​​Measure Your Mobile Rankings and Search Visibility in Moz Analytics

Posted by jon.white

We have launched a couple of new things in Moz Pro that we are excited to share with you all: Mobile Rankings and a Search Visibility score. If you want, you can jump right in by heading to a campaign and adding a mobile engine, or keep reading for more details!

Track your mobile vs. desktop rankings in Moz Analytics

Mobilegeddon came and went with slightly less fanfare than expected, somewhat due to the vast ‘Mobile Friendly’ updates we all did at super short notice (nice work everyone!). Nevertheless, mobile rankings visibility is now firmly on everyone’s radar, and will only become more important over time.

Now you can track your campaigns’ mobile rankings for all of the same keywords and locations you are tracking on desktop.

For this campaign my mobile visibility is almost 20% lower than my desktop visibility and falling;
I can drill down to find out why

Clicking on this will take you into a new Engines tab within your Keyword Rankings page where you can find a more detailed version of this chart as well as a tabular view by keyword for both desktop and mobile. Here you can also filter by label and location.

Here I can see Search Visibility across engines including mobile;
in this case, for my branded keywords.

We have given an extra engine to all campaigns

We’ve given customers an extra engine for each campaign, increasing the number from 3 to 4. Use the extra slot to add the mobile engine and unlock your mobile data!

We will begin to track mobile rankings within 24 hours of adding to a campaign. Once you are set up, you will notice a new chart on your dashboard showing visibility for Desktop vs. Mobile Search Visibility.

Measure your Search Visibility score vs. competitors

The overall Search Visibility for my campaign

Along with this change we have also added a Search Visibility score to your rankings data. Use your visibility score to track and report on your overall campaign ranking performance, compare to your competitors, and look for any large shifts that might indicate penalties or algorithm changes. For a deeper drill-down into your data you can also segment your visibility score by keyword labels or locations. Visit the rankings summary page on any campaign to get started.

How is Search Visibility calculated?

Good question!

The Search Visibility score is the percentage of clicks we estimate you receive based on your rankings positions, across all of your keywords.

We take each ranking position for each keyword, multiply by an estimated click-thru-rate, and then take the average of all of your keywords. You can think of it as the percentage of your SERPs that you own. The score is expressed as a percentage, though scores of 100% would be almost impossible unless you are tracking keywords using the “site:” modifier. It is probably more useful to measure yourself vs. your competitors rather than focus on the actual score, but, as a rule of thumb, mid-40s is probably the realistic maximum for non-branded keywords.

Jeremy, our Moz Analytics TPM, came up with this metaphor:

Think of the SERPs for your keywords as villages. Each position on the SERP is a plot of land in SERP-village. The Search Visibility score is the average amount of plots you own in each SERP-village. Prime real estate plots (i.e., better ranking positions, like #1) are worth more. A complete monopoly of real estate in SERP-village would equate to a score of 100%. The Search Visibility score equates to how much total land you own in all SERP-villages.

Some neat ways to use this feature

  • Label and group your keywords, particularly when you add them – As visibility score is an average of all of your keywords, when you add or remove keywords from your campaign you will likely see fluctuations in the score that are unrelated to performance. Solve this by getting in the habit of labeling keywords when you add them. Then segment your data by these labels to track performance of specific keyword groups over time.
  • See how location affects your mobile rankings – Using the Engines tab in Keyword Rankings, use the filters to select just local keywords. Look for big differences between Mobile and Desktop where Google might be assuming local intent for mobile searches but not for desktop. Check out how your competitors perform for these keywords. Can you use this data?

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The Linkbait Bump: How Viral Content Creates Long-Term Lift in Organic Traffic – Whiteboard Friday

Posted by randfish

A single fantastic (or “10x”) piece of content can lift a site’s traffic curves long beyond the popularity of that one piece. In today’s Whiteboard Friday, Rand talks about why those curves settle into a “new normal,” and how you can go about creating the content that drives that change.

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

Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we’re chatting about the linkbait bump, classic phrase in the SEO world and almost a little dated. I think today we’re talking a little bit more about viral content and how high-quality content, content that really is the cornerstone of a brand or a website’s content can be an incredible and powerful driver of traffic, not just when it initially launches but over time.

So let’s take a look.

This is a classic linkbait bump, viral content bump analytics chart. I’m seeing over here my traffic and over here the different months of the year. You know, January, February, March, like I’m under a thousand. Maybe I’m at 500 visits or something, and then I have this big piece of viral content. It performs outstandingly well from a relative standpoint for my site. It gets 10,000 or more visits, drives a ton more people to my site, and then what happens is that that traffic falls back down. But the new normal down here, new normal is higher than the old normal was. So the new normal might be at 1,000, 1,500 or 2,000 visits whereas before I was at 500.

Why does this happen?

A lot of folks see an analytics chart like this, see examples of content that’s done this for websites, and they want to know: Why does this happen and how can I replicate that effect? The reasons why are it sort of feeds back into that viral loop or the flywheel, which we’ve talked about in previous Whiteboard Fridays, where essentially you start with a piece of content. That content does well, and then you have things like more social followers on your brand’s accounts. So now next time you go to amplify content or share content socially, you’re reaching more potential people. You have a bigger audience. You have more people who share your content because they’ve seen that that content performs well for them in social. So they want to find other content from you that might help their social accounts perform well.

You see more RSS and email subscribers because people see your interesting content and go, “Hey, I want to see when these guys produce something else.” You see more branded search traffic because people are looking specifically for content from you, not necessarily just around this viral piece, although that’s often a big part of it, but around other pieces as well, especially if you do a good job of exposing them to that additional content. You get more bookmark and type in traffic, more searchers biased by personalization because they’ve already visited your site. So now when they search and they’re logged into their accounts, they’re going to see your site ranking higher than they normally would otherwise, and you get an organic SEO lift from all the links and shares and engagement.

So there’s a ton of different factors that feed into this, and you kind of want to hit all of these things. If you have a piece of content that gets a lot of shares, a lot of links, but then doesn’t promote engagement, doesn’t get more people signing up, doesn’t get more people searching for your brand or searching for that content specifically, then it’s not going to have the same impact. Your traffic might fall further and more quickly.

How do you achieve this?

How do we get content that’s going to do this? Well, we’re going to talk through a number of things that we’ve talked about previously on Whiteboard Friday. But there are some additional ones as well. This isn’t just creating good content or creating high quality content, it’s creating a particular kind of content. So for this what you want is a deep understanding, not necessarily of what your standard users or standard customers are interested in, but a deep understanding of what influencers in your niche will share and promote and why they do that.

This often means that you follow a lot of sharers and influencers in your field, and you understand, hey, they’re all sharing X piece of content. Why? Oh, because it does this, because it makes them look good, because it helps their authority in the field, because it provides a lot of value to their followers, because they know it’s going to get a lot of retweets and shares and traffic. Whatever that because is, you have to have a deep understanding of it in order to have success with viral kinds of content.

Next, you want to have empathy for users and what will give them the best possible experience. So if you know, for example, that a lot of people are coming on mobile and are going to be sharing on mobile, which is true of almost all viral content today, FYI, you need to be providing a great mobile and desktop experience. Oftentimes that mobile experience has to be different, not just responsive design, but actually a different format, a different way of being able to scroll through or watch or see or experience that content.

There are some good examples out there of content that does that. It makes a very different user experience based on the browser or the device you’re using.

You also need to be aware of what will turn them off. So promotional messages, pop-ups, trying to sell to them, oftentimes that diminishes user experience. It means that content that could have been more viral, that could have gotten more shares won’t.

Unique value and attributes that separate your content from everything else in the field. So if there’s like ABCD and whoa, what’s that? That’s very unique. That stands out from the crowd. That provides a different form of value in a different way than what everyone else is doing. That uniqueness is often a big reason why content spreads virally, why it gets more shared than just the normal stuff.

I’ve talk about this a number of times, but content that’s 10X better than what the competition provides. So unique value from the competition, but also quality that is not just a step up, but 10X better, massively, massively better than what else you can get out there. That makes it unique enough. That makes it stand out from the crowd, and that’s a very hard thing to do, but that’s why this is so rare and so valuable.

This is a critical one, and I think one that, I’ll just say, many organizations fail at. That is the freedom and support to fail many times, to try to create these types of effects, to have this impact many times before you hit on a success. A lot of managers and clients and teams and execs just don’t give marketing teams and content teams the freedom to say, “Yeah, you know what? You spent a month and developer resources and designer resources and spent some money to go do some research and contracted with this third party, and it wasn’t a hit. It didn’t work. We didn’t get the viral content bump. It just kind of did okay. You know what? We believe in you. You’ve got a lot of chances. You should try this another 9 or 10 times before we throw it out. We really want to have a success here.”

That is something that very few teams invest in. The powerful thing is because so few people are willing to invest that way, the ones that do, the ones that believe in this, the ones that invest long term, the ones that are willing to take those failures are going to have a much better shot at success, and they can stand out from the crowd. They can get these bumps. It’s powerful.

Not a requirement, but it really, really helps to have a strong engaged community, either on your site and around your brand, or at least in your niche and your topic area that will help, that wants to see you, your brand, your content succeed. If you’re in a space that has no community, I would work on building one, even if it’s very small. We’re not talking about building a community of thousands or tens of thousands. A community of 100 people, a community of 50 people even can be powerful enough to help content get that catalyst, that first bump that’ll boost it into viral potential.

Then finally, for this type of content, you need to have a logical and not overly promotional match between your brand and the content itself. You can see many sites in what I call sketchy niches. So like a criminal law site or a casino site or a pharmaceutical site that’s offering like an interactive musical experience widget, and you’re like, “Why in the world is this brand promoting this content? Why did they even make it? How does that match up with what they do? Oh, it’s clearly just intentionally promotional.”

Look, many of these brands go out there and they say, “Hey, the average web user doesn’t know and doesn’t care.” I agree. But the average web user is not an influencer. Influencers know. Well, they’re very, very suspicious of why content is being produced and promoted, and they’re very skeptical of promoting content that they don’t think is altruistic. So this kills a lot of content for brands that try and invest in it when there’s no match. So I think you really need that.

Now, when you do these linkbait bump kinds of things, I would strongly recommend that you follow up, that you consider the quality of the content that you’re producing. Thereafter, that you invest in reproducing these resources, keeping those resources updated, and that you don’t simply give up on content production after this. However, if you’re a small business site, a small or medium business, you might think about only doing one or two of these a year. If you are a heavy content player, you’re doing a lot of content marketing, content marketing is how you’re investing in web traffic, I’d probably be considering these weekly or monthly at the least.

All right, everyone. Look forward to your experiences with the linkbait bump, and I will see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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From Editorial Calendars to SEO: Setting Yourself Up to Create Fabulous Content

Posted by Isla_McKetta

Quick note: This article is meant to apply to teams of all sizes, from the sole proprietor who spends all night writing their copy (because they’re doing business during the day) to the copy team who occupies an entire floor and produces thousands of pieces of content per week. So if you run into a section that you feel requires more resources than you can devote just now, that’s okay. Bookmark it and revisit when you can, or scale the step down to a more appropriate size for your team. We believe all the information here is important, but that does not mean you have to do everything right now.

If you thought ideation was fun, get ready for content creation. Sure, we’ve all written some things before, but the creation phase of content marketing is where you get to watch that beloved idea start to take shape.

Before you start creating, though, you want to get (at least a little) organized, and an editorial calendar is the perfect first step.

Editorial calendars

Creativity and organization are not mutually exclusive. In fact, they can feed each other. A solid schedule gives you and your writers the time and space to be wild and creative. If you’re just starting out, this document may be sparse, but it’s no less important. Starting early with your editorial calendar also saves you from creating content willy-nilly and then finding out months later that no one ever finished that pesky (but crucial) “About” page.

There’s no wrong way to set up your editorial calendar, as long as it’s meeting your needs. Remember that an editorial calendar is a living document, and it will need to change as a hot topic comes up or an author drops out.

There are a lot of different types of documents that pass for editorial calendars. You get to pick the one that’s right for your team. The simplest version is a straight-up calendar with post titles written out on each day. You could even use a wall calendar and a Sharpie.

Monday Tuesday Wednesday Thursday Friday
Title
The Five Colors of Oscar Fashion 12 Fabrics We’re Watching for Fall Is Charmeuse the New Corduroy? Hot Right Now: Matching Your Handbag to Your Hatpin Tea-length and Other Fab Vocab You Need to Know
Author Ellie James Marta Laila Alex

Teams who are balancing content for different brands at agencies or other more complex content environments will want to add categories, author information, content type, social promo, and more to their calendars.

Truly complex editorial calendars are more like hybrid content creation/editorial calendars, where each of the steps to create and publish the content are indicated and someone has planned for how long all of that takes. These can be very helpful if the content you’re responsible for crosses a lot of teams and can take a long time to complete. It doesn’t matter if you’re using Excel or a Google Doc, as long as the people who need the calendar can easily access it. Gantt charts can be excellent for this. Here’s a favorite template for creating a Gantt chart in Google Docs (and they only get more sophisticated).

Complex calendars can encompass everything from ideation through writing, legal review, and publishing. You might even add content localization if your empire spans more than one continent to make sure you have the currency, date formatting, and even slang right.

Content governance

Governance outlines who is taking responsibility for your content. Who evaluates your content performance? What about freshness? Who decides to update (or kill) an older post? Who designs and optimizes workflows for your team or chooses and manages your CMS?

All these individual concerns fall into two overarching components to governance: daily maintenance and overall strategy. In the long run it helps if one person has oversight of the whole process, but the smaller steps can easily be split among many team members. Read this to take your governance to the next level.

Finding authors

The scale of your writing enterprise doesn’t have to be limited to the number of authors you have on your team. It’s also important to consider the possibility of working with freelancers and guest authors. Here’s a look at the pros and cons of outsourced versus in-house talent.

In-house authors

Guest authors and freelancers

Responsible to

You

Themselves

Paid by

You (as part of their salary)

You (on a per-piece basis)

Subject matter expertise

Broad but shallow

Deep but narrow

Capacity for extra work

As you wish

Show me the Benjamins

Turnaround time

On a dime

Varies

Communication investment

Less

More

Devoted audience

Smaller

Potentially huge

From that table, it might look like in-house authors have a lot more advantages. That’s somewhat true, but do not underestimate the value of occasionally working with a true industry expert who has name recognition and a huge following. Whichever route you take (and there are plenty of hybrid options), it’s always okay to ask that the writers you are working with be professional about communication, payment, and deadlines. In some industries, guest writers will write for links. Consider yourself lucky if that’s true. Remember, though, that the final paycheck can be great leverage for getting a writer to do exactly what you need them to (such as making their deadlines).

Tools to help with content creation

So those are some things you need to have in place before you create content. Now’s the fun part: getting started. One of the beautiful things about the Internet is that new and exciting tools crop up every day to help make our jobs easier and more efficient. Here are a few of our favorites.

Calendars

You can always use Excel or a Google Doc to set up your editorial calendar, but we really like Trello for the ability to gather a lot of information in one card and then drag and drop it into place. Once there are actual dates attached to your content, you might be happier with something like a Google Calendar.

Ideation and research

If you need a quick fix for ideation, turn your keywords into wacky ideas with Portent’s Title Maker. You probably won’t want to write to the exact title you’re given (although “True Facts about Justin Bieber’s Love of Pickles” does sound pretty fascinating…), but it’s a good way to get loose and look at your topic from a new angle.

Once you’ve got that idea solidified, find out what your audience thinks about it by gathering information with Survey Monkey or your favorite survey tool. Or, use Storify to listen to what people are saying about your topic across a wide variety of platforms. You can also use Storify to save those references and turn them into a piece of content or an illustration for one. Don’t forget that a simple social ask can also do wonders.

Format

Content doesn’t have to be all about the words. Screencasts, Google+ Hangouts, and presentations are all interesting ways to approach content. Remember that not everyone’s a reader. Some of your audience will be more interested in visual or interactive content. Make something for everyone.

Illustration

Don’t forget to make your content pretty. It’s not that hard to find free stock images online (just make sure you aren’t violating someone’s copyright). We like Morgue File, Free Images, and Flickr’s Creative Commons. If you aren’t into stock images and don’t have access to in-house graphic design, it’s still relatively easy to add images to your content. Pull a screenshot with Skitch or dress up an existing image with Pixlr. You can also use something like Canva to create custom graphics.

Don’t stop with static graphics, though. There are so many tools out there to help you create gifs, quizzes and polls, maps, and even interactive timelines. Dream it, then search for it. Chances are whatever you’re thinking of is doable.

Quality, not quantity

Mediocre content will hurt your cause

Less is more. That’s not an excuse to pare your blog down to one post per month (check out our publishing cadence experiment), but it is an important reminder that if you’re writing “How to Properly Install a Toilet Seat” two days after publishing “Toilet Seat Installation for Dummies,” you might want to rethink your strategy.

The thing is, and I’m going to use another cliché here to drive home the point, you never get a second chance to make a first impression. Potential customers are roving the Internet right now looking for exactly what you’re selling. And if what they find is an only somewhat informative article stuffed with keywords and awful spelling and grammar mistakes… well, you don’t want that. Oh, and search engines think it’s spammy too…

A word about copyright

We’re not copyright lawyers, so we can’t give you the ins and outs on all the technicalities. What we can tell you (and you already know this) is that it’s not okay to steal someone else’s work. You wouldn’t want them to do it to you. This includes images. So whenever you can, make your own images or find images that you can either purchase the rights to (stock imagery) or license under Creative Commons.

It’s usually okay to quote short portions of text, as long as you attribute the original source (and a link is nice). In general, titles and ideas can’t be copyrighted (though they might be trademarked or patented). When in doubt, asking for permission is smart.

That said, part of the fun of the Internet is the remixing culture which includes using things like memes and gifs. Just know that if you go that route, there is a certain amount of risk involved.

Editing

Your content needs to go through at least one editing cycle by someone other than the original author. There are two types of editing, developmental (which looks at the underlying structure of a piece that happens earlier in the writing cycle) and copy editing (which makes sure all the words are there and spelled right in the final draft).

If you have a very small team or are in a rush (and are working with writers that have some skill), you can often skip the developmental editing phase. But know that an investment in that close read of an early draft is often beneficial to the piece and to the writer’s overall growth.

Many content teams peer-edit work, which can be great. Other organizations prefer to run their work by a dedicated editor. There’s no wrong answer, as long as the work gets edited.

Ensuring proper basic SEO

The good news is that search engines are doing their best to get closer and closer to understanding and processing natural language. So good writing (including the natural use of synonyms rather than repeating those keywords over and over and…) will take you a long way towards SEO mastery.

For that reason (and because it’s easy to get trapped in keyword thinking and veer into keyword stuffing), it’s often nice to think of your SEO check as a further edit of the post rather than something you should think about as you’re writing.

But there are still a few things you can do to help cover those SEO bets. Once you have that draft, do a pass for SEO to make sure you’ve covered the following:

  • Use your keyword in your title
  • Use your keyword (or long-tail keyword phrase) in an H2
  • Make sure the keyword appears at least once (though not more than four times, especially if it’s a phrase) in the body of the post
  • Use image alt text (including the keyword when appropriate)

Finding time to write when you don’t have any

Writing (assuming you’re the one doing the writing) can require a lot of energy—especially if you want to do it well. The best way to find time to write is to break each project down into little tasks. For example, writing a blog post actually breaks down into these steps (though not always in this order):

  • Research
  • Outline
  • Fill in outline
  • Rewrite and finish post
  • Write headline
  • SEO check
  • Final edit
  • Select hero image (optional)

So if you only have random chunks of time, set aside 15-30 minutes one day (when your research is complete) to write a really great outline. Then find an hour the next to fill that outline in. After an additional hour the following day, (unless you’re dealing with a research-heavy post) you should have a solid draft by the end of day three.

The magic of working this way is that you engage your brain and then give it time to work in the background while you accomplish other tasks. Hemingway used to stop mid-sentence at the end of his writing days for the same reason.

Once you have that draft nailed, the rest of the steps are relatively easy (even the headline, which often takes longer to write than any other sentence, is easier after you’ve immersed yourself in the post over a few days).

Working with design/development

Every designer and developer is a little different, so we can’t give you any blanket cure-alls for inter-departmental workarounds (aka “smashing silos”). But here are some suggestions to help you convey your vision while capitalizing on the expertise of your coworkers to make your content truly excellent.

Ask for feedback

From the initial brainstorm to general questions about how to work together, asking your team members what they think and prefer can go a long way. Communicate all the details you have (especially the unspoken expectations) and then listen.

If your designer tells you up front that your color scheme is years out of date, you’re saving time. And if your developer tells you that the interactive version of that timeline will require four times the resources, you have the info you need to fight for more budget (or reassess the project).

Check in

Things change in the design and development process. If you have interim check-ins already set up with everyone who’s working on the project, you’ll avoid the potential for nasty surprises at the end. Like finding out that no one has experience working with that hot new coding language you just read about and they’re trying to do a workaround that isn’t working.

Proofread

Your job isn’t done when you hand over the copy to your designer or developer. Not only might they need help rewriting some of your text so that it fits in certain areas, they will also need you to proofread the final version. Accidents happen in the copy-and-paste process and there’s nothing sadder than a really beautiful (and expensive) piece of content that wraps up with a typo:

Know when to fight for an idea

Conflict isn’t fun, but sometimes it’s necessary. The more people involved in your content, the more watered down the original idea can get and the more roadblocks and conflicting ideas you’ll run into. Some of that is very useful. But sometimes you’ll get pulled off track. Always remember who owns the final product (this may not be you) and be ready to stand up for the idea if it’s starting to get off track.

We’re confident this list will set you on the right path to creating some really awesome content, but is there more you’d like to know? Ask us your questions in the comments.

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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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New Hubs of Authority Chart in Majestic brings Data to Life

Today Majestic is proud to bring an interactive “Sankey” chart into both the Clique Hunter tools and an interactive Word Cloud into the Anchor Text tab of Site Explorer. These visualizations bring data to life and I was especially impressed when I saw the new Clique Hunter visualization because you can click on elements to…

The post New Hubs of Authority Chart in Majestic brings Data to Life appeared first on Majestic Blog.

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Deconstructing the App Store Rankings Formula with a Little Mad Science

Posted by AlexApptentive

After seeing Rand’s “Mad Science Experiments in SEO” presented at last year’s MozCon, I was inspired to put on the lab coat and goggles and do a few experiments of my own—not in SEO, but in SEO’s up-and-coming younger sister, ASO (app store optimization).

Working with Apptentive to guide enterprise apps and small startup apps alike to increase their discoverability in the app stores, I’ve learned a thing or two about app store optimization and what goes into an app’s ranking. It’s been my personal goal for some time now to pull back the curtains on Google and Apple. Yet, the deeper into the rabbit hole I go, the more untested assumptions I leave in my way.

Hence, I thought it was due time to put some longstanding hypotheses through the gauntlet.

As SEOs, we know how much of an impact a single ranking can mean on a SERP. One tiny rank up or down can make all the difference when it comes to your website’s traffic—and revenue.

In the world of apps, ranking is just as important when it comes to standing out in a sea of more than 1.3 million apps. Apptentive’s recent mobile consumer survey shed a little more light this claim, revealing that nearly half of all mobile app users identified browsing the app store charts and search results (the placement on either of which depends on rankings) as a preferred method for finding new apps in the app stores. Simply put, better rankings mean more downloads and easier discovery.

Like Google and Bing, the two leading app stores (the Apple App Store and Google Play) have a complex and highly guarded algorithms for determining rankings for both keyword-based app store searches and composite top charts.

Unlike SEO, however, very little research and theory has been conducted around what goes into these rankings.

Until now, that is.

Over the course of five studies analyzing various publicly available data points for a cross-section of the top 500 iOS (U.S. Apple App Store) and the top 500 Android (U.S. Google Play) apps, I’ll attempt to set the record straight with a little myth-busting around ASO. In the process, I hope to assess and quantify any perceived correlations between app store ranks, ranking volatility, and a few of the factors commonly thought of as influential to an app’s ranking.

But first, a little context

Image credit: Josh Tuininga, Apptentive

Both the Apple App Store and Google Play have roughly 1.3 million apps each, and both stores feature a similar breakdown by app category. Apps ranking in the two stores should, theoretically, be on a fairly level playing field in terms of search volume and competition.

Of these apps, nearly two-thirds have not received a single rating and 99% are considered unprofitable. These studies, therefore, single out the rare exceptions to the rule—the top 500 ranked apps in each store.

While neither Apple nor Google have revealed specifics about how they calculate search rankings, it is generally accepted that both app store algorithms factor in:

  • Average app store rating
  • Rating/review volume
  • Download and install counts
  • Uninstalls (what retention and churn look like for the app)
  • App usage statistics (how engaged an app’s users are and how frequently they launch the app)
  • Growth trends weighted toward recency (how daily download counts changed over time and how today’s ratings compare to last week’s)
  • Keyword density of the app’s landing page (Ian did a great job covering this factor in a previous Moz post)

I’ve simplified this formula to a function highlighting the four elements with sufficient data (or at least proxy data) for our analysis:

Ranking = fn(Rating, Rating Count, Installs, Trends)

Of course, right now, this generalized function doesn’t say much. Over the next five studies, however, we’ll revisit this function before ultimately attempting to compare the weights of each of these four variables on app store rankings.

(For the purpose of brevity, I’ll stop here with the assumptions, but I’ve gone into far greater depth into how I’ve reached these conclusions in a 55-page report on app store rankings.)

Now, for the Mad Science.

Study #1: App-les to app-les app store ranking volatility

The first, and most straight forward of the five studies involves tracking daily movement in app store rankings across iOS and Android versions of the same apps to determine any trends of differences between ranking volatility in the two stores.

I went with a small sample of five apps for this study, the only criteria for which were that:

  • They were all apps I actively use (a criterion for coming up with the five apps but not one that influences rank in the U.S. app stores)
  • They were ranked in the top 500 (but not the top 25, as I assumed app store rankings would be stickier at the top—an assumption I’ll test in study #2)
  • They had an almost identical version of the app in both Google Play and the App Store, meaning they should (theoretically) rank similarly
  • They covered a spectrum of app categories

The apps I ultimately chose were Lyft, Venmo, Duolingo, Chase Mobile, and LinkedIn. These five apps represent the travel, finance, education banking, and social networking categories.

Hypothesis

Going into this analysis, I predicted slightly more volatility in Apple App Store rankings, based on two statistics:

Both of these assumptions will be tested in later analysis.

Results

7-Day App Store Ranking Volatility in the App Store and Google Play

Among these five apps, Google Play rankings were, indeed, significantly less volatile than App Store rankings. Among the 35 data points recorded, rankings within Google Play moved by as much as 23 positions/ranks per day while App Store rankings moved up to 89 positions/ranks. The standard deviation of ranking volatility in the App Store was, furthermore, 4.45 times greater than that of Google Play.

Of course, the same apps varied fairly dramatically in their rankings in the two app stores, so I then standardized the ranking volatility in terms of percent change to control for the effect of numeric rank on volatility. When cast in this light, App Store rankings changed by as much as 72% within a 24-hour period while Google Play rankings changed by no more than 9%.

Also of note, daily rankings tended to move in the same direction across the two app stores approximately two-thirds of the time, suggesting that the two stores, and their customers, may have more in common than we think.

Study #2: App store ranking volatility across the top charts

Testing the assumption implicit in standardizing the data in study No. 1, this one was designed to see if app store ranking volatility is correlated with an app’s current rank. The sample for this study consisted of the top 500 ranked apps in both Google Play and the App Store, with special attention given to those on both ends of the spectrum (ranks 1–100 and 401–500).

Hypothesis

I anticipated rankings to be more volatile the higher an app is ranked—meaning an app ranked No. 450 should be able to move more ranks in any given day than an app ranked No. 50. This hypothesis is based on the assumption that higher ranked apps have more installs, active users, and ratings, and that it would take a large margin to produce a noticeable shift in any of these factors.

Results

App Store Ranking Volatility of Top 500 Apps

One look at the chart above shows that apps in both stores have increasingly more volatile rankings (based on how many ranks they moved in the last 24 hours) the lower on the list they’re ranked.

This is particularly true when comparing either end of the spectrum—with a seemingly straight volatility line among Google Play’s Top 100 apps and very few blips within the App Store’s Top 100. Compare this section to the lower end, ranks 401–)500, where both stores experience much more turbulence in their rankings. Across the gamut, I found a 24% correlation between rank and ranking volatility in the Play Store and 28% correlation in the App Store.

To put this into perspective, the average app in Google Play’s 401–)500 ranks moved 12.1 ranks in the last 24 hours while the average app in the Top 100 moved a mere 1.4 ranks. For the App Store, these numbers were 64.28 and 11.26, making slightly lower-ranked apps more than five times as volatile as the highest ranked apps. (I say slightly as these “lower-ranked” apps are still ranked higher than 99.96% of all apps.)

The relationship between rank and volatility is pretty consistent across the App Store charts, while rank has a much greater impact on volatility at the lower end of Google Play charts (ranks 1-100 have a 35% correlation) than it does at the upper end (ranks 401-500 have a 1% correlation).

Study #3: App store rankings across the stars

The next study looks at the relationship between rank and star ratings to determine any trends that set the top chart apps apart from the rest and explore any ties to app store ranking volatility.

Hypothesis

Ranking = fn(Rating, Rating Count, Installs, Trends)

As discussed in the introduction, this study relates directly to one of the factors commonly accepted as influential to app store rankings: average rating.

Getting started, I hypothesized that higher ranks generally correspond to higher ratings, cementing the role of star ratings in the ranking algorithm.

As far as volatility goes, I did not anticipate average rating to play a role in app store ranking volatility, as I saw no reason for higher rated apps to be less volatile than lower rated apps, or vice versa. Instead, I believed volatility to be tied to rating volume (as we’ll explore in our last study).

Results

Average App Store Ratings of Top Apps

The chart above plots the top 100 ranked apps in either store with their average rating (both historic and current, for App Store apps). If it looks a little chaotic, it’s just one indicator of the complexity of ranking algorithm in Google Play and the App Store.

If our hypothesis was correct, we’d see a downward trend in ratings. We’d expect to see the No. 1 ranked app with a significantly higher rating than the No. 100 ranked app. Yet, in neither store is this the case. Instead, we get a seemingly random plot with no obvious trends that jump off the chart.

A closer examination, in tandem with what we already know about the app stores, reveals two other interesting points:

  1. The average star rating of the top 100 apps is significantly higher than that of the average app. Across the top charts, the average rating of a top 100 Android app was 4.319 and the average top iOS app was 3.935. These ratings are 0.32 and 0.27 points, respectively, above the average rating of all rated apps in either store. The averages across apps in the 401–)500 ranks approximately split the difference between the ratings of the top ranked apps and the ratings of the average app.
  2. The rating distribution of top apps in Google Play was considerably more compact than the distribution of top iOS apps. The standard deviation of ratings in the Apple App Store top chart was over 2.5 times greater than that of the Google Play top chart, likely meaning that ratings are more heavily weighted in Google Play’s algorithm.

App Store Ranking Volatility and Average Rating

Looking next at the relationship between ratings and app store ranking volatility reveals a -15% correlation that is consistent across both app stores; meaning the higher an app is rated, the less its rank it likely to move in a 24-hour period. The exception to this rule is the Apple App Store’s calculation of an app’s current rating, for which I did not find a statistically significant correlation.

Study #4: App store rankings across versions

This next study looks at the relationship between the age of an app’s current version, its rank and its ranking volatility.

Hypothesis

Ranking = fn(Rating, Rating Count, Installs, Trends)

In alteration of the above function, I’m using the age of a current app’s version as a proxy (albeit not a very good one) for trends in app store ratings and app quality over time.

Making the assumptions that (a) apps that are updated more frequently are of higher quality and (b) each new update inspires a new wave of installs and ratings, I’m hypothesizing that the older the age of an app’s current version, the lower it will be ranked and the less volatile its rank will be.

Results

How update frequency correlates with app store rank

The first and possibly most important finding is that apps across the top charts in both Google Play and the App Store are updated remarkably often as compared to the average app.

At the time of conducting the study, the current version of the average iOS app on the top chart was only 28 days old; the current version of the average Android app was 38 days old.

As hypothesized, the age of the current version is negatively correlated with the app’s rank, with a 13% correlation in Google Play and a 10% correlation in the App Store.

How update frequency correlates with app store ranking volatility

The next part of the study maps the age of the current app version to its app store ranking volatility, finding that recently updated Android apps have less volatile rankings (correlation: 8.7%) while recently updated iOS apps have more volatile rankings (correlation: -3%).

Study #5: App store rankings across monthly active users

In the final study, I wanted to examine the role of an app’s popularity on its ranking. In an ideal world, popularity would be measured by an app’s monthly active users (MAUs), but since few mobile app developers have released this information, I’ve settled for two publicly available proxies: Rating Count and Installs.

Hypothesis

Ranking = fn(Rating, Rating Count, Installs, Trends)

For the same reasons indicated in the second study, I anticipated that more popular apps (e.g., apps with more ratings and more installs) would be higher ranked and less volatile in rank. This, again, takes into consideration that it takes more of a shift to produce a noticeable impact in average rating or any of the other commonly accepted influencers of an app’s ranking.

Results

Apps with more ratings and reviews typically rank higher

The first finding leaps straight off of the chart above: Android apps have been rated more times than iOS apps, 15.8x more, in fact.

The average app in Google Play’s Top 100 had a whopping 3.1 million ratings while the average app in the Apple App Store’s Top 100 had 196,000 ratings. In contrast, apps in the 401–)500 ranks (still tremendously successful apps in the 99.96 percentile of all apps) tended to have between one-tenth (Android) and one-fifth (iOS) of the ratings count as that of those apps in the top 100 ranks.

Considering that almost two-thirds of apps don’t have a single rating, reaching rating counts this high is a huge feat, and a very strong indicator of the influence of rating count in the app store ranking algorithms.

To even out the playing field a bit and help us visualize any correlation between ratings and rankings (and to give more credit to the still-staggering 196k ratings for the average top ranked iOS app), I’ve applied a logarithmic scale to the chart above:

The relationship between app store ratings and rankings in the top 100 apps

From this chart, we can see a correlation between ratings and rankings, such that apps with more ratings tend to rank higher. This equates to a 29% correlation in the App Store and a 40% correlation in Google Play.

Apps with more ratings typically experience less app store ranking volatility

Next up, I looked at how ratings count influenced app store ranking volatility, finding that apps with more ratings had less volatile rankings in the Apple App Store (correlation: 17%). No conclusive evidence was found within the Top 100 Google Play apps.

Apps with more installs and active users tend to rank higher in the app stores

And last but not least, I looked at install counts as an additional proxy for MAUs. (Sadly, this is a statistic only listed in Google Play. so any resulting conclusions are applicable only to Android apps.)

Among the top 100 Android apps, this last study found that installs were heavily correlated with ranks (correlation: -35.5%), meaning that apps with more installs are likely to rank higher in Google Play. Android apps with more installs also tended to have less volatile app store rankings, with a correlation of -16.5%.

Unfortunately, these numbers are slightly skewed as Google Play only provides install counts in broad ranges (e.g., 500k–)1M). For each app, I took the low end of the range, meaning we can likely expect the correlation to be a little stronger since the low end was further away from the midpoint for apps with more installs.

Summary

To make a long post ever so slightly shorter, here are the nuts and bolts unearthed in these five mad science studies in app store optimization:

  1. Across the top charts, Apple App Store rankings are 4.45x more volatile than those of Google Play
  2. Rankings become increasingly volatile the lower an app is ranked. This is particularly true across the Apple App Store’s top charts.
  3. In both stores, higher ranked apps tend to have an app store ratings count that far exceeds that of the average app.
  4. Ratings appear to matter more to the Google Play algorithm, especially as the Apple App Store top charts experience a much wider ratings distribution than that of Google Play’s top charts.
  5. The higher an app is rated, the less volatile its rankings are.
  6. The 100 highest ranked apps in either store are updated much more frequently than the average app, and apps with older current versions are correlated with lower ratings.
  7. An app’s update frequency is negatively correlated with Google Play’s ranking volatility but positively correlated with ranking volatility in the App Store. This likely due to how Apple weighs an app’s most recent ratings and reviews.
  8. The highest ranked Google Play apps receive, on average, 15.8x more ratings than the highest ranked App Store apps.
  9. In both stores, apps that fall under the 401–500 ranks receive, on average, 10–20% of the rating volume seen by apps in the top 100.
  10. Rating volume and, by extension, installs or MAUs, is perhaps the best indicator of ranks, with a 29–40% correlation between the two.

Revisiting our first (albeit oversimplified) guess at the app stores’ ranking algorithm gives us this loosely defined function:

Ranking = fn(Rating, Rating Count, Installs, Trends)

I’d now re-write the function into a formula by weighing each of these four factors, where a, b, c, & d are unknown multipliers, or weights:

Ranking = (Rating * a) + (Rating Count * b) + (Installs * c) + (Trends * d)

These five studies on ASO shed a little more light on these multipliers, showing Rating Count to have the strongest correlation with rank, followed closely by Installs, in either app store.

It’s with the other two factors—rating and trends—that the two stores show the greatest discrepancy. I’d hazard a guess to say that the App Store prioritizes growth trends over ratings, given the importance it places on an app’s current version and the wide distribution of ratings across the top charts. Google Play, on the other hand, seems to favor ratings, with an unwritten rule that apps just about have to have at least four stars to make the top 100 ranks.

Thus, we conclude our mad science with this final glimpse into what it takes to make the top charts in either store:

Weight of factors in the Apple App Store ranking algorithm

Rating Count > Installs > Trends > Rating

Weight of factors in the Google Play ranking algorithm

Rating Count > Installs > Rating > Trends


Again, we’re oversimplifying for the sake of keeping this post to a mere 3,000 words, but additional factors including keyword density and in-app engagement statistics continue to be strong indicators of ranks. They simply lie outside the scope of these studies.

I hope you found this deep-dive both helpful and interesting. Moving forward, I also hope to see ASOs conducting the same experiments that have brought SEO to the center stage, and encourage you to enhance or refute these findings with your own ASO mad science experiments.

Please share your thoughts in the comments below, and let’s deconstruct the ranking formula together, one experiment at a time.

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