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 2 years ago from blog.dotmailer.com

Moz Local Officially Launches in the UK

Posted by David-Mihm

To all Moz Local fans in the UK, I’m excited to announce that your wait is over. As the sun rises “across the pond” this morning, Moz Local is officially live in the United Kingdom!

A bit of background

As many of you know, we released the US version of Moz Local in March 2014. After 12 months of terrific growth in the US, and a boatload of technical improvements and feature releases–especially for Enterprise customers–we released the Check Listing feature for a limited set of partner search engines and directories in the UK in April of this year.

Over 20,000 of you have checked your listings (or your clients’ listings) in the last 3-1/2 months. Those lookups have helped us refine and improve the background technology immensely (more on that below). We’ve been just as eager to release the fully-featured product as you’ve been to use it, and the technical pieces have finally fallen into place for us to do so.

How does it work?

The concept is the same as the US version of Moz Local: show you how accurately and completely your business is listed on the most important local search platforms and directories, and optimize and perfect as many of those business listings as we can on your behalf.

For customers specifically looking for you, accurate business listings are obviously important. For customers who might not know about you yet, they’re also among the most important factors for ranking in local searches on Google. Basically, the more times Google sees your name, address, phone, and website listed the same way on quality local websites, the more trust they have in your business, and the higher you’re likely to rank.

Moz Local is designed to help on both these fronts.

To use the product, you simply need to type a name and postcode at moz.com/local. We’ll then show you a list of the closest matching listings we found. We prioritize verified listing information that we find on Google or Facebook, and selecting one of those verified listings means we’ll be able to distribute it on your behalf.

Clicking on a result brings you to a full details report for that listing. We’ll show you how accurate and complete your listings are now, and where they could be after using our product.

Clicking the tabs beneath the Listing Score graphic will show you some of the incompletions and inconsistencies that publishing your listing with Moz Local will address.

For customers with hundreds or thousands of locations, bulk upload is also available using a modified version of your data from Google My Business–feel free to e-mail enterpriselocal@moz.com for more details.

Where do we distribute your data?

We’ve prioritized the most important commercial sites in the UK local search ecosystem, and made them the centerpieces of Moz Local. We’ll update your data directly on globally-important players Factual and Foursquare, and the UK-specific players CentralIndex, Thomson Local, and the Scoot network–which includes key directories like TouchLocal, The Independent, The Sun, The Mirror, The Daily Scotsman, and Wales Online.

We’ll be adding two more major destinations shortly, and for those of you who sign up before that time, your listings will be automatically distributed to the additional destinations when the integrations are complete.

How much does it cost?

The cost per listing is £84/year, which includes distribution to the sites mentioned above with unlimited updates throughout the year, monitoring of your progress over time, geographically- focused reporting, and the ability to find and close duplicate listings right from your Moz Local dashboard–all the great upgrades that my colleague Noam Chitayat blogged about here.

What’s next?

Well, as I mentioned just a couple paragraphs ago, we’ve got two additional destinations to which we’ll be sending your data in very short order. Once those integrations are complete, we’ll be just a few weeks away from releasing our biggest set of features since we launched. I look forward to sharing more about these features at BrightonSEO at the end of the summer!

For those of you around the world in Canada, Australia, and other countries, we know there’s plenty of demand for Moz Local overseas, and we’re working as quickly as we can to build additional relationships abroad. And to our friends in the UK, please let us know how we can continue to make the product even better!

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 3 years ago from tracking.feedpress.it

Big Data, Big Problems: 4 Major Link Indexes Compared

Posted by russangular

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

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

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

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

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

Proportional representation to Google Search Console data

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

A Visualization

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

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

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

Methodology

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

Steps

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

Results

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

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

What does this mean?

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

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

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

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

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

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

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

So what do we do?

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

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

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

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

Recommendations for the link graphing industry

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

Credits

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

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 3 years ago from tracking.feedpress.it

Creating Demand for Products, Services, and Ideas that Have Little to No Existing Search Volume – Whiteboard Friday

Posted by randfish

A lot of fantastic websites (and products, services, ideas, etc.) are in something of a pickle: The keywords they would normally think to target get next to no search volume. It can make SEO seem like a lost cause. In today’s Whiteboard Friday, Rand explains why that’s not the case, and talks about the one extra step that’ll help those organizations create the demand they want.

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

Video transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we’re going to chat about a particularly challenging problem in the world of SEO, and that is trying to do SEO or trying to do any type of web marketing when your product, service, or idea has no search volume around it. So nobody is already looking for what you offer. It’s a new thing, a new concept.

I’ll use the example here of a website that I’m very fond of, but which there’s virtually no search volume for, called Niice. It’s Niice.co.

It’s great. I searched for things in here. It brings me back all these wonderful visuals from places like Colossus and lots of design portals. I love this site. I use it all the time for inspiration, for visuals, for stuff that I might write about on blogs, for finding new artists. It’s just cool. I love it. I love the discovery aspect of it, and I think it can be really great for finding artists and designers and visuals.

But when I looked at the keyword research — and granted I didn’t go deep into the keyword research, but let’s imagine that I did — I looked for things like: “visual search engine” almost no volume; “search engine for designers” almost no volume; “graphical search engine” almost no volume; “find designer visuals” nada.

So when they look at their keyword research they go, “Man, we don’t even have keywords to target here really.” SEO almost feels like it’s not a channel of opportunity, and I think that’s where many, many companies and businesses make mistakes actually, because just because you don’t see keyword research around exactly around what you’re offering doesn’t mean that SEO can’t be a great channel. It just means we have to do an extra step of work, and that’s what I want to talk about today.

So I think when you encounter this type of challenge — and granted it might not be the challenge that there’s no keyword volume — it could be a challenge in your business, for your organization, for some ideas or products that you have or are launching that there’s just very little, and thus you’re struggling to come up with enough volume to create the quantity of leads, or free trials, or customers that you need. This process really can work.

Key questions to start.

1) Who’s the target audience?

In Niice’s case, that’s going to be a lot of designers. It might be people who are creating presentations. It might be those who are searching out designers or artists. It could be people seeking inspiration for all sorts of things. So they’re going to figure out who that is.

From there, they can look at the job title, interests, demographics of those people, and then you can do some cool stuff where you can figure out things like, “Oh, you know what? We could do some Facebook ad targeting to those right groups to help boost their interests in our product and potentially, well, create branded search volume down the road, attract direct visitors, build brand awareness for ourselves, and potentially get some traffic to the site directly as well. If we can convert some of that traffic, well, that’s fantastic.”

In their case, I think Niice is ad-supported right now, so all they really need is the traffic itself. But regardless, this is that same type of process you’d use.

2) What else do they search for?

What is that target audience searching for? Knowledge, products, tools, services, people, brands, whatever it is, if you know who the audience is, you can figure out what they’re searching for because they have needs. If they have a job title, if they have interests, if you have those profile features about the audience, you can figure out what else they’re going to be searching for, and in this case, knowing what designers are searching for, well, that’s probably relatively simplistic. The other parts of their audience might be more complex, but that one is pretty obvious.

From that, we can do content creation. We can do keyword targeting to be in front of those folks when they’re doing search by creating content that may not necessarily be exactly selling our tools, but that’s the idea of content marketing. We’re creating content to target people higher up in the funnel before they need our product.

We can use that, too, for product and feature inspiration in the product itself. So in this case, Niice might consider creating a design pattern library or several, pulling from different places, or hiring someone to come in and build one for them and then featuring that somewhere on the site if you haven’t done a search yet and then potentially trying to rank for that in the search engine, which then brings qualified visitors, the types of people who once they got exposed to Niice would be like, “Wow, this is great and it’s totally free. I love it.”

UX tool list, so list of tools for user experience, people on the design or UI side, maybe Photoshop tutorials, whatever it is that they feel like they’re competent and capable of creating and could potentially rank for, well, now you’re attracting the right audience to your site before they need your product.

3) Where do they go?

That audience, where are they going on the web? What do they do when they get there? To whom do they listen? Who are their influencers? How can we be visible in those locations? So from that I can get things like influencer targeting and outreach. I can get ad and sponsorship opportunities. I can figure out places to do partnership or guest content or business development.

In Niice’s case, that might be things like sponsor or speak at design events. Maybe they could create an awards project for Dribble. So they go to Dribble, they look at what’s been featured there, or they go to Colossus, or some of the other sites that they feature, and they find the best work of the week. At the end of the week, they feature the top 10 projects, and then they call out the designers who put them together.

Wow, that’s terrific. Now you’re getting in front of the audience whose work you’re featuring, which is going to, in turn, make them amplify Niice’s project and product to an audience who’s likely to be in their target audience. It’s sort of a win-win. That’s also going to help them build links, engagement, shares, and all sorts of signals that potentially will help them with their authority, both topically and domain-wide, which then means they can rank for all the content they create, building up this wonderful engine.

4) What types of content have achieved broad or viral distribution?

I think what we can glean from this is not just inspiration for content and keyword opportunities as we can from many other kinds of content, but also sites to target, in particular sites to target with advertising, sites to target for guest posting or sponsorship, or sites to target for business development or for partnerships, site to target in an ad network, sites to target psychographically or demographically for Facebook if we want to run ads like that, potentially bidding on ads in Google when people search for that website or for that brand name in paid search.

So if you’re Niice, you could think about contracting some featured artist to contribute visuals maybe for a topical news project. So something big is happening in the news or in the design community, you contract a few of the artists whose work you have featured or are featuring, or people from the communities whose work you’re featuring, and say, “Hey, we might not be able to pay you a lot, but we’re going to get in front of a ton of people. We’re going to build exposure for you, which is something we already do, FYI, and now you’ve got some wonderful content that has that potential to mimic that work.”

You could think about, and I love this just generally as a content marketing and SEO tactic, if you go find viral content, content that has had wide sharing success across the web from the past, say two, three, four, or five years ago, you have a great opportunity, especially if the initial creator of that content or project hasn’t continued on with it, to go say, “Hey, you know what? We can do a version of that. We’re going to modernize and update that for current audiences, current tastes, what’s currently going on in the market. We’re going to go build that, and we have a strong feeling that it’s going to be successful because it’s succeeded in the past.”

That, I think, is a great way to get content ideas from viral content and then to potentially overtake them in the search rankings too. If something from three or five years ago, that was particularly timely then still ranks today, if you produce it, you’re almost certainly going to come out on top due to Google’s bias for freshness, especially around things that have timely relevance.

5) Should brand advertisement be in our consideration set?

Then last one, I like to ask about brand advertising in these cases, because when there’s not search volume yet, a lot of times what you have to do is create awareness. I should change this from advertising to a brand awareness, because really there’s organic ways to do it and advertising ways to do it. You can think about, “Well, where are places that we can target where we could build that awareness? Should we invest in press and public relations?” Not press releases. “Then how do we own the market?” So I think one of the keys here is starting with that name or title or keyword phrase that encapsulates what the market will call your product, service or idea.

In the case of Niice, that could be, well, visual search engines. You can imagine the press saying, “Well, visual search engines like Niice have recently blah, blah, blah.” Or it could be designer search engines, or it could be graphical search engines, or it could be designer visual engines, whatever it is. You need to find what that thing is going to be and what’s going to resonate.

In the case of Nest, that was the smart home. In the case of Oculus, it was virtual reality and virtual reality gaming. In the case of Tesla, it was sort of already established. There’s electric cars, but they kind of own that market. If you know what those keywords are, you can own the market before it gets hot, and that’s really important because that means that all of the press and PR and awareness that happens around the organic rankings for that particular keyword phrase will all be owned and controlled by you.

When you search for “smart home,” Nest is going to dominate those top 10 results. When you search for “virtual reality gaming,” Oculus is going to dominate those top 10. It’s not necessarily dominate just on their own site, it’s dominate all the press and PR articles that are about that, all of the Wikipedia page about it, etc., etc. You become the brand that’s synonymous with the keyword or concept. From an SEO perspective, that’s a beautiful world to live in.

So, hopefully, for those of you who are struggling around demand for your keywords, for your volume, this process can be something that’s really helpful. I look forward to hearing from you in the comments. We’ll see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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Reblogged 3 years ago from tracking.feedpress.it

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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