Do you want to improve the search rank for your website or blog? Wondering how social media can help? Social media and search engine optimization (SEO) are undoubtedly connected and will only become more interdependent in the future. In this article, you'll discover seven ways you can use social media to boost your search rankings. [...]
This post 7 Ways to Improve Your Search Rank With Social Media first appeared on .
- Your Guide to the Social Media Jungle
Posted by larry.kim
Rand Fishkin posted another brilliant Whiteboard Friday last week on the topic of optimizing for RankBrain. In it, he explained how RankBrain helps Google select and prioritize signals it uses for ranking.
One of the most important signals Google takes into account is user engagement. As Rand noted, engagement is a "very, very important signal."
Engagement is a huge but often ignored opportunity. That's why I've been a bit obsessed with improving engagement metrics.
My theory has been that RankBrain *and/or other machine learning elements within Google's core algorithm are increasingly rewarding pages with high user engagement. Not always, but it's happening often enough that it's kind of a huge deal.
Google is looking for unicorns – and I think that machine learning is Google's ultimate Unicorn Detector.
Now, when I say unicorns, I mean those pages that have magical engagement rates that elevate them above the other donkey pages Google could show for a given query. Like if your page has a 5 percent click-through rate (CTR) when everyone else has a 1 percent CTR.
What is Google's mission? To provide the best results to searchers. One way Google does this is by looking at engagement data.
If most people are clicking on a particular search result – and then also engaging with that page – these are clear signals to Google that people think this page is fascinating. That it's a unicorn.
RankBrain, much like Google's algorithm, is a great mystery. Since Google revealed (in a Bloomberg article just under a year ago) the important role of machine learning and artificial intelligence in its algorithm, RankBrain has been a surprisingly controversial topic, generating speculation and debate within the search industry.
Then, we found out in June that Google RankBrain was no longer just for long-tail queries. It was "involved in every query."
We learned quite a few things about RankBrain. We were told by Google that you can't optimize for it. Yet we also learned that Google's engineers don't really understand what RankBrain does or how it works.
Some people have even argued that there is absolutely nothing you can do to see Google's machine learning systems at work.
Give me a break! It's an algorithm. Granted, a more complex algorithm thanks to machine learning, but an algorithm nonetheless. All algorithms have rules and patterns.
When Google tweaked Panda and Penguin, we saw it. When Google tweaked its exact-match domain algorithm, we saw it. When Google tweaked its mobile algorithm, we saw it.
If you carefully set up an experiment, you should be able to isolate some aspect of what Google is proclaiming as the third most important ranking factor. You should be able to find evidence – a digital fingerprint.
What you're about to look at is organic search click-through rate vs. the average organic search position for three separate 30-day periods ending April 30, July 12, and September 19 of this year. This data, obtained from the Google Search Console, tracked the same keywords in the Internet marketing niche.
I see some of the most compelling evidence of RankBrain (and/or other machine learning search algorithms!) at work.
The shape of CTR vs. ranking curve is changing every month – for the 30 days ending:
The top, most prominent positions are getting even more clicks. Obviously, they were already getting a lot of clicks. But now they're getting more clicks than they have in recent history.
This is the winner-take-all nature of Google's organic SERPs today. It's coming at the expense of Positions 4–10, which are being clicked on much less over time.
Results that are more likely to attract engagement are pushed further up the SERP, while results with lower engagement get pushed further down. That's what we believe RankBrain is doing.
This data is showing us something very interesting. A couple thoughts:
Could anything else be causing this shift to the click curve? Could it have been the elimination of right rail ads?
No, that happened in February. I was careful to use date ranges that were after the right rail apocalypse.
Could it be more Knowledge Graph elements creeping into the SERPs? If that were the case, it would look like everything got pushed down by one position (e.g., Position 1 becomes Position 2, Position 2 becomes Position 3, and so on).
The data didn't show that happening. We see a bending of the click curve, not a shifting of the curve.
OK, so we've looked at the big picture. Now let's look at the little picture to illustrate the remarkable power of CTR optimization.
Let's talk about guerrilla marketing. Here are two headlines. Which headline do you think has the higher CTR?
This was the original headline for an article published on the WordStream blog in 2014.
This is the updated headline, which we changed just a few months ago, in the hopes of increasing the CTR. And yep, we sure did!
Before we updated the headline, the article had a CTR of 1 percent and was ranking in position 8. Nothing awesome.
Since we updated the headline, the article has had a CTR of 4.19 percent and is ranking in position 5. Pretty awesome, no?
Increasingly, we've been trying to move away from "SEO titles" that look like the original headline, where you have the primary keyword followed by a colon and the rest of your headline. They aren't catchy enough.
Yes, you still need to include keywords in your headline. But you don't have to use this tired format, which will deliver (at best) solid but unspectacular results.
To be clear: we only changed the title tag. No other optimization tactics were used.
We didn't point any links (internal or external) at it. We didn't add any images or anything else to the post. Nothing.
Changing the title tag changed the CTR. Which gave it "magical points" that resulted in 97 percent more organic traffic:
What does it all mean?This example illustrates that if you increase your CTR, you'll see a nice boost in traffic. Ranking in a better position means more traffic, which means a higher CTR, which also means more traffic.
What's so remarkable is that this is on-page SEO. No link building was required! Besides, pointing new links to a page wouldn't result in a higher click-through rate – a catchier headline, however, would result in a higher CTR.
What's also interesting about this is that RankBrain isn't like other algorithms, say Panda or Penguin, where it was obvious when you got hit. You lost half your traffic!
If RankBrain or a machine learning algorithm impacts your site due to engagement metrics (positive or negative), it's a much more subtle shift. All your best pages do better. All your “upper class donkey” pages do slightly worse. Ultimately, the two forces cancel each other out, to some extent, so that the SEO alarms don't go off.
When it comes to SEO, your mission is to seek out every advantage. It's my belief that organic CTR and website engagement rates impact organic rankings.
So boldly go where many SEOs are failing to go now. Hop aboard the USS Unicorn, make the jump to warp speed, and discover the wonders of those magical creatures.
Oh, and…
Are you optimizing your click-through rates? If not, why not? If so, what have you been seeing in your analytics?
Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!
Advanced surveillance technology is already intensifying racial discrimination at police departments in the United States, and there's a good chance it's going to get worse.
Police departments across the country target communities of color with racially-biased policing strategies. This is a fact well-documented by plenty of extensive reviews conducted by the Department of Justice that have unearthed a tremendous number of civil rights violations committed by officers against minority residents.
What's less understood is how surveillance technologies employed by the police intensify the racially discriminatory strategies that already exist. Read more...
More about Facial Recognition, Stingray, Surveillance, Social Media, and Geofeedia
Posted by willcritchlow
“What would we have to do to outrank that site?”
“Why is our competitor outranking us on this search?”
These kind of questions - from bosses, from clients, and from prospective clients - are a standard part of day-to-day life for many SEOs. I know I've been asked both in the last week.
It's relatively easy to figure out ways that a page can be made more relevant and compelling for a given search, and it's straightforward to think of ways the page or site could be more authoritative (even if it's less straight-forward to get it done). But will those changes or that extra link cause an actual reordering of a specific ranking? That's a very hard question to answer with a high degree of certainty.
When we asked a few hundred people to pick which of two pages would rank better for a range of keywords, the average accuracy on UK SERPs was 46%. That's worse than you'd get if you just flipped a coin! This chart shows the performance by keyword. It's pretty abysmal:
I've participated in each iteration of Moz's ranking factors survey since its inception in 2009. At one of our recent conferences (the last time I was in San Diego for SearchLove) I talked about how I used to enjoy it and feel like I could add real value by taking the survey, but how that's changed over the years as the complexity has increased.
While I remain confident when building strategies to increase overall organic visibility, traffic, and revenue, I'm less sure than ever which individual ranking factors will outweigh which others in a specific case.
My approach is generally to zoom out and build business cases on assumptions about portfolios of rankings, but it's been on my mind recently as I think about the ways machine learning should make Google rankings ever more of a black box, and cause the ranking factors to vary more and more between niches.
I've been teaching myself about deep neural networks using TensorFlow and Keras - an area I'm pretty sure I'd have ended up studying and working in if I'd gone to college 5 years later. As I did so, I started thinking about how you would model a SERP (which is a set of high-dimensional non-linear relationships). I realized that the litmus test of understanding ranking factors - and thus being able to answer “why does that page outrank us?” - boils down to being able to answer a simpler question:
If you can answer that in the general case, then you know why one page outranks another, and vice-versa.
I thought that answering this with greater accuracy than a coin flip was going to be a pretty low bar. As you saw from the sneak peak of my results above, that turned out not to be the case. Reckon you can do better? Skip ahead to take the test and find out.
(In fact, if you could find a way to test this effectively, I wonder if it would make a good qualifying question for the next moz ranking factors survey. Should you only listen only to the opinion of those experts who are capable of answering with reasonable accuracy? Note that my test that follows isn't at all rigorous because you can cheat by Googling the keywords - it's just for entertainment purposes).
With my curiosity piqued, I put together a simple test, thinking it would be interesting to see how good expert SEOs actually are at this, as well as to see how well laypeople do.
I've included a bit more about the methodology and some early results below, but if you'd like to skip ahead and test yourself you can go ahead here.
Note that to simplify the adversarial side, I'm going to let you rely on all of Google's spam filtering - you can trust that every URL ranks in the top 10 for its example keyword - so you're choosing an ordering of two pages that do rank for the query rather than two pages from potentially any domain on the Internet.
I haven't designed this to be uncheatable - you can obviously cheat by Googling the keywords - but as my old teachers used to say: "If you do, you'll only be cheating yourself."
Unfortunately, Google Forms seems to have removed the option to be emailed your own answers outside of an apps domain, so if you want to know how you did, note down your answers as you go along and compare them to the correct answers (which are linked from the final page of the test).
You can try your hand with just one keyword or keep going, trying anywhere up to 10 keywords (each with a pair of pages to put in order). Note that you don't need to do all of them; you can submit after any number.
You can take the survey either for the US (google.com) or UK (google.co.uk). All results are considering only the "blue links" results - i.e. links to web pages - rather than universal search results / one-boxes etc.
Before publishing this post, we sent it out to the @distilled and @moz networks. At the time of writing, almost 300 people have taken the test, and there are already some interesting results:
The UK test appears to be a little harder (judging both by the accuracy of laypeople, and with a subjective eye). And while accuracy generally increases with experience in both the UK and the US, the vast majority of UK respondents performed worse than a coin flip:
Digging into the data, there are a few of the US questions that are absolute no-brainers (e.g. there's a question about the keyword [mortgage calculator] in the US that 84% of respondents get right regardless of their experience). In comparison, the easiest one in the UK was also a mortgage-related query ([mortgage comparisons]) but only 2/3 of people got that right (67%).
Compare the UK results by keyword...
...To the same chart for the US keywords:
So, even though the overall accuracy was a little above 50% in the US (around 56% or roughly 5/9), I'm not actually convinced that US SERPs are generally easier to understand. I think there are a lot of US SERPs where human accuracy is in the 40% range.
The Dunning-Kruger effect is a well-studied psychological phenomenon whereby people “fail to adequately assess their level of competence,” typically feeling unsure in areas where they are actually strong (impostor syndrome) and overconfident in areas where they are weak. Alongside the raw predictions, I asked respondents to give their confidence in their rankings for each URL pair on a scale from 1 (“Essentially a guess, but I've picked the one I think”) to 5 (“I'm sure my chosen page should rank better”).
The effect was most pronounced on the UK SERPs - where respondents answering that they were sure or fairly sure (4–5) were almost as likely to be wrong as those guessing (1) - and almost four percentage points worse than those who said they were unsure (2–3):
The question I asked SEOs was “which page do you think ranks better?”, not “which page is a better result?”, so in general, most of the results say very little about whether Google is picking the right result in terms of user satisfaction. I did, however, ask people to share the survey with their non-SEO friends and ask them to answer the latter question.
If I had a large enough sample-size, you might expect to see some correlation here - but remember that these were a diverse array of queries and the average respondent might well not be in the target market, so it's perfectly possible that Google knows what a good result looks like better than they do.
Having said that, in my own opinion, there are one or two of these results that are clearly wrong in UX terms, and it might be interesting to analyze why the “wrong” page is ranking better. Maybe that'll be a topic for a follow-up post. If you want to dig into it, there's enough data in both the post above and the answers given at the end of the survey to find the ones I mean (I don't want to spoil it for those who haven't tried it out yet). Let me know if you dive into the ranking factors and come up with any theories.
One of the disappointments of putting together this test was that by the time I'd made the Google Form I knew too many of the answer to be able to test myself fairly. But I was comforted by the fact that I could do the next best thing - I could test my neural network (well, my model, refactored by our R&D team and trained on data they gathered, which we flippantly called Deeprank).
I think this is fair; the instructions did say “use whatever tools you like to assess the sites, but please don't skew the results by performing the queries on Google yourself.” The neural network wasn't trained on these results, so I think that's within the rules. I ran it on the UK questions because it was trained on google.co.uk SERPs, and it did better than a coin flip:
So maybe there is hope that smarter tools could help us continue to answer questions like “why is our competitor outranking us on this search?”, even as Google's black box gets ever more complex and impenetrable.
If you want to hear more about these results as I gather more data and get updates on Deeprank when it's ready for prime-time, be sure to add your email address when you:
Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!
Have you noticed a drop in your Facebook engagement? Wondering how you can better engage with your fans? Making small changes to what and how you post can help your Facebook updates generate clicks, likes, and comments. In this article, you'll discover 26 tips for boosting Facebook engagement. #1: Pose a Question One of the [...]
This post 26 Tips for Better Facebook Page Engagement first appeared on .
- Your Guide to the Social Media Jungle
The experts welcome special guest Donald Miller, NYT Best-Selling Author and President of StoryBrand, to discuss how to create a marketing message that filters through the noise, enters the customer's story, and connects you with your audience.
Listen in to learn this easy process and visit digitalmarketer.com/podcast to gain valuable resources you can apply to any business.
IN THIS EPISODE YOU'LL LEARN:
LINKS AND RESOURCES MENTIONED IN THIS EPISODE:
Episode 38: The 4-Step Podcast Launch Strategy
Episode 56: How DollarBeardClub.com Generated 100 Million Video Views in 13 Months
The 5 Minute Marketing Makeover Course or text "makeover" to 72000 -- 3 five minute training videos that helps to clarify your marketing message.
The 7 Proven Story Formula Worksheet
Press and hold link to visit the page
Welcome to our weekly edition of what's hot in social media news. To help you stay up to date with social media, here are some of the news items that caught our attention. What's New This Week Twitter Makes Moments Available to All Users: Twitter announced that Moments is now available to all users. According [...]
This post Twitter Moments Rolls Out Storytelling Feature for All: This Week in Social Media first appeared on .
- Your Guide to the Social Media Jungle
