliably. Now we’re better able to detect when both queries and documents are local to the user.”