Local SEO in 2017 and beyond: managed strategy vs. automation

There are many great software options for automating local search tasks, but columnist Andrew Beckman argues that a human-managed approach may still be necessary to see results. The post Local SEO in 2017 and beyond: managed strategy vs. automation appeared first on Search Engine Land.

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What's the Real Relationship Between Organic Rankings & Social Shares? (Hint: They're Related, But Not the Way You Think)

Posted by larry.kim

One of the biggest areas of speculation, contention, and confusion within the SEO universe over the past six years or so has been whether (or how much) social media signals impact organic search rankings.

But even if Google isn’t directly using social share counts in their search algorithms, there ought to be some other explanation out there about why high share counts correlate with high organic search rankings.

Well, that is exactly what we’re going to research in this post.

Are social shares a ranking signal?

People have noticed the connection between social shares and ranking going back to 2010. But correlating rankings and social signals has been a bit of a cat-and-mouse game.

If you’ve done any SEO at all, you’ve probably noticed that the stories that rank well tend to have high social share counts.

These are your unicorns – the extremely popular magical pieces of content that drive a ridiculous amount of traffic to your site. These types of elite "unicorn" content drive 10-1000x better results than all your other content (the donkeys).

Why do top-performing posts often also have a high number of shares? What exactly is causing these observable correlations?

Some SEOs believed that Google was somehow factoring social share counts into the algorithm like links (though not with nearly the same amount of weight).

Social shares figured into Moz's Search Engine Ranking Factors 2015, albeit as a low factor:

"Always controversial, the number of social shares a page accumulates tends to show a positive correlation with rankings. Although there is strong reason to believe Google doesn’t use social share counts directly in its algorithm, there are many secondary SEO benefits to be gained through successful social sharing."

Indeed, there is a strong reason to believe Google doesn't use share counts as a direct ranking factor. Google has said so.

Repeatedly and emphatically.

Google doesn't use Facebook, Twitter, or any other social share counts as a direct ranking factor.

It's not shares, it's engagement

We need a new approach to answer these important questions. Maybe we’re looking at the wrong social metrics. Maybe we should be looking at social engagement rates rather than just the total number of social shares.

What percentage of total unique people who saw your update clicked on it and/or shared it?

Perhaps the relationship is that the social posts that get very high engagement rates (which leads to high numbers of shares) come from the same content that get above-average click-through rates in organic search results pages, which we know tends to result in better organic rankings.

But how can we test this theory?

A crazy new correlation study: Social engagement, organic search CTR, & rankings

So here’s my crazy idea: to compare social engagement rates with normalized organic click-through rates for 1,000 pages.

Previous studies have only looked at external-facing number of shares. But bots and other factors can easily taint share counts. Plus, studies have shown that many social media users share content without actually reading it.

How did I do this? I:

• Downloaded post engagement data from Facebook Insights (sharing and engagement data).
• Downloaded query data from Google Search Console (CTR and ranking data).
• Matched up the data. This was somewhat difficult because neither Facebook nor Google provided me with the destination URLs, so some custom programming was required.

Important note: You have to normalize your CTR for search based on position. Obviously higher average positions have higher CTRs than lower positions, so I’ve used my Donkey detection algorithm to compute the expected CTR by position to help determine whether the CTR is above or below expectations.

The results: Organic search CTR vs. Facebook post engagement

Here's what I'd consider a pretty strong link between higher social post engagement and higher organic CTR (and vice-versa):

Here, a 100% Relative Search CTR corresponds to a keyword/page achieving the expected CTR for organic search for a given ranking; 200% percent is double the expected search CTR; 50% is half the expected CTR, and so on.

What I found was that Facebook posts with extraordinarily high engagement rates – anywhere from 6 to 13 percent – also tended to have above expected organic search CTR.

Why? My theory: The same emotions that make people share things also make people click on those things in the SERPs. This is particularly true for headlines with unusually high CTRs.

The correlations were much stronger with unicorn content. The R-squared values were well above 0.5 – the model is stronger the more of an outlier you're pushing. Unicorns with high social engagement rates almost always had high organic CTR, and vice versa.

The correlations were substantially weaker with donkey content. The R-squared values were pretty noisy, around .1 to .4. Donkeys sometimes had high engagement rates, sometimes low engagement rates. The same was true with CTR, some high, some low.

So this research illustrates how high social engagement rates correlate with high CTR, and vice versa.

Really, the argument isn't whether social sharing causes organic search rankings or organic rankings cause social sharing.

It's about how engaging your content is.

Actual examples

Theory is great. But let's see if the theory matches by looking at some top-performing content.

Here are just three examples of posts from my company that have top organic rankings on Google and above-expected organic CTR. What was the engagement rate on Facebook?

This post has brought in nearly 500,000 visits from organic search. It had a 7.4 engagement rate on Facebook.

OK. Once is just a fluke.

This post brought in more than 250,000 visits from organic search. It got an 8.5 engagement rate on Facebook.

Two times? Could just be a coincidence.

This piece brought in 100,000 organic visits. It had a 7.1 percent engagement rate when shared on Facebook.

Guys, now we have a trend! All of these posts that rank well had 3x or 4x higher engagement than my average Facebook post.

I could keep posting more examples like these, but it would be more of the same.

Correlation or causation?

What is causing the correlation? There is one thing that makes me certain that the relationship between social engagement and organic click through rates is a co-dependent, causal relationship.

Machine learning.

Machine learning systems actually reward high engagement with higher visibility.

Higher visibility means higher organic rankings and more social shares.

To determine success, an algorithm looks at whether users engaged. If more people engage, that's a clear sign that their algorithm is showing this right content; if not, their systems will audition other content instead to find something that does generate that interest.

Here's a greatly simplified look at the role machine learning systems play in the Facebook news feed and Google search results. Basically, it's all about rewarding content that has above-expected engagement:

When a piece of content fails to beat the expected engagement, it won't get that same visibility, whether it's on Google, Facebook, or any other system that measures user engagement.

Whenever someone searches on Google for something, Google wants to return the best result. Out of all the potential results Google could show for any given query, Google must find what's most useful and relevant.

One way Google checks itself is to look at organic click-through rate (but not the only way!). Did users click on the result in Position 1, or did more people click on the Position 2 or 3 result?

Even though all three of these pages may answer a user's need, click-through rate is a huge clue about whether Google is providing the best answers in the right order for users.

Now let's think about Facebook. Whenever a piece of content gets hot, it means lots of people are talking about it relative to the number of people who see it, in a short period of time. Are tons of people liking, commenting, and sharing a post?

When this happens, Facebook's machine learning algorithm gives these posts or topics greater visibility. It becomes a virtuous cycle:

• Post gets lots of user engagement (shares, likes, comments).
• Facebook rewards the engagement by showing it to more users.
• Higher visibility results in the post getting lots more user engagement.
• Facebook rewards the engagement by showing it to more users.
• And so on, until the the social post is no longer new and engagement dwindles.

What to do?

Turn your best social stuff into organic content and vice-versa.

Since stuff that does well on organic social tends to also do great in paid social, it follows that your content that gets top organic rankings will make great content for paid and organic social.

Conversely, your content that gets tons of engagement on social media platforms (paid and organic) will likely rank highly organically for the topics that they cover.

These unicorns I've been obsessing about forever matter. Big time. Is your content a sparkly majestic unicorn or a boring old donkey?

At the heart of a unicorn is a truly remarkable, inspiring idea. Truly exciting ideas (not just ideas you think are awesome). Content with remarkably high engagement rates has high conversion rates and does incredibly well in paid and organic search and social media, because of machine learning systems that greatly reward remarkably high user engagement.

Conclusion

The old theory was that high social shares correlates with high organic rankings.

But really it's not the number of shares that matters. It's the engagement rate.

Remarkably high social engagement rates correlate strongly with high organic search CTR, which correlates with high rankings. Meaning, click-through rate matters a great deal. Think of it like an invisible hand that helps determine whether your content succeeds (thumbs up) or fails (thumbs down).

What’s happening here is that Facebook Ads, Facebook's news feed algorithm, Google AdWords, and increasingly Google organic search are all systems governed by machine learning systems that reward remarkable engagement with greater visibility.

High engagement rates and machine learning systems are the common factor that explains the correlation between SEO and social metrics.

What do you think? Do your very best-performing pieces of content get tons of social shares, have a high social engagement rates, and drive a ton of traffic from organic search and convert well?

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Don’t get duped by duplicate content: 8 quick checks for every SEO

Duplicate content can often arise without our knowledge, despite our best efforts to prevent it. Columnist Stephanie LeVonne shows how you can identify and fix it. The post Don’t get duped by duplicate content: 8 quick checks for every SEO appeared first on Search Engine Land.

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Labor Day Google doodle marks holiday honoring the American workforce

Today's Google logo has been switched out with a doodle depicting men and women at work. The post Labor Day Google doodle marks holiday honoring the American workforce appeared first on Search Engine Land.

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10 Things I've Learned Recently About Hiring and Applying for SEO Roles

Posted by bridget.randolph

Here at Distilled NY we’ve been running a hiring cycle, and it’s really brought front and center for me the key elements that make a digital marketing (and specifically SEO) candidate stand out from the crowd. So I wanted to share a few things I’ve learned in the process.

For the purpose of this post, I’m going to tackle this topic from two angles (with 5 points on each, in true "10 Things I’ve Learned…" style):

Part I: 5 attributes I now look for in any new analyst or consultant hire (and what you as an employer might want to think about before making someone an offer), and

Part II: 5 things to consider as a job seeker if you’re applying for a role at a company like Distilled.

I should also note that this post is based on my own personal approach and viewpoint, rather than representing any kind of official Distilled documentation.

What I look for in a new SEO hire

At Distilled, we hire for SEO consultants at two levels — analyst (entry-level) and consultant (3+ years experience). The core elements we look for are the same for each, but for consultants there’s obviously also an expected baseline of technical knowledge.

There are four key skillsets we look for when we evaluate a candidate throughout this process (based on our Distilled manifesto), in addition to their level of technical knowledge.

These are some questions that I've found useful to ask myself (not necessarily the candidate!) when identifying whether someone is a good fit in each of these areas. Note that no single one of these questions will necessarily make or break the outcome, but taken all together they can provide a relatively strong indicator of the level of the candidate in each area:

1. Communication skills

• How well do you express yourself?
• How professional do you seem (both on the phone and/or in person)?
• Are you engaging and enthusiastic?
• How clearly can you tell a story?
• How clearly can you explain a technical concept?
• How clearly can you explain a subject I don’t know anything about?
• Could I trust you to lead a client meeting with confidence? At the C-Suite level?

2. Getting things done

• Can you give me clear examples of being a self-motivated person?
• Do you have any side projects (I don’t really care what they are, but this indicates a self-motivated learner)?
• Can you give me examples of achieving goals or targets?
• Can you give me examples of when you took action that had an impact?

3. Raw smarts and curiosity

Note that what I call "smartness" is not necessarily academic achievement, book learning, etc.

• Teach me about a topic you geek out about. Why?
• Are you a curious person?
• Do you ask questions about ‘why’?
• Did you teach yourself at least part of your marketing skillset? (I have no issue with people learning marketing from a course or degree, but I want to know that you will keep teaching yourself new skills without a teacher grading you or giving you assignments. This question is really about assessing self-starter indicators).

For me, this “smartness” piece really comes down to the curiosity part. I want to work with people who are always asking why, and who get excited about discovering new ideas or learning new skills. These people make great consultants.

4. Culture fit

• Would I be excited to have this person on my team?
• For me, this usually means that they show enthusiasm for the topic of SEO/digital, and that they're a self-motivated learner. Basically, I want to feel that this person is going to push me to up my game, push themselves to constantly get better, and in the process will bring the whole consulting team up with them.
• What sort of work environment are you looking for?
  • We have a relaxed environment at Distilled, but this only works because our employees are self-motivated. If you tell me you’re looking for a flexible work environment, I’ll want to understand why.
  • Is it because you know how you work best, and you want a job that supports your best work? Or is it because you’re lazy? Because I can tell the difference.

5. Technical knowledge

If you’re applying at the consultant level, I will also test your technical knowledge and experience.

Examples of the type of technical questions I’ll ask on the initial phone screen are:

• What’s the biggest site you’ve ever done a technical audit of, in terms of number of pages?
  • Many of our clients have sites with millions of pages, so I want to know that you can handle this scale.
  • If you haven’t worked with a site this size before, it’s not necessarily a dealbreaker, but in that case I want to see that you’re aware that you haven’t worked with a truly massive site, and get a sense that you’d at least have a thought on how to approach this type of site. I once had a candidate respond to this question with an answer along the lines of "Oh yes, I’ve worked with some really big sites, they had, like, thousands of pages." That makes me think that you don’t truly understand the scale that some of our enterprise clients operate at.

• Talk me through your process for a technical SEO audit.
  • What tools do you use?
  • What questions will you ask?
  • What are the issues that you would prioritize?
  • I don’t necessarily expect you to answer the way I would, but I want to see that you understand basic technical SEO principles and that you have a process that is logical and thorough.
• What was your biggest technical win for a client?
  • This gives me insight into how you think about technical priorities and value.
• What is the most common problem that you come across with client websites?
  • This gives me a sense of the kind of experience that you have.
• What do you think the biggest difference will be in SEO in five years’ time?
  • The main things I look for with this question are whether you…
    • Get excited at the opportunity to talk about the future of search
    • Have thoughts on this topic already because you think about/talk about this stuff for fun (curiosity and self-learning, remember?!)
• Rapid-fire round:
  • I say a task, you tell me your preferred tool:
    • Information architecture audit?
    • Keyword research?
    • Site crawl?
    • Content gap analysis?
    • Backlink audit?

There aren’t necessarily any right answers for most of these tasks, but if you don’t mention any of the common tools that we use frequently in the SEO space, even just to tell me why they’re not your tool of choice, that’s a red flag for me that you’re not particularly experienced. Bonus points if you can also tell me why you do or don’t use certain tools.

If a candidate moves forward to an in-person interview, we’ll dig a little deeper on technical expertise. As part of this, we will provide some common client-based scenarios and ask for your process for how you might approach the scenario. There is usually no one right answer, but if it’s a diagnostic problem, there are certain steps or sense-checks I would expect every competent SEO consultant to take before making a recommendation.

For instance, if I give you a scenario around how to handle duplicate content from faceted navigation, where the client has asked for separate pages for 10 color variants of the product across thousands of products, I would expect you to at least mention the following:

• Keyword research
• Handling parameters and crawl budget
• Ideas for how to differentiate identical product description content
• And also being willing and able to challenge, or at least sense-check, client assumptions about what the correct approach might be! In this scenario, for instance, maybe they don’t actually need to have every color variant of the product indexed if the search volume isn’t there.

We will also ask technical questions which do have clear right and wrong answers, to ensure that you have the baseline of knowledge that we would expect an analyst to achieve before we would be able to promote him or her to consultant. These are not always particularly challenging questions, but surprisingly, a lot of candidates get them wrong. An example of this type of question would be something like "Can you explain how Google search works to someone with limited technical knowledge?," "Can you draw an example of a SERP layout on the whiteboard?," or "How would you set up a robots.txt file to block these pages and folders?"

How to be a great SEO candidate (agency-specific)

Of course, all of the above applies equally as an applicant in terms of things to think about in preparation for an SEO interview. In fact, if you're preparing for an interview like this, you may want to think about how you would respond to each of the questions I’ve outlined above, and how you could tell stories that would demonstrate these 5 key attributes that we’re looking for. The four main criteria are pretty universally valuable attributes in any workplace — and they’re also key indicators in my experience of whether a candidate will succeed in this specific type of role, and especially in an agency environment.

But! I promised you 10 things in the title of this post, so here are 5 applicant-specific things I’ve learned recently from seeing the process from the other side:

1. Don’t bullshit.

Be honest if you don’t know something. Especially at the analyst level, we’re looking for people we can train, and honesty about where you’re at is essential to that process.

2. Stay on point.

I need to see that you can communicate clearly with a client and outline the 5 Ws of a recommendation or strategy, without getting lost in unnecessary detail or losing your train of thought.

3. Don’t try to guess what answer I’m looking for.

I want to understand your thought process. It’s obvious when you’re just trying to tell me what I want to hear — because you’re not speaking with authenticity or conviction.

This one ties into the first two, because when you try to guess what I’m looking for, it also makes it harder to stay on point. You end up waffling and um-ing and ah-ing because you’re trying to feel your way to my point of view instead of presenting your own opinion. It’s an easy mistake to make when you get nervous, so a tip for dealing with the nerves is to just take a quick second to breathe before you answer, and check in with yourself about how you really feel about the topic. And if the answer is "I don’t know the answer" — that’s ok. Feel free in that case to talk about how you might approach figuring out the answer, though — if we’re going to be working together I want to know that you’ll be proactive enough to find out the answer, or at least have an idea of where to start when you get stuck!

4. Don’t try to “win” the interview.

Don’t go in with the end game of getting the offer. Go in with a sense of what you’re looking for in your next position and approach this time we’re spending together as an opportunity for us to explore together whether the role and the company is a good fit for you. I’ve made this mistake in both directions, as an interviewee prior to my current role and more recently sometimes as an interviewer (because I want you to like me, too!).

Remember: I really want you to be the perfect fit for what I need! So I’m not out to trip you up — in fact, if I can help you perform well, I will. For instance, if you don’t quite seem to understand the question, or if I don’t quite hear what I was hoping for, I’ll rephrase the question differently to help you see what I’m getting at and see if we can get there together. If you still don’t manage to get there when we give you that support, though, at that point it’s pretty clear that we aren’t a good fit.

5. Do the research.

We once interviewed someone for a sales role, and we asked them if they knew what services Distilled offered. She clearly didn’t know but tried to answer anyway, and went on to guess a couple correctly but then threw in a third service which is not a specialty of ours and is not advertised publicly as a service we provide. To me this showed a basic lack of preparation which I would view as necessary in any sort of consulting or sales-based role, and it was one of the reasons I didn’t recommend moving her forward in the process (although not the only reason).

---

So there you have it — 10 things I’ve learned recently about hiring and applying for SEO jobs!

I hope that you’ve found this post helpful, regardless of which side of the table you’re currently finding yourself on. I’d love to hear your best tips and worst experiences in the comments ;) and if you’re looking for a new opportunity, and this process sounds like something you’d like to explore further, check out our Jobs page for current openings!

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SearchCap: Google algorithm update, SEO business & PPC updates

Below is what happened in search today, as reported on Search Engine Land and from other places across the web. The post SearchCap: Google algorithm update, SEO business & PPC updates appeared first on Search Engine Land.

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Is SEO right for your business?

Search engine optimization (SEO) can deliver strong results for every client, but columnist Marcus Miller explains why it may not be right for every business or every situation. The post Is SEO right for your business? appeared first on Search Engine Land.

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