5 05, 2017

Wake Forest MSBA & Beacon – A Successful First Year

By | 2017-06-05T07:59:21+00:00 May 5th, 2017|Categories: Google Analytics|

Final exams for our Wake Forest MSBA students ended Wed. What a great opportunity. Quad at Wake Forest UnivPosed with the question on how to improve the mobile marketing strategy for one of our top clients, the graduate students had to dig into our client’s live dataset in Google Analytics, produce a compelling executive level report and deliver a convincing, focused 5-minute presentation directly to the client and Beacon’s entire Digital Marketing Team. Yes, it was stressful.  Nerves were apparent.  But this was a real world scenario to get practice before they enter the job market.  We evaluated 38 presentations over 2 days and were impressed (and proud) of what they had learned from our team during the intensive 7-week course, especially with their poise and the ideas they delivered.  Afterward, our clients said they liked the variety and how the students made them think about their business, marketing and online strategy from new, different angles.  They also planned to share many of the ideas (and the experience) with the company’s president.

Beacon’s DMS Team put in a lot of time to structure the class around live data sets (provided graciously by 3 of our clients) and critical thinking exercises using real-world approaches with Google Analytics, SEO and Paid Search. Beacon was also able to arrange for Deepak Aujla, Global Analytics Program Manager at Google, to give a 45 minute online presentation about the importance of analytics in the marketing industry and the increasing demand for analytics professionals.  Another great learning opportunity, for everyone attending. (See previous post)

As I strolled through the Quad afterward, not only did the beauty of the campus consume me (again), but I was flooded with memories – especially of exam time and the relief when they were over. It was a similar feeling this time as I’m excited for the careers ahead of these students.  They were certainly anxious to graduate and move on, as I was in 1983, but they will miss this place.

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

29 03, 2017

Google Analytics Event Tracking Tutorial

By | 2018-09-14T14:51:54+00:00 March 29th, 2017|Categories: Google Analytics|

Google Analytics, with its out-of-the-box tracking features, provides meaningful data about your website visitors and their activity. However, you are still required to configure goal conversion points, in order to track the overall success of your website. So, now you know where a user comes from, what pages they visit, and how many eventually reach a goal conversion point. But what about the rest of the user’s experience on your website?

Steps one and three of the conversion path are accounted for and can be analyzed. But what did the user do while on your pages? Why did some users reach conversion points while others did not? Event tracking is a feature in Google Analytics that can help fill in this critical middle step of conversion analysis.

Identify content elements that you would expect to influence the user experience. When setting up event tracking for those elements, you have a hierarchy of four data slots at your disposal: category, action, label, and value. It is best to assess your entire website for event tracking, so that the hierarchy of your setup is consistent and intentional. Event tracking can be configured by hard-coding the snippets on your website, or through Google Tag Manager. With this series of reports indicating your users’ content interactions, you are now able to bridge the gap between where your users come from and which ones reach conversion points. The most important question to answer when analyzing website user conversion trends is, “Why?”

Now, you are more equipped to provide that answer, which can lead to successful website updates.

GA Audit Request

23 03, 2017

Using Google Analytics to Identify Prospective Students with Custom Dimensions

By | 2017-07-20T09:20:24+00:00 March 23rd, 2017|Categories: Google Analytics|

When auditing higher ed Google Analytics accounts, we typically see that clients calculate admissions content stats and goal conversion rates against their global data. This is despite the fact that they know not all people who visit the website are prospective students.

Wouldn’t it be great to have Google Analytics reporting that focuses on prospective students? How about other reporting sets for other audiences, too? The custom dimension feature in Google Analytics is a great way to build audience segments, and we can start with prospective students. First, you need to identify pages, links, buttons, and other content elements with which you have a high level of confidence that only prospective students would interact. Some examples include clicking an Apply Online call-to-action or scheduling a campus visit. Simply landing on the admissions home page is probably not a specific enough indicator of a prospective student. In the Google Analytics admin, you will need to configure a new custom dimension, possibly naming it Visitor Type. Be sure to set it as a user-level dimension so that data spanning multiple website sessions will be collected. If your Google Analytics tracking is hard-coded on the website, you would apply the given code snippet to all pages and page elements that indicate a user is a prospective student. If you are using Google Tag Manager, you would update your tags to include the custom dimension variable, ensuring it is only triggered by any of the pages or page elements you identified earlier.

After testing the new tracking and taking it live, you can utilize the custom dimension in a number of ways, including custom reports, dashboards, or even a new reporting view dedicated to the audience. Be mindful that you should assess the viability of each page and page element that make up your prospective student audience, in order to continue to have confidence in the parameters that define the audience. Of course, you can add or remove any pages or page elements as you see fit, always striving to have the audience tagging as accurate as possible.

 

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.

13 04, 2016

Four Ways that a Google Analytics Session Could Break

By | 2016-10-31T10:36:49+00:00 April 13th, 2016|Categories: Google Analytics|Tags: , , , |

Google Analytics provides great tools for data collection and reporting. One of the critical aspects of analytics for your business, though, is ensuring that you have clean data.

An issue that I come across occasionally is a lack of session continuity. This means that a visitor’s session on your website is split into two or more website sessions. When this happens, your website session totals, site usage metrics, and traffic source attribution are all filled with incorrect data.

Beyond those reporting metrics, eCommerce websites rely on data analysis that includes Multi-Channel attribution models, total sessions per transaction, and assisted conversions. Broken sessions makes this reporting unusable. This can hurt eCommerce website marketing, because so much is dependent on proper traffic source attribution. Picture this: A new visitor comes to an eCommerce website and begins shopping. At some point, the website session being captured by Google Analytics breaks, and a new session begins during the visitor’s same shopping visit. Once a purchase is made, the marketing channel that brought the visitor will be considered an assisting source, not the actual source. Depending on the website’s attribution model, this could hurt analysis that will lead to marketing budget decisions.

If you are not confident that your visitors’ website sessions are maintained from beginning to end, then you have some work to do.

Here four ways that a Google Analytics session could break:

1) Session Timeout

There is a 30 minute session timeout, by default. Once that mark is hit, the session ends. If a user kept a tab open in their browser with your website, and resumes activity in the browser, then a new session will begin. Google Analytics will note that it is the same user with a new session. You have the option of adjusting the timeout marker, anywhere from one minute to four hours. This can be done in the Session Settings section of Tracking Info configurations for your Google Analytics property (see screenshot below).

google-analytics-session-settings

2) Missing Google Analytics Tracking Code

Every now and then, I come across a website that has not applied consistent Google Analytics tracking code across the entire site. Google Analytics data collection is based on its JavaScript being installed and readable. If a page on your website is loaded, and the JavaScript is not present, then there will be no data capture. Consequently, the previous pageview will mark the end of a user’s session. If the user clicks from the non-tracked page to a page with the Google Analytics JavaScript, then a new session will begin. Just like with the session timeout, your data will show one user with two sessions.

missing-google-analytics-tracking-code

The best way to avoid missing code is to apply the Google Analytics JavaScript in your website template. Every time a new page is created with your template, the Google Analytics code will automatically be in place. If you use multiple templates on your website, be sure to apply the Google Analytics JavaScript to each template.

3) Cross-Domain Tracking Error

Anyone who intends to set up cross-domain tracking knows that the most valuable aspect of the setup is maintaining session continuity between the two domains.

The industry I most frequently see cross-domain tracking is Higher Education. Many institutions utilize multiple domains, and there is an obvious relationship between the content across those domains. Perhaps from the institution’s standpoint, content, data collection, and reporting are segregated by departments. However, the website visitors have a unified experience across all of the content during their website sessions.

Cross-domain tracking with Google Analytics can be tricky, which is why even Google recommends using the linker plugin to make life easier. Validate your tracking code setup in a test environment. If at all possible, never use your live environment to test your tracking code. If, while testing, you notice that the source/medium changes when clicking to the second domain, then there is an issue with the tracking code.

4) Conflicts with Other Scripts

A very talented JavaScript developer once explained to me that, with the broader use of scripts on websites these days, there is potential for some scripts to conflict with each other and cause one or both to break. The best way to catch this is to validate your tracking code setup in a test environment. Not only should you make sure that the Google Analytics reports are showing data, but you should also verify the appropriate Google Analytics cookies, and use your browser’s developer tools to check for any script errors.

Get More Reliable Data

Guarding against the above issues helps ensure that your website’s Google Analytics tracking is as accurate as possible. More specifically, these issues skew website session totals and sometimes source/medium attribution, which then skew conversion rates and other helpful KPIs. The goal of analytics is to make informed decisions that improve your business. Make sure your data is reliable, for that purpose.

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