Darryl, the man behind dotmailer’s Custom Technical Solutions team

Why did you decide to come to dotmailer?

I first got to know dotmailer when the company was just a bunch of young enthusiastic web developers called Ellipsis Media back in 1999. I was introduced by one of my suppliers and we decided to bring them on board to build a recruitment website for one of our clients. That client was Amnesty International and the job role was Secretary General. Not bad for a Croydon company whose biggest client before that was Scobles the plumber’s merchants. So, I was probably dotmailer’s first ever corporate client! After that, I used dotmailer at each company I worked for and then one day they approached a colleague and me and asked us if we wanted to work for them. That was 2013.  We grabbed the opportunity with both hands and haven’t looked back since.

Tell us a bit about your role

I’m the Global Head of Technical Solutions which actually gives me responsibility for 2 teams. First, Custom Technical Solutions (CTS), who build bespoke applications and tools for customers that allow them to integrate more closely with dotmailer and make life easier. Second, Technical Pre-sales, which spans our 3 territories (EMEA, US and APAC) and works with prospective and existing clients to figure out the best solution and fit within dotmailer.

What accomplishments are you most proud of from your dotmailer time so far?

I would say so far it has to be helping to turn the CTS team from just 2 people into a group of 7 highly skilled and dedicated men and women who have become an intrinsic and valued part of the dotmailer organization. Also I really enjoy being part of the Senior Technical Management team. Here we have the ability to influence the direction and structure of the platform on a daily basis.

Meet Darryl Clark – the cheese and peanut butter sandwich lover

Can you speak a bit about your background and that of your team? What experience and expertise is required to join this team?

My background is quite diverse from a stint in the Army, through design college, web development, business analysis to heading up my current teams. I would say the most valuable skill that I have is being highly analytical. I love nothing more than listening to a client’s requirements and digging deep to work out how we can answer these if not exceed them.

As a team, we love nothing more than brainstorming our ideas. Every member has a valid input and we listen. Everyone has the opportunity to influence what we do and our motto is “there is no such thing as a stupid question.”

To work in my teams you have to be analytical but open minded to the fact that other people may have a better answer than you. Embrace other people’s input and use it to give our clients the best possible solution. We are hugely detail conscious, but have to be acutely aware that we need to tailor what we say to our audience so being able to talk to anyone at any level is hugely valuable.

How much of the dotmailer platform is easily customizable and when does it cross over into something that requires your team’s expertise? How much time is spent on these custom solutions one-time or ongoing?

I’ll let you in on a little secret here. We don’t actually do anything that our customers can’t do with dotmailer given the right knowledge and resources. This is because we build all of our solutions using the dotmailer public API. The API has hundreds of methods in both SOAP and REST versions, which allows you to do a huge amount with the dotmailer platform. We do have a vast amount of experience and knowledge in the team so we may well be able to build a solution quicker than our customers. We are more than happy to help them and their development teams build a solution using us on a consultancy basis to lessen the steepness of the learning curve.

Our aim when building a solution for a customer is that it runs silently in the background and does what it should without any fuss.

What are your plans for the Custom Tech Solutions team going forward?

The great thing about Custom Technical Solutions is you never know what is around the corner as our customers have very diverse needs. What we are concentrating on at the moment is refining our processes to ensure that they are as streamlined as possible and allow us to give as much information to the customer as we can. We are also always looking at the technology and coding approaches that we use to make sure that we build the most innovative and robust solutions.

We are also looking at our external marketing and sharing our knowledge through blogs so keep an eye on the website for our insights.

What are the most common questions that you get when speaking to a prospective customer?

Most questions seem to revolve around reassurance such as “Have you done this before?”, “How safe is my data?”, “What about security?”, “Can you talk to my developers?”, “Do I need to do anything?”.  In most instances, we are the ones asking the questions as we need to find out information as soon as possible so that we can analyse it to ensure that we have the right detail to provide the right solution.

Can you tell us about the dotmailer differentiators you highlight when speaking to prospective customers that seem to really resonate?

We talk a lot about working with best of breed so for example a customer can use our Channel Extensions in automation programs to fire out an SMS to a contact using their existing provider. We don’t force customers down one route, we like to let them decide for themselves.

Also, I really like to emphasize the fact that there is always more than one way to do something within the dotmailer platform. This means we can usually find a way to do something that works for a client within the platform. If not, then we call in CTS to work out if there is a way that we can build something that will — whether this is automating uploads for a small client or mass sending from thousands of child accounts for an enterprise level one.

What do you see as the future of marketing automation technology?  Will one size ever fit all? Or more customization going forward?

The 64 million dollar question. One size will never fit all. Companies and their systems are too organic for that. There isn’t one car that suits every driver or one racquet that suits every sport. Working with a top drawer partner network and building our system to be as open as possible from an integration perspective means that our customers can make dotmailer mold to their business and not the other way round…and adding to that the fact that we are building lots of features in the platform that will blow your socks off.

Tell us a bit about yourself – favorite sports team, favorite food, guilty pleasure, favorite band, favorite vacation spot?

I’m a dyed in the wool Gooner (aka Arsenal Football Club fan) thanks to my Grandfather leading me down the right path as a child. If you are still reading this after that bombshell, then food-wise I pretty much like everything apart from coriander which as far as I’m concerned is the Devils own spawn. I don’t really have a favorite band, but am partial to a bit of Level 42 and Kings of Leon and you will also find me listening to 90s drum and bass and proper old school hip hop. My favorite holiday destination is any decent villa that I can relax in and spend time with my family and I went to Paris recently and loved that. Guilty pleasure – well that probably has to be confessing to liking Coldplay or the fact that my favorite sandwich is peanut butter, cheese and salad cream. Go on try it, you’ll love it.

Want to meet more of the dotmailer team? Say hi to Darren Hockley, Global Head of Support, and Dan Morris, EVP for North America.

Reblogged 3 years ago from blog.dotmailer.com

Is Australia the land of opportunity for your retail brand?

Australia has a resident population of more than 24 million and, according to eMarketer, the country’s ecommerce sales are predicted to reach A$32.56 billion by 2017. The country’s remote location in the APAC region means that unlike European countries or the USA, traditionally there have been a lack of global brands sold locally.

Of course, we also know that many expatriates, particularly from inside the Commonwealth, have made Australia their home and are keen to buy products they know and love from their country of origin.

All of these factors present a huge and potentially lucrative opportunity for non-Australian brands wanting to open up their new and innovative products to a fresh market, or compete for market share.

But it’s not just non-Australian retailers who are at an advantage here: Australia was late to the ecommerce party because native, established brands were trading well without it. Subsequently, Australian retailers’ ecommerce technology stacks are much more recent and not burdened by legacy systems. This makes it much easier to extend, or get started with, best-of-breed technologies and cash in on a market that’s booming. To put some of this into perspective, Magento’s innovative ecommerce platform currently takes 42% of Australia’s market share and the world’s first adopter of Magento 2.0 was an Australian brand.

The GST loophole

At the moment, local retailers are campaigning against a rule that exempts foreign websites from being charged a 10% general sales tax (GST) on purchases under A$1,000. And in 2013, Australian consumers made $3.11 billion worth of purchases under A$1,000.[1]

While the current GST break appears to put non-Australian retailers at an advantage, Australian-based brands such as Harvey Norman are using it to their advantage by setting up ecommerce operations in Asia to enjoy the GST benefit.

Australian consumers have also countered the argument by saying that price isn’t always the motivator when it comes to making purchasing decisions.

It’s not a place where no man has gone before

Often, concerns around meeting local compliance and lack of overseas business knowledge prevent outsiders from taking the leap into cross-border trade. However, this ecommerce passport, created by Ecommerce Worldwide and NORA, is designed to support those considering selling in Australia. The guide provides a comprehensive look into everything from the country’s economy and trade status, to logistics and dealing with international payments.

Global expansion success stories are also invaluable sources of information. For instance, it’s not just lower-end retailers that are fitting the bill, with brands like online luxury fashion retailer Net-a-Porter naming Australia as one of its biggest markets.

How tech-savvy are the Aussies?

One of the concerns you might have as a new entrant into the market is how you’ll reach and sell to your new audience, particularly without having a physical presence. The good news is that more than 80% of the country is digitally enabled and 60% of mobile phone users own a smartphone – so online is deeply rooted into the majority of Australians’ lives. [2]

Marketing your brand

Heard the saying “Fire bullets then fire cannonballs”? In any case, you’ll want to test the waters and gauge people’s reactions to your product or service.

It all starts with the website because, without it, you’re not discoverable or searchable, and you’ve nowhere to drive people to when running campaigns. SEO and SEM should definitely be a priority, and an online store that can handle multiple regions and storefronts, like Magento, will make your life easier. A mobile-first mentality and well thought-out UX will also place you in a good position.

Once your new web store is set up, you should be making every effort to collect visitors’ email addresses, perhaps via a popover. Why? Firstly, email is one of the top three priority areas for Australian retailers, because it’s a cost-effective, scalable marketing channel that enables true personalization.

Secondly, email marketing automation empowers you to deliver the customer experience today’s consumer expects, as well as enabling you to communicate with them throughout the lifecycle. Check out our ‘Do customer experience masters really exist?’ whitepaper for some real-life success stories.

Like the Magento platform, dotmailer is set up to handle multiple languages, regions and accounts, and is designed to grow with you.

In summary, there’s great scope for ecommerce success in Australia, whether you’re a native bricks-and-mortar retailer, a start-up or a non-Australian merchant. The barriers to cross-border trade are falling and Australia is one of APAC’s most developed regions in terms of purchasing power and tech savviness.

We recently worked with ecommerce expert Chloe Thomas to produce a whitepaper on cross-border trade, which goes into much more detail on how to market and sell successfully in new territories. You can download a free copy here.

[1] Australian Passport 2015: Cross-Border Trading Report

[2] Australian Passport 2015: Cross-Border Trading Report

Reblogged 3 years ago from blog.dotmailer.com

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.

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

Reblogged 4 years ago from tracking.feedpress.it

A Vision for Brand Engagement Online, or "The Goal"

Posted by EricEnge

Today’s post focuses on a vision for your online presence. This vision outlines what it takes to be the best, both from an overall reputation and visibility standpoint, as well as an SEO point of view. The reason these are tied together is simple: Your overall online reputation and visibility is a huge factor in your SEO. Period. Let’s start by talking about why.

Core ranking signals

For purposes of this post, let’s define three cornerstone ranking signals that most everyone agrees on:

Links

Links remain a huge factor in overall ranking. Both Cyrus Shepard and Marcus Tober re-confirmed this on the Periodic Table of SEO Ranking Factors session at the SMX Advanced conference in Seattle this past June.

On-page content

On-page content remains a huge factor too, but with some subtleties now thrown in. I wrote about some of this in earlier posts I did on Moz about Term Frequency and Inverse Document Frequency. Suffice it to say that on-page content is about a lot more than pure words on the page, but also includes the supporting pages that you link to.

User engagement with your site

This is not one of the traditional SEO signals from the early days of SEO, but most advanced SEO pros that I know consider it a real factor these days. One of the most popular concepts people talk about is called pogo-sticking, which is illustrated here:

You can learn more about the pogosticking concept by visiting this Whiteboard Friday video by a rookie SEO with a last name of Fishkin.

New, lesser-known signals

OK, so these are the more obvious signals, but now let’s look more broadly at the overall web ecosystem and talk about other types of ranking signals. Be warned that some of these signals may be indirect, but that just doesn’t matter. In fact, my first example below is an indirect factor which I will use to demonstrate why whether a signal is direct or indirect is not an issue at all.

Let me illustrate with an example. Say you spend $1 billion dollars building a huge brand around a product that is massively useful to people. Included in this is a sizable $100 million dollar campaign to support a highly popular charitable foundation, and your employees regularly donate time to help out in schools across your country. In short, the great majority of people love your brand.

Do you think this will impact the way people link to your site? Of course it does. Do you think it will impact how likely people are to be satisified with quality of the pages of your site? Consider this A/B test scenario of 2 pages from different “brands” (for the one on the left, imagine the image of Coca Cola or Pepsi Cola, whichever one you prefer):

Do you think that the huge brand will get a benefit of a doubt on their page that the no-name brand does not even though the pages are identical? Of course they will. Now let’s look at some simpler scenarios that don’t involve a $1 billion investment.

1. Cover major options related to a product or service on “money pages”

Imagine that a user arrives on your auto parts site after searching on the phrase “oil filter” at Google or Bing. Chances are pretty good that they want an oil filter, but here are some other items they may also want:

  • A guide to picking the right filter for their car
  • Oil
  • An oil filter wrench
  • A drainage pan to drain the old oil into

This is just the basics, right? But, you would be surprised with how many sites don’t include links or information on directly related products on their money pages. Providing this type of smart site and page design can have a major impact on user engagement with the money pages of your site.

2. Include other related links on money pages

In the prior item we covered the user’s most directly related needs, but they may have secondary needs as well. Someone who is changing a car’s oil is either a mechanic or a do-it-yourself-er. What else might they need? How about other parts, such as windshield wipers or air filters?

These are other fairly easy maintenance steps for someone who is working on their car to complete. Presence of these supporting products could be one way to improve user engagement with your pages.

3. Offer industry-leading non-commercial content on-site

Publishing world-class content on your site is a great way to produce links to your site. Of course, if you do this on a blog on your site, it may not provide links directly to your money pages, but it will nonetheless lift overall site authority.

In addition, if someone has consumed one or more pieces of great content on your site, the chance of their engaging in a more positive manner with your site overall go way up. Why? Because you’ve earned their trust and admiration.

4. Be everywhere your audiences are with more high-quality, relevant, non-commercial content

Are there major media sites that cover your market space? Do they consider you to be an expert? Will they quote you in articles they write? Can you provide them with guest posts or let you be a guest columnist? Will they collaborate on larger content projects with you?

All of these activities put you in front of their audiences, and if those audiences overlap with yours, this provides a great way to build your overall reputation and visibility. This content that you publish, or collaborate on, that shows up on 3rd-party sites will get you mentions and links. In addition, once again, it will provide you with a boost to your branding. People are now more likely to consume your other content more readily, including on your money pages.

5. Leverage social media

The concept here shares much in common with the prior point. Social media provides opportunities to get in front of relevant audiences. Every person that’s an avid follower of yours on a social media site is more likely to show very different behavior characteristics interacting with your site than someone that does not know you well at all.

Note that links from social media sites are nofollowed, but active social media behavior can lead to people implementing “real world” links to your site that are followed, from their blogs and media web sites.

6. Be active in the offline world as well

Think your offline activity doesn’t matter online? Think again. Relationships are still most easily built face-to-face. People you meet and spend time with can well become your most loyal fans online. This is particularly important when it comes to building relationships with influential people.

One great way to do that is to go to public events related to your industry, such as conferences. Better still, obtain speaking engagements at those conferences. This can even impact people who weren’t there to hear you speak, as they become aware that you have been asked to do that. This concept can also work for a small local business. Get out in your community and engage with people at local events.

The payoff here is similar to the payoff for other items: more engaged, highly loyal fans who engage with you across the web, sending more and more positive signals, both to other people and to search engines, that you are the real deal.

7. Provide great customer service/support

Whatever your business may be, you need to take care of your customers as best you can. No one can make everyone happy, that’s unrealistic, but striving for much better than average is a really sound idea. Having satisfied customers saying nice things about you online is a big impact item in the grand scheme of things.

8. Actively build relationships with influencers too

While this post is not about the value of influencer relationships, I include this in the list for illustration purposes, for two reasons:

  1. Some opportunities are worth extra effort. Know of someone who could have a major impact on your business? Know that they will be at a public event in the near future? Book your plane tickets and get your butt out there. No guarantee that you will get the result you are looking for, or that it will happen quickly, but your chances go WAY up if you get some face time with them.
  2. Influencers are worth special attention and focus, but your relationship-building approach to the web and SEO is not only about influencers. It’s about the entire ecosystem.

It’s an integrated ecosystem

The web provides a level of integrated, real-time connectivity of a kind that the world has never seen before. This is only going to increase. Do something bad to a customer in Hong Kong? Consumers in Boston will know within 5 minutes. That’s where it’s all headed.

Google and Bing (and any future search engine that may emerge) want to measure these types of signals because they tell them how to improve the quality of the experience on their platforms. There are may ways they can perform these measurements.

One simple concept is covered by Rand in this recent Whiteboard Friday video. The discussion is about a recent patent granted to Google that shows how the company can use search queries to detect who is an authority on a topic.

The example he provides is about people who search on “email finding tool”. If Google also finds that a number of people search on “voila norbert email tool”, Google may use that as an authority signal.

Think about that for a moment. How are you going to get people to search on your brand more while putting it together with a non-branded querly like that? (OK, please leave Mechanical Turk and other services like that out of the discussion).

Now you can start to see the bigger picture. Measurements like pogosticking and this recent search behavior related patent are just the tip of the iceberg. Undoubtedly, there are many other ways that search engines can measure what people like and engage with the most.

This is all part of SEO now. UX, product breadth, problem solving, UX, engaging in social media, getting face to face, creating great content that you publish in front of other people’s audiences, and more.

For the small local business, you can still win at this game, as your focus just needs to be on doing it better than your competitors. The big brands will never be hyper-local like you are, so don’t think you can’t play the game, because you can.

Whoever you are, get ready, because this new integrated ecosystem is already upon us, and you need to be a part of it.

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Reblogged 4 years ago from tracking.feedpress.it

8 Ways Content Marketers Can Hack Facebook Multi-Product Ads

Posted by Alan_Coleman

The trick most content marketers are missing

Creating great content is the first half of success in content marketing. Getting quality content read by, and amplified to, a relevant audience is the oft overlooked second half of success. Facebook can be a content marketer’s best friend for this challenge. For reach, relevance and amplification potential, Facebook is unrivaled.

  1. Reach: 1 in 6 mobile minutes on planet earth is somebody reading something on Facebook.
  2. Relevance: Facebook is a lean mean interest and demo targeting machine. There is no online or offline media that owns as much juicy interest and demographic information on its audience and certainly no media has allowed advertisers to utilise this information as effectively as Facebook has.
  3. Amplification: Facebook is literally built to encourage sharing. Here’s the first 10 words from their mission statement: “Facebook’s mission is to give people the power to share…”, Enough said!

Because of these three digital marketing truths, if a content marketer gets their paid promotion* right on Facebook, the battle for eyeballs and amplification is already won.

For this reason it’s crucial that content marketers keep a close eye on Facebook advertising innovations and seek out ways to use them in new and creative ways.

In this post I will share with you eight ways we’ve hacked a new Facebook ad format to deliver content marketing success.

Multi-Product Ads (MPAs)

In 2014, Facebook unveiled multi-product ads (MPAs) for US advertisers, we got them in Europe earlier this year. They allow retailers to show multiple products in a carousel-type ad unit.

They look like this:

If the user clicks on the featured product, they are guided directly to the landing page for that specific product, from where they can make a purchase.

You could say MPAs are Facebook’s answer to Google Shopping.

Facebook’s mistake is a content marketer’s gain

I believe Facebook has misunderstood how people want to use their social network and the transaction-focused format is OK at best for selling products. People aren’t really on Facebook to hit the “buy now” button. I’m a daily Facebook user and I can’t recall a time this year where I have gone directly from Facebook to an e-commerce website and transacted. Can you remember a recent time when you did?

So, this isn’t an innovation that removes a layer of friction from something that we are all doing online already (as the most effective innovations do). Instead, it’s a bit of a “hit and hope” that, by providing this functionality, Facebook would encourage people to try to buy online in a way they never have before.

The Wolfgang crew felt the MPA format would be much more useful to marketers and users if they were leveraging Facebook for the behaviour we all demonstrate on the platform every day, guiding users to relevant content. We attempted to see if Facebook Ads Manager would accept MPAs promoting content rather than products. We plugged in the images, copy and landing pages, hit “place order”, and lo and behold the ads became active. We’re happy to say that the engagement rates, and more importantly the amplification rates, are fantastic!

Multi-Content Ads

We’ve re-invented the MPA format for multi-advertisers in multi-ways, eight ways to be exact! Here’s eight MPA Hacks that have worked well for us. All eight hacks use the MPA format to promote content rather than promote products.

Hack #1: Multi-Package Ads

Our first variation wasn’t a million miles away from multi-product ads; we were promoting the various packages offered by a travel operator.

By looking at the number of likes, comments, and shares (in blue below the ads) you can see the ads were a hit with Facebook users and they earned lots of free engagement and amplification.

NB: If you have selected “clicks to website” as your advertising objective, all those likes, comments and shares are free!

Independent Travel Multi Product Ad

The ad sparked plenty of conversation amongst Facebook friends in the comments section.

Comments on a Facebook MPA

Hack #2: Multi-Offer Ads

Everybody knows the Internet loves a bargain. So we decided to try another variation moving away from specific packages, focusing instead on deals for a different travel operator.

Here’s how the ads looked:

These ads got valuable amplification beyond the share. In the comments section, you can see people tagging specific friends. This led to the MPAs receiving further amplification, and a very targeted and personalised form of amplification to boot.

Abbey Travel Facebook Ad Comments

Word of mouth referrals have been a trader’s best friend since the stone age. These “personalised” word of mouth referrals en masse are a powerful marketing proposition. It’s worth mentioning again that those engagements are free!

Hack #3: Multi-Locations Ads

Putting the Lo in SOLOMO.

This multi-product feed ad was hacked to promote numerous locations of a waterpark. “Where to go?” is among the first questions somebody asks when researching a holiday. In creating this top of funnel content, we can communicate with our target audience at the very beginning of their research process. A simple truth of digital marketing is: the more interactions you have with your target market on their journey to purchase, the more likely they are to seal the deal with you when it comes time to hit the “buy now” button. Starting your relationship early gives you an advantage over those competitors who are hanging around the bottom of the purchase funnel hoping to make a quick and easy conversion.

Abbey Travel SplashWorld Facebook MPA

What was surprising here, was that because we expected to reach people at the very beginning of their research journey, we expected the booking enquiries to be some time away. What actually happened was these ads sparked an enquiry frenzy as Facebook users could see other people enquiring and the holidays selling out in real time.

Abbey Travel comments and replies

In fact nearly all of the 35 comments on this ad were booking enquiries. This means what we were measuring as an “engagement” was actually a cold hard “conversion”! You don’t need me to tell you a booking enquiry is far closer to the money than a Facebook like.

The three examples outlined so far are for travel companies. Travel is a great fit for Facebook as it sits naturally in the Facebook feed, my Facebook feed is full of envy-inducing friends’ holiday pictures right now. Another interesting reason why travel is a great fit for Facebook ads is because typically there are multiple parties to a travel purchase. What happened here is the comments section actually became a very visible and measurable forum for discussion between friends and family before becoming a stampede inducing medium of enquiry.

So, stepping outside of the travel industry, how do other industries fare with hacked MPAs?

Hack #3a: Multi-Location Ads (combined with location targeting)

Location, location, location. For a property listings website, we applied location targeting and repeated our Multi-Location Ad format to advertise properties for sale to people in and around that location.

Hack #4: Multi-Big Content Ad

“The future of big content is multi platform”

– Cyrus Shepard

The same property website had produced a report and an accompanying infographic to provide their audience with unique and up-to-the-minute market information via their blog. We used the MPA format to promote the report, the infographic and the search rentals page of the website. This brought their big content piece to a larger audience via a new platform.

Rental Report Multi Product Ad

Hack #5: Multi-Episode Ad

This MPA hack was for an online TV player. As you can see we advertised the most recent episodes of a TV show set in a fictional Dublin police station, Red Rock.

Engagement was high, opinion was divided.

TV3s Red Rock viewer feedback

LOL.

Hack #6: Multi-People Ads

In the cosmetic surgery world, past patients’ stories are valuable marketing material. Particularly when the past patients are celebrities. We recycled some previously published stories from celebrity patients using multi-people ads and targeted them to a very specific audience.

Avoca Clinic Multi People Ads

Hack #7: Multi-UGC Ads

Have you witnessed the power of user generated content (UGC) in your marketing yet? We’ve found interaction rates with authentic UGC images can be up to 10 fold of those of the usual stylised images. In order to encourage further UGC, we posted a number of customer’s images in our Multi-UGC Ads.

The CTR on the above ads was 6% (2% is the average CTR for Facebook News feed ads according to our study). Strong CTRs earn you more traffic for your budget. Facebook’s relevancy score lowers your CPC as your CTR increases.

When it comes to the conversion, UGC is a power player, we’ve learned that “customers attracting new customers” is a powerful acquisition tool.

Hack #8: Target past customers for amplification

“Who will support and amplify this content and why?”

– Rand Fishkin

Your happy customers Rand, that’s the who and the why! Check out these Multi-Package Ads targeted to past customers via custom audiences. The Camino walkers have already told all their friends about their great trip, now allow them to share their great experiences on Facebook and connect the tour operator with their Facebook friends via a valuable word of mouth referral. Just look at the ratio of share:likes and shares:comments. Astonishingly sharable ads!

Camino Ways Mulit Product Ads

Targeting past converters in an intelligent manner is a super smart way to find an audience ready to share your content.

How will hacking Multi-Product Ads work for you?

People don’t share ads, but they do share great content. So why not hack MPAs to promote your content and reap the rewards of the world’s greatest content sharing machine: Facebook.

MPAs allow you to tell a richer story by allowing you to promote multiple pieces of content simultaneously. So consider which pieces of content you have that will work well as “content bundles” and who the relevant audience for each “content bundle” is.

As Hack #8 above illustrates, the big wins come when you match a smart use of the format with the clever and relevant targeting Facebook allows. We’re massive fans of custom audiences so if you aren’t sure where to start, I’d suggest starting there.

So ponder your upcoming content pieces, consider your older content you’d like to breathe some new life into and perhaps you could become a Facebook Ads Hacker.

I’d love to hear about your ideas for turning Multi-Product Ads into Multi-Content Ads in the comments section below.

We could even take the conversation offline at Mozcon!

Happy hacking.


*Yes I did say paid promotion, it’s no secret that Facebook’s organic reach continues to dwindle. The cold commercial reality is you need to pay to play on FB. The good news is that if you select ‘website clicks’ as your objective you only pay for website traffic and engagement while amplification by likes, comments, and shares are free! Those website clicks you pay for are typically substantially cheaper than Adwords, Taboola, Outbrain, Twitter or LinkedIn. How does it compare to display? It doesn’t. Paying for clicks is always preferable to paying for impressions. If you are spending money on display advertising I’d urge you to fling a few spondoolas towards Facebook ads and compare results. You will be pleasantly surprised.

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How to Rid Your Website of Six Common Google Analytics Headaches

Posted by amandaecking

I’ve been in and out of Google Analytics (GA) for the past five or so years agency-side. I’ve seen three different code libraries, dozens of new different features and reports roll out, IP addresses stop being reported, and keywords not-so-subtly phased out of the free platform.

Analytics has been a focus of mine for the past year or so—mainly, making sure clients get their data right. Right now, our new focus is closed loop tracking, but that’s a topic for another day. If you’re using Google Analytics, and only Google Analytics for the majority of your website stats, or it’s your primary vehicle for analysis, you need to make sure it’s accurate.

Not having data pulling in or reporting properly is like building a house on a shaky foundation: It doesn’t end well. Usually there are tears.

For some reason, a lot of people, including many of my clients, assume everything is tracking properly in Google Analytics… because Google. But it’s not Google who sets up your analytics. People do that. And people are prone to make mistakes.

I’m going to go through six scenarios where issues are commonly encountered with Google Analytics.

I’ll outline the remedy for each issue, and in the process, show you how to move forward with a diagnosis or resolution.

1. Self-referrals

This is probably one of the areas we’re all familiar with. If you’re seeing a lot of traffic from your own domain, there’s likely a problem somewhere—or you need to extend the default session length in Google Analytics. (For example, if you have a lot of long videos or music clips and don’t use event tracking; a website like TEDx or SoundCloud would be a good equivalent.)

Typically one of the first things I’ll do to help diagnose the problem is include an advanced filter to show the full referrer string. You do this by creating a filter, as shown below:

Filter Type: Custom filter > Advanced
Field A: Hostname
Extract A: (.*)
Field B: Request URI
Extract B: (.*)
Output To: Request URI
Constructor: $A1$B1

You’ll then start seeing the subdomains pulling in. Experience has shown me that if you have a separate subdomain hosted in another location (say, if you work with a separate company and they host and run your mobile site or your shopping cart), it gets treated by Google Analytics as a separate domain. Thus, you ‘ll need to implement cross domain tracking. This way, you can narrow down whether or not it’s one particular subdomain that’s creating the self-referrals.

In this example below, we can see all the revenue is being reported to the booking engine (which ended up being cross domain issues) and their own site is the fourth largest traffic source:

I’ll also a good idea to check the browser and device reports to start narrowing down whether the issue is specific to a particular element. If it’s not, keep digging. Look at pages pulling the self-referrals and go through the code with a fine-tooth comb, drilling down as much as you can.

2. Unusually low bounce rate

If you have a crazy-low bounce rate, it could be too good to be true. Unfortunately. An unusually low bounce rate could (and probably does) mean that at least on some pages of your website have the same Google Analytics tracking code installed twice.

Take a look at your source code, or use Google Tag Assistant (though it does have known bugs) to see if you’ve got GA tracking code installed twice.

While I tell clients having Google Analytics installed on the same page can lead to double the pageviews, I’ve not actually encountered that—I usually just say it to scare them into removing the duplicate implementation more quickly. Don’t tell on me.

3. Iframes anywhere

I’ve heard directly from Google engineers and Google Analytics evangelists that Google Analytics does not play well with iframes, and that it will never will play nice with this dinosaur technology.

If you track the iframe, you inflate your pageviews, plus you still aren’t tracking everything with 100% clarity.

If you don’t track across iframes, you lose the source/medium attribution and everything becomes a self-referral.

Damned if you do; damned if you don’t.

My advice: Stop using iframes. They’re Netscape-era technology anyway, with rainbow marquees and Comic Sans on top. Interestingly, and unfortunately, a number of booking engines (for hotels) and third-party carts (for ecommerce) still use iframes.

If you have any clients in those verticals, or if you’re in the vertical yourself, check with your provider to see if they use iframes. Or you can check for yourself, by right-clicking as close as you can to the actual booking element:

iframe-booking.png

There is no neat and tidy way to address iframes with Google Analytics, and usually iframes are not the only complicated element of setup you’ll encounter. I spent eight months dealing with a website on a subfolder, which used iframes and had a cross domain booking system, and the best visibility I was able to get was about 80% on a good day.

Typically, I’d approach diagnosing iframes (if, for some reason, I had absolutely no access to viewing a website or talking to the techs) similarly to diagnosing self-referrals, as self-referrals are one of the biggest symptoms of iframe use.

4. Massive traffic jumps

Massive jumps in traffic don’t typically just happen. (Unless, maybe, you’re Geraldine.) There’s always an explanation—a new campaign launched, you just turned on paid ads for the first time, you’re using content amplification platforms, you’re getting a ton of referrals from that recent press in The New York Times. And if you think it just happened, it’s probably a technical glitch.

I’ve seen everything from inflated pageviews result from including tracking on iframes and unnecessary implementation of virtual pageviews, to not realizing the tracking code was installed on other microsites for the same property. Oops.

Usually I’ve seen this happen when the tracking code was somewhere it shouldn’t be, so if you’re investigating a situation of this nature, first confirm the Google Analytics code is only in the places it needs to be.Tools like Google Tag Assistant and Screaming Frog can be your BFFs in helping you figure this out.

Also, I suggest bribing the IT department with sugar (or booze) to see if they’ve changed anything lately.

5. Cross-domain tracking

I wish cross-domain tracking with Google Analytics out of the box didn’t require any additional setup. But it does.

If you don’t have it set up properly, things break down quickly, and can be quite difficult to untangle.

The older the GA library you’re using, the harder it is. The easiest setup, by far, is Google Tag Manager with Universal Analytics. Hard-coded universal analytics is a bit more difficult because you have to implement autoLink manually and decorate forms, if you’re using them (and you probably are). Beyond that, rather than try and deal with it, I say update your Google Analytics code. Then we can talk.

Where I’ve seen the most murkiness with tracking is when parts of cross domain tracking are implemented, but not all. For some reason, if allowLinker isn’t included, or you forget to decorate all the forms, the cookies aren’t passed between domains.

The absolute first place I would start with this would be confirming the cookies are all passing properly at all the right points, forms, links, and smoke signals. I’ll usually use a combination of the Real Time report in Google Analytics, Google Tag Assistant, and GA debug to start testing this. Any debug tool you use will mean you’re playing in the console, so get friendly with it.

6. Internal use of UTM strings

I’ve saved the best for last. Internal use of campaign tagging. We may think, oh, I use Google to tag my campaigns externally, and we’ve got this new promotion on site which we’re using a banner ad for. That’s a campaign. Why don’t I tag it with a UTM string?

Step away from the keyboard now. Please.

When you tag internal links with UTM strings, you override the original source/medium. So that visitor who came in through your paid ad and then who clicks on the campaign banner has now been manually tagged. You lose the ability to track that they came through on the ad the moment they click on the tagged internal link. Their source and medium is now your internal campaign, not that paid ad you’re spending gobs of money on and have to justify to your manager. See the problem?

I’ve seen at least three pretty spectacular instances of this in the past year, and a number of smaller instances of it. Annie Cushing also talks about the evils of internal UTM tags and the odd prevalence of it. (Oh, and if you haven’t explored her blog, and the amazing spreadsheets she shares, please do.)

One clothing company I worked with tagged all of their homepage offers with UTM strings, which resulted in the loss of visibility for one-third of their audience: One million visits over the course of a year, and $2.1 million in lost revenue.

Let me say that again. One million visits, and $2.1 million. That couldn’t be attributed to an external source/campaign/spend.

Another client I audited included campaign tagging on nearly every navigational element on their website. It still gives me nightmares.

If you want to see if you have any internal UTM strings, head straight to the Campaigns report in Acquisition in Google Analytics, and look for anything like “home” or “navigation” or any language you may use internally to refer to your website structure.

And if you want to see how users are moving through your website, go to the Flow reports. Or if you really, really, really want to know how many people click on that sidebar link, use event tracking. But please, for the love of all things holy (and to keep us analytics lovers from throwing our computers across the room), stop using UTM tagging on your internal links.

Now breathe and smile

Odds are, your Google Analytics setup is fine. If you are seeing any of these issues, though, you have somewhere to start in diagnosing and addressing the data.

We’ve looked at six of the most common points of friction I’ve encountered with Google Analytics and how to start investigating them: self-referrals, bounce rate, iframes, traffic jumps, cross domain tracking and internal campaign tagging.

What common data integrity issues have you encountered with Google Analytics? What are your favorite tools to investigate?

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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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Reblogged 4 years ago from tracking.feedpress.it

Inverse Document Frequency and the Importance of Uniqueness

Posted by EricEnge

In my last column, I wrote about how to use term frequency analysis in evaluating your content vs. the competition’s. Term frequency (TF) is only one part of the TF-IDF approach to information retrieval. The other part is inverse document frequency (IDF), which is what I plan to discuss today.

Today’s post will use an explanation of how IDF works to show you the importance of creating content that has true uniqueness. There are reputation and visibility reasons for doing this, and it’s great for users, but there are also SEO benefits.

If you wonder why I am focusing on TF-IDF, consider these words from a Google article from August 2014: “This is the idea of the famous TF-IDF, long used to index web pages.” While the way that Google may apply these concepts is far more than the simple TF-IDF models I am discussing, we can still learn a lot from understanding the basics of how they work.

What is inverse document frequency?

In simple terms, it’s a measure of the rareness of a term. Conceptually, we start by measuring document frequency. It’s easiest to illustrate with an example, as follows:

IDF table

In this example, we see that the word “a” appears in every document in the document set. What this tells us is that it provides no value in telling the documents apart. It’s in everything.

Now look at the word “mobilegeddon.” It appears in 1,000 of the documents, or one thousandth of one percent of them. Clearly, this phrase provides a great deal more differentiation for the documents that contain them.

Document frequency measures commonness, and we prefer to measure rareness. The classic way that this is done is with a formula that looks like this:

idf equation

For each term we are looking at, we take the total number of documents in the document set and divide it by the number of documents containing our term. This gives us more of a measure of rareness. However, we don’t want the resulting calculation to say that the word “mobilegeddon” is 1,000 times more important in distinguishing a document than the word “boat,” as that is too big of a scaling factor.

This is the reason we take the Log Base 10 of the result, to dampen that calculation. For those of you who are not mathematicians, you can loosely think of the Log Base 10 of a number as being a count of the number of zeros – i.e., the Log Base 10 of 1,000,000 is 6, and the log base 10 of 1,000 is 3. So instead of saying that the word “mobilegeddon” is 1,000 times more important, this type of calculation suggests it’s three times more important, which is more in line with what makes sense from a search engine perspective.

With this in mind, here are the IDF values for the terms we looked at before:

idf table logarithm values

Now you can see that we are providing the highest score to the term that is the rarest.

What does the concept of IDF teach us?

Think about IDF as a measure of uniqueness. It helps search engines identify what it is that makes a given document special. This needs to be much more sophisticated than how often you use a given search term (e.g. keyword density).

Think of it this way: If you are one of 6.78 million web sites that comes up for the search query “super bowl 2015,” you are dealing with a crowded playing field. Your chances of ranking for this term based on the quality of your content are pretty much zero.

massive number of results for broad keyword

Overall link authority and other signals will be the only way you can rank for a term that competitive. If you are a new site on the landscape, well, perhaps you should chase something else.

That leaves us with the question of what you should target. How about something unique? Even the addition of a simple word like “predictions”—changing our phrase to “super bowl 2015 predictions”—reduces this playing field to 17,800 results.

Clearly, this is dramatically less competitive already. Slicing into this further, the phrase “super bowl 2015 predictions and odds” returns only 26 pages in Google. See where this is going?

What IDF teaches us is the importance of uniqueness in the content we create. Yes, it will not pay nearly as much money to you as it would if you rank for the big head term, but if your business is a new entrant into a very crowded space, you are not going to rank for the big head term anyway

If you can pick out a smaller number of terms with much less competition and create content around those needs, you can start to rank for these terms and get money flowing into your business. This is because you are making your content more unique by using rarer combinations of terms (leveraging what IDF teaches us).

Summary

People who do keyword analysis are often wired to pursue the major head terms directly, simply based on the available keyword search volume. The result from this approach can, in fact, be pretty dismal.

Understanding how inverse document frequency works helps us understand the importance of standing out. Creating content that brings unique angles to the table is often a very potent way to get your SEO strategy kick-started.

Of course, the reasons for creating content that is highly differentiated and unique go far beyond SEO. This is good for your users, and it’s good for your reputation, visibility, AND also your SEO.

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

Reblogged 4 years ago from tracking.feedpress.it