12 06, 2017

New Variable Configuration in Tag Manager

By | 2017-06-06T12:05:15+00:00 June 12th, 2017|Categories: Google Analytics|Tags: , |

If you’ve been using Tag Manger, you probably know how easy it is to forget about setting certain fields in each of your Tags, such as Cookie domain, cross domain tracking, etc. We’ve run into a couple instances of companies that have set up Tag Manager Tags for their websites and forgot to set all the proper settings in their tags. For one company in particular this caused their GA to show a large amount of self-referrals because their subdomains were not tracking properly. Luckily, that shouldn’t be an issue anymore for anyone using Tag Manager. Why you might be asking? It’s because now you have the ability to set up a Variable Configuration which can be used across all of your tags and contain the settings that need to always be in place to keep your website tracking properly.

This new Variable Configuration is called Google Analytics Settings.

variable configuration settings for tag manager

Within this variable configuration you can set up things like – cookie domain, cross domain tracking, ecommerce tracking, content groups, etc. Before this new variable configuration, you had to manually set these up in every.single.tag. Now you can set it up here, then use it when you set up new tags.

tag settings

Of course, if for some reason you don’t want to use it or shouldn’t, then you can always select the box to override the settings. When you do that, you’ll have to manually set up whatever fields you need though.

So tell me, have you used this new variable configuration for tag manager yet? Do you think it makes it easier to make sure all the proper settings are in place for each of your tags?

6 06, 2017

Don’t Forget about Google Analytics when Redesigning Your Website

By | 2017-06-06T10:52:29+00:00 June 6th, 2017|Categories: Google Analytics|Tags: , |

Are you planning to redesign your website soon? Have you already laid out the changes you want to make and have a timeline in place for getting the redesigned completed and launched? Is Google Analytics tracking code migration a task that is on your redesign list? If you answered yes, then I can tell website tracking is important to you. If you answered no, then you could be making a HUGE mistake and causing your team undue stress!! So this post is for you and I highly recommend you read on.

Make It A Priority

We have worked with many clients here at Beacon who have redesigned their sites. Some have worked with our development team and others have their own team. In house, Google analytics code migrations are always accounted for and known as a TOP PRIORITY before a site goes live. However, when we’ve worked with outside companies for development we’ve run into many instances where Google Analytics is a last thought. I’m actually working on site redesign right now where I get constant updates on when the site is planning to be launched live and yet the tag manager code hasn’t even been added to the site nor is eCommerce tracking in place. Despite sending numerous emails and having multiple phone calls, it just doesn’t seem Google Analytics tracking is a priority for the development team working on the site nor the PM managing all of the agencies. In all honesty, I’m very worried this site will be launched with no code in place or launched with the code in place but give me no time to get everything set up and tested before the site goes live. Either scenario is not good, which is why I wanted to write this post.

In a perfect world, all codes for GA (such as Tag manager container scripts, data layers, etc) would be added in the test environment so that GA can be fully set up and tested before the site goes live. Then when the site is ready to be pushed live, you switch out the UA ID variable, hit publish and you’re done.

What Can Go Wrong

In a not so perfect world, if the codes are added to the site after the site goes live it could potentially cause issues with codes conflicting, loss of tracking for a period of time and other problems. Let me share with you some examples of issues we’ve seen:

  • We’ve had GA codes conflict with other codes on a page which has caused pages to break.
  • We’ve seen checkout break due to codes conflicting. This is a BIG Problem for eCommerce site not just because people can’t check out and they are losing revenue now but they also could losing a lifetime customer.
  • We’ve seen websites go live with no tracking and therefore no visits were tracked for days which in turn messes up YOY data and keeps you from seeing if the site has any potential issues with SEO or usage.

While these might sound like easy fixes, they have not been. Which is why I would highly recommend making GA Code Migration an important step in your website redesign. Whether you’re in the midst of a redesign or just considering it, now is the perfect time to add Tag Manager to your site and move away from hard-coding GA. If you don’t have a large complicated site, then it takes no time for a developer to add the container code and any data layers needed for tracking. It’s much faster than adding hard-coded snippets to different elements on a site.

Start Planning Now

So with that said, don’t let GA tracking be an afterthought in your redesign process. Don’t let it fall through the cracks and miss out on tracking visits and engagements on your new site. Talk about it when you first start meeting to layout the redesign process. Make sure you have a GA specialist in your meetings who can tell you what codes to add, when to add them and get it tested before you push your new site live.

I promise you, making sure the code is in place and working correctly before a site goes live, keeps you and your development team sane and saves everyone from many headaches and the potential for lots of stress if it’s added afterwards.

21 04, 2017

WFU Selects Beacon to Teach Graduate Level Analytics Course

By | 2017-08-15T16:00:39+00:00 April 21st, 2017|Categories: Beacon News, Digital Marketing, Google Analytics|Tags: , , |

Last year, when I discovered that Wake Forest’s Business School was starting a Master’s Program in Business Analytics (MSBA), I had to see how I could help. After all, it’s my alma mater AND analytics – two of my favorite things! So I was thrilled when our many discussions and planning sessions led to Wake selecting Beacon to teach its graduate level course in Digital Marketing Analytics this Spring.

Farrell Hall at WFU Analytics has been a critical component of Beacon’s offering since almost the day the company started back in 1998. It’s why Beacon is one of the longest active Google Analytics Certified Partners in the country.  The entire Beacon Digital Marketing Team is involved with this class, led by Gus Kroustalis, Beacon’s Lead Analytics Strategist and Andrea Cole, Beacon’s Director of Digital Marketing.  The team meets regularly internally to carefully plan each class around important topics, crafting in-class and homework assignments that expose the students to real world tools and thinking.  For most companies nowadays, their website is the centerpiece of their marketing strategy.  So this course emphasizes Google Analytics and walks the students through 7 intense weeks that includes

  • Key Metrics for the Web
  • Consumer Targeting
  • Engagement Analysis
  • Channel Analysis (SEO & Paid Search)
  • Attribution Models
  • Conversion Testing

The demand for critical thinking skills with respect to analytics data is enormous in today’s business world. Students that have tangible experience will hit the ground running and be able to provide immediate value to their employers.  Certainly, technology and the widespread availability of data are drivers, but it’s also about “brain-power”, the ability to analyze data with all the available tools to gain insights, formulate strategy and communicate well-founded recommendations that will improve ROI and/or decision-making.

Companies are clamoring for critical and creative thinkers. Graduates of Wake Forest’s MSBA program will certainly fill this demand.  The students will experience a rigorous, hands-on course that exposes them to actual live data from several of Beacon’s clients that have graciously agreed to participate.  Although they will learn many different tools, the emphasis will be on stimulating their business minds to develop intelligent insights, drive creative ideas and improve business.

It’s exciting that Wake’s MSBA students have the opportunity to work alongside Beacon’s recognized experts in Digital Marketing to get first-hand experience and knowledge. It will certainly make their resumes stand out.  Likewise, my DMS Team is equally excited to collaborate with, and learn from, the high-caliber students for which Wake Forest University is known.

Beacon's Gus Kroustalis Teaching

19 10, 2016

Google Analytics Most Underused Report – Network Visits

By | 2017-08-08T08:26:55+00:00 October 19th, 2016|Categories: Google Analytics|Tags: |

Assuming your familiar with Google Analytics, then you know that GA has many valuable reports and lots of great information related to your website. At the basic level you can get sessions, pageviews, bounce rates and more. With advanced tracking you can get engagement metrics, goal conversions, offline data and more. However, did you know that from a basic level you can also get information related to sessions from certain Networks which can then be used for prospecting new clients?

The Networks report has been around a long time, yet we don’t see clients use it very often. When we talk to them, we realize they don’t see the benefit in the report and therefore don’t look at it. Yet, this report has a huge benefit, especially for B2B companies who could benefit from knowing what other companies are viewing their site.

Let’s dive into this report so I can give you an example of how we use it here at Beacon. First, to view this report you’ll need to open analytics and then go to Audience > Technology > Network.

service provider path

 

Now that you have this report open, you should see data related to Service Providers.

service provider report

 

Before I show you how we use this report, I want to fill you in on a secret you might not know.

Larger companies and even some small ones, have their own service providers, so therefore you will see their company name listed as a Service Provider!

Did you know that? Are you able to start seeing how this report can be useful? Have I sparked your interest and got your idea wheel spinning? I hope so.

Moving on though, let me show you how we find this report helpful here at Beacon.

Recently, we’ve started to work with more and more Universities and are slowly becoming a leader in this industry for providing web development and digital marketing services. So this report is great for us to see what Universities are looking at on our website. To do this, I use the filter function and Include Only Service Providers matching “university|college|school”.

service provider filter

Once this filter is in place, then I’m only seeing sessions from service providers with one of those keywords in the name. An example is below.

 

google analytics service provider

Now that I can see what schools are interested in Beacon, I can then filter it further by adding a second dimension for Pages and see what pages on our website these schools looked at. From here, I can pass along this information to our sales team so they can begin the process of reaching out to these Universities to see if our services could be of help to them.

This same method could be beneficial to you as well. You can apply the same steps I used, just change out the information to match your customers better. As an added bonus, since I know your filtering might not be as easy as ours, here’s a list of service providers you can exclude so you can then see what companies are left.

Time warner|mci|Verizon|Comcast|charter|cox|telecom|at&t|north state|communications|embarq|sprint|service provider|centurytel|private

From there, you’ll be able to get an idea of how you can better filter your data to get the information that would be most helpful to your business.

Don’t wait any longer! Go Dig in!

 

1 09, 2016

Dig Deeper into your Data with Advanced Segments

By | 2017-06-16T13:13:56+00:00 September 1st, 2016|Categories: Google Analytics|Tags: , , |

I love Google Analytics. I love that you’re able to easily dig deep into data to discover hidden secrets about your website that might not be obvious with the basic reports in GA. In order to do this deeper analysis, you’ve got to use advanced segments. It can be scary at first for the average GA user, but once you start using them you discover how powerful they can be and the greater insights you can get from your data.

Recently, we performed a deep dive (aka some advanced reporting) for a client to try to uncover some of these hidden secrets about their website. We wanted to find out if certain features available to users was helping or hurting the sites performance. We could see that people were using these features, but needed to dig deeper to see how that usage affected goal completions and behavior.

Let me set the scene:

This client sells B2B (offline) and B2C (online). The goal of the website is to provide information about their products and also generate sales. For our deep dive, we looked at many data points, but for this post I want to focus on only two:

  • If the blog was helping to drive goal completions and qualified traffic

and

  • How the retailer locator affected behavior on the site and goal completions

So to look at both of these, I had to set up advanced segments for visits including blog views and visits with no blog view.

Here’s a look at how those advanced segments looked:

Visits including Blog View

advanced segment set up

Visits with no blog view

advanced segment set up

Notice the only difference is one says “include” and the other “exclude”. Now let’s look at the data.

advanced segment in google analytics

Look at the parts I highlighted. We see from a high level that visits with NO blog view have much better behavior. Sessions have lower bounce rate, more pages per session and higher session duration. Not only that, these visits’ goal conversion rate was 2.5x better.

So now you’re probably asking yourself, “What does this mean?” Well, it means the blog isn’t helping provide value for this site and increase the likelihood of a goal completion. No, they shouldn’t kill the blog and remove it; instead they need to look at their current blog strategy and how it can be tweaked and improved to help increase behavior and goal completions. For our analysis, we stopped at this point due to time constraints but when the client is ready to look at the blog and come up with a new strategy, we’ll dig deeper into this data and look at their top blog posts over the past year and how each of those has affected behavior. Doing that will allow us to get info on which blog posts provide value and which do not. Then we can come up with a strategy to refresh those older posts and create new posts.

Now let’s look at the retailer locator and see how it affects behavior and conversions.

Here is how I set up these advanced segments:

Sessions excluding Retailer Page

advanced segment set up

Sessions including Retailer Page

advanced segment set up

 

Looking at this chart, we can see the retailer locator improves behavior on the site and results in higher session duration, more pages viewed and lower bounce rate. However, it does NOT help ecommerce.

advanced segment in google analytics

So what does this mean? Well it means, the retailer locator is a good feature to help improve session behavior but shouldn’t be as visible since it doesn’t increase online ecommerce conversions. Currently, the retailer locator was highly visible in the main navigation and the utility navigation. After looking at this data along with other data (not shown in this post) we determined it was best to leave this feature on the site but since selling online was the #1 goal of the website, we wanted to make it less visible and remove it from the navigations and move the link to the footer. This way the link is still accessible from all pages.

Something to note, with the retailer locator, we can only go off the data we have. Unfortunately, for this client it’s not possible for us to get offline information that we could then import into GA to get a clearer understanding of whether the retailer locator helps to increase offline sales or not and should be left highly visible.

As with any website change, it’s very important to annotate the change in Google Analytics so you can easily see if your change has caused any fluctuations in your data. Now it’s your turn! Look at your website and see if there are things on it you would like to dig into deeper to see if it’s helping or hurting engagement. I bet you’ll be surprised and excited with the new data you’ll get!

And by the way, if you don’t feel comfortable digging into GA yourself, let Beacon help! :) We offer GA Training which can be customized to teach you how to set up Advanced segments and reporting or we can do the deep dive for you.

23 08, 2016

How To Use Annotations in Google Analytics

By | 2017-06-16T12:50:19+00:00 August 23rd, 2016|Categories: Google Analytics|Tags: , , |

Picture this: you’re checking out your website data in Google Analytics, and decide to look at your monthly traffic year-over-year. You see a huge spike in traffic on a single day last year, but you aren’t quite sure what caused it. Were you running a special that day? Perhaps a new TV commercial aired? Or maybe a direct mail piece dropped? Hmm…you start shuffling through old emails and notes to solve the mystery.

Traffic Spike

Without knowing exactly what could have affected last year’s traffic spike, it’s impossible to measure the impact individual circumstances have on your website. Sure, you can keep an Excel spreadsheet with a long list of dates. But what if I told you there was an easy way to keep all those events organized, in one place, and in context? Yep, you can do it right alongside your website data with Google Analytics annotations.

Annotations allow you to note a particular event that could have an impact on your data right on the date that it occurred.

Here are some of the types of things I like to annotate:

–          Website downtime

–          Sales and special promotions

–          Website development changes

–          Marketing campaigns (direct mail, TV, radio)

–          Content changes

–          Press releases or high profile featured content around the web

–          And any other time-specific event that could possibly affect website visits and user behavior

Making annotations in GA is incredibly easy. Here’s how it’s done:

  1. Click the little down arrow under your traffic chart and click “Create New Annotation” on the right.
  2. Enter a date, a note, and choose the annotation’s visibility.
  3. Save.

Annotate

That’s it. No, really. It’s that simple!! Annotations are indicated by the little text bubbles at the bottom of your chart. To see the details simply click the bubble.

To see a comprehensive list of all annotations for your view, go to the Admin panel and click Annotations.

Admin

If I can offer you one final tip for using annotations in GA, it is to be explicit. Trust me when I say, it will save future you a lot of frustration. “Online Sale”…great…but what was on sale? While Google only gives you 160 characters, be as detailed as possible! If your notes are enigmatic, you’re wasting your time creating them to begin with.

How do you use GA annotations to help analyze your website data?

19 08, 2016

Benefits of Upgrading to Universal Analytics

By | 2017-08-08T08:15:58+00:00 August 19th, 2016|Categories: Google Analytics|Tags: , , , , |

Universal-Google-Analytics

Yes, Google Analytics announced their Universal version way back in 2012. It made sense to hold off on upgrading back then so that many eventual bugs could be worked through. I occasionally come across websites that have yet to upgrade. If your website is still using the Async version, it is time to upgrade to Universal Analytics. Here are some of the benefits that are waiting:

1) Report on users, not just website sessions

With User-ID implementation, you can connect a single user’s website activity across multiple devices. Subsequently, there is reporting that shows truer user totals. There are also reports focused on the user experience across multiple devices. If your website collects many email addresses, has log-in features, or is eCommerce, then this is a must-have feature.

2) Simplified configuration options

In the admin section of your Google Analytics account, you are given the ability to clean up organic traffic attribution. You can also change the session and campaign timeout times, which are which are 30 minutes and six months, respectively, by default. Referral exclusions is a great new tool available with the Universal Analytics tracking code. One of the frustrating aspects of the Async version is the issue of self-referrals that sometimes cannot seem to be solved. I have personally seen websites that upgrade their tracking to Universal, utilize the referral exclusions feature, and end up with far more accurate attribution reporting.

3) Custom dimensions and metrics

With the Async version of Google Analytics, you are limited to five custom variables. That feature is replaced with custom dimensions and metrics, and the limit is increased to 20 each. Using the dimensions to segment your website users, build funnel groups, and so on leads to more valuable data analysis and decision-making. Custom metrics can be used with data imports, combined with product information, or used to create additional helpful data related to the user experience.

4) Enhanced eCommerce

Enhanced eCommerce

Certainly, one of the biggest beneficiaries of Universal Analytics are eCommerce websites. The enhanced eCommerce feature opens the door to new data elements and reports. For example, you can use enhanced eCommerce to build a shopping funnel that goes from when a user views a product on the website, to the point of sale. Having funnel reporting during the shopping experience, and not just the checkout process, can help lead to user experience improvements.

Upgrade the Right Way

When beginning the process of upgrading to Universal Analytics, be sure to map out a project process. It is important to leave all current tracking in place until the new tracking is scoped, coded, installed, tested, and verified. A best practice would be to install your fully built-out Universal Analytics tracking alongside the current tracking, using a different UA-ID, so you can verify that the two tracking instances are delivering similar data.

 

12 08, 2016

eCommerce Analysis: Using Google Analytics to Identify Your Whales and Minnows

By | 2016-11-22T17:47:23+00:00 August 12th, 2016|Categories: Ecommerce, Google Analytics|Tags: , , |

If you manage an eCommerce site, you probably spend a lot of time in Google Analytics. There’s a ton of great metrics and reports to check out, like mutli-channel attribution, average order values by channel, eComm conversion rates, and so on. You’ve probably even segmented data by demographic, device type, or geography. All of this is great, high-five yourself if you’re doing these things because you’re probably a few steps ahead of your competition. But have you ever segmented by transaction dollar amount? I’m about to enlighten you on a couple advanced segments to help you identify your whales (biggest customers), your minnows (smallest customers), and how to get more whales and less minnows.

OK, got your coffee? Let’s go!

First thing we’re going to do is figure out your top 10% and bottom 10% transaction thresholds.

Go to Conversions > Ecommerce > Sales Performance. Expand your list to show all available transactions, then export to XLSX.

transaction report

The next step is to identify the thresholds for your top 10% of transactions. Open up the XLSX file, put filters in your headings, and remove the last row of data where your totals show (keeping it in skews your sorting).

Sort the revenue column from largest to smallest, then apply some conditional formatting, as seen in the screenshot below. Repeat this step with the bottom 10%.

*Side note: If you’re not familiar with this feature in Excel, I highly recommend becoming a conditional-formatting-ninja, it will shave tons of time off of your analysis.

top 10

Once you’ve got both conditional formats applied, simply look at the lowest dollar amount in your upper 10% grouping, and the highest dollar amount in your lower 10% grouping. These are your thresholds. In my case, using the Google Merch Store test account, I’ve identified $259.50 as the upper threshold, and $13.59 as the lower threshold.

Now the good stuff begins.

Head back into your Google Analytics account and create a new advanced segment. We’re looking for users who have a per-user revenue of $259.50 or greater, so we create the segment as shown below:

advanced segment

Now that you’ve got a segment created, apply it, and you’re free to check out other reports to analyze where these users come from, how the interact with the site, and figure out what you can do to acquire more people that would fall into this segment.

A few good starting points for conducting this analysis are:

  • The Source/Medium report in Acquisition – Perfect for learning how your whales found you
  • The Mobile Overview report in Audience – This is great for device type analysis. i.e. are your whales coming through mobile or desktop? Assumptions can be dangerous, so it’s always a good idea to investigate
  • The Landing Page report in Behavior – Surely, you’ve got some pages on your site that are more likely to drive purchase, but which ones are the best?

Of course there are plenty of other reports you can gain insights from, this list is only intended to kick start your analysis engine.

Once you’ve conducted your whales analysis, circle back and repeat the process for minnows. The idea is the same, but this time around you’re trying to identify ways to attract fewer minnows. So check out the same reports in Google Analytics and identify channels that drive small transactions, landing pages the don’t perform as well, et al.

If you do this on a regular basis and make adjustments to your marketing efforts accordingly, you’ll start to see your thresholds shifting upwards, as well as increases in your average order value.

5 08, 2016

Multiple Department Higher Ed Analytics Setup

By | 2017-07-20T09:25:14+00:00 August 5th, 2016|Categories: Higher Education|Tags: , , , |

Are you a Higher Education institution who is concerned about:

  1. What visitors are doing/looking for on your site?
  2. Looking at analytics by a department and/or field of study?
  3. Having multiple stakeholders view Analytics for one or more departments ONLY?
  4. How to better organize your Google Analytics account?

If you answered yes to one or all of the above questions, Beacon has a comprehensive overview of how to best setup your Google Analytics account to support multiple departments within your college/university. Our Google Analytics Strategist, Gus Kroustalis, walks you through a few steps to better organize your account into properties and profiles that will satisfy all groups on campus. Please view the video below.

Subscribe For More Tips

Beacon will release a series of Higher Education focused Youtube videos covering Common Questions About Higher Ed Analytics And How To Answer Them. Please subscribe to our channel for more content like what you watched above.

3 03, 2016

Two Reasons for Missing Transactions in Google Analytics

By | 2017-07-20T09:27:34+00:00 March 3rd, 2016|Categories: Google Analytics|Tags: , |

missing transaction data in analytics

How closely have you looked at your transaction data in Google Analytics? Have you seen where sometimes there are missing transactions in GA?

Here is an example of what I mean:

 

transaction data in analytics 2

Notice, in this example transaction numbers that are missing are: W000051, W000050, W000043.

Can you guess why they might be missing?

Alright don’t give yourself a headache trying to rack your brain for reason this happens. Let me give you a couple reasons I’ve found and just keep in mind this could be true for your CMS or there could be a totally different reason.

 

Reason #1 for Missing Transactions

Remember the data above, well the reason for the skipped transaction IDs there is because this particular CMS generates an order number for any user who gets past the billing/shipping screen in the checkout process but didn’t make it through and complete the order.

Basically, an order is created and a cookie set so that the user can come back to the site within a months’ time and complete their order should they decide too. If they don’t and the month has passed the order is deleted out of the system.

 

Reason #2 for Missing Transactions

Here is another example of missing orders from a separate GA account.

transaction data in analytics 2

Notice in this example missing order numbers are: 121098, 121097, 121092, 121091, 121089, 121088, 121085.

Quite a few, huh!

The reason for these missing orders is totally unrelated to the first reason. This particular CMS is Aspdotnetstorefront which is a popular ecommerce platform. Missing orders here are related to a user going through the checkout and putting in credit card information then clicking to submit the order and getting a payment error message. When they enter their info again and click submit a brand new order number is created.

Crazy! I know! It’s always so interesting to me how CMS’s function. I don’t understand the reasoning for this but we’ll just table that for another discussion.

So anyway, I’d love to hear if you’ve noticed this problem in your analytics account and if the same reasons apply to your data or if you have other reasoning’s for it! Leave me a comment below and let me know.

Make sure you check back often too. I’ll update this post if I find any other reasons this can happens.  :)

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