Why Effective, Modern SEO Requires Technical, Creative, and Strategic Thinking – Whiteboard Friday

Posted by randfish

There’s no doubt that quite a bit has changed about SEO, and that the field is far more integrated with other aspects of online marketing than it once was. In today’s Whiteboard Friday, Rand pushes back against the idea that effective modern SEO doesn’t require any technical expertise, outlining a fantastic list of technical elements that today’s SEOs need to know about in order to be truly effective.

For reference, here’s a still of this week’s whiteboard. Click on it to open a high resolution image in a new tab!

Video transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week I’m going to do something unusual. I don’t usually point out these inconsistencies or sort of take issue with other folks’ content on the web, because I generally find that that’s not all that valuable and useful. But I’m going to make an exception here.

There is an article by Jayson DeMers, who I think might actually be here in Seattle — maybe he and I can hang out at some point — called “Why Modern SEO Requires Almost No Technical Expertise.” It was an article that got a shocking amount of traction and attention. On Facebook, it has thousands of shares. On LinkedIn, it did really well. On Twitter, it got a bunch of attention.

Some folks in the SEO world have already pointed out some issues around this. But because of the increasing popularity of this article, and because I think there’s, like, this hopefulness from worlds outside of kind of the hardcore SEO world that are looking to this piece and going, “Look, this is great. We don’t have to be technical. We don’t have to worry about technical things in order to do SEO.”

Look, I completely get the appeal of that. I did want to point out some of the reasons why this is not so accurate. At the same time, I don’t want to rain on Jayson, because I think that it’s very possible he’s writing an article for Entrepreneur, maybe he has sort of a commitment to them. Maybe he had no idea that this article was going to spark so much attention and investment. He does make some good points. I think it’s just really the title and then some of the messages inside there that I take strong issue with, and so I wanted to bring those up.

First off, some of the good points he did bring up.

One, he wisely says, “You don’t need to know how to code or to write and read algorithms in order to do SEO.” I totally agree with that. If today you’re looking at SEO and you’re thinking, “Well, am I going to get more into this subject? Am I going to try investing in SEO? But I don’t even know HTML and CSS yet.”

Those are good skills to have, and they will help you in SEO, but you don’t need them. Jayson’s totally right. You don’t have to have them, and you can learn and pick up some of these things, and do searches, watch some Whiteboard Fridays, check out some guides, and pick up a lot of that stuff later on as you need it in your career. SEO doesn’t have that hard requirement.

And secondly, he makes an intelligent point that we’ve made many times here at Moz, which is that, broadly speaking, a better user experience is well correlated with better rankings.

You make a great website that delivers great user experience, that provides the answers to searchers’ questions and gives them extraordinarily good content, way better than what’s out there already in the search results, generally speaking you’re going to see happy searchers, and that’s going to lead to higher rankings.

But not entirely. There are a lot of other elements that go in here. So I’ll bring up some frustrating points around the piece as well.

First off, there’s no acknowledgment — and I find this a little disturbing — that the ability to read and write code, or even HTML and CSS, which I think are the basic place to start, is helpful or can take your SEO efforts to the next level. I think both of those things are true.

So being able to look at a web page, view source on it, or pull up Firebug in Firefox or something and diagnose what’s going on and then go, “Oh, that’s why Google is not able to see this content. That’s why we’re not ranking for this keyword or term, or why even when I enter this exact sentence in quotes into Google, which is on our page, this is why it’s not bringing it up. It’s because it’s loading it after the page from a remote file that Google can’t access.” These are technical things, and being able to see how that code is built, how it’s structured, and what’s going on there, very, very helpful.

Some coding knowledge also can take your SEO efforts even further. I mean, so many times, SEOs are stymied by the conversations that we have with our programmers and our developers and the technical staff on our teams. When we can have those conversations intelligently, because at least we understand the principles of how an if-then statement works, or what software engineering best practices are being used, or they can upload something into a GitHub repository, and we can take a look at it there, that kind of stuff is really helpful.

Secondly, I don’t like that the article overly reduces all of this information that we have about what we’ve learned about Google. So he mentions two sources. One is things that Google tells us, and others are SEO experiments. I think both of those are true. Although I’d add that there’s sort of a sixth sense of knowledge that we gain over time from looking at many, many search results and kind of having this feel for why things rank, and what might be wrong with a site, and getting really good at that using tools and data as well. There are people who can look at Open Site Explorer and then go, “Aha, I bet this is going to happen.” They can look, and 90% of the time they’re right.

So he boils this down to, one, write quality content, and two, reduce your bounce rate. Neither of those things are wrong. You should write quality content, although I’d argue there are lots of other forms of quality content that aren’t necessarily written — video, images and graphics, podcasts, lots of other stuff.

And secondly, that just doing those two things is not always enough. So you can see, like many, many folks look and go, “I have quality content. It has a low bounce rate. How come I don’t rank better?” Well, your competitors, they’re also going to have quality content with a low bounce rate. That’s not a very high bar.

Also, frustratingly, this really gets in my craw. I don’t think “write quality content” means anything. You tell me. When you hear that, to me that is a totally non-actionable, non-useful phrase that’s a piece of advice that is so generic as to be discardable. So I really wish that there was more substance behind that.

The article also makes, in my opinion, the totally inaccurate claim that modern SEO really is reduced to “the happier your users are when they visit your site, the higher you’re going to rank.”

Wow. Okay. Again, I think broadly these things are correlated. User happiness and rank is broadly correlated, but it’s not a one to one. This is not like a, “Oh, well, that’s a 1.0 correlation.”

I would guess that the correlation is probably closer to like the page authority range. I bet it’s like 0.35 or something correlation. If you were to actually measure this broadly across the web and say like, “Hey, were you happier with result one, two, three, four, or five,” the ordering would not be perfect at all. It probably wouldn’t even be close.

There’s a ton of reasons why sometimes someone who ranks on Page 2 or Page 3 or doesn’t rank at all for a query is doing a better piece of content than the person who does rank well or ranks on Page 1, Position 1.

Then the article suggests five and sort of a half steps to successful modern SEO, which I think is a really incomplete list. So Jayson gives us;

  • Good on-site experience
  • Writing good content
  • Getting others to acknowledge you as an authority
  • Rising in social popularity
  • Earning local relevance
  • Dealing with modern CMS systems (which he notes most modern CMS systems are SEO-friendly)

The thing is there’s nothing actually wrong with any of these. They’re all, generally speaking, correct, either directly or indirectly related to SEO. The one about local relevance, I have some issue with, because he doesn’t note that there’s a separate algorithm for sort of how local SEO is done and how Google ranks local sites in maps and in their local search results. Also not noted is that rising in social popularity won’t necessarily directly help your SEO, although it can have indirect and positive benefits.

I feel like this list is super incomplete. Okay, I brainstormed just off the top of my head in the 10 minutes before we filmed this video a list. The list was so long that, as you can see, I filled up the whole whiteboard and then didn’t have any more room. I’m not going to bother to erase and go try and be absolutely complete.

But there’s a huge, huge number of things that are important, critically important for technical SEO. If you don’t know how to do these things, you are sunk in many cases. You can’t be an effective SEO analyst, or consultant, or in-house team member, because you simply can’t diagnose the potential problems, rectify those potential problems, identify strategies that your competitors are using, be able to diagnose a traffic gain or loss. You have to have these skills in order to do that.

I’ll run through these quickly, but really the idea is just that this list is so huge and so long that I think it’s very, very, very wrong to say technical SEO is behind us. I almost feel like the opposite is true.

We have to be able to understand things like;

  • Content rendering and indexability
  • Crawl structure, internal links, JavaScript, Ajax. If something’s post-loading after the page and Google’s not able to index it, or there are links that are accessible via JavaScript or Ajax, maybe Google can’t necessarily see those or isn’t crawling them as effectively, or is crawling them, but isn’t assigning them as much link weight as they might be assigning other stuff, and you’ve made it tough to link to them externally, and so they can’t crawl it.
  • Disabling crawling and/or indexing of thin or incomplete or non-search-targeted content. We have a bunch of search results pages. Should we use rel=prev/next? Should we robots.txt those out? Should we disallow from crawling with meta robots? Should we rel=canonical them to other pages? Should we exclude them via the protocols inside Google Webmaster Tools, which is now Google Search Console?
  • Managing redirects, domain migrations, content updates. A new piece of content comes out, replacing an old piece of content, what do we do with that old piece of content? What’s the best practice? It varies by different things. We have a whole Whiteboard Friday about the different things that you could do with that. What about a big redirect or a domain migration? You buy another company and you’re redirecting their site to your site. You have to understand things about subdomain structures versus subfolders, which, again, we’ve done another Whiteboard Friday about that.
  • Proper error codes, downtime procedures, and not found pages. If your 404 pages turn out to all be 200 pages, well, now you’ve made a big error there, and Google could be crawling tons of 404 pages that they think are real pages, because you’ve made it a status code 200, or you’ve used a 404 code when you should have used a 410, which is a permanently removed, to be able to get it completely out of the indexes, as opposed to having Google revisit it and keep it in the index.

Downtime procedures. So there’s specifically a… I can’t even remember. It’s a 5xx code that you can use. Maybe it was a 503 or something that you can use that’s like, “Revisit later. We’re having some downtime right now.” Google urges you to use that specific code rather than using a 404, which tells them, “This page is now an error.”

Disney had that problem a while ago, if you guys remember, where they 404ed all their pages during an hour of downtime, and then their homepage, when you searched for Disney World, was, like, “Not found.” Oh, jeez, Disney World, not so good.

  • International and multi-language targeting issues. I won’t go into that. But you have to know the protocols there. Duplicate content, syndication, scrapers. How do we handle all that? Somebody else wants to take our content, put it on their site, what should we do? Someone’s scraping our content. What can we do? We have duplicate content on our own site. What should we do?
  • Diagnosing traffic drops via analytics and metrics. Being able to look at a rankings report, being able to look at analytics connecting those up and trying to see: Why did we go up or down? Did we have less pages being indexed, more pages being indexed, more pages getting traffic less, more keywords less?
  • Understanding advanced search parameters. Today, just today, I was checking out the related parameter in Google, which is fascinating for most sites. Well, for Moz, weirdly, related:oursite.com shows nothing. But for virtually every other sit, well, most other sites on the web, it does show some really interesting data, and you can see how Google is connecting up, essentially, intentions and topics from different sites and pages, which can be fascinating, could expose opportunities for links, could expose understanding of how they view your site versus your competition or who they think your competition is.

Then there are tons of parameters, like in URL and in anchor, and da, da, da, da. In anchor doesn’t work anymore, never mind about that one.

I have to go faster, because we’re just going to run out of these. Like, come on. Interpreting and leveraging data in Google Search Console. If you don’t know how to use that, Google could be telling you, you have all sorts of errors, and you don’t know what they are.

  • Leveraging topic modeling and extraction. Using all these cool tools that are coming out for better keyword research and better on-page targeting. I talked about a couple of those at MozCon, like MonkeyLearn. There’s the new Moz Context API, which will be coming out soon, around that. There’s the Alchemy API, which a lot of folks really like and use.
  • Identifying and extracting opportunities based on site crawls. You run a Screaming Frog crawl on your site and you’re going, “Oh, here’s all these problems and issues.” If you don’t have these technical skills, you can’t diagnose that. You can’t figure out what’s wrong. You can’t figure out what needs fixing, what needs addressing.
  • Using rich snippet format to stand out in the SERPs. This is just getting a better click-through rate, which can seriously help your site and obviously your traffic.
  • Applying Google-supported protocols like rel=canonical, meta description, rel=prev/next, hreflang, robots.txt, meta robots, x robots, NOODP, XML sitemaps, rel=nofollow. The list goes on and on and on. If you’re not technical, you don’t know what those are, you think you just need to write good content and lower your bounce rate, it’s not going to work.
  • Using APIs from services like AdWords or MozScape, or hrefs from Majestic, or SEM refs from SearchScape or Alchemy API. Those APIs can have powerful things that they can do for your site. There are some powerful problems they could help you solve if you know how to use them. It’s actually not that hard to write something, even inside a Google Doc or Excel, to pull from an API and get some data in there. There’s a bunch of good tutorials out there. Richard Baxter has one, Annie Cushing has one, I think Distilled has some. So really cool stuff there.
  • Diagnosing page load speed issues, which goes right to what Jayson was talking about. You need that fast-loading page. Well, if you don’t have any technical skills, you can’t figure out why your page might not be loading quickly.
  • Diagnosing mobile friendliness issues
  • Advising app developers on the new protocols around App deep linking, so that you can get the content from your mobile apps into the web search results on mobile devices. Awesome. Super powerful. Potentially crazy powerful, as mobile search is becoming bigger than desktop.

Okay, I’m going to take a deep breath and relax. I don’t know Jayson’s intention, and in fact, if he were in this room, he’d be like, “No, I totally agree with all those things. I wrote the article in a rush. I had no idea it was going to be big. I was just trying to make the broader points around you don’t have to be a coder in order to do SEO.” That’s completely fine.

So I’m not going to try and rain criticism down on him. But I think if you’re reading that article, or you’re seeing it in your feed, or your clients are, or your boss is, or other folks are in your world, maybe you can point them to this Whiteboard Friday and let them know, no, that’s not quite right. There’s a ton of technical SEO that is required in 2015 and will be for years to come, I think, that SEOs have to have in order to be effective at their jobs.

All right, everyone. Look forward to some great comments, and we’ll see you again next time for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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Reblogged 4 years ago from tracking.feedpress.it

Case Study: How I Turned Autocomplete Ideas into Traffic & Ranking Results with Only 5 Hours of Effort

Posted by jamiejpress

Many of us have known for a while that Google Autocomplete can be a useful tool for identifying keyword opportunities. But did you know it is also an extremely powerful tool for content ideation?

And by pushing the envelope a little further, you can turn an Autocomplete topic from a good content idea into a link-building, traffic-generating powerhouse for your website.

Here’s how I did it for one of my clients. They are in the diesel power generator industry in the Australian market, but you can use this same process for businesses in literally any industry and market you can think of.

Step 1: Find the spark of an idea using Google Autocomplete

I start by seeking out long-tail keyword ideas from Autocomplete. By typing in some of my client’s core keywords, I come across one that sparked my interest in particular—diesel generator fuel consumption.

What’s more, the Google AdWords Keyword Planner says it is a high competition term. So advertisers are prepared to spend good money on this phrase—all the better to try to rank well organically for the term. We want to get the traffic without incurring the click costs.

keyword_planner.png

Step 2: Check the competition and find an edge

Next, we find out what pages rank well for the phrase, and then identify how we can do better, with user experience top of mind.

In the case of “diesel generator fuel consumption” in Google.com.au, the top-ranking page is this one: a US-focused piece of content using gallons instead of litres.

top_ranking_page.png

This observation, paired with the fact that the #2 Autocomplete suggestion was “diesel generator fuel consumption in litres” gives me the right slant for the content that will give us the edge over the top competing page: Why not create a table using metric measurements instead of imperial measurements for our Australian audience?

So that’s what I do.

I work with the client to gather the information and create the post on the their website. Also, I insert the target phrase in the page title, meta description, URL, and once in the body content. We also create a PDF downloadable with similar content.

client_content.png

Note: While figuring out how to make product/service pages better than those of competitors is the age-old struggle when it comes to working on core SEO keywords, with longer-tail keywords like the ones you work with using this tactic, users generally want detailed information, answers to questions, or implementable tips. So it makes it a little easier to figure out how you can do it better by putting yourself in the user’s shoes.

Step 3: Find the right way to market the content

If people are searching for the term in Google, then there must also be people on forums asking about it.

A quick search through Quora, Reddit and an other forums brings up some relevant threads. I engage with the users in these forums and add non-spammy, helpful no-followed links to our new content in answering their questions.

Caveat: Forum marketing has had a bad reputation for some time, and rightly so, as SEOs have abused the tactic. Before you go linking to your content in forums, I strongly recommend you check out this resource on the right way to engage in forum marketing.

Okay, what about the results?

Since I posted the page in December 2014, referral traffic from the forums has been picking up speed; organic traffic to the page keeps building, too.

referral_traffic.png

organic_traffic.jpg

Yeah, yeah, but what about keyword rankings?

While we’re yet to hit the top-ranking post off its perch (give us time!), we are sitting at #2 and #3 in the search results as I write this. So it looks like creating that downloadable PDF paid off.

ranking.jpg

All in all, this tactic took minimal time to plan and execute—content ideation, research and creation (including the PDF version) took three hours, while link building research and implementation took an additional two hours. That’s only five hours, yet the payoff for the client is already evident, and will continue to grow in the coming months.

Why not take a crack at using this technique yourself? I would love to hear how your ideas about how you could use it to benefit your business or clients.

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Reblogged 4 years ago from tracking.feedpress.it

Big Data, Big Problems: 4 Major Link Indexes Compared

Posted by russangular

Given this blog’s readership, chances are good you will spend some time this week looking at backlinks in one of the growing number of link data tools. We know backlinks continue to be one of, if not the most important
parts of Google’s ranking algorithm. We tend to take these link data sets at face value, though, in part because they are all we have. But when your rankings are on the line, is there a better way to get at which data set is the best? How should we go
about assessing these different link indexes like
Moz,
Majestic, Ahrefs and SEMrush for quality? Historically, there have been 4 common approaches to this question of index quality…

  • Breadth: We might choose to look at the number of linking root domains any given service reports. We know
    that referring domains correlates strongly with search rankings, so it makes sense to judge a link index by how many unique domains it has
    discovered and indexed.
  • Depth: We also might choose to look at how deep the web has been crawled, looking more at the total number of URLs
    in the index, rather than the diversity of referring domains.
  • Link Overlap: A more sophisticated approach might count the number of links an index has in common with Google Webmaster
    Tools.
  • Freshness: Finally, we might choose to look at the freshness of the index. What percentage of links in the index are
    still live?

There are a number of really good studies (some newer than others) using these techniques that are worth checking out when you get a chance:

  • BuiltVisible analysis of Moz, Majestic, GWT, Ahrefs and Search Metrics
  • SEOBook comparison of Moz, Majestic, Ahrefs, and Ayima
  • MatthewWoodward
    study of Ahrefs, Majestic, Moz, Raven and SEO Spyglass
  • Marketing Signals analysis of Moz, Majestic, Ahrefs, and GWT
  • RankAbove comparison of Moz, Majestic, Ahrefs and Link Research Tools
  • StoneTemple study of Moz and Majestic

While these are all excellent at addressing the methodologies above, there is a particular limitation with all of them. They miss one of the
most important metrics we need to determine the value of a link index: proportional representation to Google’s link graph
. So here at Angular Marketing, we decided to take a closer look.

Proportional representation to Google Search Console data

So, why is it important to determine proportional representation? Many of the most important and valued metrics we use are built on proportional
models. PageRank, MozRank, CitationFlow and Ahrefs Rank are proportional in nature. The score of any one URL in the data set is relative to the
other URLs in the data set. If the data set is biased, the results are biased.

A Visualization

Link graphs are biased by their crawl prioritization. Because there is no full representation of the Internet, every link graph, even Google’s,
is a biased sample of the web. Imagine for a second that the picture below is of the web. Each dot represents a page on the Internet,
and the dots surrounded by green represent a fictitious index by Google of certain sections of the web.

Of course, Google isn’t the only organization that crawls the web. Other organizations like Moz,
Majestic, Ahrefs, and SEMrush
have their own crawl prioritizations which result in different link indexes.

In the example above, you can see different link providers trying to index the web like Google. Link data provider 1 (purple) does a good job
of building a model that is similar to Google. It isn’t very big, but it is proportional. Link data provider 2 (blue) has a much larger index,
and likely has more links in common with Google that link data provider 1, but it is highly disproportional. So, how would we go about measuring
this proportionality? And which data set is the most proportional to Google?

Methodology

The first step is to determine a measurement of relativity for analysis. Google doesn’t give us very much information about their link graph.
All we have is what is in Google Search Console. The best source we can use is referring domain counts. In particular, we want to look at
what we call
referring domain link pairs. A referring domain link pair would be something like ask.com->mlb.com: 9,444 which means
that ask.com links to mlb.com 9,444 times.

Steps

  1. Determine the root linking domain pairs and values to 100+ sites in Google Search Console
  2. Determine the same for Ahrefs, Moz, Majestic Fresh, Majestic Historic, SEMrush
  3. Compare the referring domain link pairs of each data set to Google, assuming a
    Poisson Distribution
  4. Run simulations of each data set’s performance against each other (ie: Moz vs Maj, Ahrefs vs SEMrush, Moz vs SEMrush, et al.)
  5. Analyze the results

Results

When placed head-to-head, there seem to be some clear winners at first glance. In head-to-head, Moz edges out Ahrefs, but across the board, Moz and Ahrefs fare quite evenly. Moz, Ahrefs and SEMrush seem to be far better than Majestic Fresh and Majestic Historic. Is that really the case? And why?

It turns out there is an inversely proportional relationship between index size and proportional relevancy. This might seem counterintuitive,
shouldn’t the bigger indexes be closer to Google? Not Exactly.

What does this mean?

Each organization has to create a crawl prioritization strategy. When you discover millions of links, you have to prioritize which ones you
might crawl next. Google has a crawl prioritization, so does Moz, Majestic, Ahrefs and SEMrush. There are lots of different things you might
choose to prioritize…

  • You might prioritize link discovery. If you want to build a very large index, you could prioritize crawling pages on sites that
    have historically provided new links.
  • You might prioritize content uniqueness. If you want to build a search engine, you might prioritize finding pages that are unlike
    any you have seen before. You could choose to crawl domains that historically provide unique data and little duplicate content.
  • You might prioritize content freshness. If you want to keep your search engine recent, you might prioritize crawling pages that
    change frequently.
  • You might prioritize content value, crawling the most important URLs first based on the number of inbound links to that page.

Chances are, an organization’s crawl priority will blend some of these features, but it’s difficult to design one exactly like Google. Imagine
for a moment that instead of crawling the web, you want to climb a tree. You have to come up with a tree climbing strategy.

  • You decide to climb the longest branch you see at each intersection.
  • One friend of yours decides to climb the first new branch he reaches, regardless of how long it is.
  • Your other friend decides to climb the first new branch she reaches only if she sees another branch coming off of it.

Despite having different climb strategies, everyone chooses the same first branch, and everyone chooses the same second branch. There are only
so many different options early on.

But as the climbers go further and further along, their choices eventually produce differing results. This is exactly the same for web crawlers
like Google, Moz, Majestic, Ahrefs and SEMrush. The bigger the crawl, the more the crawl prioritization will cause disparities. This is not a
deficiency; this is just the nature of the beast. However, we aren’t completely lost. Once we know how index size is related to disparity, we
can make some inferences about how similar a crawl priority may be to Google.

Unfortunately, we have to be careful in our conclusions. We only have a few data points with which to work, so it is very difficult to be
certain regarding this part of the analysis. In particular, it seems strange that Majestic would get better relative to its index size as it grows,
unless Google holds on to old data (which might be an important discovery in and of itself). It is most likely that at this point we can’t make
this level of conclusion.

So what do we do?

Let’s say you have a list of domains or URLs for which you would like to know their relative values. Your process might look something like
this…

  • Check Open Site Explorer to see if all URLs are in their index. If so, you are looking metrics most likely to be proportional to Google’s link graph.
  • If any of the links do not occur in the index, move to Ahrefs and use their Ahrefs ranking if all you need is a single PageRank-like metric.
  • If any of the links are missing from Ahrefs’s index, or you need something related to trust, move on to Majestic Fresh.
  • Finally, use Majestic Historic for (by leaps and bounds) the largest coverage available.

It is important to point out that the likelihood that all the URLs you want to check are in a single index increases as the accuracy of the metric
decreases. Considering the size of Majestic’s data, you can’t ignore them because you are less likely to get null value answers from their data than
the others. If anything rings true, it is that once again it makes sense to get data
from as many sources as possible. You won’t
get the most proportional data without Moz, the broadest data without Majestic, or everything in-between without Ahrefs.

What about SEMrush? They are making progress, but they don’t publish any relative statistics that would be useful in this particular
case. Maybe we can hope to see more from them soon given their already promising index!

Recommendations for the link graphing industry

All we hear about these days is big data; we almost never hear about good data. I know that the teams at Moz,
Majestic, Ahrefs, SEMrush and others are interested in mimicking Google, but I would love to see some organization stand up against the
allure of
more data in favor of better data—data more like Google’s. It could begin with testing various crawl strategies to see if they produce
a result more similar to that of data shared in Google Search Console. Having the most Google-like data is certainly a crown worth winning.

Credits

Thanks to Diana Carter at Angular for assistance with data acquisition and Andrew Cron with statistical analysis. Thanks also to the representatives from Moz, Majestic, Ahrefs, and SEMrush for answering questions about their indices.

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Why We Can’t Do Keyword Research Like It’s 2010 – Whiteboard Friday

Posted by randfish

Keyword Research is a very different field than it was just five years ago, and if we don’t keep up with the times we might end up doing more harm than good. From the research itself to the selection and targeting process, in today’s Whiteboard Friday Rand explains what has changed and what we all need to do to conduct effective keyword research today.

For reference, here’s a still of this week’s whiteboard. Click on it to open a high resolution image in a new tab!

What do we need to change to keep up with the changing world of keyword research?

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we’re going to chat a little bit about keyword research, why it’s changed from the last five, six years and what we need to do differently now that things have changed. So I want to talk about changing up not just the research but also the selection and targeting process.

There are three big areas that I’ll cover here. There’s lots more in-depth stuff, but I think we should start with these three.

1) The Adwords keyword tool hides data!

This is where almost all of us in the SEO world start and oftentimes end with our keyword research. We go to AdWords Keyword Tool, what used to be the external keyword tool and now is inside AdWords Ad Planner. We go inside that tool, and we look at the volume that’s reported and we sort of record that as, well, it’s not good, but it’s the best we’re going to do.

However, I think there are a few things to consider here. First off, that tool is hiding data. What I mean by that is not that they’re not telling the truth, but they’re not telling the whole truth. They’re not telling nothing but the truth, because those rounded off numbers that you always see, you know that those are inaccurate. Anytime you’ve bought keywords, you’ve seen that the impression count never matches the count that you see in the AdWords tool. It’s not usually massively off, but it’s often off by a good degree, and the only thing it’s great for is telling relative volume from one from another.

But because AdWords hides data essentially by saying like, “Hey, you’re going to type in . . .” Let’s say I’m going to type in “college tuition,” and Google knows that a lot of people search for how to reduce college tuition, but that doesn’t come up in the suggestions because it’s not a commercial term, or they don’t think that an advertiser who bids on that is going to do particularly well and so they don’t show it in there. I’m giving an example. They might indeed show that one.

But because that data is hidden, we need to go deeper. We need to go beyond and look at things like Google Suggest and related searches, which are down at the bottom. We need to start conducting customer interviews and staff interviews, which hopefully has always been part of your brainstorming process but really needs to be now. Then you can apply that to AdWords. You can apply that to suggest and related.

The beautiful thing is once you get these tools from places like visiting forums or communities, discussion boards and seeing what terms and phrases people are using, you can collect all this stuff up, plug it back into AdWords, and now they will tell you how much volume they’ve got. So you take that how to lower college tuition term, you plug it into AdWords, they will show you a number, a non-zero number. They were just hiding it in the suggestions because they thought, “Hey, you probably don’t want to bid on that. That won’t bring you a good ROI.” So you’ve got to be careful with that, especially when it comes to SEO kinds of keyword research.

2) Building separate pages for each term or phrase doesn’t make sense

It used to be the case that we built separate pages for every single term and phrase that was in there, because we wanted to have the maximum keyword targeting that we could. So it didn’t matter to us that college scholarship and university scholarships were essentially people looking for exactly the same thing, just using different terminology. We would make one page for one and one page for the other. That’s not the case anymore.

Today, we need to group by the same searcher intent. If two searchers are searching for two different terms or phrases but both of them have exactly the same intent, they want the same information, they’re looking for the same answers, their query is going to be resolved by the same content, we want one page to serve those, and that’s changed up a little bit of how we’ve done keyword research and how we do selection and targeting as well.

3) Build your keyword consideration and prioritization spreadsheet with the right metrics

Everybody’s got an Excel version of this, because I think there’s just no awesome tool out there that everyone loves yet that kind of solves this problem for us, and Excel is very, very flexible. So we go into Excel, we put in our keyword, the volume, and then a lot of times we almost stop there. We did keyword volume and then like value to the business and then we prioritize.

What are all these new columns you’re showing me, Rand? Well, here I think is how sophisticated, modern SEOs that I’m seeing in the more advanced agencies, the more advanced in-house practitioners, this is what I’m seeing them add to the keyword process.

Difficulty

A lot of folks have done this, but difficulty helps us say, “Hey, this has a lot of volume, but it’s going to be tremendously hard to rank.”

The difficulty score that Moz uses and attempts to calculate is a weighted average of the top 10 domain authorities. It also uses page authority, so it’s kind of a weighted stack out of the two. If you’re seeing very, very challenging pages, very challenging domains to get in there, it’s going to be super hard to rank against them. The difficulty is high. For all of these ones it’s going to be high because college and university terms are just incredibly lucrative.

That difficulty can help bias you against chasing after terms and phrases for which you are very unlikely to rank for at least early on. If you feel like, “Hey, I already have a powerful domain. I can rank for everything I want. I am the thousand pound gorilla in my space,” great. Go after the difficulty of your choice, but this helps prioritize.

Opportunity

This is actually very rarely used, but I think sophisticated marketers are using it extremely intelligently. Essentially what they’re saying is, “Hey, if you look at a set of search results, sometimes there are two or three ads at the top instead of just the ones on the sidebar, and that’s biasing some of the click-through rate curve.” Sometimes there’s an instant answer or a Knowledge Graph or a news box or images or video, or all these kinds of things that search results can be marked up with, that are not just the classic 10 web results. Unfortunately, if you’re building a spreadsheet like this and treating every single search result like it’s just 10 blue links, well you’re going to lose out. You’re missing the potential opportunity and the opportunity cost that comes with ads at the top or all of these kinds of features that will bias the click-through rate curve.

So what I’ve seen some really smart marketers do is essentially build some kind of a framework to say, “Hey, you know what? When we see that there’s a top ad and an instant answer, we’re saying the opportunity if I was ranking number 1 is not 10 out of 10. I don’t expect to get whatever the average traffic for the number 1 position is. I expect to get something considerably less than that. Maybe something around 60% of that, because of this instant answer and these top ads.” So I’m going to mark this opportunity as a 6 out of 10.

There are 2 top ads here, so I’m giving this a 7 out of 10. This has two top ads and then it has a news block below the first position. So again, I’m going to reduce that click-through rate. I think that’s going down to a 6 out of 10.

You can get more and less scientific and specific with this. Click-through rate curves are imperfect by nature because we truly can’t measure exactly how those things change. However, I think smart marketers can make some good assumptions from general click-through rate data, which there are several resources out there on that to build a model like this and then include it in their keyword research.

This does mean that you have to run a query for every keyword you’re thinking about, but you should be doing that anyway. You want to get a good look at who’s ranking in those search results and what kind of content they’re building . If you’re running a keyword difficulty tool, you are already getting something like that.

Business value

This is a classic one. Business value is essentially saying, “What’s it worth to us if visitors come through with this search term?” You can get that from bidding through AdWords. That’s the most sort of scientific, mathematically sound way to get it. Then, of course, you can also get it through your own intuition. It’s better to start with your intuition than nothing if you don’t already have AdWords data or you haven’t started bidding, and then you can refine your sort of estimate over time as you see search visitors visit the pages that are ranking, as you potentially buy those ads, and those kinds of things.

You can get more sophisticated around this. I think a 10 point scale is just fine. You could also use a one, two, or three there, that’s also fine.

Requirements or Options

Then I don’t exactly know what to call this column. I can’t remember the person who’ve showed me theirs that had it in there. I think they called it Optional Data or Additional SERPs Data, but I’m going to call it Requirements or Options. Requirements because this is essentially saying, “Hey, if I want to rank in these search results, am I seeing that the top two or three are all video? Oh, they’re all video. They’re all coming from YouTube. If I want to be in there, I’ve got to be video.”

Or something like, “Hey, I’m seeing that most of the top results have been produced or updated in the last six months. Google appears to be biasing to very fresh information here.” So, for example, if I were searching for “university scholarships Cambridge 2015,” well, guess what? Google probably wants to bias to show results that have been either from the official page on Cambridge’s website or articles from this year about getting into that university and the scholarships that are available or offered. I saw those in two of these search results, both the college and university scholarships had a significant number of the SERPs where a fresh bump appeared to be required. You can see that a lot because the date will be shown ahead of the description, and the date will be very fresh, sometime in the last six months or a year.

Prioritization

Then finally I can build my prioritization. So based on all the data I had here, I essentially said, “Hey, you know what? These are not 1 and 2. This is actually 1A and 1B, because these are the same concepts. I’m going to build a single page to target both of those keyword phrases.” I think that makes good sense. Someone who is looking for college scholarships, university scholarships, same intent.

I am giving it a slight prioritization, 1A versus 1B, and the reason I do this is because I always have one keyword phrase that I’m leaning on a little more heavily. Because Google isn’t perfect around this, the search results will be a little different. I want to bias to one versus the other. In this case, my title tag, since I more targeting university over college, I might say something like college and university scholarships so that university and scholarships are nicely together, near the front of the title, that kind of thing. Then 1B, 2, 3.

This is kind of the way that modern SEOs are building a more sophisticated process with better data, more inclusive data that helps them select the right kinds of keywords and prioritize to the right ones. I’m sure you guys have built some awesome stuff. The Moz community is filled with very advanced marketers, probably plenty of you who’ve done even more than this.

I look forward to hearing from you in the comments. I would love to chat more about this topic, and we’ll see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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Reblogged 4 years ago from tracking.feedpress.it

Has Google Gone Too Far with the Bias Toward Its Own Content?

Posted by ajfried

Since the beginning of SEO time, practitioners have been trying to crack the Google algorithm. Every once in a while, the industry gets a glimpse into how the search giant works and we have opportunity to deconstruct it. We don’t get many of these opportunities, but when we do—assuming we spot them in time—we try to take advantage of them so we can “fix the Internet.”

On Feb. 16, 2015, news started to circulate that NBC would start removing images and references of Brian Williams from its website.

This was it!

A golden opportunity.

This was our chance to learn more about the Knowledge Graph.

Expectation vs. reality

Often it’s difficult to predict what Google is truly going to do. We expect something to happen, but in reality it’s nothing like we imagined.

Expectation

What we expected to see was that Google would change the source of the image. Typically, if you hover over the image in the Knowledge Graph, it reveals the location of the image.

Keanu-Reeves-Image-Location.gif

This would mean that if the image disappeared from its original source, then the image displayed in the Knowledge Graph would likely change or even disappear entirely.

Reality (February 2015)

The only problem was, there was no official source (this changed, as you will soon see) and identifying where the image was coming from proved extremely challenging. In fact, when you clicked on the image, it took you to an image search result that didn’t even include the image.

Could it be? Had Google started its own database of owned or licensed images and was giving it priority over any other sources?

In order to find the source, we tried taking the image from the Knowledge Graph and “search by image” in images.google.com to find others like it. For the NBC Nightly News image, Google failed to even locate a match to the image it was actually using anywhere on the Internet. For other television programs, it was successful. Here is an example of what happened for Morning Joe:

Morning_Joe_image_search.png

So we found the potential source. In fact, we found three potential sources. Seemed kind of strange, but this seemed to be the discovery we were looking for.

This looks like Google is using someone else’s content and not referencing it. These images have a source, but Google is choosing not to show it.

Then Google pulled the ol’ switcheroo.

New reality (March 2015)

Now things changed and Google decided to put a source to their images. Unfortunately, I mistakenly assumed that hovering over an image showed the same thing as the file path at the bottom, but I was wrong. The URL you see when you hover over an image in the Knowledge Graph is actually nothing more than the title. The source is different.

Morning_Joe_Source.png

Luckily, I still had two screenshots I took when I first saw this saved on my desktop. Success. One screen capture was from NBC Nightly News, and the other from the news show Morning Joe (see above) showing that the source was changed.

NBC-nightly-news-crop.png

(NBC Nightly News screenshot.)

The source is a Google-owned property: gstatic.com. You can clearly see the difference in the source change. What started as a hypothesis in now a fact. Google is certainly creating a database of images.

If this is the direction Google is moving, then it is creating all kinds of potential risks for brands and individuals. The implications are a loss of control for any brand that is looking to optimize its Knowledge Graph results. As well, it seems this poses a conflict of interest to Google, whose mission is to organize the world’s information, not license and prioritize it.

How do we think Google is supposed to work?

Google is an information-retrieval system tasked with sourcing information from across the web and supplying the most relevant results to users’ searches. In recent months, the search giant has taken a more direct approach by answering questions and assumed questions in the Answer Box, some of which come from un-credited sources. Google has clearly demonstrated that it is building a knowledge base of facts that it uses as the basis for its Answer Boxes. When it sources information from that knowledge base, it doesn’t necessarily reference or credit any source.

However, I would argue there is a difference between an un-credited Answer Box and an un-credited image. An un-credited Answer Box provides a fact that is indisputable, part of the public domain, unlikely to change (e.g., what year was Abraham Lincoln shot? How long is the George Washington Bridge?) Answer Boxes that offer more than just a basic fact (or an opinion, instructions, etc.) always credit their sources.

There are four possibilities when it comes to Google referencing content:

  • Option 1: It credits the content because someone else owns the rights to it
  • Option 2: It doesn’t credit the content because it’s part of the public domain, as seen in some Answer Box results
  • Option 3: It doesn’t reference it because it owns or has licensed the content. If you search for “Chicken Pox” or other diseases, Google appears to be using images from licensed medical illustrators. The same goes for song lyrics, which Eric Enge discusses here: Google providing credit for content. This adds to the speculation that Google is giving preference to its own content by displaying it over everything else.
  • Option 4: It doesn’t credit the content, but neither does it necessarily own the rights to the content. This is a very gray area, and is where Google seemed to be back in February. If this were the case, it would imply that Google is “stealing” content—which I find hard to believe, but felt was necessary to include in this post for the sake of completeness.

Is this an isolated incident?

At Five Blocks, whenever we see these anomalies in search results, we try to compare the term in question against others like it. This is a categorization concept we use to bucket individuals or companies into similar groups. When we do this, we uncover some incredible trends that help us determine what a search result “should” look like for a given group. For example, when looking at searches for a group of people or companies in an industry, this grouping gives us a sense of how much social media presence the group has on average or how much media coverage it typically gets.

Upon further investigation of terms similar to NBC Nightly News (other news shows), we noticed the un-credited image scenario appeared to be a trend in February, but now all of the images are being hosted on gstatic.com. When we broadened the categories further to TV shows and movies, the trend persisted. Rather than show an image in the Knowledge Graph and from the actual source, Google tends to show an image and reference the source from Google’s own database of stored images.

And just to ensure this wasn’t a case of tunnel vision, we researched other categories, including sports teams, actors and video games, in addition to spot-checking other genres.

Unlike terms for specific TV shows and movies, terms in each of these other groups all link to the actual source in the Knowledge Graph.

Immediate implications

It’s easy to ignore this and say “Well, it’s Google. They are always doing something.” However, there are some serious implications to these actions:

  1. The TV shows/movies aren’t receiving their due credit because, from within the Knowledge Graph, there is no actual reference to the show’s official site
  2. The more Google moves toward licensing and then retrieving their own information, the more biased they become, preferring their own content over the equivalent—or possibly even superior—content from another source
  3. If feels wrong and misleading to get a Google Image Search result rather than an actual site because:
    • The search doesn’t include the original image
    • Considering how poor Image Search results are normally, it feels like a poor experience
  4. If Google is moving toward licensing as much content as possible, then it could make the Knowledge Graph infinitely more complicated when there is a “mistake” or something unflattering. How could one go about changing what Google shows about them?

Google is objectively becoming subjective

It is clear that Google is attempting to create databases of information, including lyrics stored in Google Play, photos, and, previously, facts in Freebase (which is now Wikidata and not owned by Google).

I am not normally one to point my finger and accuse Google of wrongdoing. But this really strikes me as an odd move, one bordering on a clear bias to direct users to stay within the search engine. The fact is, we trust Google with a heck of a lot of information with our searches. In return, I believe we should expect Google to return an array of relevant information for searchers to decide what they like best. The example cited above seems harmless, but what about determining which is the right religion? Or even who the prettiest girl in the world is?

Religion-and-beauty-queries.png

Questions such as these, which Google is returning credited answers for, could return results that are perceived as facts.

Should we next expect Google to decide who is objectively the best service provider (e.g., pizza chain, painter, or accountant), then feature them in an un-credited answer box? The direction Google is moving right now, it feels like we should be calling into question their objectivity.

But that’s only my (subjective) opinion.

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Reblogged 4 years ago from tracking.feedpress.it

Simple Steps for Conducting Creative Content Research

Posted by Hannah_Smith

Most frequently, the content we create at Distilled is designed to attract press coverage, social shares, and exposure (and links) on sites our clients’ target audience reads. That’s a tall order.

Over the years we’ve had our hits and misses, and through this we’ve recognised the value of learning about what makes a piece of content successful. Coming up with a great idea is difficult, and it can be tough to figure out where to begin. Today, rather than leaping headlong into brainstorming sessions, we start with creative content research.

What is creative content research?

Creative content research enables you to answer the questions:

“What are websites publishing, and what are people sharing?”

From this, you’ll then have a clearer view on what might be successful for your client.

A few years ago this required quite an amount of work to figure out. Today, happily, it’s much quicker and easier. In this post I’ll share the process and tools we use.

Whoa there… Why do I need to do this?

I think that the value in this sort of activity lies in a couple of directions:

a) You can learn a lot by deconstructing the success of others…

I’ve been taking stuff apart to try to figure out how it works for about as long as I can remember, so applying this process to content research felt pretty natural to me. Perhaps more importantly though, I think that deconstructing content is actually easier when it isn’t your own. You’re not involved, invested, or in love with the piece so viewing it objectively and learning from it is much easier.

b) Your research will give you a clear overview of the competitive landscape…

As soon as a company elects to start creating content, they gain a whole raft of new competitors. In addition to their commercial competitors (i.e. those who offer similar products or services), the company also gains content competitors. For example, if you’re a sports betting company and plan to create content related to the sports events that you’re offering betting markets on; then you’re competing not just with other betting companies, but every other publisher who creates content about these events. That means major news outlets, sports news site, fan sites, etc. To make matters even more complicated, it’s likely that you’ll actually be seeking coverage from those same content competitors. As such, you need to understand what’s already being created in the space before creating content of your own.

c) You’re giving yourself the data to create a more compelling pitch…

At some point you’re going to need to pitch your ideas to your client (or your boss if you’re working in-house). At Distilled, we’ve found that getting ideas signed off can be really tough. Ultimately, a great idea is worthless if we can’t persuade our client to give us the green light. This research can be used to make a more compelling case to your client and get those ideas signed off. (Incidentally, if getting ideas signed off is proving to be an issue you might find this framework for pitching creative ideas useful).

Where to start

Good ideas start with a good brief, however it can be tough to pin clients down to get answers to a long list of questions.

As a minimum you’ll need to know the following:

  • Who are they looking to target?
    • Age, sex, demographic
    • What’s their core focus? What do they care about? What problems are they looking to solve?
    • Who influences them?
    • What else are they interested in?
    • Where do they shop and which brands do they buy?
    • What do they read?
    • What do they watch on TV?
    • Where do they spend their time online?
  • Where do they want to get coverage?
    • We typically ask our clients to give us a wishlist of 10 or so sites they’d love to get coverage on
  • Which topics are they comfortable covering?
    • This question is often the toughest, particularly if a client hasn’t created content specifically for links and shares before. Often clients are uncomfortable about drifting too far away from their core business—for example, if they sell insurance, they’ll typically say that they really want to create a piece of content about insurance. Whilst this is understandable from the clients’ perspective it can severely limit their chances of success. It’s definitely worth offering up a gentle challenge at this stage—I’ll often cite Red Bull, who are a great example of a company who create content based on what their consumers love, not what they sell (i.e. Red Bull sell soft drinks, but create content about extreme sports because that’s the sort of content their audience love to consume). It’s worth planting this idea early, but don’t get dragged into a fierce debate at this stage—you’ll be able to make a far more compelling argument once you’ve done your research and are pitching concrete ideas.

Processes, useful tools and sites

Now you have your brief, it’s time to begin your research.

Given that we’re looking to uncover “what websites are publishing and what’s being shared,” It won’t surprise you to learn that I pay particular attention to pieces of content and the coverage they receive. For each piece that I think is interesting I’ll note down the following:

  • The title/headline
  • A link to the coverage (and to the original piece if applicable)
  • How many social shares the coverage earned (and the original piece earned)
  • The number of linking root domains the original piece earned
  • Some notes about the piece itself: why it’s interesting, why I think it got shares/coverage
  • Any gaps in the content, whether or not it’s been executed well
  • How we might do something similar (if applicable)

Whilst I’m doing this I’ll also make a note of specific sites I see being frequently shared (I tend to check these out separately later on), any interesting bits of research (particularly if I think there might be an opportunity to do something different with the data), interesting threads on forums etc.

When it comes to kicking off your research, you can start wherever you like, but I’d recommend that you cover off each of the areas below:

What does your target audience share?

Whilst this activity might not uncover specific pieces of successful content, it’s a great way of getting a clearer understanding of your target audience, and getting a handle on the sites they read and the topics which interest them.

  • Review social profiles / feeds
    • If the company you’re working for has a Facebook page, it shouldn’t be too difficult to find some people who’ve liked the company page and have a public profile. It’s even easier on Twitter where most profiles are public. Whilst this won’t give you quantitative data, it does put a human face to your audience data and gives you a feel for what these people care about and share. In addition to uncovering specific pieces of content, this can also provide inspiration in terms of other sites you might want to investigate further and ideas for topics you might want to explore.
  • Demographics Pro
    • This service infers demographic data from your clients’ Twitter followers. I find it particularly useful if the client doesn’t know too much about their audience. In addition to demographic data, you get a breakdown of professions, interests, brand affiliations, and the other Twitter accounts they follow and who they’re most influenced by. This is a paid-for service, but there are pay-as-you-go options in addition to pay monthly plans.

Finding successful pieces of content on specific sites

If you’ve a list of sites you know your target audience read, and/or you know your client wants to get coverage on, there are a bunch of ways you can uncover interesting content:

  • Using your link research tool of choice (e.g. Open Site Explorer, Majestic, ahrefs) you can run a domain level report to see which pages have attracted the most links. This can also be useful if you want to check out commercial competitors to see which pieces of content they’ve created have attracted the most links.
  • There are also tools which enable you to uncover the most shared content on individual sites. You can use Buzzsumo to run content analysis reports on individual domains which provide data on average social shares per post, social shares by network, and social shares by content type.
  • If you just want to see the most shared content for a given domain you can run a simple search on Buzzsumo using the domain; and there’s also the option to refine by topic. For example a search like [guardian.com big data] will return the most shared content on the Guardian related to big data. You can also run similar reports using ahrefs’ Content Explorer tool.

Both Buzzsumo and ahrefs are paid tools, but both offer free trials. If you need to explore the most shared content without using a paid tool, there are other alternatives. Check out Social Crawlytics which will crawl domains and return social share data, or alternatively, you can crawl a site (or section of a site) and then run the URLs through SharedCount‘s bulk upload feature.

Finding successful pieces of content by topic

When searching by topic, I find it best to begin with a broad search and then drill down into more specific areas. For example, if I had a client in the financial services space, I’d start out looking at a broad topic like “money” rather than shooting straight to topics like loans or credit cards.

As mentioned above, both Buzzsumo and ahrefs allow you to search for the most shared content by topic and both offer advanced search options.

Further inspiration

There are also several sites I like to look at for inspiration. Whilst these sites don’t give you a great steer on whether or not a particular piece of content was actually successful, with a little digging you can quickly find the original source and pull link and social share data:

  • Visually has a community area where users can upload creative content. You can search by topic to uncover examples.
  • TrendHunter have a searchable archive of creative ideas, they feature products, creative campaigns, marketing campaigns, advertising and more. It’s best to keep your searches broad if you’re looking at this site.
  • Check out Niice (a moodboard app) which also has a searchable archive of handpicked design inspiration.
  • Searching Pinterest can allow you to unearth some interesting bits and pieces as can Google image searches and regular Google searches around particular topics.
  • Reviewing relevant sections of discussion sites like Quora can provide insight into what people are asking about particular topics which may spark a creative idea.

Moving from data to insight

By this point you’ve (hopefully) got a long list of content examples. Whilst this is a great start, effectively what you’ve got here is just data, now you need to convert this to insight.

Remember, we’re trying to answer the questions: “What are websites publishing, and what are people sharing?”

Ordinarily as I go through the creative content research process, I start to see patterns or themes emerge. For example, across a variety of topics areas you’ll see that the most shared content tends to be news. Whilst this is good to know, it’s not necessarily something that’s going to be particularly actionable. You’ll need to dig a little deeper—what else (aside from news) is given coverage? Can you split those things into categories or themes?

This is tough to explain in the abstract, so let me give you an example. We’d identified a set of music sites (e.g. Rolling Stone, NME, CoS, Stereogum, Pitchfork) as target publishers for a client.

Here’s a summary of what I concluded following my research:

The most-shared content on these music publications is news: album launches, new singles, videos of performances etc. As such, if we can work a news hook into whatever we create, this could positively influence our chances of gaining coverage.

Aside from news, the content which gains traction tends to fall into one of the following categories:

Earlier in this post I mentioned that it can be particularly tough to create content which attracts coverage and shares if clients feel strongly that they want to do something directly related to their product or service. The example I gave at the outset was a client who sold insurance and was really keen to create something about insurance. You’re now in a great position to win an argument with data, as thanks to your research you’ll be able to cite several pieces of insurance-related content which have struggled to gain traction. But it’s not all bad news as you’ll also be able to cite other topics which are relevant to the client’s target audience and stand a better chance of gaining coverage and shares.

Avoiding the pitfalls

There are potential pitfalls when it comes to creative content research in that it’s easy to leap to erroneous conclusions. Here’s some things to watch out for:

Make sure you’re identifying outliers…

When seeking out successful pieces of content you need to be certain that what you’re looking at is actually an outlier. For example, the average post on BuzzFeed gets over 30k social shares. As such, that post you found with just 10k shares is not an outlier. It’s done significantly worse than average. It’s therefore not the best post to be holding up as a fabulous example of what to create to get shares.

Don’t get distracted by formats…

Pay more attention to the idea than the format. For example, the folks at Mashable, kindly covered an infographic about Instagram which we created for a client. However, the takeaway here is not that Instagram infographics get coverage on Mashable. Mashable didn’t cover this because we created an infographic. They covered the piece because it told a story in a compelling and unusual way.

You probably shouldn’t create a listicle…

This point is related to the point above. In my experience, unless you’re a publisher with a huge, engaged social following, that listicle of yours is unlikely to gain traction. Listicles on huge publisher sites get shares, listicles on client sites typically don’t. This is doubly important if you’re also seeking coverage, as listicles on clients sites don’t typically get links or coverage on other sites.

How we use the research to inform our ideation process

At Distilled, we typically take a creative brief and complete creative content research and then move into the ideation process. A summary of the research is included within the creative brief, and this, along with a copy of the full creative content research is shared with the team.

The research acts as inspiration and direction and is particularly useful in terms of identifying potential topics to explore but doesn’t mean team members don’t still do further research of their own.

This process by no means acts as a silver bullet, but it definitely helps us come up with ideas.


Thanks for sticking with me to the end!

I’d love to hear more about your creative content research processes and any tips you have for finding inspirational content. Do let me know via the comments.

Image credits: Research, typing, audience, inspiration, kitteh.

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Why Good Unique Content Needs to Die – Whiteboard Friday

Posted by randfish

We all know by now that not just any old content is going to help us rank in competitive SERPs. We often hear people talking about how it takes “good, unique content.” That’s the wrong bar. In today’s Whiteboard Friday, Rand talks about where we should be aiming, and how to get there.

For reference, here’s a still of this week’s whiteboard. Click on it to open a high resolution image in a new tab!

Video transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we’re going to chat about something that I really have a problem with in the SEO world, and that is the phrase “good, unique content.” I’ll tell you why this troubles me so much. It’s because I get so many emails, I hear so many times at conferences and events with people I meet, with folks I talk to in the industry saying, “Hey, we created some good, unique content, but we don’t seem to be performing well in search.” My answer back to that is always that is not the bar for entry into SEO. That is not the bar for ranking.

The content quality scale

So I made this content quality scale to help illustrate what I’m talking about here. You can see that it starts all the way up at 10x, and down here I’ve got Panda Invasion. So quality, like Google Panda is coming for your site, it’s going to knock you out of the rankings. It’s going to penalize you, like your content is thin and largely useless.

Then you go up a little bit, and it’s like, well four out of five searchers find it pretty bad. They clicked the Back button. Maybe one out of five is thinking, “Well, this is all right. This solves my most basic problems.”

Then you get one level higher than that, and you have good, unique content, which I think many folks think of as where they need to get to. It’s essentially, hey, it’s useful enough. It answers the searcher’s query. It’s unique from any other content on the Web. If you read it, you wouldn’t vomit. It’s good enough, right? Good, unique content.

Problem is almost everyone can get here. They really can. It’s not a high bar, a high barrier to entry to say you need good, unique content. In fact, it can scale. So what I see lots of folks doing is they look at a search result or a set of search results in their industry. Say you’re in travel and vacations, and you look at these different countries and you’re going to look at the hotels or recommendations in those countries and then see all the articles there. You go, “Yeah, you know what, I think we could do something as good as what’s up there or almost.” Well, okay, that puts you in the range. That’s good, unique content.

But in my opinion, the minimum bar today for modern SEO is a step higher, and that is as good as the best in the search results on the search results page. If you can’t consistently say, “We’re the best result that a searcher could find in the search results,” well then, guess what? You’re not going to have an opportunity to rank. It’s much, much harder to get into those top 10 positions, page 1, page 2 positions than it was in the past because there are so many ranking signals that so many of these websites have already built up over the last 5, 10, 15 years that you need to go above and beyond.

Really, where I want folks to go and where I always expect content from Moz to go is here, and that is 10x, 10 times better than anything I can find in the search results today. If I don’t think I can do that, then I’m not going to try and rank for those keywords. I’m just not going to pursue it. I’m going to pursue content in areas where I believe I can create something 10 times better than the best result out there.

What changed?

Why is this? What changed? Well, a bunch of things actually.

  • User experience became a much bigger element in the ranking algorithms, and that’s direct influences, things that we’ve talked about here on Whiteboard Friday before like pogo-sticking, and lots of indirect ones like the links that you earn based on the user experience that you provide and Google rendering pages, Google caring about load speed and device rendering, mobile friendliness, all these kinds of things.
  • Earning links overtook link building. It used to be you put out a page and you built a bunch of links to it. Now that doesn’t so much work anymore because Google is very picky about the links that it’s going to consider. If you can’t earn links naturally, not only can you not get links fast enough and not get good ones, but you also are probably earning links that Google doesn’t even want to count or may even penalize you for. It’s nearly impossible to earn links with just good, unique content. If there’s something better out there on page one of the search results, why would they even bother to link to you? Someone’s going to do a search, and they’re going to find something else to link to, something better.
  • Third, the rise of content marketing over the last five, six years has meant that there’s just a lot more competition. This field is a lot more crowded than it used to be, with many people trying to get to a higher and higher quality bar.
  • Finally, as a result of many of these things, user expectations have gone crazy. Users expect pages to load insanely fast, even on mobile devices, even when their connection’s slow. They expect it to look great. They expect to be provided with an answer almost instantaneously. The quality of results that Google has delivered and the quality of experience that sites like Facebook, which everyone is familiar with, are delivering means that our brains have rewired themselves to expect very fast, very high quality results consistently.

How do we create “10x” content?

So, because of all these changes, we need a process. We need a process to choose, to figure out how we can get to 10x content, not good, unique content, 10x content. A process that I often like to use — this probably is not the only one, but you’re welcome to use it if you find it valuable — is to go, “All right, you know what? I’m going to perform some of these search queries.”

By the way, I would probably perform the search query in two places. One is in Google and their search results, and the other is actually in BuzzSumo, which I think is a great tool for this, where I can see the content that has been most shared. So if you haven’t already, check out BuzzSumo.com.

I might search for something like Costa Rica ecolodges, which I might be considering a Costa Rica vacation at some point in the future. I look at these top ranking results, probably the whole top 10 as well as the most shared content on social media.

Then I’m going to ask myself these questions;

  • What questions are being asked and answered by these search results?
  • What sort of user experience is provided? I look at this in terms of speed, in terms of mobile friendliness, in terms of rendering, in terms of layout and design quality, in terms of what’s required from the user to be able to get the information? Is it all right there, or do I need to click? Am I having trouble finding things?
  • What’s the detail and thoroughness of the information that’s actually provided? Is it lacking? Is it great?
  • What about use of visuals? Visual content can often take best in class all the way up to 10x if it’s done right. So I might check out the use of visuals.
  • The quality of the writing.
  • I’m going to look at information and data elements. Where are they pulling from? What are their sources? What’s the quality of that stuff? What types of information is there? What types of information is missing?

In fact, I like to ask, “What’s missing?” a lot.

From this, I can determine like, hey, here are the strengths and weaknesses of who’s getting all of the social shares and who’s ranking well, and here’s the delta between me and them today. This is the way that I can be 10 times better than the best results in there.

If you use this process or a process like this and you do this type of content auditing and you achieve this level of content quality, you have a real shot at rankings. One of the secret reasons for that is that the effort axis that I have here, like I go to Fiverr, I get Panda invasion. I make the intern write it. This is going to take a weekend to build versus there’s no way to scale this content.

This is a super power. When your competitors or other folks in the field look and say, “Hey, there’s no way that we can scale content quality like this. It’s just too much effort. We can’t keep producing it at this level,” well, now you have a competitive advantage. You have something that puts you in a category by yourself and that’s very hard for competitors to catch up to. It’s a huge advantage in search, in social, on the Web as a whole.

All right everyone, hope you’ve enjoyed this edition of Whiteboard Friday, and we’ll see you again next week. Take care.

Video transcription by Speechpad.com

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Reblogged 4 years ago from tracking.feedpress.it