SearchCap: Google Knowledge Graph, Schema Markup & Local SEO

Below is what happened in search today, as reported on Search Engine Land and from other places across the web.

The post SearchCap: Google Knowledge Graph, Schema Markup & Local SEO appeared first on Search Engine Land.

Please visit Search Engine Land for the full article.

Reblogged 4 years ago from feeds.searchengineland.com

The 2015 #MozCon Video Bundle Has Arrived!

Posted by EricaMcGillivray

The bird has landed, and by bird, I mean the MozCon 2015 Video Bundle! That’s right, 27 sessions and over 15 hours of knowledge from our top notch speakers right at your fingertips. Watch presentations about SEO, personalization, content strategy, local SEO, Facebook graph search, and more to level up your online marketing expertise.

If these videos were already on your wish list, skip ahead:

If you attended MozCon, the videos are included with your ticket. You should have an email in your inbox (sent to the address you registered for MozCon with) containing your unique URL for a free “purchase.”

MozCon 2015 was fantastic! This year, we opened up the room for a few more attendees and to fit our growing staff, which meant 1,600 people showed up. Each year we work to bring our programming one step further with incredible speakers, diverse topics, and tons of tactics and tips for you.


What did attendees say?

We heard directly from 30% of MozCon attendees. Here’s what they had to say about the content:

Did you find the presentations to be advanced enough? 74% found them to be just perfect.

Wil Reynolds at MozCon 2015


What do I get in the bundle?

Our videos feature the presenter and their presentation side-by-side, so there’s no need to flip to another program to view a slide deck. You’ll have easy access to links and reference tools, and the videos even offer closed captioning for your enjoyment and ease of understanding.

For $299, the 2015 MozCon Video Bundle gives you instant access to:

  • 27 videos (over 15 hours) from MozCon 2015
  • Stream or download the videos to your computer, tablet, phone, phablet, or whatever you’ve got handy
  • Downloadable slide decks for all presentations


Bonus! A free full session from 2015!

Because some sessions are just too good to hide behind a paywall. Sample what the conference is all about with a full session from Cara Harshman about personalization on the web:


Surprised and excited to see these videos so early? Huge thanks is due to the Moz team for working hard to process, build, program, write, design, and do all the necessaries to make these happen. You’re the best!

Still not convinced you want the videos? Watch the preview for the Sherlock Christmas Special. Want to attend the live show? Buy your early bird ticket for MozCon 2016. We’ve sold out the conference for the last five years running, so grab your ticket now!

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!

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The Inbound Marketing Economy

Posted by KelseyLibert

When it comes to job availability and security, the future looks bright for inbound marketers.

The Bureau of Labor Statistics (BLS) projects that employment for marketing managers will grow by 13% between 2012 and 2022. Job security for marketing managers also looks positive according to the BLS, which cites that marketing employees are less likely to be laid off since marketing drives revenue for most businesses.

While the BLS provides growth estimates for managerial-level marketing roles, these projections don’t give much insight into the growth of digital marketing, specifically the disciplines within digital marketing. As we know, “marketing” can refer to a variety of different specializations and methodologies. Since digital marketing is still relatively new compared to other fields, there is not much comprehensive research on job growth and trends in our industry.

To gain a better understanding of the current state of digital marketing careers, Fractl teamed up with Moz to identify which skills and roles are the most in demand and which states have the greatest concentration of jobs.

Methodology

We analyzed 75,315 job listings posted on Indeed.com during June 2015 based on data gathered from job ads containing the following terms:

  • “content marketing” or “content strategy”
  • “SEO” or “search engine marketing”
  • “social media marketing” or “social media management”
  • “inbound marketing” or “digital marketing”
  • “PPC” (pay-per-click)
  • “Google Analytics”

We chose the above keywords based on their likelihood to return results that were marketing-focused roles (for example, just searching for “social media” may return a lot of jobs that are not primarily marketing focused, such as customer service). The occurrence of each of these terms in job listings was quantified and segmented by state. We then combined the job listing data with U.S. Census Bureau population estimates to calculate the jobs per capita for each keyword, giving us the states with the greatest concentration of jobs for a given search query.

Using the same data, we identified which job titles appeared most frequently. We used existing data from Indeed to determine job trends and average salaries. LinkedIn search results were also used to identify keyword growth in user profiles.

Marketing skills are in high demand, but talent is hard to find

As the marketing industry continues to evolve due to emerging technology and marketing platforms, marketers are expected to pick up new skills and broaden their knowledge more quickly than ever before. Many believe this rapid rate of change has caused a marketing skills gap, making it difficult to find candidates with the technical, creative, and business proficiencies needed to succeed in digital marketing.

The ability to combine analytical thinking with creative execution is highly desirable and necessary in today’s marketing landscape. According to an article in The Guardian, “Companies will increasingly look for rounded individuals who can combine analytical rigor with the ability to apply this knowledge in a practical and creative context.” Being both detail-oriented and a big picture thinker is also a sought-after combination of attributes. A report by The Economist and Marketo found that “CMOs want people with the ability to grasp and manage the details (in data, technology, and marketing operations) combined with a view of the strategic big picture.”

But well-rounded marketers are hard to come by. In a study conducted by Bullhorn, 64% of recruiters reported a shortage of skilled candidates for available marketing roles. Wanted Analytics recently found that one of the biggest national talent shortages is for marketing manager roles, with only two available candidates per job opening.

Increase in marketers listing skills in content marketing, inbound marketing, and social media on LinkedIn profiles

While recruiter frustrations may indicate a shallow talent pool, LinkedIn tells a different story—the number of U.S.-based marketers who identify themselves as having digital marketing skills is on the rise. Using data tracked by Rand and LinkedIn, we found the following increases of marketing keywords within user profiles.

growth of marketing keywords in linkedin profiles

The number of profiles containing “content marketing” has seen the largest growth, with a 168% increase since 2013. “Social media” has also seen significant growth with a 137% increase. “Social media” appears on a significantly higher volume of profiles than the other keywords, with more than 2.2 million profiles containing some mention of social media. Although “SEO” has not seen as much growth as the other keywords, it still has the second-highest volume with it appearing in 630,717 profiles.

Why is there a growing number of people self-identifying as having the marketing skills recruiters want, yet recruiters think there is a lack of talent?

While there may be a lot of specialists out there, perhaps recruiters are struggling to fill marketing roles due to a lack of generalists or even a lack of specialists with surface-level knowledge of other areas of digital marketing (also known as a T-shaped marketer).

Popular job listings show a need for marketers to diversify their skill set

The data we gathered from LinkedIn confirm this, as the 20 most common digital marketing-related job titles being advertised call for a broad mix of skills.

20 most common marketing job titles

It’s no wonder that marketing manager roles are hard to fill, considering the job ads are looking for proficiency in a wide range of marketing disciplines including social media marketing, SEO, PPC, content marketing, Google Analytics, and digital marketing. Even job descriptions for specialist roles tend to call for skills in other disciplines. A particular role such as SEO Specialist may call for several skills other than SEO, such as PPC, content marketing, and Google Analytics.

Taking a more granular look at job titles, the chart below shows the five most common titles for each search query. One might expect mostly specialist roles to appear here, but there is a high occurrence of generalist positions, such as Digital Marketing Manager and Marketing Manager.

5 most common job titles by search query

Only one job title containing “SEO” cracked the top five. This indicates that SEO knowledge is a desirable skill within other roles, such as general digital marketing and development.

Recruiter was the third most common job title among job listings containing social media keywords, which suggests a need for social media skills in non-marketing roles.

Similar to what we saw with SEO job titles, only one job title specific to PPC (Paid Search Specialist) made it into the top job titles. PPC skills are becoming necessary for more general marketing roles, such as Marketing Manager and Digital Marketing Specialist.

Across all search queries, the most common jobs advertised call for a broad mix of skills. This tells us hiring managers are on the hunt for well-rounded candidates with a diverse range of marketing skills, as opposed to candidates with expertise in one area.

Marketers who cultivate diverse skill sets are better poised to gain an advantage over other job seekers, excel in their job role, and accelerate career growth. Jason Miller says it best in his piece about the new breed hybrid marketer:

future of marketing quote linkedin

Inbound job demand and growth: Most-wanted skills and fastest-growing jobs

Using data from Indeed, we identified which inbound skills have the highest demand and which jobs are seeing the most growth. Social media keywords claim the largest volume of results out of the terms we searched for during June 2015.

number of marketing job listings by keyword

“Social media marketing” or “social media management” appeared the most frequently in the job postings we analyzed, with 46.7% containing these keywords. “PPC” returned the smallest number of results, with only 3.8% of listings containing this term.

Perhaps this is due to social media becoming a more necessary skill across many industries and not only a necessity for marketers (for example, social media’s role in customer service and recruitment). On the other hand, job roles calling for PPC or SEO skills are most likely marketing-focused. The prevalence of social media jobs also may indicate that social media has gained wide acceptance as a necessary part of a marketing strategy. Additionally, social media skills are less valuable compared to other marketing skills, making it cheaper to hire for these positions (we will explore this further in the average salaries section below).

Our search results also included a high volume of jobs containing “digital marketing” and “SEO” keywords, which made up 19.5% and 15.5% respectively. At 5.8%, “content marketing” had the lowest search volume after “PPC.”

Digital marketing, social media, and content marketing experienced the most job growth

While the number of job listings tells us which skills are most in demand today, looking at which jobs are seeing the most growth can give insight into shifting demands.

digital marketing growth on  indeed.com

Digital marketing job listings have seen substantial growth since 2009, when it accounted for less than 0.1% of Indeed.com search results. In January 2015, this number had climbed to nearly 0.3%.

social media job growth on indeed.com

While social media marketing jobs have seen some uneven growth, as of January 2015 more than 0.1% of all job listings on Indeed.com contained the term “social media marketing” or “social media management.” This shows a significant upward trend considering this number was around 0.05% for most of 2014. It’s also worth noting that “social media” is currently ranked No. 10 on Indeed’s list of top job trends.

content marketing job growth on indeed.com

Despite its growth from 0.02% to nearly 0.09% of search volume in the last four years, “content marketing” does not make up a large volume of job postings compared to “digital marketing” or “social media.” In fact, “SEO” has seen a decrease in growth but still constitutes a higher percentage of job listings than content marketing.

SEO, PPC, and Google Analytics job growth has slowed down

On the other hand, search volume on Indeed has either decreased or plateaued for “SEO,” “PPC,” and “Google Analytics.”

seo job growth on indeed.com

As we see in the graph, the volume of “SEO job” listings peaked between 2011 and 2012. This is also around the time content marketing began gaining popularity, thanks to the Panda and Penguin updates. The decrease may be explained by companies moving their marketing budgets away from SEO and toward content or social media positions. However, “SEO” still has a significant amount of job listings, with it appearing in more than 0.2% of job listings on Indeed as of 2015.

ppc job growth on indeed.com

“PPC” has seen the most staggered growth among all the search terms we analyzed, with its peak of nearly 0.1% happening between 2012 and 2013. As of January of this year, search volume was below 0.05% for “PPC.”

google analytics job growth on indeed.com

Despite a lack of growth, the need for this skill remains steady. Between 2008 and 2009, “Google Analytics” job ads saw a huge spike on Indeed. Since then, the search volume has tapered off and plateaued through January 2015.

Most valuable skills are SEO, digital marketing, and Google Analytics

So we know the number of social media, digital marketing, and content marketing jobs are on the rise. But which skills are worth the most? We looked at the average salaries based on keywords and estimates from Indeed and salaries listed in job ads.

national average marketing salaries

Job titles containing “SEO” had an average salary of $102,000. Meanwhile, job titles containing “social media marketing” had an average salary of $51,000. Considering such a large percentage of the job listings we analyzed contained “social media” keywords, there is a much larger pool of jobs; therefore, a lot of entry level social media jobs or internships are probably bringing down the average salary.

Job titles containing “Google Analytics” had the second-highest average salary at $82,000, but this should be taken with a grain of salt considering “Google Analytics” will rarely appear as part of a job title. The chart below, which shows average salaries for jobs containing keywords anywhere in the listing as opposed to only in the title, gives a more accurate idea of how much “Google Analytics” job roles earn on average.national salary averages marketing keywords

Looking at the average salaries based on keywords that appeared anywhere within the job listing (job title, job description, etc.) shows a slightly different picture. Based on this, jobs containing “digital marketing” or “inbound marketing” had the highest average salary of $84,000. “SEO” and “Google Analytics” are tied for second with $76,000 as the average salary.

“Social media marketing” takes the bottom spot with an average salary of $57,000. However, notice that there is a higher average salary for jobs that contain “social media” within the job listing as opposed to jobs that contain “social media” within the title. This suggests that social media skills may be more valuable when combined with other responsibilities and skills, whereas a strictly social media job, such as Social Media Manager or Social Media Specialist, does not earn as much.

Massachusetts, New York, and California have the most career opportunities for inbound marketers

Looking for a new job? Maybe it’s time to pack your bags for Boston.

Massachusetts led the U.S. with the most jobs per capita for digital marketing, content marketing, SEO, and Google Analytics. New York took the top spot for social media jobs per capita, while Utah had the highest concentration of PPC jobs. California ranked in the top three for digital marketing, content marketing, social media, and Google Analytics. Illinois appeared in the top 10 for every term and usually ranked within the top five. Most of the states with the highest job concentrations are in the Northeast, West, and East Coast, with a few exceptions such as Illinois and Minnesota.

But you don’t necessarily have to move to a new state to increase the odds of landing an inbound marketing job. Some unexpected states also made the cut, with Connecticut and Vermont ranking within the top 10 for several keywords.

concentration of digital marketing jobs

marketing jobs per capita

Job listings containing “digital marketing” or “inbound marketing” were most prevalent in Massachusetts, New York, Illinois, and California, which is most likely due to these states being home to major cities where marketing agencies and large brands are headquartered or have a presence. You will notice these four states make an appearance in the top 10 for every other search query and usually rank close to the top of the list.

More surprising to find in the top 10 were smaller states such as Connecticut and Vermont. Many major organizations are headquartered in Connecticut, which may be driving the state’s need for digital marketing talent. Vermont’s high-tech industry growth may explain its high concentration of digital marketing jobs.

content marketing job concentration

per capita content marketing jobs

Although content marketing jobs are growing, there are still a low volume overall of available jobs, as shown by the low jobs per capita compared to most of the other search queries. With more than three jobs per capita, Massachusetts and New York topped the list for the highest concentration of job listings containing “content marketing” or “content strategy.” California and Illinois rank in third and fourth with 2.8 and 2.1 jobs per capita respectively.

seo job concentration

seo jobs per capita

Again, Massachusetts and New York took the top spots, each with more than eight SEO jobs per capita. Utah took third place for the highest concentration of SEO jobs. Surprised to see Utah rank in the top 10? Its inclusion on this list and others may be due to its booming tech startup scene, which has earned the metropolitan areas of Salt Lake City, Provo, and Park City the nickname Silicon Slopes.

social media job concentration

social media jobs per capita

Compared to the other keywords, “social media” sees a much higher concentration of jobs. New York dominates the rankings with nearly 24 social media jobs per capita. The other top contenders of California, Massachusetts, and Illinois all have more than 15 social media jobs per capita.

The numbers at the bottom of this list can give you an idea of how prevalent social media jobs were compared to any other keyword we analyzed. Minnesota’s 12.1 jobs per capita, the lowest ranking state in the top 10 for social media, trumps even the highest ranking state for any other keyword (11.5 digital marketing jobs per capita in Massachusetts).

ppc job concentration

ppc jobs per capita

Due to its low overall number of available jobs, “PPC” sees the lowest jobs per capita out of all the search queries. Utah has the highest concentration of jobs with just two PPC jobs per 100,000 residents. It is also the only state in the top 10 to crack two jobs per capita.

google analytics job concentration

google analytics jobs per capita

Regionally, the Northeast and West dominate the rankings, with the exception of Illinois. Massachusetts and New York are tied for the most Google Analytics job postings, each with nearly five jobs per capita. At more than three jobs per 100,000 residents, California, Illinois, and Colorado round out the top five.

Overall, our findings indicate that none of the marketing disciplines we analyzed are dying career choices, but there is a need to become more than a one-trick pony—or else you’ll risk getting passed up for job opportunities. As the marketing industry evolves, there is a greater need for marketers who “wear many hats” and have competencies across different marketing disciplines. Marketers who develop diverse skill sets can gain a competitive advantage in the job market and achieve greater career growth.

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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.

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