Archive for 2014
Recently, an issue came to light with one of our clients which turned our world upside down – quite literally.
In the graph (shown below), Unique Pageviews vs. Pageviews was compared for a given date range for a select group of pages.
If you click on the image to zoom in, you’ll notice something weird. For some reason, the line of the Pageviews metric — which is higher in number — is lower visually than the unique pageviews.
What the @#$^ is happening?
The unique pageviews line (the higher of the lines) is graphed according to the y-axis scale on the left. What you probably didn’t notice is the pageviews line (the lower of the two lines) is graphed according to the secondary y-axis on the right. Yes, there is another y-axis on the right side.
Because the scales are different, they’re spatially and visually apples and oranges in terms of height.It’s a bit counter-intuitive and weird, but we thought we’d share this finding with you in case any runs into this issue and get’s confused.
Still confused? That’s ok. At least you know why now
Also, see cool interactive data visualization chart of 2014 World Cup data here.
As the month-long World Cup Tournament in Brazil is at an end, it is amazing to see that the biggest winner of the tourney is not the one who scored the most on the green field, but rather, the one who scored the most on social media.
The most watched sporting event on earth generates millions of social mentions and millions of viral video views produced by individuals as well as major brands for marketing and advertising.
During the USA match against Belgium, for example, the US Goalkeeper, Tim Howard’s, name exploded all over the internet after his astonishing performance and his world record saves in the match. He was lauded greatly by his fans on different social networks and was even briefly named the U.S. Secretary of Defense on Wikipedia!
Neymar, the 22-year-old Brazilian striker with four crucial goals and successful pass rate, has been leading the World Cup social buzz as well. He is by far the most talked about player of the tournament with 33 million social mentions. He has 12.5M followers on Twitter and has been in the spotlight ever since his two goals scored in the first match, all the way until his last match in the tournament where he took a knock in the back from a Colombia defender, causing a fracture to his third lumbar vertebra.
Obviously, social mentions can correlate positively or negatively based on the performance of the players and their teams. In order to understand and analyze the online data generated by this social buzz, we need to marry that data with real-time offline data generated by the “feet” of the players.
To get the best of both worlds, detailed statistics were collected by the E-Nor consultants using Google Analytics (Universal Analytics) for every World Cup player, team and match, including:
- Pitch condition
- Goals scored
- Goals against
- Fouls committed
- Fouls suffered
- Attempts on target
- Attempts off target
- Games played
- Minutes played
- Yellow cards
- Red cards
Here is a sample of the matches report:
This report shows the top 5 scored players:
Here are few other snapshots of the data in action:
Teamwork and Performance
The aspect that fascinates me the most in soccer is a team attempting play as one complete system intending to score one goal.
Although this year’s World Cup winner, Germany, may have no internationally recognized stars, such as Neymar, Messi, and Ronaldo, I enjoyed watching all their games in the tournament. The beauty of their team work definitely overcame the absence of entertainment from an individual superstar, and ultimately led them to true victory. Congratulations to Germany, very well deserving champions indeed!
Here is how the top 8 teams performed:
Pitch Conditions and Performance
Poor pitch conditions could easily hurt the playing style and the performance of teams. A well-maintained playing surface helps players with running and quick-passing. According to data gathered, teams had a hard time scoring on wet and dry pitches, while scoring was above average on soft pitches.
Here is the same report based on the temperature during the match. Do you see any correlation?
Age and Performance
While the 36-year-old Ivory Coast striker, Didier Drogba, wasn’t directly involved in any goals, his presence was enough to energize his team and to worry the opponent’s defense! This is my response whenever someone criticizes the performance of players who pass the 35-year-old milestone. Maybe I am biased in my view, but that is why we need to look at data and what it says about players’ age and their performance.
History and Performance
While this is the first time for us to record World Cup data in Google Analytics, it was impossible for us to enjoy looking at trending event or to predict based on historical data. With this humble experiment that we conducted for the 2014 World Cup, we are hoping that we left the doors of possibilities wide open for other smart people to build on top of this and provide data and soccer lovers a more comprehensive coverage of the World Cup data all in GA
||1958 1962 1970 1994 2002
||1954 1974 1990 2014
||1934 1938 1982 2006
It has been said that this World Cup will be the most social sporting event in history and it certainly was. All available data easily validates that assertion. World Cup data also provides major opportunities for brands and for marketing agencies. As you see in the experiment, Google’s Universal Analytics infrastructure can handle the marriage of the two worlds; offline and online activities. I believe with the new Google Analytics platform we will see many creative solutions built to answer real business needs that we failed or were unable to answer in the past.
Interested in our collected data? Send us your email address and we will grant you a temporary ready-only access to our 2014 World Cup GA reports.
The World Cup is the most viewed global event (yes, even more than the Olympic Games). Internationally, one of the most, if not the most, common sport is soccer (known as football in places other than the U.S.), and for good reason. Who can resist the fun of the sport! This year, there was the fastest goal scored by U.S. (32 seconds!), Algeria’s defense against Germany, and the mighty Tim Howard’s record-making game for most saves in a single game (16 saves people! 16!) — just to highlight a few!
The beauty of Universal Analytics is you can pull in any sort of data into the Google Analytics interface. To demonstrate this, in our last post, we pulled World Cup data (up till 7/7/2014) into Universal Analytics.
We looked at the following data:
- Top Matches
- Team Performance
- Top 10 Scored Players
- Players with Red Cards.
It’s already cool that you can see the data in GA, because now you can take advantage of the cool reports and filters and really chop up the stats. But the data is in multiple reports, so to really analyze the data, you’d have to click through to look at all the info. Plus, it’s mostly numbers, so it’s hard to really tell a story.
We wanted to show that there are even other fun and engaging ways to present and share data.
Tableau Software – Interactive Data Visualization
“There is a magic in graphs. The profile of a curve reveals in a flash a whole situation — the life history of an epidemic, a panic, or an era of prosperity. The curve informs the mind, awakens the imagination, convinces.” – Henry D. Hubbard
Endless tables of numbers might seem intimidating to some of us, particularly marketers who usually aren’t as technical. Sure, you could create charts in Excel, but it’s 2014, why limit ourselves to static 2-Dimentional shapes and charts? Let’s really wow our audience.
Tableau is an awesome data visualizaiton tool that lets you pull in data directly from your analytics account into the software. From there, you can create really cool interactive dashboards and visualizations. The tool provides several interactive elements geared towards helping the user slice and dice data on the fly. Check it out!
Behold! Hover/click over any country and see how the data changes below!
The “viz” above is more than just a bunch of static charts – a story unfolds, each country is denoted by its location on the map as well as flags. Hover over the country of your choice and get the data you want. It’s that flexible. Tableau users, download this report for free.
Make your predictions on the World Cup!
You now don’t have to guess who’s going to win strictly based on your favorite team, you now have the data to prove it! Who do you think will win the 2014 World Cup?
Soccer image by Pallus23 of Deviant Art.
Every World Cup game I watch overwhelms me with the amount of historical numbers and statistics thrown around by game commentators about the teams and players. Soccer fans, including myself, are becoming numbers addicts more and more and we enjoy game analytics and prediction as much as we enjoy the games themselves.
There was a time, not so long ago, when statistics in soccer were only as complex as goals scored (with maybe a few other small metrics!)
This is similar to Digital Analytics where we used to foolishly measure website performance based on rudimentary data, such as the infamous hit counters! (Sad days, I know!) Thank goodness that isn’t the case anymore as every day more advanced metrics are introduced and the entire world is exposed to and becoming more familiar with data/statistics in all fields and aspects of life. Rudimentary metrics have been replaced with a world of rich numbers and sophisticated metrics. For example, soccer fans and analysts have more data to work with than most could ever use after years of analysis.
Here at E-Nor, we wanted to make this year’s World Cup even more enjoyable and interesting for marketers and analysts in the Digital Analytics industry. So we decided to record some key players’ activities as they are happening and send that data to our beloved analytics and reporting tool – Google Analytics.
As you may know, Universal Analytics is a game changer when it comes to the possibilities of what can be measured using Google Analytics. With the Universal Analytics Measurement Protocol, we can make HTTP requests and send raw user interaction data directly to Google Analytics servers. This gives us the power to measure users’ interaction from any environment – including the soccer field!
Just for fun, we collected around 300 events for every match. Lots to look at and hopefully enough information to satisfy dedicated soccer fans
In this first blog post, I will share a few reports that we already gathered during the first round of the competition. Next post, we’ll take another angle and show you how we did it and share some code samples.
This report shows the top 10 matches based on the goals scored:
This report shows the performance of the teams that made it to the round of 16. Yes, we made it; Go USA
This report shows the top 10 scored players in the first round:
This report shows the names and positions of the players with red cards:
Photo from Getty Images
As a Google Analytics Premium Reseller for several government agencies, we’ve noticed that Web and mobile analytics is as important to government digital initiatives as it is for the private sector. Fundamentally, it’s about organizations leveraging digital media to offer products and services to a target audience or to communicate and connect with constituents.
Similar to their counterparts in the private sector, federal communication managers, webmasters and those in charge of digital initiatives (eGovernment, Digital Government, etc.) need to navigate through oceans of data to derive insights to impact the business. This is easier said than done with scarce financial and human resources, and the fast pace of innovations in digital analytics.
It’s As Easy As ABC.
With a couple of tips using the “ABC’s” of digital analytics, you can simplify the complexity a bit.
This post is intended to provide reporting tips and best practices for analytics relating to government websites. If you are looking for a comprehensive how-to implementation guide check out our other technical posts on our blog for implementation best practices and posts similar to our Universal Analytics Resource Kit.
The concepts presented apply to any analytics platform, but the naming convention and the sample reports are all taken from Google Analytics (GA), since it’s the most commonly and widely used analytics platform.
We will also leverage the “ABC” framework to highlight three important reporting aspects of every government digital program:
- A for Acquisition- how visitors came to the site.
- B for Behavior- what they did when they got there.
- C for Conversion- did they do what you wanted to them to.
In addition to and for each of the above sections, we will show how you can leverage Google Analytics’ recent demographic reports to better understand your audience (here is a link on how to enable demographics in Google Analytics reports).
*Disclaimer #1: There was no personally identifying information used for the examples provided; all are aggregated data and/or case studies.
*Disclaimer #2: Data in the reports below do not reflect any specific government site; reports/numbers are listed for illustration purposes only.
Acquisition – How Visitors Came to Your Site
1. Figure out what’s driving the traffic to your website or mobile app.
Acquisition reports allow you to answer the following questions:
- Where is the traffic coming from?
- What social media networks are really working for the organization?
- Which defined campaigns are driving qualified traffic?
Let’s take a look at the Department of Education site as an example, specifically the Free Application for Federal Student Aid (FAFSA) office. Students and parents can submit the FAFSA forms through the Education Assistance Agencies or can submit the form online. Let’s say the application deadline has just ended and it’s time to analyze the traffic patterns to the online form section.
- Where did the traffic come from?
- What sorts of searches were made?
- Is most of the traffic organic or other sites referring traffic to the online form?
In the sample report below, Social is the second highest source of traffic. Perhaps specific universities had FAFSA awareness campaigns via social media and drove students to the site.
Knowing what drives the most traffic to your site (for example, the most effective social network) can help you know where to focus your attention and ad dollars in your next campaign. When we get into demographics, you can see that maybe the age group that is sharing the FAFSA information is a younger group, more inclined to use social media for communication.
Google Analytics traffic reports are available on the left side under Acquisition –> Channels
Google Analytics also offers mobile analytics capabilities. If you have a mobile app for one of the key user experiences/functions of the organization, you can easily track user adoption.
Under Acquisition –> New Users, the following report is available:
The report will show a count of:
• New Users (The number of first-time users during the selected date range.) as well overall new and returning users and the number of sessions for these users.
• A breakdown of new users by operating system (in the case above, there is an iOS app only, and if an Android version existed, it would show in this report)
• As well as New Users by App Version
2. Segment traffic by Demographics.
Now that we see that forms have been filled out, we want to know the age range of those who have opted to filling out the online form. Perhaps there is a difference between older parents vs. younger students in using online paperwork. In Google Analytics we can apply “Age” as Second Dimension and break out the traffic data by age and see the trend for adoption between the generations.
In a case like this, it makes sense that that the most popular demographic is 18-24 (since FAFSA is typically for college students).
Now that you know your most valuable marketing channel is social and mostly younger students are filling out online forms, you can tailor the messaging/designs of your campaign to the younger crowd, and focus your marketing spend on social networks.
Behavior reports in Google Analytics allow you to understand what users are doing once they have come to your website.
3. Identify engaging content.
Now that visitors are on the site, what are they doing? Downloading forms, how-to guides or videos?
Let’s look at the Teachers Loan Forgiveness Program, which is a program that encourages individuals to go into teaching by offering to forgive part of their student loan.
Say the University Career Center sends out an email to all students enrolled in the Teaching Credentials track about this particular program. In Google Analytics, you notice that there is a lot of traffic from that email. However, do you know what these visitors are interacting with on the site?
The benefit of these reports is not only can you see which pages have the most views or how much time they are spending on those pages, but you can also monitor “Event” interactions on the page, such as video “Play”, “Pause”, or “Watch to End” events (this does require custom code/event implementation). So if you’ve spent marketing dollars producing a video demonstrating how to apply for the program and want to know if it’s actually getting played or if they’re watching the video all the way through, you can see that here.
Google Analytics Events are available in Behavior –> Top Events –> Videos:
In this example report, 2,326 users have watched through the end! That’s about 40% of those who pressed play. Impressive! Seems like the video is engaging and getting the necessary information across, so it was a good investment. Maybe you’d want to invest in more instructional videos.
Note: for Mobile Apps, all user interactions within the app (buttons, clicks, navigation, etc.) can be tracked in Events.
4. Combine Demographics & Engagement to see who is doing what.
Are older users more likely to watch the video or younger users? By segmenting the engagement by demographics, you get deeper insights and can once again can narrow your efforts – tailor your messaging, wording, and visuals to the users you know are more likely to engage.
You can also see what demographic is lacking in engagement and maybe place an alternative focus on them. For example, if you find that only younger users are playing the video, you may want to have the instructions in text for older users who aren’t so inclined to play it.
While segmenting by age and gender, we can also throw social in the mix. How is this information shared across social networks? Perhaps the younger age bracket prefers sharing your page (by clicking on the “share” event you’ve created) on one social network, while an older age range prefers another. Again, knowing which age/gender comes from which social networks can help you tailor and target your paid ads and even organic postings.
Ultimately, this is the goal of your site or app. Traffic and even engagement have little value if your visitors aren’t converting. Conversions happens when users complete a task you want them to complete, which you can define and trigger in Google Analytics as a Conversion Goal. For example, this may include submitting and completing a form/application (such as FAFSA), downloading a pdf, even purchasing a product or making a payment/donation.
5. Find out if visitors are accomplishing site goals.
You’re a communication manager for a governmental agency in Dubai, UAE. You want to know how many people are leveraging the eServices applications on the site to acquire permits, doing business in the UAE or process online payments.
Let’s cover a common use case that this site can leverage. People traveling to Dubai typically want to know more about the entry visa process, what’s involved to enter the country, and better, apply for the entry visa online. One of the “goals” in Google Analytics can be set up to measure how many visitors go to your eServices section and apply for visa online. By setting up this “goal” in Google Analytics, you can now measure the conversion rate (i.e. the completion rate) of the site visitors who applied for an entry visa.
Just like any other good analyst or marketer, you heed the advice and set up this “goal” and you see that your online application completion rate is 2%. We now have numbers, let’s get some insights. You start to see a steady increase in this number, you go from 2% to 3% to %4.5. Great, what can this data tell us? The increase in completion rate, could be a good indicator of visitors’ adoption of this new eService (which means cost savings over the manual visa application). Or it could be an indicator of increased interest in visiting the country. There are other factors that could contribute to the fluctuation of the goal complete rate (such as seasonality, major business/sports events, etc..) but at least you now have a baseline that you can leverage in gaining additional insights.
6. Segment Conversions by Demographics to see who is accomplishing site goals.
Let’s pull an example from a relatively recent political event. Say you are in charge of communication in the new Ukraine government, and the country is undergoing drastic governmental changes. One of the government goals is to communicate directly with constituents. You intend on doing so by building up a large database of email addresses. You set up “email list subscription” as a Google Analytics Goal and track conversion by the various demographics segments.
What age/gender is subscribing to your newsletter? This could be a political indication of many things – it could indicate who is politically concerned or active, who is being politically neglected, or which group you might need to find other ways to communicate with.
Again, segment by demographics and you might find that majority of email subscribers are middle-aged men. As the Ukraine government, you now can tailor your email information to that demographic, but you also might want to figure out how to reach the other demographics, such as younger adults and women.
Bonus: Advanced Data Visualization Tip for Content-Rich Government Sites
All the reports we’ve shown in the post so far are from within the Google Analytics interface. They are easy to access and easy to share. For advanced users and those who are stitching data from different sources, leveraging a data visualization platform such as Tableau might be the way to go, so this tip is for you! With powerful visualization tools like this, you can quickly and easily tell a story that raw numbers just can’t.
For example, many government sites have a lot of informational pages. A common reporting request is to quickly trend all pageview data in a month-over-month format. Tableau can do just that! Once you pull in the data and organize it by content categories, you can easily see which content is popular compared to others, or which has more views and at what times.
In the sample report below, and for Category #2, notice how those pages have the most views consistently than all the other pages, especially in 2014 (The darker the green the more views you have). Thus Tableau makes it easy for to see how pages (or any metric) are doing with just a quick glance.
Keep an eye out for the next post on how to create Advanced Segments to drill down and find actionable insights from the various audiences we discussed in the post above!
Have other ideas, metrics or reports that work for your government site? Share and comment below.
Picture from Getty Images
No, this isn’t the new horror movie by M. Night Shaymalan, but there is a twist at the end!
A couple of weeks ago, Google Analytics made slight changes to their labels. They changed “Visits” into “Sessions” and “Unique Visitors” into “Users”. While intuitively this makes a lot of sense, many of our clients have been confused by the affect this has on the math and the metrics presented by GA, particularly the total visitors aren’t adding up to the total users.
New Visitors and Returning Visitors Don’t Add Up to Total Users
Let’s pretend you’re an analyst for the California DMV and you’ve been asked to find out how many people have renewed their vehicle registration online for a given time-period. Easy – you create an advanced segment to filter converted traffic (in this case, traffic that ended in registration renewal) and you look at the Sessions/Users reports to find out.
You have a total of 7875 users.
New Visitors + Returning Visitors = (7007 + 1316) = 8,323!
Which one is the correct answer of how many people signed up? First the long lines at the DMV were killing you, now the data discrepancy makes you want to poke your own eyes out.
(Note: often times sampling may cause mathematical errors, so if you’re a Google Analytics Premium subscriber, you can look at the unsampled data to triple-check and make sure it’s not being sampled.)
So, what the heck is the issue here?
New Labels, Old Definitions
Before we can figure out what’s happening, we need to understand the Google Analytics definition of each term.
A session is the period time a user is actively engaged with your website, app, etc. All usage data (Screen Views, Events, Ecommerce, etc.) is associated with a session. “Sessions” then represent the total number of Sessions within the date range.
Users that have had at least one session within the selected date range. If you think about it, this is a little easier to intuitively grasp than the difference between a “unique visitor” and a “visitor”.
The number of first-time users during the selected date range.
New (first-time) or Returning user.
An estimate of the percentage of first time visits. What this really is saying is “sessions that are of a new user”. This is the part that’s a bit confusing. If you’re a Returning Visitor coming for your second session, in plain english, this might be another “new” session, but in GA, it’s not. So by definition, returning users will not have new sessions.
Solving the Mystery: Returning Visitors and Double Counting
So to get the amount of DMV users that have renewed their registration online, looks like it’s between one of two things – adding New and Returning Visitors (different from “new and returning users”) or use the User total?
Looking at the Returning Visitors (and taking into account the date-range) is key here when making that decision and why the totals don’t match.
Users may be doubled as both New and Returning Visitors within a given date-range.
Meaning that if a New Visitor came during this time period and returned during this same time period, they’d be counted twice (within a given date-range, both as a New Visitor and a Returning Visitor.
Returning Visitors may also be “unique” within a given date-range.
What if visitor X came before the given date-range, but then later returned within the given date-range? How would they be counted? They would be counted as a Returning Visitor but that first visit would not be counted as a New Visitor within the specified date-range.
While sessions can increase indefinitely, a User can only be counted a maximum number of twice as a visitor.
What if visitor X returned 3 times within a date-range? They would be counted once as a New Visitors (if it was their first time), once as a Returning Visitor, but that 3rd visit, they already have been counted as a Returning Visitor, so while the sessions would increase, the Returning Visitor metric would NOT increment!
Calculating the New Visitors who were doubled as Returning Visitors within a date-range
To get the true number of visitors who were doubled within the date range, you’d need to separate the unique Users from the Visitors aggregate (New + Returning Visitors). Adding up the New and Returning Visitors will include:
- New Visitors
- New Visitors that may have doubled as Returning Visitors if they came back within the date-range
- Returning Visitors whose New Visits aren’t within the date range, and thus only counted once within Returning Visitors.
So the Visitors aggregate (New + Returning) is 7007 + 1316 = 8,323. Subtract the unique Users from that (7875) and you get 448. Again, since the Users are unique, you are basically getting rid of all Unique Visitors. The Returning Visitors with New Visits outside of the date range is actually a “Unique Visitor” respective to the date range, and since you are getting rid of all the Unique Visitors, whatever is left has to be the doubled visitors, which is 448.
Calculating the “Unique” Returning Visitors
Then to get the Returning Visitors that have New Visits outside of the date range, just take the Returning Visitors and remove the doubled visitors that we calculated above. So 1316 – 448 = 868. Those are “Unique Returning Visitors” if you will.
So, to the original question – in this particular case, how many individual users renewed their registrations online? Intuitively you may have thought, “Just add New and Returning Visitors”. As you can see now, those metrics may not add up the way you think it should. You’re better off going with the round number of users, and thus, the number of users who have converted (renewed their registration online) according to this report is 7875.
For more information on how users are calculated in Google Analytics, click here.
Our team is at the Google Analytics Summit (exclusive to Google Analytics Certified Partners and Google Analytics Premium customers!) learning about the exciting new initiatives in store for the product. Most of it is top secret, but here are the things we can share.
Google will be revamping their Google Analytics Ecommerce capabilities to be more inclusive of the entire customer experience, shoppers behaviors and conversion path (rather than it’s traditional focus, which was strictly on purchases and product information). They’ve announced a beta release of their upgrade.
This will include detailed metrics out-of-box on:
- Product detail views
- ‘Add to cart’ actions
- Internal campaign clicks
- The success of internal merchandising tools
- The checkout process
Flexible and Scalable Reporting (including Unsampled Custom Tables)
Google has upgraded to some general enhanced reporting features, namely Unified Channel Groupings, traffic is now classified in-line with your unique channel definitions, and expanded Dimension Widening (now known as Data Import), which enables users to import more types of their own data and stitch it into the system.
But what really has us giggling like little children is the unsampled Custom Tables, available for Google Analytics Premium users only. For really high traffic sites, GA Standard will sample your data, which sometimes makes it hard to calculate accurate metrics. While Google Analytics Premium gives you access to unsampled data, the only way to access it was to export it.
But now, using Custom Tables you can have tables in your custom reports with pure unsampled data, which you can now crank the data through the powerful slicing and dicing of the GA UI.
There are some limits – some features like the user metrics, Flow Visualization, Search Engine Optimization, Multi-Channel Funnels, and Attribution are not available, and it takes 2 days from creation of those tables for the data to appear, but it’s a step in the right direction.
For Google Analytics Premium users, you now have new integration with DoubleClick Campaign Manager and DoubleClick Bid Manager, so advertisers can get deep insights into their robust DoubleClick paid ad campaigns by leveraging power of Google’s premium analysis tool (as well as being able to combine this data with their other organic metrics).
Finally, again, for enterprise customers that manage many accounts, Google is giving acces to 4 new APIs:
- (1) Provisioning API to create new GA accounts (invite only)
- (2) The AdWords and (3) Filters API to manage configurations
- (4) Embed API to surface key reports and dashboards
Once again, a feature available only for enterprise customers using Google Analytics Premium. We happen to have a premium client on several domains and digital properties. They have a ton of verticals, several versions of each one, testing which has the best conversion, for example, 6 sites generating real-estate leads in different ways, 10 sites generating car leads, etc. You could even throw in some mobile apps.
Say they wanted to make an overall comparison on the performance of all their digital properties. Normally, they’d have to export then stitch everything together in an outside program.
Roll-Up Reporting is now built into Google Analytics premium – a single interface that aggregates all your site and app data into one place. A “master” Dashboard, Real-time, etc.
A huge benefit is truly holistic, universal analytics – a single view to really see your customers journey.
Most enhancements will be available immediately or within the coming weeks.
For more details, read the full Google Analytics blog announcement here.
For more details on Enterprise Roll-Up Reporting, click here.
At the very end of my first week on the job at E-Nor, I sat down with Feras to make sure we had covered all the steps in the on-boarding process for new consultants. With my head spinning from the barrage of new processes, clients, and projects, I was feeling just a little overwhelmed. Thinking about how much more I had to learn before traveling back to the Portland, Oregon office, Feras began describing what he expected from the expert consultants at E-Nor. As my confidence was already reeling from the week’s introductions to some entirely new concepts and to new depths of familiar ones, he explained that I didn’t have to know everything about everything.
T-Shaped: Depth meets Breadth
“I like to say that a good consultant is T-shaped,” said Feras. As any good analytical communicator would, he grabbed the marker from the tray on the whiteboard behind him. He drew a horizontal line and then a long vertical line extending below the first line’s midpoint.
Tapping the horizontal line, he said, “You should be familiar with all of the concepts that affect our business, but you should explore the area that most interests you to develop a level of expertise,” as he dragged the marker along the vertical line.
He went on to explain that the experts at E-Nor weren’t experts in all the same areas. Feras talked about the range and variety among the individuals on the team.
“Others are closer to reality and know every little in and every little out of almost every digital analytics tool known to mankind. And some are super creative, super right brained, and are very social and are able to apply their innovative ideas toward qualitative analysis, as well as all things site optimization and mobile usability. And then you get those of us who can do account management in their sleep and some who just love to coach and train on all things Google Analytics.
“And then some of us see the big picture clearly and develop optimization frameworks and analytics methodologies, and love to publish and speak at leading marketing conferences and can extract insights from Google Analytics Premium and BigQuery. But the point is, we are collectively very broad and individually very deep. Together, we provide a comprehensive level of service and consultation to our clients.”
Clearly, the results speak for themselves.
So now that I’ve been on the job for a few months, I have first-hand experience on what Feras was talking about. Each of these unique, but overlapping skillsets equals way more than the sum of their parts. It’s clear to me that if the letter “T” describes an expert, it also stands for Team.
Every now and then, we like to get “back to basics”. We still find established, experienced clients making simple mistakes that could easily be avoided and corrected using basic features already available in Google Analytics. One of them is properly using annotations – basically taking notes on different events (internal or external) that impact your site. These “sticky notes” might seem insignificant, but can often be a life-saver, providing insight as to why your data sometimes looks the way it does, especially anomalies or outliers.
Let’s talk about some strategies and best practices as to when and how to create valuable Google Analytics annotations.
What Are Annotations in Google Analytics
In early 2010, Google Analytics introduced annotations. Annotations offer a simple way to track notes in the Google Analytics reporting interface by date, so you can mark important events based on that may have impacted your data in otherwise seemingly inexplicable ways. In this way, it can explain reasons for jumps in the data to your entire team (if shared with everyone) that otherwise may be unclear.
To create annotations, simple go to any report and click the down arrow on the tab at the bottom.
Click “Create New Annotation”. Enter the date of the event and a small note about what happened. Choose if you’d like the note to be private or public.
Viola! Annotations are indicated by the tiny little talking bubbles at the bottom. To see the details, click the “down arrow tab” again for a list of annotations. The notes stay is available on any report in case your dissecting the data, see something weird, and need some insight into what happened that day!
The Benefits of Using Annotations
There is a spike in your data, a sharp increase, a drop, flat-line, etc., and you have no idea why. Wouldn’t it be nice to have an clear explanation or clue as to why any of this happened?
Imagine the following scenario.
The traffic for your company’s most valuable landing page died for 2 weeks. Someone’s paycheck is about to get cut!
You’re the marketing manager and you have a meeting with your CFO in 5 minutes. Sure, you could spend hours combing through emails, trying to figure out last week if your development team made an update to your site that tanked ecommerce. Luckily, you annotated exactly on that day that your developers switched to Google Tag Manager. You check with them, and they forgot to publish your new version of Universal Analytics code. You check the bank account, and sure enough, the money is still coming in, it’s just the data is missing. (Phew!)
Another example might be that an influencer shared your page to 1,000,000 followers, and for 2-3 days, your traffic has increased by thousands of visits. For something like that, there is no email paper trail that can lead you to the cause, and now, you’ve lost a potentially valuable partner that has a genuine interest in you that could help you blast your next campaign. It would have been best to “sticky note” or annotation right when it happened.
How to Use Annotations: 5 Tips on What to Annotate
1. Be explicit.
There’s nothing more frustrating than an incomplete clue to a burning mystery. “Blog Post shared”. What the hec does that mean? Who shared it? Which post? The worst part is I don’t understand my own note! If you’re notes are mysterious, you’re wasting your time creating it in the first place if no one’s going to understand it. While you only have a handful of characters (160), be as detailed as possible – it’s plenty of room to get specific points across.
2. Keep in mind who will be reading it in the future.
In the cases of shared annotations, you aren’t the only person who will be reading these notes. Your analysts, marketing team, etc., will be reading them and potentially using them for analysis and insights. For example, chances are if you use personal abbreviations, they’ll be interpreted in a way you didn’t intend. So when you wrote “ICBINB” to mean “internet consultant Brian implemented new banner” your colleagues will be wondering why you noted “I Can’t Believe It’s Not Butter”. Make sure your notes are understandable to any one reading it without context.
3. Record marketing campaigns, online and offline.
As mentioned, many things can affect your traffic, and you want to know what those things are. Obviously online campaigns probably will. If you release an email blast to 1000 subscribers, if even 10% click through, that’s 100 extra visits, so you’ll want to know what caused that when you look at your data a month later. But what about a TV ad? A radio ad? Flyers you passed out at the bus stop? That could increase traffic too, and you obviously want to know what offline campaigns worked the best for you. Log as much as you can.
4. Record any update or issue to the site/app.
When updating your website, you QA furiously to make sure nothing breaks – not SEO, not Analytics. Unfortunately, best laid plans don’t always come through. If you’re not looking at your data regularly, a change to your site that affects your tracking code may be discovered late. At this time, usually you’re in panic mode, so minimize your stress by being diligent noting site updates. Usually, these notes can give you direction into exactly what happened and exactly how to fix it.
5. Record any external event that may affect you traffic.
In March, you meet Tim Cook on the street and give him your card. Next thing you know, Apple tweets your site to millions of followers. You think it’s awesome. At the end of the year, you’re analyzing how some of your campaigns are doing and it looks like for some reason March traffic skyrocketed. You want to do that again! You drill down deeper, turns out one day spiked your data, but you can’t remember what happened that day! If you had annotated that you met Tim Cook and that he tweeted, you could filter that day out for a more accurate trend.
Hope that helps and gives you a new appreciate for such a basic but useful feature in GA. Have special uses for annotations? Leave a tip or trick in the comments!
To view the full press release, click here.
It’s our pleasure to announce that Bilal Saleh, our Principal Partner in the southeast, has accepted to join St. Leo University’s Advisory Council for the Department of Communication, Marketing and Multimedia and Management at the Donald R. Tapia School of Business at St. Leo University. He was invited to be part of the council to lend advice on vision-impacting issues as well as strategic objectives. We congratulate him and are very excited for future involvement in the planning and shaping of programs relevant to the industry.
Bilal Saleh has more than 20 years of experience in consulting, qualitative and quantitative market research, business development, sales, marketing and general management as a global executive. We believe he is well suited for this position and brings expertise that will guide through industry trends and growth.