Why should I implement user tracking software?

Now more than ever, brands need to be data-driven and offer a highly personalized experience. To get noticed in the inbox – over and above everybody else – it’s important to send timely, contextual emails that are meaningful to subscribers.

This is where user tracking software comes in; unlocking the power of web insight enables you to enhance the relevancy of your email campaigns. dotmailer’s web insight tool tracks the website behaviour of customers and prospects after they’ve clicked through from your emails. It gathers rich behavioural insights from your site visitors:

  • Duration of a user’s visit
  • Pages viewed
  • Point of drop out

This enriched data helps you quantify the impact of your campaigns, identify highly engaged subscribers and follow up with timely, appropriate content.

There are two key ways that our web behavioural tool can give your email marketing results a dramatic lift:

  1. Building segments that target individuals based on their web activity; for instance, those who’ve viewed pages which indicate a strong intent to buy or enquire.
  2. Powering your automations; i.e. a browse abandonment program that prompts the completion of a form or a cart recovery program that encourages the placement of an order.

Forest Holidays has recently enabled the dotmailer web behaviour tool to great effect. At present, user tracking is being leveraged to target individuals who’ve abandoned their basket by sending them a personalized, well-timed email. The results speak for themselves: a significant uplift in engagement and a 5% COS in the first 30 days of implementation.

If you’d like to know more about dotmailer’s web insight tool, contact your Account Manager, or take a free trial of our platform.

The post Why should I implement user tracking software? appeared first on The Marketing Automation Blog.

Reblogged 2 weeks ago from blog.dotmailer.com

SearchCap: SEO periodic table, Google updates & rank tracking

Below is what happened in search today, as reported on Search Engine Land and from other places across the web.

The post SearchCap: SEO periodic table, Google updates & rank tracking appeared first on Search Engine Land.

Please visit Search Engine Land for the full article.

Reblogged 10 months ago from feeds.searchengineland.com

A first look @ the UK Digital Marketing Association (DMA) Email Tracking Report 2017

Sometimes a bit of that déjà vu feeling can be a giggle, but when repetition is costing you time and money, it’s a little less amusing.

We’ve just been given first access to The UK Digital Marketing Association (DMA) Email Tracking Report 2017, sponsored by dotmailer. Awesome statistics, actionable insights, and a little bit like something we read this time last year.

The good news is that email is still firmly seated atop the throne as consumers’ preferred marketing channel. In fact, according to the report, email use is still on the rise, with the DMA likening the act of checking your inbox to a routine as subconscious as brushing your teeth in the morning. That’s the kind of healthy recurrence we like to hear about.

And the bad news?

Email marketing is in danger of losing its crown. And the culprit? It’s not new laws, or poor technology, or pesky Millennials whining and moaning and taking everything for granted…

It’s relevancy.

Back in yesteryear, our Client Services Director Skip Fidura wrote a blog post to accompany the recently published DMA Email Tracking Report 2015, detailing a call to action for the prioritization of relevant content in email marketing campaigns. 63% of the 2016 versions of our consumers had said: “Most of the marketing emails I receive include NO content or offers that are of interest to me.” Subject lines were generic, offers were universal, and content was characterless. We all took note; relevancy needed to be improved if email marketing was going to continue to top the charts.

So why are we now looking at a 5% rise in consumers failing to identify the relevancy of our campaigns? 68% now agree with the above statement, and 84% now find less than half of their emails ‘interesting or relevant’. And that’s if they even get to the campaign itself; the DMA Email Tracker Report 2017 reveals that only 6% of consumers opened and read all of their emails – 67% read fewer than half. This is hardly a surprising statistic, when you consider that most feel there’s nothing of worth to them inside.

Email marketers are losing their customers’ trust because they’re not able to prove that they know how to engage with them. When you don’t feel like somebody knows you, you’re not going to open up, invite them in for a cup of tea, give them the nice biscuits with chocolate on. And if you feel like someone else is making a better attempt to get to know you, you’re going to turn your attention to them. It’s that simple.

Is it that we just don’t like “simple”?

Why is it that we haven’t yet cracked relevancy in email marketing campaigns, when we’ve got the tools at our fingertips? We can track consumer behavior; we can segment our contact lists by gender, location, and shoe size (if appropriate) we can test subject lines, copy, images and layout at the click of a button, and all of this data can be fed into a campaign that reaches Mrs. Smith when she gets home at 7pm on a Monday and starts surfing for size six shoes.

We need to start effectively using the tools that are available to us.

What can you do before the year is out?

Ask if you are relevant – When we released last year’s results, one of our clients took some of the key metrics, built them into a survey and asked her recipients the same questions. It would be inappropriate to share what she found but it was interesting to compare the responses from her recipients with those of the average consumer.

Pay your data some attention – If you have gaps in your database, create a campaign via email or on your website that seeks to gain a better picture of both your prospects and your customers. Alternatively, you can connect your email platform to your CRM or e-commerce software to get access to live customer data

Strategize your segmentation – Dividing by two and hoping for the best hasn’t worked since school, so start thinking about what your brand can offer to different consumers, and create intelligent segments based on your results. Quizzes, competitions, and preference surveys are a great way to collect additional explicit data, on top of implicit data such as order history and behavioral data.

Think harder about context – You need to keep up to date with what’s happening with your different audiences. Got an internationally active brand? Make sure your content is going to be relevant to everyone – and don’t forget about delivering your emails at a time that the recipient is likely to be looking at email or at least be awake. dotmailer’s Send Time Optimization feature gets your message to your recipient’s inbox at the time that is best for them.

Split-test ‘til the cows come home – Performing a split-test is a brilliant way to find out what works for your brand in a time-effective manner. You can afford to be creative when your ideas are backed up by intelligent reporting.

What can you put in place for 2017?

Get better insight – dotmailer’s WebInsight tool lets you track prospects’ and customers’ online behaviors. You can then use the data you receive to send relevant, automated campaigns that “react” to your recipients most recent actions on your site.

Nurture your valued customers – With a tool like dotmailer’s OrderInsight, you can quickly and easily data-mine your customers to identify those highest scoring by frequency and value of purchase, as well as product category. Then design a targeted appreciation campaign for your most valued segments in minutes using our drag-and-drop segmentation tool.

Get to know our friends – We’ve got the top pick of partners to boost campaign relevancy. Phrasee gives you the insight on what subject lines will perform best for you, Sweet Tooth is the number one platform for points based loyalty programs, and Moveable Ink eats real-time relevancy for breakfast.

Want to get more of the most up-to-date data on the habits of email consumers? Book now for the 2017 DMA Email Tracking Report launch!

Reblogged 1 year ago from blog.dotmailer.com

Local SEO now has an organic ROI tracking method

Heard about the new partnership between Yext and Uber? Columnist Lydia Jorden explains its implications for tracking return on investment for local search.

The post Local SEO now has an organic ROI tracking method appeared first on Search Engine Land.

Please visit Search Engine Land for the full article.

Reblogged 1 year ago from feeds.searchengineland.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.)

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 2 years ago from tracking.feedpress.it

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

Posted by jon.white

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

Track your mobile vs. desktop rankings in Moz Analytics

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

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

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

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

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

We have given an extra engine to all campaigns

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

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

Measure your Search Visibility score vs. competitors

The overall Search Visibility for my campaign

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

How is Search Visibility calculated?

Good question!

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

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

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

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

Some neat ways to use this feature

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

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 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?

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