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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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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Spam Score: Moz’s New Metric to Measure Penalization Risk

Posted by randfish

Today, I’m very excited to announce that Moz’s Spam Score, an R&D project we’ve worked on for nearly a year, is finally going live. In this post, you can learn more about how we’re calculating spam score, what it means, and how you can potentially use it in your SEO work.

How does Spam Score work?

Over the last year, our data science team, led by 
Dr. Matt Peters, examined a great number of potential factors that predicted that a site might be penalized or banned by Google. We found strong correlations with 17 unique factors we call “spam flags,” and turned them into a score.

Almost every subdomain in 
Mozscape (our web index) now has a Spam Score attached to it, and this score is viewable inside Open Site Explorer (and soon, the MozBar and other tools). The score is simple; it just records the quantity of spam flags the subdomain triggers. Our correlations showed that no particular flag was more likely than others to mean a domain was penalized/banned in Google, but firing many flags had a very strong correlation (you can see the math below).

Spam Score currently operates only on the subdomain level—we don’t have it for pages or root domains. It’s been my experience and the experience of many other SEOs in the field that a great deal of link spam is tied to the subdomain-level. There are plenty of exceptions—manipulative links can and do live on plenty of high-quality sites—but as we’ve tested, we found that subdomain-level Spam Score was the best solution we could create at web scale. It does a solid job with the most obvious, nastiest spam, and a decent job highlighting risk in other areas, too.

How to access Spam Score

Right now, you can find Spam Score inside 
Open Site Explorer, both in the top metrics (just below domain/page authority) and in its own tab labeled “Spam Analysis.” Spam Score is only available for Pro subscribers right now, though in the future, we may make the score in the metrics section available to everyone (if you’re not a subscriber, you can check it out with a free trial). 

The current Spam Analysis page includes a list of subdomains or pages linking to your site. You can toggle the target to look at all links to a given subdomain on your site, given pages, or the entire root domain. You can further toggle source tier to look at the Spam Score for incoming linking pages or subdomains (but in the case of pages, we’re still showing the Spam Score for the subdomain on which that page is hosted).

You can click on any Spam Score row and see the details about which flags were triggered. We’ll bring you to a page like this:

Back on the original Spam Analysis page, at the very bottom of the rows, you’ll find an option to export a disavow file, which is compatible with Google Webmaster Tools. You can choose to filter the file to contain only those sites with a given spam flag count or higher:

Disavow exports usually take less than 3 hours to finish. We can send you an email when it’s ready, too.

WARNING: Please do not export this file and simply upload it to Google! You can really, really hurt your site’s ranking and there may be no way to recover. Instead, carefully sort through the links therein and make sure you really do want to disavow what’s in there. You can easily remove/edit the file to take out links you feel are not spam. When Moz’s Cyrus Shepard disavowed every link to his own site, it took more than a year for his rankings to return!

We’ve actually made the file not-wholly-ready for upload to Google in order to be sure folks aren’t too cavalier with this particular step. You’ll need to open it up and make some edits (specifically to lines at the top of the file) in order to ready it for Webmaster Tools

In the near future, we hope to have Spam Score in the Mozbar as well, which might look like this: 

Sweet, right? 🙂

Potential use cases for Spam Analysis

This list probably isn’t exhaustive, but these are a few of the ways we’ve been playing around with the data:

  1. Checking for spammy links to your own site: Almost every site has at least a few bad links pointing to it, but it’s been hard to know how much or how many potentially harmful links you might have until now. Run a quick spam analysis and see if there’s enough there to cause concern.
  2. Evaluating potential links: This is a big one where we think Spam Score can be helpful. It’s not going to catch every potentially bad link, and you should certainly still use your brain for evaluation too, but as you’re scanning a list of link opportunities or surfing to various sites, having the ability to see if they fire a lot of flags is a great warning sign.
  3. Link cleanup: Link cleanup projects can be messy, involved, precarious, and massively tedious. Spam Score might not catch everything, but sorting links by it can be hugely helpful in identifying potentially nasty stuff, and filtering out the more probably clean links.
  4. Disavow Files: Again, because Spam Score won’t perfectly catch everything, you will likely need to do some additional work here (especially if the site you’re working on has done some link buying on more generally trustworthy domains), but it can save you a heap of time evaluating and listing the worst and most obvious junk.

Over time, we’re also excited about using Spam Score to help improve the PA and DA calculations (it’s not currently in there), as well as adding it to other tools and data sources. We’d love your feedback and insight about where you’d most want to see Spam Score get involved.

Details about Spam Score’s calculation

This section comes courtesy of Moz’s head of data science, Dr. Matt Peters, who created the metric and deserves (at least in my humble opinion) a big round of applause. – Rand

Definition of “spam”

Before diving into the details of the individual spam flags and their calculation, it’s important to first describe our data gathering process and “spam” definition.

For our purposes, we followed Google’s definition of spam and gathered labels for a large number of sites as follows.

  • First, we randomly selected a large number of subdomains from the Mozscape index stratified by mozRank.
  • Then we crawled the subdomains and threw out any that didn’t return a “200 OK” (redirects, errors, etc).
  • Finally, we collected the top 10 de-personalized, geo-agnostic Google-US search results using the full subdomain name as the keyword and checked whether any of those results matched the original keyword. If they did not, we called the subdomain “spam,” otherwise we called it “ham.”

We performed the most recent data collection in November 2014 (after the Penguin 3.0 update) for about 500,000 subdomains.

Relationship between number of flags and spam

The overall Spam Score is currently an aggregate of 17 different “flags.” You can think of each flag a potential “warning sign” that signals that a site may be spammy. The overall likelihood of spam increases as a site accumulates more and more flags, so that the total number of flags is a strong predictor of spam. Accordingly, the flags are designed to be used together—no single flag, or even a few flags, is cause for concern (and indeed most sites will trigger at least a few flags).

The following table shows the relationship between the number of flags and percent of sites with those flags that we found Google had penalized or banned:

ABOVE: The overall probability of spam vs. the number of spam flags. Data collected in Nov. 2014 for approximately 500K subdomains. The table also highlights the three overall danger levels: low/green (< 10%) moderate/yellow (10-50%) and high/red (>50%)

The overall spam percent averaged across a large number of sites increases in lock step with the number of flags; however there are outliers in every category. For example, there are a small number of sites with very few flags that are tagged as spam by Google and conversely a small number of sites with many flags that are not spam.

Spam flag details

The individual spam flags capture a wide range of spam signals link profiles, anchor text, on page signals and properties of the domain name. At a high level the process to determine the spam flags for each subdomain is:

  • Collect link metrics from Mozscape (mozRank, mozTrust, number of linking domains, etc).
  • Collect anchor text metrics from Mozscape (top anchor text phrases sorted by number of links)
  • Collect the top five pages by Page Authority on the subdomain from Mozscape
  • Crawl the top five pages plus the home page and process to extract on page signals
  • Provide the output for Mozscape to include in the next index release cycle

Since the spam flags are incorporated into in the Mozscape index, fresh data is released with each new index. Right now, we crawl and process the spam flags for each subdomains every two – three months although this may change in the future.

Link flags

The following table lists the link and anchor text related flags with the the odds ratio for each flag. For each flag, we can compute two percents: the percent of sites with that flag that are penalized by Google and the percent of sites with that flag that were not penalized. The odds ratio is the ratio of these percents and gives the increase in likelihood that a site is spam if it has the flag. For example, the first row says that a site with this flag is 12.4 times more likely to be spam than one without the flag.

ABOVE: Description and odds ratio of link and anchor text related spam flags. In addition to a description, it lists the odds ratio for each flag which gives the overall increase in spam likelihood if the flag is present).

Working down the table, the flags are:

  • Low mozTrust to mozRank ratio: Sites with low mozTrust compared to mozRank are likely to be spam.
  • Large site with few links: Large sites with many pages tend to also have many links and large sites without a corresponding large number of links are likely to be spam.
  • Site link diversity is low: If a large percentage of links to a site are from a few domains it is likely to be spam.
  • Ratio of followed to nofollowed subdomains/domains (two separate flags): Sites with a large number of followed links relative to nofollowed are likely to be spam.
  • Small proportion of branded links (anchor text): Organically occurring links tend to contain a disproportionate amount of banded keywords. If a site does not have a lot of branded anchor text, it’s a signal the links are not organic.

On-page flags

Similar to the link flags, the following table lists the on page and domain name related flags:

ABOVE: Description and odds ratio of on page and domain name related spam flags. In addition to a description, it lists the odds ratio for each flag which gives the overall increase in spam likelihood if the flag is present).

  • Thin content: If a site has a relatively small ratio of content to navigation chrome it’s likely to be spam.
  • Site mark-up is abnormally small: Non-spam sites tend to invest in rich user experiences with CSS, Javascript and extensive mark-up. Accordingly, a large ratio of text to mark-up is a spam signal.
  • Large number of external links: A site with a large number of external links may look spammy.
  • Low number of internal links: Real sites tend to link heavily to themselves via internal navigation and a relative lack of internal links is a spam signal.
  • Anchor text-heavy page: Sites with a lot of anchor text are more likely to be spam then those with more content and less links.
  • External links in navigation: Spam sites may hide external links in the sidebar or footer.
  • No contact info: Real sites prominently display their social and other contact information.
  • Low number of pages found: A site with only one or a few pages is more likely to be spam than one with many pages.
  • TLD correlated with spam domains: Certain TLDs are more spammy than others (e.g. pw).
  • Domain name length: A long subdomain name like “bycheapviagra.freeshipping.onlinepharmacy.com” may indicate keyword stuffing.
  • Domain name contains numerals: domain names with numerals may be automatically generated and therefore spam.

If you’d like some more details on the technical aspects of the spam score, check out the 
video of Matt’s 2012 MozCon talk about Algorithmic Spam Detection or the slides (many of the details have evolved, but the overall ideas are the same):

We’d love your feedback

As with all metrics, Spam Score won’t be perfect. We’d love to hear your feedback and ideas for improving the score as well as what you’d like to see from it’s in-product application in the future. Feel free to leave comments on this post, or to email Matt (matt at moz dot com) and me (rand at moz dot com) privately with any suggestions.

Good luck cleaning up and preventing link spam!



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Everything You Need to Know About Mobile App Search

Posted by Justin_Briggs

Mobile isn’t the future. It’s the present. Mobile apps are not only changing how we interact with devices and websites, they’re changing the way we search. Companies are creating meaningful experiences on mobile-friendly websites and apps, which in turn create new opportunities to get in front of users.

I’d like to explore the growth of mobile app search and its current opportunities to gain visibility and drive engagement.

Rise of mobile app search

The growth of mobile device usage has driven a significant lift in app-related searches. This is giving rise to mobile app search as a vertical within traditional universal search.

While it has been clear for some time that mobile search is important, that importance has been more heavily emphasized by Google recently, as they continue to push
mobile-friendly labels in SERPs, and are likely increasing mobile-friendliness’s weight as a ranking factor.

The future of search marketing involves mobile, and it will not be limited to optimizing HTML webpages, creating responsive designs, and optimizing UX. Mobile SEO is a world where apps, knowledge graph, and conversational search are front and center.

For the
top 10 leading properties online, 34% of visitors are mobile-only (comScore data), and, anecdotally, we’re seeing similar numbers with our clients, if not more.

Mobile device and app growth

It’s also worth noting that
72% of mobile engagement relies on apps vs. on browsers. Looking at teen usage, apps are increasingly dominant. Additionally,
55% of teens use voice search more than once per day

If you haven’t read it, grab some coffee and read
A Teenagers View on Social Media, which is written by a 19-year old who gives his perspective of online behavior. Reading between the lines shows a number of subtle shifts in behavior. I noticed that every time I expected him say website, he said application. In fact, he referenced application 15 times, and it is the primary way he describes social networks.

This means that one of the fasting growing segments of mobile users cannot be marketed to by optimizing HTML webpages alone, requiring search marketers to expand their skills into app optimization.

The mobile app pack

This shift is giving rise to the mobile app pack and app search results, which are triggered on searches from mobile devices in instances of high mobile app intent. Think of these as being similar to local search results. Considering
mobile searcher behavior, these listings dominate user attention.

Mobile app search results and mobile app pack

As with local search, mobile app search can reorder traditional results, completely push them down, or integrate app listings with traditional web results.

You can test on your desktop using a
user-agent switcher, or by searching on your iOS or Android device. 

There are slight differences between iPhone and Android mobile app results:

iOS and Android mobile search result listing

From what I’ve seen, mobile app listings trigger more frequently, and with more results, on Android search results when compared to iOS. Additionally, iOS mobile app listings are represented as a traditional website result listing, while mobile app listings on Android are more integrated.

Some of the differences also come from the differences in app submission guidelines on the two major stores, the Apple App Store and Google Play.

Overview of differences in mobile app results

  1. Title – Google uses the app listing page’s HTML title (which is the app’s title). iOS app titles can exceed 55-62 characters, which causes wrapping and title truncation like a traditional result. Android app title requirements are shorter, so titles are typically shorter on Android mobile app listings.
  2. URL – iOS mobile app listings display the iTunes URL to the App Store as part of the search result.
  3. Icon – iOS icons are square and Android icons have rounded corners.
  4. Design – Android results stand out more, with an “Apps” headline above the pack and a link to Google Play at the end.
  5. App store content – The other differences show up in the copy, ratings, and reviews on each app store.

Ranking in mobile app search results

Ranking in mobile app search results is a
combination of App Store Optimization (ASO) and traditional SEO. The on-page factors are dependent upon your app listing, so optimization starts with having solid ASO. If you’re not familiar with ASO, it’s the process of optimizing your app listing for internal app store search.

Basics of ASO

Ranking in the Apple App Store and in Google Play is driven by two primary factors: keyword alignment and app performance. Text fields in the app store listing, such as title, description, and keyword list, align the app with a particular set of keywords. Performance metrics including download velocity, app ratings, and reviews determine how well the app will rank for each of those keywords. (Additionally, the Google Play algorithm may include external, web-based performance metrics like citations and links as ranking factors.)

App store ranking factors

Mobile app listing optimization

While I won’t explore ASO in-depth here, as it’s very similar to traditional SEO,
optimizing app listings is primarily a function of keyword targeting.

Tools like
Sensor Tower, MobileDevHQ, and App Annie can help you with mobile app keyword research. However, keep in mind that mobile app search listings show up in universal search, so it’s important to leverage traditional keyword research tools like the AdWords Tool or Google Trends.

While there are similarities with ASO, optimizing for these mobile app search listings on the web has some slight differences.

Differences between ASO & mobile app SEO targeting

  1. Titles – While the Apple App Store allows relatively long titles, they are limited to the preview length in organic search. Titles should be optimized with Google search in mind, in addition to optimizing for the app store. Additionally, several apps aggressively target keywords in their app title, but caution should be used as spamming keywords could influence app performance in Google.
  2. Description – The app description on the App Store may not be a factor in internal search, but it will impact external app search results. Leverage keyword targeting best practices when writing your iOS app description, as well as your Android app description.
  3. Device and platform keywords – When targeting for app store search, it is not as important to target terms related to the OS or device. However, these terms can help visibility in external search. Include device and OS terms, such as Android, Samsung Note, iOS, iPad, and iPhone.

App performance optimization

Outside of content optimization, Google looks at the performance of the app. On the Android side, they have access to the data, but for iOS they have to rely on publicly available information.

App performance factors

  • Number of ratings
  • Average rating score
  • Content and sentiment analysis of reviews
  • Downloads / installs
  • Engagement and retention
  • Internal links on app store

For iOS, the primary public metrics are ratings and reviews. However, app performance can be inferred using the App Store’s ranking charts and search results, which can be leveraged as proxies of these performance metrics.


The following objectives will have the greatest influence on your mobile app search ranking:

  1. Increase your average rating number
  2. Increase your number of ratings
  3. Increase downloads

For app ratings and reviews, leverage platforms like
Apptentive to improve your ratings. They are very effective at driving positive ratings. Additionally, paid tactics are a great way to drive install volume and are one area where paid budget capacity could directly influence organic results in Google. Anecdotally, both app stores use rating numbers (typically above or below 4 stars) to make decisions around promoting an app, either through merchandising spots or co-branded campaigns. I suspect this is being used as a general cut-off for what is displayed in universal results. Increasing your rating above 4 stars should improve the likelihood you’ll appear in mobile app search results.

Lastly, think of merchandising and rankings in terms of 
internal linking structures. The more visible you are inside of the app store, the more visibility you have in external search.

App web performance optimization

Lastly, we’re talking Google rankings, so factors like links, citations, and social shares matter. You should be
conducting content marketing, PR, and outreach for your app. Focus on merchandising your app on your own site, as well as increasing coverage of your app (linking to the app store page). The basics of link optimization apply here.

App indexation – drive app engagement

Application search is not limited to driving installs via app search results. With app indexing, you can leverage your desktop/mobile website visibility in organic search to drive engagement with those who have your app installed. Google can discover and expose content deep inside your app directly in search results. This means that when a user clicks on your website in organic search, it can open your app directly, taking them to that exact piece of content in your app, instead of opening your website.

App indexation fundamentally changes technical SEO, extending SEO from server and webpage setup to the setup and optimization of applications.

App indexation on Google

This also fundamentally changes search. Your most avid and engaged user may choose to no longer visit your website. For example, on my Note 4, when I click a link to a site of a brand that I have an app installed for, Google gives me the option not only to open in the app, but to set opening the app as a default behavior.

If a user chooses to open your site in your app, they may never visit your site from organic search again.

App indexation is currently limited to Android devices, but there is evidence to suggest that it’s already in the works and is
soon to be released on iOS devices. There have been hints for some time, but markup is showing up in the wild suggesting that Google is actively working with Apple and select brands to develop iOS app indexing.

URI optimization for apps

The first step in creating an indexable app is to set up your app to support deep links. Deep links are URIs that are understood by your app and will open up a specific piece of content. They are effectively URLs for applications.

Once this URI is supported, a user can be sent to deep content in the app. These can be discovered as alternates to your desktop site’s URLs, similar to how
separate-site mobile sites are defined as alternate URLs for the desktop site. In instances of proper context (on an Android device with the app installed), Google can direct a user to the app instead of the website.

Setting this up requires working with your app developer to implement changes inside the app as well as working with your website developers to add references on your desktop site.

Adding intent filters

Android has
documented the technical setup of deep links in detail, but it starts with setting up intent filters in an app’s Android manifest file. This is done with the following code.

<activity android:name="com.example.android.GizmosActivity"
android:label="@string/title_gizmos" >
<intent-filter android:label="@string/filter_title_viewgizmos">
<action android:name="android.intent.action.VIEW" />
<data android:scheme="http"
android:host="example.com"
android:pathPrefix="/gizmos" />
<category android:name="android.intent.category.DEFAULT" />
<category android:name="android.intent.category.BROWSABLE" />
</intent-filter>
</activity>

This dictates the technical optimization of your app URIs for app indexation and defines the elements used in the URI example above.

  • The <intent-filter> element should be added for activities that should be launchable from search results.
  • The <action> element specifies the ACTION_VIEW intent action so that the intent filter can be reached from Google Search.
  • The <data> tag represents a URI format that resolves to the activity. At minimum, the <data> tag must include the android:scheme attribute.
  • Include the BROWSABLE category. The BROWSABLE category is required in order for the intent filter to be accessible from a web browser. Without it, clicking a link in a browser cannot resolve to your app. The DEFAULT category is optional, but recommended. Without this category, the activity can be started only with an explicit intent, using your app component name.

Testing deep links

Google has created tools to help test your deep link setup. You can use
Google’s Deep Link Test Tool to test your app behavior with deep links on your phone. Additionally, you can create an HTML page with an intent:// link in it.

For example
:

<a href="intent://example.com/page-1#Intent;scheme=http;package=com.example.android;end;"> <a href="http://example.com/page-1">http://example.com/page-1></a>

This link would open up deep content inside the app from the HTML page.

App URI crawl and discovery

Once an app has deep link functionality, the next step is to
ensure that Google can discover these URIs as part of its traditional desktop crawling.

Ways to get apps crawled

  1. Rel=”alternate” in HTML head
  2. ViewAction with Schema.org
  3. Rel=”alternate” in XML Sitemap

Implementing all three will create clear signals, but at minimum you should add the rel=”alternate” tag to the HTML head of your webpages.

Effectively, think of the app URI as being similar to a mobile site URL when
setting up a separate-site mobile site for SEO. The mobile deep link is an alternative way to view a webpage on your site. You map a piece of content on your site to a corresponding piece of content inside the app.

Before you get started, be sure to
verify your website and app following the guidelines here. This will verify your app in Google Play Developer Console and Google Webmaster Tools.

#1: Rel=”alternate” in HTML head

On an example page, such as example.com/page-1, you would add the following code to the head of the document. Again, very similar to separate-site mobile optimization.

<html>
<head> 
... 
<link rel="alternate" href="android-app://com.example.android/http/example.com/page-1" /> 
...
</head>
<body>
</body>
#2: ViewAction with Schema.org

Additionally, you can reference the deep link using Schema.org and JSON by using a 
ViewAction.

<script type="application/ld+json"> 
{ 
"@context": "http://schema.org", 
"@type": "WebPage", 
"@id": "http://example.com/gizmos", 
"potentialAction": { 
"@type": "ViewAction", 
"target": "android-app://com.example.android/http/example.com/gizmos" 
} 
} 
</script>
#3 Rel=”alternate” in XML sitemap

Lastly, you can reference the alternate URL in your XML Sitemaps, similar to using the rel=”alternate” for mobile sites.

<?xml version="1.0" encoding="UTF-8" ?>
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:xhtml="http://www.w3.org/1999/xhtml"> 
<url> 
<loc>http://example.com/page-1</loc> 
<xhtml:link rel="alternate" href="android-app://com.example.android/http/example.com/page-1" /> 
</url> 
... 
</urlset>

Once these are in place, Google can discover the app URI and provide your app as an alternative way to view content found in search.

Bot control and robots noindex for apps

There may be instances where there is content within your app that you do not want indexed in Google. A good example of this might be content or functionality that is built out on your site, but has not yet been developed in your app. This would create an inferior experience for users. The good news is that we can block indexation with a few updates to the app.

First, add the following to your app resource directory (res/xml/noindex.xml).

<?xml version="1.0" encoding="utf-8"?> 
<search-engine xmlns:android="http://schemas.android.com/apk/res/android"> 
<noindex uri="http://example.com/gizmos/hidden_uri"/> 
<noindex uriPrefix="http://example.com/gizmos/hidden_prefix"/> 
<noindex uri="gizmos://hidden_path"/> 
<noindex uriPrefix="gizmos://hidden_prefix"/> 
</search-engine>

As you can see above, you can block an individual URI or define a URI prefix to block entire folders.

Once this has been added, you need to update the AndroidManifest.xml file to denote that you’re using noindex.html to block indexation.

<manifest xmlns:android="http://schemas.android.com/apk/res/android" package="com.example.android.Gizmos"> 
<application> 
<activity android:name="com.example.android.GizmosActivity" android:label="@string/title_gizmos" > 
<intent-filter android:label="@string/filter_title_viewgizmos"> 
<action android:name="android.intent.action.VIEW"/> 
... 
</activity> 
<meta-data android:name="search-engine" android:resource="@xml/noindex"/> 
</application> 
<uses-permission android:name="android.permission.INTERNET"/> 
</manifest>

App indexing API to drive re-engagement

In addition to URI discovery via desktop crawl, your mobile app can integrate
Google’s App Indexing API, which communicates with Google when users take actions inside your app. This sends information to Google about what users are viewing in the app. This is an additional method for deep link discovery and has some benefits.

The primary benefit is the ability to appear in
autocomplete. This can drive re-engagement through Google Search query autocompletions, providing access to inner pages in apps.

App auto suggest

Again, be sure to
verify your website and app following the guidelines here. This will verify your app in Google Play Developer Console and Google Webmaster Tools.

App actions with knowledge graph

The next, and most exciting, evolution of search is leveraging actions. These will be powerful when
combined with voice search, allowing search engines to take action on behalf of users, turning spoken language into executed actions.

App indexing allows you to take advantage of actions by allowing Google to not only launch an app, but execute actions inside of the app. Order me a pizza? Schedule my meeting? Drive my car? Ok, Google.

App actions work via entity detection and the application of the knowledge graph, allowing search engines to understand actions, words, ideas and objects. With that understanding, they can build an action graph that allows them to define common actions by entity type.

Here is a list of actions currently supported by Schema.org

For example, the PlayAction could be used to play a song in a music app. This can be achieve with the following markup.

<script type="application/ld+json">
{
"@context": "http://schema.org",
"@type": "MusicGroup",
"name": "Weezer", "potentialAction": {
"@type": "ListenAction",
"target": "android-app://com.spotify.music/http/we.../listen"
}
}
</script>
Once this is implemented, these app actions can begin to appear in search results and knowledge graph.

deep links in app search results

Overview of mobile app search opportunities

In summary, there are five primary ways to increase visibility and engagement for your mobile app in traditional organic search efforts.

Mobile apps in search results

The growth of mobile search is transforming how we define technical SEO, moving beyond front-end and back-end optimization of websites into the realm of structured data and application development. As app indexing expands to include iOS, I suspect the possibilities and opportunities associated with indexing applications, and their corresponding actions, to grow extensively. 

For those with Android apps, app indexing is a potential leapfrog style opportunity to get ahead of competitors who are dominant in traditional desktop search. Those with iOS devices should start by optimizing their app listings, while preparing to implement indexation, as I suspect it’ll be released for iOS this year.

Have you been leveraging traditional organic search to drive visibility and engagement for apps? Share your experiences in the comments below.

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How to Include Influencers in Your Content Strategy

Posted by Amanda_Gallucci

The first thing most people think when they hear “influencers” is promotion. Important people with an engaged following can amplify the reach of whatever idea, content or brand they choose to share. If you only weave influencers into your content strategy when your finished product is ready to be promoted, however, you’re missing out on the full potential of having respected experts on your team.

Knowing when and how they can best be engaged at different stages is critical to moving these leaders from outside influencers to brand partners.

Measure an influencer’s true value

In order to find the right influencers to give your content strategy a boost, you first should understand what makes a person an influencer and how influence will play a role within the larger content landscape.

Whether you’re looking to build brand awareness or drive traffic, what matters is not sheer numbers of followers, but the amount of engaged followers.

Twitalyzer’s analytics provide a good start to assessing who is influential on Twitter. The tool measures not only the potential impact users have based on their number of followers, but also the likelihood that other Twitter users will retweet or mention a particular user. 

Beyond finding an influencer who’s engaged enough to spread your message, also consider how this person became influential in the first place. Whether he or she has years of experience, brilliant ideas, cohesive arguments or all of the above, consider how you can harness these strengths to maximize your potential for creating a successful relationship. Asking influencers to tweet out a link might give you a bump in traffic, but asking for their opinions, advice and time in different ways will be infinitely more valuable.

Lead with strategy

How influencers fit into your campaign should be determined according to audience research and campaign goals. Know what platforms your target audience interacts with, what interests are strong enough to drive them to take action and who they trust. The more naturally these insights are woven into your content, the easier it will be to find influencers in this segment who will appreciate what you have to share.

Campaign goals are equally crucial because depending on what you want to achieve, you might change the angle of your messaging or favor different platforms. Not every influencer has the same level of activity and reach on every social channel, so identify influencers who are stars on the right platforms. Similarly, tailor your message for each influencer so that anything they share on your behalf looks organic alongside their other content.

Once you have a solid foundation for your strategy, start looking for influencers and begin your outreach process. With enough lead time to send along a beta version or rough draft, you can tweak content based on their feedback. You’ll also need allow time for them to collaborate with you on original content, create any sponsored or guest content or write a review or give a quote that you can use on your content’s release.

Don’t ask for too much of an influencer’s time, however, especially if you are asking for offhand feedback and not entering into a paid engagement. Build a relationship before you ask for favors, and even still, make the ask as easy as possible by providing the right amount of background and simplifying what you want the person to do. Rand’s
Whiteboard Friday on earning the amplification of influencer walks through the importance of the relationship-building aspect and enticing influencers with what’s in it for them.

Find influencers

With a clear understanding of the role influencers play within your overall strategy, you’re ready to identify the right candidates.

Countless tools are available to help you find influencers in different verticals, so choose based on the action you want the influencer to take. If you are searching for a thought leader who can write engaging content, a tool like
ClearVoice will help you find credible authors who focus on a particular topic. For each writer, you can view a list of articles he or she has written on that subject.

image host

When you need social influencers who can help you amplify content,
Buzzsumo is a great tool. Through their Influencer search, you can find people who frequently share content on a given topic and can click through to see what these links are.

542b33e610b8f6.92633300.png

Another approach to finding social influencers is to search Twitter bios using
Followerwonk and sorting by Social Authority

542b33e821e0c1.60336850.png

Engage influencers at different stages

Outreach

Outreach ideally starts with organically following influencers and engaging with them over time. Then reaching out to them via email or social media is less about introductions and more about the specific project you want to pitch to the influencer.

There will also be times when you find an influencer who aligns with your strategy but you don’t have the relationship-building lead time. For this cold outreach, write a succinct introduction that includes goals your goals for the content and the benefits the influencer will receive by working with you. Then make your ask. Personalization and quality are key. If you find outreach challenging, this
guide from Portent is a great place to start.

Make outreach easier for yourself by using a tool like
BuzzStream that automates and tracks the process. It will help you find contacts at certain publishers—giving you the twofold opportunity to pitch your own content as well as get in touch with influential authors. It also generates templated, customizable outreach emails.

542b33ebcc0947.89852064.png

Just remember, even if you already have a solid relationship with an influencer, show that you value his or her time. Do as much of the groundwork as you can in advance. For instance, if you want people to share something on social, draft one to three example social posts specifically crafted for each influencer and platform.

Start of relationship

Once an influencer agrees to work with you, provide just the right amount of background information and instruction. This will vary by project and influencer.

For an influencer creating content, define the basics (e.g., article, ebook, video, etc.), in addition to length and editorial theme. Find a good balance between leaving room for the influencer to share his or her expertise, while setting up key points and takeaways you want the content to achieve. You should also create and send an abbreviated style guide. There’s no need to disclose every internal note you have, but if you can provide the basic stylistic do’s and don’ts, product or company background, audience information, and voice and tone guidelines, you will spend less time on edits and back-and-forths with the influencer. Set clear expectations and schedule benchmark dates where you can check in on progress and make revisions where necessary.

In the case of engaging influencers to amplify content, you won’t need to give quite as much guidance on how to craft the social message, but you can still offer suggestions on angles that would work well or any topics or phrases your brand wouldn’t want to be associated with. It’s also important to provide summaries of any piece of content you are asking influencers to share so that a) if they don’t have time to read every word, they still feel comfortable with the concept and b) there won’t have to be any guesswork in deciding what part of the content is most important to share.

Relationship maintenance

If your experience with an influencer is mutually beneficial and you know you’ll want to partner again, make sure to check in periodically. Don’t ask for something new every time you reach out. Keep in touch by sending along interesting content or company updates the influencer might find useful. Better yet, always extend a congratulations on a promotion or a new position.

To ensure you remember to engage with the right people, use tools like
Commun.it, which identify the influential people you interact with on Twitter, and prompt you to re-engage with people you haven’t @ mentioned recently. 

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LinkedIn Contacts is also a handy way to keep track of conversations and check on any updates on the influencer’s end to look out for opportunities to get in touch.

As you continue to grow existing influencer relationships, adjust your overarching strategy to incorporate more key industry leaders. Create new roles for influencers to play in shaping your content and its promotion.

Always be strategizing

The best way to include influencers in your content strategy is to involve them at every stage of the process, including:

  1. Creation: Plan out what types of influencers will be helpful and the role they should play based on the target audience and campaign goals.
  2. Implementation: Share a strategic brief with onboarded influencers and leave flexibility for changes based on the influencer’s feedback.
  3. Measurement: Factor in the reach of influencers as part of the success of your campaign.

Over time, integrating and managing influencer relationships will become second nature, and they will seem more like team members and partners.

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