Why merchants are moving to Shopify Plus

Any retail business – be it a budding startup or an international big-name – knows that a slick and optimized online store is essential to ecommerce success. Get lumbered with ill-fitting or outdated tech and, quite quickly, you’re leaking revenue like a cracked flowerpot. The companies who drive the best ROI and experience the most growth are those that secure smart, affordable and scalable commerce platform.

The ecommerce space has typically been dominated by a select few solutions – until recently, when out-of-the-box ecommerce solution Shopify began to attract retailers with its ease-of-use, power and flexibility. The platform as a whole is now used by more than 500,000 merchants globally, and has facilitated more than $34 billion worth of retail transactions. The company have since launched Shopify Plus, a super-scalable version of Shopify that provides customers with an additional layer of expertise and services.

So why are so many businesses making the switch to Shopify Plus?

Shopify Plus provides a great fit for the fledgling and established stores alike. For the former, the ability to opt for a SaaS platform means a less technical and more manageable way to run their online store – without the reliance on resources in the developer department. And for the latter who are more likely to be running with legacy tech, the opportunity to swap out outdated functionality, temperamental integrations and risks to data security is undoubtedly appealing.

We spoke to COO of Dormify and dotmailer customer, Nicole Gardner about her recent replatform to Shopify Plus. She described her company’s position before the switch:

“At Dormify, we had been on the same platform for about five years. During that time (as you can imagine) we went through a lot of redesigns, updates and upgrades. It got to the point where we were spending the bulk of our time and resources fixing bugs and addressing speed and performance issues. As you can imagine, this was really holding us back from focusing on conversion and optimization, creating a bottleneck in our ability to actualize our team’s brilliant ideas.

The biggest challenge for Dormify was aligning their replatforming timeline with their shopping season, which is typically during the summer months during the academic break. Nicole explains:

‘We were looking at a 10-12 month timeline for upgrading to the latest version of our existing ecommerce platform, but we were loath to wait for that length of time and go through another key growth season with the same issues. We needed a solution that could get our infrastructure in better shape within a few months time before this next season.

The move to Shopify Plus freed the brand from the inhibitions of tech worry, allowing them to focus on the real ROI-driver – strategy:

‘What it came down to was speed, performance and stability. As a seasonal business, we previously had to spend so much time and resource thinking about how many servers we needed, and how we’d scale up during those periods, without having to spend a ton of money,’ Nicole explains.

‘Shopify Plus’ biggest benefit for us was speed – the sites we were looking at were pretty fast, and Shopify handles all the hosting, scaling and performance, so you’re only dealing with one platform provider that is accountable for all of these areas. That in itself was one of the biggest attractions for us.

dotmailer’s Commerce Flow

One of the perceived pitfalls of replatforming is its effect on your inter-stack relations. Commerce Flow from dotmailer connects to over 50% of the world’s online stores, giving you the ability to get contact, product and order data automatically flowing into your account. Nicole explains:
‘Initially, we were worried that we’d face the challenge of integrating our new ecommerce platform with everything else in our stack, especially as we were moving away from a best-of-breed cloud we’d built up over time. However, we worked with all of our partners to see what would be feasible, and were pleasantly surprised at how many partners already had integrations or were eager to build them. dotmailer was particularly easily to check off our list because they have a Shopify connector.
With so many retailers opting to replatform to Shopify Plus, we thought we’d delve a little deeper into the benefits of the switch:

10 reasons why retailers are choosing Shopify Plus

1. Cost effectiveness – Smaller companies and startups will enjoy the value for investment that Shopify offers as a whole; the platform’s most basic functionality starts at just $29 per month. This includes enterprise-level hosting and environment updates and management. Shopify Plus’ added functionality and support is also competitively priced.

2. Scalability – The platform offers limitless scalability and extensive APIs, making it a good investment for fast-growing and larger companies who may have worries about hitting the ceiling elsewhere. Unlimited bandwidth provides reassurance over your site’s performance during peak traffic times.”

Shopify allows us to scale and be creative with promotions, without having to require a developer on our beck and call. We also never have to worry about our site being down during crazy traffic spikes. Our site is always up, which means we’re always ready to sell and make money, 24/7.” – Charity Gerke, Marketing Manager at US EliteGear

3. Easy customization – The platform’s intuitive drag-and-drop editor allows businesses to build on-brand, highly customized sites without coding knowhow. And for the well-versed in web programming, its scripting capabilities allows you to create custom functionality for your store with ease.

4. Mobile-friendly – the platform’s fully responsive website themes ensure that your ecommerce store is designed for mobile. Plus, it’s Responsive Checkout functionality is free to all users and deemed one of the best in the business.

5. Unlimited products and inventory – Pretty self-explanatory: whatever pricing plan you’re on, you’ll never reach a limit on how many products you can sell on your site.

6. Payments – Shopify Plus has its own payments tool available to all its customers as standard, dissolving the need for businesses to add the cost of third-party payment providers to their store bill.

7. Vetting – Shopify vet every app and plugin before it gets added to their marketplace to make sure it’s safe and optimized for use by its customers. Plus, with an extensive list of apps to aid everything from marketing to accounting, you’ll never be spoilt for choice. Anything you can’t find can be commissioned for build.

8. Security – Shopify Plus’ is Secure Sockets Layer (SSL) and Level 1 Payment Card Industry (PCI) compliant, providing your customer data with the same level of security as a bank. Customers shopping on your store will also be able to see the green lock icon, instilling trust in your brand from the off.

9. Graduated pricing plans – Shopify’s pricing structure is transparent from the off, and shows a clear path of progression which you can pass on to your decision-makers with confidence. A graduated price plan means you’re only paying for the level of functionality you need.

10. Knowledgeable community – Whether you want to learn how to build something, commission a tailored piece of tech, or simply ask about abandoned carts, Shopify’s ecommerce forums and Experts Directory provides access to professional and technical support for every customer need.

If you’re already a Shopify or Shopify Plus customer, you can connect your ecommerce store to dotmailer using Commerce Flow. To find out more about replatforming to Shopify Plus, head to their website.
We have the pleasure of hosting Nicola at our inaugural  Shopify Plus meetup in New York; we hope to see you there!

 

 

 

The post Why merchants are moving to Shopify Plus appeared first on The Email Marketing Blog.

Reblogged 4 months ago from blog.dotmailer.com

Stop Ghost Spam in Google Analytics with One Filter

Posted by CarloSeo

The spam in Google Analytics (GA) is becoming a serious issue. Due to a deluge of referral spam from social buttons, adult sites, and many, many other sources, people are starting to become overwhelmed by all the filters they are setting up to manage the useless data they are receiving.

The good news is, there is no need to panic. In this post, I’m going to focus on the most common mistakes people make when fighting spam in GA, and explain an efficient way to prevent it.

But first, let’s make sure we understand how spam works. A couple of months ago, Jared Gardner wrote an excellent article explaining what referral spam is, including its intended purpose. He also pointed out some great examples of referral spam.

Types of spam

The spam in Google Analytics can be categorized by two types: ghosts and crawlers.

Ghosts

The vast majority of spam is this type. They are called ghosts because they never access your site. It is important to keep this in mind, as it’s key to creating a more efficient solution for managing spam.

As unusual as it sounds, this type of spam doesn’t have any interaction with your site at all. You may wonder how that is possible since one of the main purposes of GA is to track visits to our sites.

They do it by using the Measurement Protocol, which allows people to send data directly to Google Analytics’ servers. Using this method, and probably randomly generated tracking codes (UA-XXXXX-1) as well, the spammers leave a “visit” with fake data, without even knowing who they are hitting.

Crawlers

This type of spam, the opposite to ghost spam, does access your site. As the name implies, these spam bots crawl your pages, ignoring rules like those found in robots.txt that are supposed to stop them from reading your site. When they exit your site, they leave a record on your reports that appears similar to a legitimate visit.

Crawlers are harder to identify because they know their targets and use real data. But it is also true that new ones seldom appear. So if you detect a referral in your analytics that looks suspicious, researching it on Google or checking it against this list might help you answer the question of whether or not it is spammy.

Most common mistakes made when dealing with spam in GA

I’ve been following this issue closely for the last few months. According to the comments people have made on my articles and conversations I’ve found in discussion forums, there are primarily three mistakes people make when dealing with spam in Google Analytics.

Mistake #1. Blocking ghost spam from the .htaccess file

One of the biggest mistakes people make is trying to block Ghost Spam from the .htaccess file.

For those who are not familiar with this file, one of its main functions is to allow/block access to your site. Now we know that ghosts never reach your site, so adding them here won’t have any effect and will only add useless lines to your .htaccess file.

Ghost spam usually shows up for a few days and then disappears. As a result, sometimes people think that they successfully blocked it from here when really it’s just a coincidence of timing.

Then when the spammers later return, they get worried because the solution is not working anymore, and they think the spammer somehow bypassed the barriers they set up.

The truth is, the .htaccess file can only effectively block crawlers such as buttons-for-website.com and a few others since these access your site. Most of the spam can’t be blocked using this method, so there is no other option than using filters to exclude them.

Mistake #2. Using the referral exclusion list to stop spam

Another error is trying to use the referral exclusion list to stop the spam. The name may confuse you, but this list is not intended to exclude referrals in the way we want to for the spam. It has other purposes.

For example, when a customer buys something, sometimes they get redirected to a third-party page for payment. After making a payment, they’re redirected back to you website, and GA records that as a new referral. It is appropriate to use referral exclusion list to prevent this from happening.

If you try to use the referral exclusion list to manage spam, however, the referral part will be stripped since there is no preexisting record. As a result, a direct visit will be recorded, and you will have a bigger problem than the one you started with since. You will still have spam, and direct visits are harder to track.

Mistake #3. Worrying that bounce rate changes will affect rankings

When people see that the bounce rate changes drastically because of the spam, they start worrying about the impact that it will have on their rankings in the SERPs.

bounce.png

This is another mistake commonly made. With or without spam, Google doesn’t take into consideration Google Analytics metrics as a ranking factor. Here is an explanation about this from Matt Cutts, the former head of Google’s web spam team.

And if you think about it, Cutts’ explanation makes sense; because although many people have GA, not everyone uses it.

Assuming your site has been hacked

Another common concern when people see strange landing pages coming from spam on their reports is that they have been hacked.

landing page

The page that the spam shows on the reports doesn’t exist, and if you try to open it, you will get a 404 page. Your site hasn’t been compromised.

But you have to make sure the page doesn’t exist. Because there are cases (not spam) where some sites have a security breach and get injected with pages full of bad keywords to defame the website.

What should you worry about?

Now that we’ve discarded security issues and their effects on rankings, the only thing left to worry about is your data. The fake trail that the spam leaves behind pollutes your reports.

It might have greater or lesser impact depending on your site traffic, but everyone is susceptible to the spam.

Small and midsize sites are the most easily impacted – not only because a big part of their traffic can be spam, but also because usually these sites are self-managed and sometimes don’t have the support of an analyst or a webmaster.

Big sites with a lot of traffic can also be impacted by spam, and although the impact can be insignificant, invalid traffic means inaccurate reports no matter the size of the website. As an analyst, you should be able to explain what’s going on in even in the most granular reports.

You only need one filter to deal with ghost spam

Usually it is recommended to add the referral to an exclusion filter after it is spotted. Although this is useful for a quick action against the spam, it has three big disadvantages.

  • Making filters every week for every new spam detected is tedious and time-consuming, especially if you manage many sites. Plus, by the time you apply the filter, and it starts working, you already have some affected data.
  • Some of the spammers use direct visits along with the referrals.
  • These direct hits won’t be stopped by the filter so even if you are excluding the referral you will sill be receiving invalid traffic, which explains why some people have seen an unusual spike in direct traffic.

Luckily, there is a good way to prevent all these problems. Most of the spam (ghost) works by hitting GA’s random tracking-IDs, meaning the offender doesn’t really know who is the target, and for that reason either the hostname is not set or it uses a fake one. (See report below)

Ghost-Spam.png

You can see that they use some weird names or don’t even bother to set one. Although there are some known names in the list, these can be easily added by the spammer.

On the other hand, valid traffic will always use a real hostname. In most of the cases, this will be the domain. But it also can also result from paid services, translation services, or any other place where you’ve inserted GA tracking code.

Valid-Referral.png

Based on this, we can make a filter that will include only hits that use real hostnames. This will automatically exclude all hits from ghost spam, whether it shows up as a referral, keyword, or pageview; or even as a direct visit.

To create this filter, you will need to find the report of hostnames. Here’s how:

  1. Go to the Reporting tab in GA
  2. Click on Audience in the lefthand panel
  3. Expand Technology and select Network
  4. At the top of the report, click on Hostname

Valid-list

You will see a list of all hostnames, including the ones that the spam uses. Make a list of all the valid hostnames you find, as follows:

  • yourmaindomain.com
  • blog.yourmaindomain.com
  • es.yourmaindomain.com
  • payingservice.com
  • translatetool.com
  • anotheruseddomain.com

For small to medium sites, this list of hostnames will likely consist of the main domain and a couple of subdomains. After you are sure you got all of them, create a regular expression similar to this one:

yourmaindomain\.com|anotheruseddomain\.com|payingservice\.com|translatetool\.com

You don’t need to put all of your subdomains in the regular expression. The main domain will match all of them. If you don’t have a view set up without filters, create one now.

Then create a Custom Filter.

Make sure you select INCLUDE, then select “Hostname” on the filter field, and copy your expression into the Filter Pattern box.

filter

You might want to verify the filter before saving to check that everything is okay. Once you’re ready, set it to save, and apply the filter to all the views you want (except the view without filters).

This single filter will get rid of future occurrences of ghost spam that use invalid hostnames, and it doesn’t require much maintenance. But it’s important that every time you add your tracking code to any service, you add it to the end of the filter.

Now you should only need to take care of the crawler spam. Since crawlers access your site, you can block them by adding these lines to the .htaccess file:

## STOP REFERRER SPAM 
RewriteCond %{HTTP_REFERER} semalt\.com [NC,OR] 
RewriteCond %{HTTP_REFERER} buttons-for-website\.com [NC] 
RewriteRule .* - [F]

It is important to note that this file is very sensitive, and misplacing a single character it it can bring down your entire site. Therefore, make sure you create a backup copy of your .htaccess file prior to editing it.

If you don’t feel comfortable messing around with your .htaccess file, you can alternatively make an expression with all the crawlers, then and add it to an exclude filter by Campaign Source.

Implement these combined solutions, and you will worry much less about spam contaminating your analytics data. This will have the added benefit of freeing up more time for you to spend actually analyze your valid data.

After stopping spam, you can also get clean reports from the historical data by using the same expressions in an Advance Segment to exclude all the spam.

Bonus resources to help you manage spam

If you still need more information to help you understand and deal with the spam on your GA reports, you can read my main article on the subject here: http://www.ohow.co/what-is-referrer-spam-how-stop-it-guide/.

Additional information on how to stop spam can be found at these URLs:

In closing, I am eager to hear your ideas on this serious issue. Please share them in the comments below.

(Editor’s Note: All images featured in this post were created by the author.)

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Reblogged 2 years ago from tracking.feedpress.it

Pinpoint vs. Floodlight Content and Keyword Research Strategies – Whiteboard Friday

Posted by randfish

When we’re doing keyword research and targeting, we have a choice to make: Are we targeting broader keywords with multiple potential searcher intents, or are we targeting very narrow keywords where it’s pretty clear what the searchers were looking for? Those different approaches, it turns out, apply to content creation and site architecture, as well. In today’s Whiteboard Friday, Rand illustrates that connection.

Pinpoint vs Floodlight Content and Keyword Research Strategy Whiteboard

For reference, here are stills of this week’s whiteboards. 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 pinpoint versus floodlight tactics for content targeting, content strategy, and keyword research, keyword targeting strategy. This is also called the shotgun versus sniper approach, but I’m not a big gun fan. So I’m going to stick with my floodlight versus pinpoint, plus, you know, for the opening shot we don’t have a whole lot of weaponry here at Moz, but we do have lighting.

So let’s talk through this at first. You’re going through and doing some keyword research. You’re trying to figure out which terms and phrases to target. You might look down a list like this.

Well, maybe, I’m using an example here around antique science equipment. So you see these various terms and phrases. You’ve got your volume numbers. You probably have lots of other columns. Hopefully, you’ve watched the Whiteboard Friday on how to do keyword research like it’s 2015 and not 2010.

So you know you have all these other columns to choose from, but I’m simplifying here for the purpose of this experiment. So you might choose some of these different terms. Now, they’re going to have different kinds of tactics and a different strategic approach, depending on the breadth and depth of the topic that you’re targeting. That’s going to determine what types of content you want to create and where you place it in your information architecture. So I’ll show you what I mean.

The floodlight approach

For antique science equipment, this is a relatively broad phrase. I’m going to do my floodlight analysis on this, and floodlight analysis is basically saying like, “Okay, are there multiple potential searcher intents?” Yeah, absolutely. That’s a fairly broad phase. People could be looking to transact around it. They might be looking for research information, historical information, different types of scientific equipment that they’re looking for.

<img src="http://d1avok0lzls2w.cloudfront.net/uploads/blog/55b15fc96679b8.73854740.jpg" rel="box-shadow: 0 0 10px 0 #999; border-radius: 20px;"

Are there four or more approximately unique keyword terms and phrases to target? Well, absolutely, in fact, there’s probably more than that. So antique science equipment, antique scientific equipment, 18th century scientific equipment, all these different terms and phrases that you might explore there.

Is this a broad content topic with many potential subtopics? Again, yes is the answer to this. Are we talking about generally larger search volume? Again, yes, this is going to have a much larger search volume than some of the narrower terms and phrases. That’s not always the case, but it is here.

The pinpoint approach

For pinpoint analysis, we kind of go the opposite direction. So we might look at a term like antique test tubes, which is a very specific kind of search, and that has a clear single searcher intent or maybe two. Someone might be looking for actually purchasing one of those, or they might be looking to research them and see what kinds there are. Not a ton of additional intents behind that. One to three unique keywords, yeah, probably. It’s pretty specific. Antique test tubes, maybe 19th century test tubes, maybe old science test tubes, but you’re talking about a limited set of keywords that you’re targeting. It’s a narrow content topic, typically smaller search volume.

<img src="http://d1avok0lzls2w.cloudfront.net/uploads/blog/55b160069eb6b1.12473448.jpg" rel="box-shadow: 0 0 10px 0 #999; border-radius: 20px;"

Now, these are going to feed into your IA, your information architecture, and your site structure in this way. So floodlight content generally sits higher up. It’s the category or the subcategory, those broad topic terms and phrases. Those are going to turn into those broad topic category pages. Then you might have multiple, narrower subtopics. So we could go into lab equipment versus astronomical equipment versus chemistry equipment, and then we’d get into those individual pinpoints from the pinpoint analysis.

How do I decide which approach is best for my keywords?

Why are we doing this? Well, generally speaking, if you can take your terms and phrases and categorize them like this and then target them differently, you’re going to provide a better, more logical user experience. Someone who searches for antique scientific equipment, they’re going to really expect to see that category and then to be able to drill down into things. So you’re providing them the experience they predict, the one that they want, the one that they expect.

It’s better for topic modeling analysis and for all of the algorithms around things like Hummingbird, where Google looks at: Are you using the types of terms and phrases, do you have the type of architecture that we expect to find for this keyword?

It’s better for search intent targeting, because the searcher intent is going to be fulfilled if you provide the multiple paths versus the narrow focus. It’s easier keyword targeting for you. You’re going to be able to know, “Hey, I need to target a lot of different terms and phrases and variations in floodlight and one very specific one in pinpoint.”

There’s usually higher searcher satisfaction, which means you get lower bounce rate. You get more engagement. You usually get a higher conversion rate. So it’s good for all those things.

For example…

I’ll actually create pages for each of antique scientific equipment and antique test tubes to illustrate this. So I’ve got two different types of pages here. One is my antique scientific equipment page.

<img src="http://d1avok0lzls2w.cloudfront.net/uploads/blog/55b161fa871e32.54731215.jpg" rel="box-shadow: 0 0 10px 0 #999; border-radius: 20px;"

This is that floodlight, shotgun approach, and what we’re doing here is going to be very different from a pinpoint approach. It’s looking at like, okay, you’ve landed on antique scientific equipment. Now, where do you want to go? What do you want to specifically explore? So we’re going to have a little bit of content specifically about this topic, and how robust that is depends on the type of topic and the type of site you are.

If this is an e-commerce site or a site that’s showing information about various antiques, well maybe we don’t need very much content here. You can see the filtration that we’ve got is going to be pretty broad. So I can go into different centuries. I can go into chemistry, astronomy, physics. Maybe I have a safe for kids type of stuff if you want to buy your kids antique lab equipment, which you might be. Who knows? Maybe you’re awesome and your kids are too. Then different types of stuff at a very broad level. So I can go to microscopes or test tubes, lab searches.

This is great because it’s got broad intent foci, serving many different kinds of searchers with the same page because we don’t know exactly what they want. It’s got multiple keyword targets so that we can go after broad phrases like antique or old or historical or 13th, 14th, whatever century, science and scientific equipment ,materials, labs, etc., etc., etc. This is a broad page that could reach any and all of those. Then there’s lots of navigational and refinement options once you get there.

Total opposite of pinpoint content.

<img src="http://d1avok0lzls2w.cloudfront.net/uploads/blog/55b1622740f0b5.73477500.jpg" rel="box-shadow: 0 0 10px 0 #999; border-radius: 20px;"

Pinpoint content, like this antique test tubes page, we’re still going to have some filtration options, but one of the important things to note is note how these are links that take you deeper. Depending on how deep the search volume goes in terms of the types of queries that people are performing, you might want to make a specific page for 17th century antique test tubes. You might not, and if you don’t want to do that, you can have these be filters that are simply clickable and change the content of the page here, narrowing the options rather than creating completely separate pages.

So if there’s no search volume for these different things and you don’t think you need to separately target them, go ahead and just make them filters on the data that already appears on this page or the results that are already in here as opposed to links that are going to take you deeper into specific content and create a new page, a new experience.

You can also see I’ve got my individual content here. I probably would go ahead and add some content specifically to this page that is just unique here and that describes antique test tubes and the things that your searchers need. They might want to know things about price. They might want to know things about make and model. They might want to know things about what they were used for. Great. You can have that information broadly, and then individual pieces of content that someone might dig into.

This is narrower intent foci obviously, serving maybe one or two searcher intents. This is really talking about targeting maybe one to two separate keywords. So antique test tubes, maybe lab tubes or test tube sets, but not much beyond that.

Ten we’re going to have fewer navigational paths, fewer distractions. We want to keep the searcher. Because we know their intent, we want to guide them along the path that we know they probably want to take and that we want them to take.

So when you’re considering your content, choose wisely between shotgun/floodlight approach or sniper/pinpoint approach. Your searchers will be better served. You’ll probably rank better. You’ll be more likely to earn links and amplification. You’re going to be more successful.

Looking forward to the comments, and 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 2 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?

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!

Your Daily SEO Fix: Week 5

Posted by Trevor-Klein

We’ve arrived, folks! This is the last installment of our short (< 2-minute) video tutorials that help you all get the most out of Moz’s tools. If you haven’t been following along, these are each designed to solve a use case that we regularly hear about from Moz community members.

Here’s a quick recap of the previous round-ups in case you missed them:

  • Week 1: Reclaim links using Open Site Explorer, build links using Fresh Web Explorer, and find the best time to tweet using Followerwonk.
  • Week 2: Analyze SERPs using new MozBar features, boost your rankings through on-page optimization, check your anchor text using Open Site Explorer, do keyword research with OSE and the keyword difficulty tool, and discover keyword opportunities in Moz Analytics.
  • Week 3: Compare link metrics in Open Site Explorer, find tweet topics with Followerwonk, create custom reports in Moz Analytics, use Spam Score to identify high-risk links, and get link building opportunities delivered to your inbox.
  • Week 4: Use Fresh Web Explorer to build links, analyze rank progress for a given keyword, use the MozBar to analyze your competitors’ site markup, use the Top Pages report to find content ideas, and find on-site errors with Crawl Test.

We’ve got five new fixes for you in this edition:

  • How to Use the Full SERP Report
  • How to Find Fresh Links and Manage Your Brand Online Using Open Site Explorer
  • How to Build Your Link Profile with Link Intersect
  • How to Find Local Citations Using the MozBar
  • Bloopers: How to Screw Up While Filming a Daily SEO Fix

Hope you enjoy them!


Fix 1: How to Use the Full SERP Report

Moz’s Full SERP Report is a detailed report that shows the top ten ranking URLs for a specific keyword and presents the potential ranking signals in an easy-to-view format. In this Daily SEO Fix, Meredith breaks down the report so you can see all the sections and how each are used.

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Fix 2: How to Find Fresh Links and Manage Your Brand Online Using Open Site Explorer

The Just-Discovered Links report in Open Site Explorer helps you discover recently created links within an hour of them being published. In this fix, Nick shows you how to use the report to view who is linking to you, how they’re doing it, and what they are saying, so you can capitalize on link opportunities while they’re still fresh and join the conversation about your brand.


Fix 3: How to Build Your Link Profile with Link Intersect

The quantity and (more importantly) quality of backlinks to your website make up your link profile, one of the most important elements in SEO and an incredibly important factor in search engine rankings. In this Daily SEO Fix, Tori shows you how to use Moz’s Link Intersect tool to analyze the competitions’ backlinks. Plus, learn how to find opportunities to build links and strengthen your own link profile.


Fix 4: How to Find Local Citations Using the MozBar

Citations are mentions of your business and address on webpages other than your own such as an online yellow pages directory or a local business association page. They are a key component in search engine ranking algorithms so building consistent and accurate citations for your local business(s) is a key Local SEO tactic. In today’s Daily SEO Fix, Tori shows you how to use MozBar to find local citations around the web


Bloopers: How to Screw Up While Filming a Daily SEO Fix

We had a lot of fun filming this series, and there were plenty of laughs along the way. Like these ones. =)


Looking for more?

We’ve got more videos in the previous four weeks’ round-ups!

Your Daily SEO Fix: Week 1

Your Daily SEO Fix: Week 2

Your Daily SEO Fix: Week 3

Your Daily SEO Fix: Week 4


Don’t have a Pro subscription? No problem. Everything we cover in these Daily SEO Fix videos is available with a free 30-day trial.

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

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