Multifaceted featured snippets begin rolling out in Google search results

Google updates the search results features with an expanded featured snippet targeting broad, nuanced queries

The post Multifaceted featured snippets begin rolling out in Google search results appeared first on Search Engine Land.

Please visit Search Engine Land for the full article.

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Your Daily SEO Fix: Week 4

Posted by Trevor-Klein

This week, we’ve got the fourth (and second-to-last) installment of our short (< 2-minute) video tutorials that help you all get the most out of Moz’s tools. They’re each designed to solve a use case that we regularly hear about from Moz community members.

Here’s a quick recap of the previous round-ups in case you missed them:

  • Week 1: Reclaim links using Open Site Explorer, build links using Fresh Web Explorer, and find the best time to tweet using Followerwonk.
  • Week 2: Analyze SERPs using new MozBar features, boost your rankings through on-page optimization, check your anchor text using Open Site Explorer, do keyword research with OSE and the keyword difficulty tool, and discover keyword opportunities in Moz Analytics.
  • Week 3: Compare link metrics in Open Site Explorer, find tweet topics with Followerwonk, create custom reports in Moz Analytics, use Spam Score to identify high-risk links, and get link building opportunities delivered to your inbox.

In this installment, we’ve got five brand new tutorials:

  • How to Use Fresh Web Explorer to Build Links
  • How to Analyze Rank Progress for a Given Keyword
  • How to Use the MozBar to Analyze Your Competitors’ Site Markup
  • How to Use the Top Pages Report to Find Content Ideas
  • How to Find On-Site Errors with Crawl Test

Hope you enjoy them!

Fix 1: How to Use Fresh Web Explorer to Build Links

If you have unique data or a particularly excellent resource on your site, that content can be a great link magnet. In this Daily SEO Fix, Felicia shows you how to set up alerts in Fresh Web Explorer to track mentions of relevant keyword phrases, find link opportunities, and build links to your content.

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Fix 2: How to Analyze Rank Progress for a Given Keyword

Moz’s Rank Tracker tool retrieves search engine rankings for pages and keywords, storing them for easy comparison later. In this fix, James shows you how to use this helpful tool to track keywords, save time, and improve your rankings.


Fix 3: How to Use the MozBar to Analyze Your Competitors’ Site Markup

Schema markup helps search engines better identify what your (and your competitors’) website pages are all about and as a result can lead to a boost to rankings. In this Daily SEO Fix, Jordan shows you how to use the MozBar to analyze the schema markup of the competition and optimize your own site and pages for rich snippets.


Fix 4: How to Use the Top Pages Report to Find Content Ideas

With Moz’s Top Pages report in Open Site Explorer, you can see the pages on your site (and the competitions’ sites!) that are top performers. In this fix, Nick shows you how to use the report to analyze your competitors’ content marketing efforts and to inform your own.


Fix 5: How to Find On-Site Errors with Crawl Test

Identifying and understanding any potential errors on your site is crucial to the life of any SEO. In this Daily SEO Fix Sean shows you how to use the Crawl Test tool in Moz Analytics to pull reports and identify any errors on your site.


Looking for more?

We’ve got more videos in the previous three weeks’ round-ups!

Your Daily SEO Fix: Week 1

Your Daily SEO Fix: Week 2

Your Daily SEO Fix: Week 3


Don’t have a Pro subscription? No problem. Everything we cover in these Daily SEO Fix videos is available with a free 30-day trial.

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The Long Click and the Quality of Search Success

Posted by billslawski

“On the most basic level, Google could see how satisfied users were. To paraphrase Tolstoy, happy users were all the same. The best sign of their happiness was the “Long Click” — This occurred when someone went to a search result, ideally the top one, and did not return. That meant Google has successfully fulfilled the query.”

~ Steven Levy. In the Plex: How Google Thinks, Works, and Shapes our Lives

I often explore and read patents and papers from the search engines to try to get a sense of how they may approach different issues, and learn about the assumptions they make about search, searchers, and the Web. Lately, I’ve been keeping an eye open for papers and patents from the search engines where they talk about a metric known as the “long click.”

A recently granted Google patent uses the metric of a “Long Click” as the center of a process Google may use to track results for queries that were selected by searchers for long visits in a set of search results.

This concept isn’t new. In 2011, I wrote about a Yahoo patent in How a Search Engine May Measure the Quality of Its Search Results, where they discussed a metric that they refer to as a “target page success metric.” It included “dwell time” upon a result as a sign of search success (Yes, search engines have goals, too).

5543947f5bb408.24541747.jpg

Another Google patent described assigning web pages “reachability scores” based upon the quality of pages linked to from those initially visited pages. In the post Does Google Use Reachability Scores in Ranking Resources? I described how a Google patent that might view a long click metric as a sign to see if visitors to that page are engaged by the links to content they find those links pointing to, including links to videos. Google tells us in that patent that it might consider a “long click” to have been made on a video if someone watches at least half the video or 30 seconds of it. The patent suggests that a high reachability score on a page may mean that page could be boosted in Google search results.

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But the patent I’m writing about today is focused primarily upon looking at and tracking a search success metric like a long click or long dwell time. Here’s the abstract:

Modifying ranking data based on document changes

Invented by Henele I. Adams, and Hyung-Jin Kim

Assigned to Google

US Patent 9,002,867

Granted April 7, 2015

Filed: December 30, 2010

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media for determining a weighted overall quality of result statistic for a document.

One method includes receiving quality of result data for a query and a plurality of versions of a document, determining a weighted overall quality of result statistic for the document with respect to the query including weighting each version specific quality of result statistic and combining the weighted version-specific quality of result statistics, wherein each quality of result statistic is weighted by a weight determined from at least a difference between content of a reference version of the document and content of the version of the document corresponding to the version specific quality of result statistic, and storing the weighted overall quality of result statistic and data associating the query and the document with the weighted overall quality of result statistic.

This patent tells us that search results may be be ranked in an order, according to scores assigned to the search results by a scoring function or process that would be based upon things such as:

  • Where, and how often, query terms appear in the given document,
  • How common the query terms are in the documents indexed by the search engine, or
  • A query-independent measure of quality of the document itself.

Last September, I wrote about how Google might identify a category associated with a query term base upon clicks, in the post Using Query User Data To Classify Queries. In a query for “Lincoln.” the results that appear in response might be about the former US President, the town of Lincoln, Nebraska, and the model of automobile. When someone searches for [Lincoln], Google returning all three of those responses as a top result could be said to be reasonable. The patent I wrote about in that post told us that Google might collect information about “Lincoln” as a search entity, and track which category of results people clicked upon most when they performed that search, to determine what categories of pages to show other searchers. Again, that’s another “search success” based upon a past search history.

There likely is some value in working to find ways to increase the amount of dwell time someone spends upon the pages of your site, if you are already having some success in crafting page titles and snippets that persuade people to click on your pages when they those appear in search results. These approaches can include such things as:

  1. Making visiting your page a positive experience in terms of things like site speed, readability, and scannability.
  2. Making visiting your page a positive experience in terms of things like the quality of the content published on your pages including spelling, grammar, writing style, interest, quality of images, and the links you share to other resources.
  3. Providing a positive experience by offering ideas worth sharing with others, and offering opportunities for commenting and interacting with others, and by being responsive to people who do leave comments.

Here are some resources I found that discuss this long click metric in terms of “dwell time”:

Your ability to create pages that can end up in a “long click” from someone who has come to your site in response to a query, is also a “search success” metric on the search engine’s part, and you both succeed. Just be warned that as the most recent patent from Google on Long Clicks shows us, Google will be watching to make sure that the content of your page doesn’t change too much, and that people are continuing to click upon it in search results, and spend a fair amount to time upon it.

(Images for this post are from my Go Fish Digital Design Lead Devin Holmes @DevinGoFish. Thank you, Devin!)

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I Can’t Drive 155: Meta Descriptions in 2015

Posted by Dr-Pete

For years now, we (and many others) have been recommending keeping your Meta Descriptions shorter than
about 155-160 characters. For months, people have been sending me examples of search snippets that clearly broke that rule, like this one (on a search for “hummingbird food”):

For the record, this one clocks in at 317 characters (counting spaces). So, I set out to discover if these long descriptions were exceptions to the rule, or if we need to change the rules. I collected the search snippets across the MozCast 10K, which resulted in 92,669 snippets. All of the data in this post was collected on April 13, 2015.

The Basic Data

The minimum snippet length was zero characters. There were 69 zero-length snippets, but most of these were the new generation of answer box, that appears organic but doesn’t have a snippet. To put it another way, these were misidentified as organic by my code. The other 0-length snippets were local one-boxes that appeared as organic but had no snippet, such as this one for “chichen itza”:

These zero-length snippets were removed from further analysis, but considering that they only accounted for 0.07% of the total data, they didn’t really impact the conclusions either way. The shortest legitimate, non-zero snippet was 7 characters long, on a search for “geek and sundry”, and appears to have come directly from the site’s meta description:

The maximum snippet length that day (this is a highly dynamic situation) was 372 characters. The winner appeared on a search for “benefits of apple cider vinegar”:

The average length of all of the snippets in our data set (not counting zero-length snippets) was 143.5 characters, and the median length was 152 characters. Of course, this can be misleading, since some snippets are shorter than the limit and others are being artificially truncated by Google. So, let’s dig a bit deeper.

The Bigger Picture

To get a better idea of the big picture, let’s take a look at the display length of all 92,600 snippets (with non-zero length), split into 20-character buckets (0-20, 21-40, etc.):

Most of the snippets (62.1%) cut off as expected, right in the 141-160 character bucket. Of course, some snippets were shorter than that, and didn’t need to be cut off, and some broke the rules. About 1% (1,010) of the snippets in our data set measured 200 or more characters. That’s not a huge number, but it’s enough to take seriously.

That 141-160 character bucket is dwarfing everything else, so let’s zoom in a bit on the cut-off range, and just look at snippets in the 120-200 character range (in this case, by 5-character bins):

Zooming in, the bulk of the snippets are displaying at lengths between about 146-165 characters. There are plenty of exceptions to the 155-160 character guideline, but for the most part, they do seem to be exceptions.

Finally, let’s zoom in on the rule-breakers. This is the distribution of snippets displaying 191+ characters, bucketed in 10-character bins (191-200, 201-210, etc.):

Please note that the Y-axis scale is much smaller than in the previous 2 graphs, but there is a pretty solid spread, with a decent chunk of snippets displaying more than 300 characters.

Without looking at every original meta description tag, it’s very difficult to tell exactly how many snippets have been truncated by Google, but we do have a proxy. Snippets that have been truncated end in an ellipsis (…), which rarely appears at the end of a natural description. In this data set, more than half of all snippets (52.8%) ended in an ellipsis, so we’re still seeing a lot of meta descriptions being cut off.

I should add that, unlike titles/headlines, it isn’t clear whether Google is cutting off snippets by pixel width or character count, since that cut-off is done on the server-side. In most cases, Google will cut before the end of the second line, but sometimes they cut well before this, which could suggest a character-based limit. They also cut off at whole words, which can make the numbers a bit tougher to interpret.

The Cutting Room Floor

There’s another difficulty with telling exactly how many meta descriptions Google has modified – some edits are minor, and some are major. One minor edit is when Google adds some additional information to a snippet, such as a date at the beginning. Here’s an example (from a search for “chicken pox”):

With the date (and minus the ellipsis), this snippet is 164 characters long, which suggests Google isn’t counting the added text against the length limit. What’s interesting is that the rest comes directly from the meta description on the site, except that the site’s description starts with “Chickenpox.” and Google has removed that keyword. As a human, I’d say this matches the meta description, but a bot has a very hard time telling a minor edit from a complete rewrite.

Another minor rewrite occurs in snippets that start with search result counts:

Here, we’re at 172 characters (with spaces and minus the ellipsis), and Google has even let this snippet roll over to a third line. So, again, it seems like the added information at the beginning isn’t counting against the length limit.

All told, 11.6% of the snippets in our data set had some kind of Google-generated data, so this type of minor rewrite is pretty common. Even if Google honors most of your meta description, you may see small edits.

Let’s look at our big winner, the 372-character description. Here’s what we saw in the snippet:

Jan 26, 2015 – Health• Diabetes Prevention: Multiple studies have shown a correlation between apple cider vinegar and lower blood sugar levels. … • Weight Loss: Consuming apple cider vinegar can help you feel more full, which can help you eat less. … • Lower Cholesterol: … • Detox: … • Digestive Aid: … • Itchy or Sunburned Skin: … • Energy Boost:1 more items

So, what about the meta description? Here’s what we actually see in the tag:

Were you aware of all the uses of apple cider vinegar? From cleansing to healing, to preventing diabetes, ACV is a pantry staple you need in your home.

That’s a bit more than just a couple of edits. So, what’s happening here? Well, there’s a clue on that same page, where we see yet another rule-breaking snippet:

You might be wondering why this snippet is any more interesting than the other one. If you could see the top of the SERP, you’d know why, because it looks something like this:

Google is automatically extracting list-style data from these pages to fuel the expansion of the Knowledge Graph. In one case, that data is replacing a snippet
and going directly into an answer box, but they’re performing the same translation even for some other snippets on the page.

So, does every 2nd-generation answer box yield long snippets? After 3 hours of inadvisable mySQL queries, I can tell you that the answer is a resounding “probably not”. You can have 2nd-gen answer boxes without long snippets and you can have long snippets without 2nd-gen answer boxes,
but there does appear to be a connection between long snippets and Knowledge Graph in some cases.

One interesting connection is that Google has begun bolding keywords that seem like answers to the query (and not just synonyms for the query). Below is an example from a search for “mono symptoms”. There’s an answer box for this query, but the snippet below is not from the site in the answer box:

Notice the bolded words – “fatigue”, “sore throat”, “fever”, “headache”, “rash”. These aren’t synonyms for the search phrase; these are actual symptoms of mono. This data isn’t coming from the meta description, but from a bulleted list on the target page. Again, it appears that Google is trying to use the snippet to answer a question, and has gone well beyond just matching keywords.

Just for fun, let’s look at one more, where there’s no clear connection to the Knowledge Graph. Here’s a snippet from a search for “sons of anarchy season 4”:

This page has no answer box, and the information extracted is odd at best. The snippet bears little or no resemblance to the site’s meta description. The number string at the beginning comes out of a rating widget, and some of the text isn’t even clearly available on the page. This seems to be an example of Google acknowledging IMDb as a high-authority site and desperately trying to match any text they can to the query, resulting in a Frankenstein’s snippet.

The Final Verdict

If all of this seems confusing, that’s probably because it is. Google is taking a lot more liberties with snippets these days, both to better match queries, to add details they feel are important, or to help build and support the Knowledge Graph.

So, let’s get back to the original question – is it time to revise the 155(ish) character guideline? My gut feeling is: not yet. To begin with, the vast majority of snippets are still falling in that 145-165 character range. In addition, the exceptions to the rule are not only atypical situations, but in most cases those long snippets don’t seem to represent the original meta description. In other words, even if Google does grant you extra characters, they probably won’t be the extra characters you asked for in the first place.

Many people have asked: “How do I make sure that Google shows my meta description as is?” I’m afraid the answer is: “You don’t.” If this is very important to you, I would recommend keeping your description below the 155-character limit, and making sure that it’s a good match to your target keyword concepts. I suspect Google is going to take more liberties with snippets over time, and we’re going to have to let go of our obsession with having total control over the SERPs.

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The Incredible Shrinking SERP – 2015 Edition

Posted by Dr-Pete

In the beginning, there were 10 results, and it was good. Then, came expanded site-links and Google’s 
7-result SERP. Around the middle of 2014, we started to hear reports of SERPs with odd numbers of organic results – 9, 8, 6, 5, and even 4 page-1 results. At first, these were sporadic and hard to replicate, but they quietly expanded. This is a recent 4-result SERP for “autism speaks”:

By some counts, there are as many as 16 non-paid links on this page (not counting images), but by traditional SEO standards, there are only 4 true organic positions for which you can compete. So, what’s going on here? Is it just random, or is there a method to Google’s madness?

It’s all in the news

For a couple of months, I just assumed these strange result counts were some kind of glitch. Then I noticed an unusual pattern. Last October, Google rolled out the 
“In The News” Update. This update expanded news results to many new sources, but it also seemed to change the pattern of when news results appear. This is 28 days of data from MozCast’s Feature Graph (10K queries):

The presence of News results seemed to be cyclical, dipping early in the week and peaking later in the week. I don’t follow News results closely, so it was just a curiosity at first, until I saw another bit of data. This is the average page-1 result count for that same period:

While the scale of the change was much smaller (please note that both graphs have a restricted Y-axis to make the effect more visible), the opposing shapes of the curves seemed like more than a coincidence. As News results increased, the average page-1 organic result count decreased.

It’s a vertical, vertical world

Spot-checking various SERPs, I was able to confirm this effect. If page 1 had a News box, then the organic result count would be decreased by one (to either 9 results or 6, depending on the starting point). Here’s a sample SERP (I’ve removed snippets to simplify the image) for “samsung galaxy tab”:

This is a basic 10-result SERP, but when a News box comes into play, we’re only left with 9 organic results. This raised the question – were other verticals having a similar impact? Digging deeper, I found that, in addition to News results, Image results and In-depth Articles also occupied one organic position. Remember the example at the top of the post? It’s a brand query, resulting in a 7-result SERP, but it also has News results, Image results, and In-depth Articles. If we do the math: 7 – 1 – 1 – 1 = 4 results. It’s not random at all.

In the interest of being more methodical, what if we looked at the average page-1 organic result across every combination of verticals in our data set? We’ll stick with a starting point of 10 results, to keep the data clean. Here’s a table with the average counts by vertical combination:

I’ve taken the average out to two decimal places just to be more transparent, but what we’re seeing here is little more than a tiny bit of measurement error. Generally speaking, each instance of a vertical result type (as a whole, not individual links within these verticals) costs a 10-result SERP one organic ranking position. It’s worth nothing that SERPs with all 3 verticals are pretty rare, but when they occur, each of those 3 verticals costs one position and one opportunity for you to rank on page 1.

It’s always something

So, do the same rules apply to 7-result SERPs? Well, Google isn’t a big fan of making my life easy, so it turns out this gets a bit more complicated. When 7-result SERPs originally launched, our data showed that they almost always came with expanded sitelinks in the #1 organic position. By “expanded sitelinks”, I mean something like the following:

Sitelinks usually appear for queries that either have a strong brand connotation or at least a dominant interpretation. While we typically use 6-packs of expanded sitelinks as an example, actual counts can vary from 1 to 6. Originally, the presence of any sitelinks yielded a 7-result SERP. Now, it’s gotten a bit more complicated, as shown by the table below:

Since each row of sitelinks can contain up to 2 links, the general logic seems to be that 1 row of sitelinks equates to 1 additional organic result. If you have 3 rows of sitelinks, then Google will remove 3 organic results from page 1.

Google’s logic here seems to revolve around the actual display of information and length of the page. As they add some elements, they’re going to subtract others. Since the physical display length of of most elements can vary quite a bit, the rules right now are pretty simplistic, but the core logic seems to be based on constraining the total number of results displayed on page 1.

It’s time to rethink organic

All of this raises a difficult question – what is an organic result? As SEOs, we typically don’t think of vertical results as “organic” by our fairly narrow definition, but they’re much more organic than paid results or even Knowledge Graph. What’s more, Google is starting to blur the lines with verticals.

For example, in the past couple of weeks, Google has redesigned the look of In-depth Articles twice. You might think “So what? It’s just a design change,” but take a closer look. At the end of March, Googled removed the “In-depth articles” header. Here’s an example of the new design (for the query “jobs”):

While the thumbnail images and horizontal dividers still set these results apart somewhat, Google’s intent seems to be to make them appear more organic. Keep in mind, too, that other, organic results use thumbnails as well (including videos and recipes).

Then, just a couple of weeks later (our systems detected this on the morning of April 8th), Google went much farther, removing the thumbnails and even the byline. Here’s part of a screenshot for “Putin”:

Can you spot the true organic results here? They’re the first two – the rest of this screenshot is In-depth Articles. The only real clue, beside the count and source-code markers, is the horizontal divider on either end of the 3-pack. On mobile, even the dividers are gone, as every result is treated like a “card” (see below).

As an SEO, I’m still inclined to call these results “vertical” for two reasons: (1) historical precedent, and (2) these results play by different ranking rules. I think reason #2 is the more important one – In-depth Articles are currently dominated by a core set of big publishers, and the algorithm differs quite a bit from regular, organic results.

It’s only the beginning…

You wanna get really crazy? Let’s look at an entire SERP for “polar” on an Android device (Moto G). This result also includes In-depth Articles (warning: scrolling ahead):

Let’s do the math. For starters, it’s a branded result with expanded sitelinks, so we should have a 7-result page. Remember that those last 3 results are In-depth Articles, so we’ll subtract 1, leaving us with what should be 6 results. See the “app pack” in the middle? That’s an Android-specific vertical, and instead of counting the pack as just 1 result, Google is counting each link as a result. So, we’re only left with 3 traditional organic results on this SERP, despite it being packed with information.

I strongly suspect this trend will continue, and it will probably expand. The definition of “organic” is blurring, and I think that all of these vertical results represent SEO opportunities that can’t be ignored. If we’re stuck in the mindset of only one “true” organic, then our opportunities are going to keep shrinking every day.

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Reblogged 3 years ago from tracking.feedpress.it