I discovered six Google Analytics strategies that completely transformed my approach to using the platform. Up until recently, my Google Analytics usage was very basic. I would briefly browse around after logging in, leaving with only a hazy understanding of our traffic patterns. Essentially, I was barely scratching the surface of its potential.

We had an all-day intensive Google Analytics training recently, which introduced me to a plethora of functionalities I was unaware of and had never utilized. My primary use of Google Analytics before the training was to monitor daily and weekly blog traffic patterns. But, the capabilities I will discuss allow me to see:

• Comprehensive visitor demographic information and how the actions of specific user groups can be compared to “typical” visitors
• The alignment of our traffic with our objectives and the actual progression of visitors through our goal funnels
• Our conversion routes, including the (frequently complicated) path users take from their initial action to conversion
• Unusual traffic trends and the root causes of sudden changes
• Traffic pattern comparisons to prior time periods I’m excited to share these insights with you! Here are six essential Google Analytics tips you should familiarize yourself with immediately.

1. Leverage Audience Insights for Custom Visitor Segment Creation

You’re probably already classifying your visitors using custom segments based on demographic characteristics like age, gender, and location. However, if you’re not utilizing the data in the Audience reporting views to create your custom visitor segments, you’re overlooking a treasure trove of information regarding how certain users engage with your site. This feature was completely unknown to me until recently, making it my personal favorite Google Analytics tip. Begin by navigating to the Interests Overview within the Audience reporting section (Audience > Interests > Overview). This will display a high-level summary of the other three Interests reports: Affinity Categories, In-Market Segments, and Other Categories, as depicted below.

This data reveals that nearly 8% of visitors across all sessions are classified as “technophiles” – those with a keen interest in technology. We can also see that almost 5% of visitors in the In-Market Segment are either employed in or interested in Financial/Investment Services. We’re starting to develop a clearer picture of our typical visitor, but we’ll delve deeper before defining our custom segment. Next, we’ll examine Age and Gender data by selecting these reports from the Demographics section of the Audience reports (Audience > Demographics):

The majority of our visitors, according to this data, are between the ages of 25 and 34, and the graph below demonstrates that our site receives significantly more male visitors than female visitors (unsurprising, given the gender disparity in search):

Thus, we’ve discovered through our analysis that a significant portion of our visitors are:

• Male
• Aged 25-34
• Highly interested in technology
• Employed in or interested in financial or investment services

Creating Custom Segments in Google Analytics

With this data in hand, we can construct a custom visitor segment that can be tracked in relation to goals (more on this later). To do so, return to Audience reporting and click the downward-facing chevron to the left of “All Sessions”:

We’ll then construct our custom segment based on the aforementioned demographic data. For this illustration, we’ll also incorporate information from the Other Category report within Interests Overview, which in our case was Arts & Entertainment/TV & Video/Online Video:

All that remains is to name and save your custom segment. Alternatively, you can test this advanced custom segment to estimate the number of visitors who fit these criteria. This segment can then be compared to other visitor traffic to better comprehend how different visitor types behave in comparison to one another, rather than relying on a general overview of all pageviews or sessions. Keep in mind that depending on your sample size, selected date range, and the number of advanced segments already in use, this process may take some time (or even fail), necessitating adjustments before successfully saving your custom segment. BONUS GOOGLE ANALYTICS TIP: After creating your custom segment, you can refine it further by filtering by the date of these visitors’ first session within a specific date range. This recently introduced feature enables you to refine your tracking of specific visitors, proving incredibly valuable for remarketing initiatives.

2. Assigning Monetary Value to Goals

The second Google Analytics tip focuses on goals. It’s critical to establish goals within Google Analytics. Otherwise, you’re essentially analyzing relatively meaningless indicators like pageviews and time spent on site. However, you shouldn’t stop at simply establishing goals; you should also give them a monetary value. Let’s examine a sample Goal Flow report from nexus-security’s Google Analytics account.

It’s fairly straightforward, as you can see. Google is the primary source of traffic for this specific objective, followed by direct traffic. The red sections to the right of the second and third stages of the goal funnel steps are referred to as “funnel exits” – visitors who did not complete the desired action at a specific step, which in this case is signing up for a free trial – if you’re unfamiliar with Goal Flow reports. So, why assign a monetary value to your Goal Flow? Because you can’t determine how much money you’re losing on each lost lead that exits the funnel until you assign a monetary value to your goal flow. Have you ever noticed the “Page Value” statistic on your traffic scorecard? This is where you’ll find the financial worth of a page in relation to its goal value and its position in your conversion paths. If you haven’t assigned a value to your goals, these values will be zero.

Assume you give a goal a value of $25. It’s crucial to remember that the values in this column won’t always be $25 or $0 – the page’s involvement in assisted conversions is also factored into the Page Value column, so these values will fluctuate depending on the page and its function in one or more conversion paths.

Assigning Values to Goals in Google Analytics

To assign a value to a goal, go to the Admin section of Google Analytics (accessible from the top menu) and select “Goals”:

A list of your objectives will now appear. When you click on one, an interface will appear where you can specify the monetary value you want to assign to the goal.

The exact value of a goal will vary depending on a number of factors, but it’s generally best to underestimate the value of a goal. Stick to a conservative estimate until you have a better understanding of the financial worth of each conversion. You can begin to see (in actual financial terms) how much money you could be losing with your current goal flow by estimating the value of a lead and applying this value to each goal. This, in turn, could encourage you to consider whether your goal funnel is properly optimized. Should you include more steps? Is it necessary to improve navigation in order for users to easily revisit previous funnel sections? Is it necessary to eliminate something basic that is impeding your conversion rate? These are all questions that could come up as a result of assigning a dollar value to each goal.

3. Analyzing Your Top Conversion Paths

Unfortunately, website visitors do not always act in the way you want them to. Wouldn’t it be fantastic if potential customers saw your ads, visited your website, and made a purchase – all in one sitting? Unfortunately, this is rarely the case, which is why understanding your conversion paths is so critical – especially in today’s advertising environment, where people rarely complete a purchase on a single device, let alone in a single session.

Image © Peter Andrew Examining your top conversion paths in Google Analytics not only reveals how your visitors are actually converting (as opposed to how you believe they are converting), but it also provides intriguing insights into user behavior – and the often-convoluted path many visitors take from first interaction to final conversion.

Examining Conversion Paths in Google Analytics

Navigate to the Top Conversion Paths section of the Conversions reports to examine these visitor journeys (Conversions > Multi-Channel Funnels > Top Conversion Paths). The top ten conversion paths are shown here by default, with the option to increase the number of rows displayed.

The most effective conversion paths in this example are fairly standard (two direct visits, an organic search leading to a display ad, three direct visits, and so on), but some are a little more unusual. Two display advertisements? Is it possible to conduct a direct search that leads to a display ad? Two organic searches? You can also display the top conversion paths by MCF Channel Grouping Path and compare these results to the Keyword (Or Source/Medium) Path, which can provide more information about how each of your channels is performing:

Damn you, (not provided)!

4. Setting Up Intelligence Events

While it is critical to monitor your website’s performance on a regular basis, it is unlikely that you will see significant changes from day to day. But what about those strange anomalies that make you do a double-take? What about those massive traffic spikes (or drops) that defy explanation? This is where Intelligence Events come into play. Intelligence Events is a Google Analytics feature that allows you to define custom parameters for tracking unusual site activity and sending alerts to designated account managers. For example, a 200% increase in traffic in a single day would be deemed unusual, and Google Analytics would log and alert you to the data associated with this event. You might believe that simply monitoring your regular metrics would alert you to such a significant increase in traffic to your website, but this is not always the case. Let’s take a look at an example we recently encountered.

We received an Intelligence Event alert on Saturday, April 19th, notifying us of a 216% increase in traffic to a specific page. The alert also included information about the origin of the majority of the traffic (in this case, California) as well as the associated metric (one of our conversion goals). A spike of this magnitude should be obvious, right? We, too, assumed this was the case. We were mistaken, however.

As you can see in the image above, overall traffic for that day appeared to be low – certainly not unusual for a Saturday, when our traffic tends to be lower than weekdays. If we had simply glanced at our Pageviews report, we would have been completely unaware that we received over 200% more traffic to that page, and this spike would have gone completely unnoticed.

Configuring Custom Intelligence Event Notifications in Google Analytics

By default, Google Analytics will notify you of unusual site activity, such as the anomaly described above. However, don’t rely on Google to notify you when something significant occurs. Instead, create your own Intelligence Events. To begin, open the Intelligence Events reporting section and select the “Custom Alerts” tab from the menu on the right. Then, select “Manage Custom Alerts.”

After that, select “+ New Alert” from the red button. This will bring up the interface where you’ll create your custom Intelligence Events.

You’ll specify a set of parameters here that will trigger custom Intelligence Events notifications. As you can see, you can customize the views to which the alert conditions will apply, the time period, and how notifications are sent – either by email (to one or more specified addresses) or by email and SMS text alerts (note that SMS alerts are only available to Google Analytics users with United States-based cell numbers). Next, you must specify the conditions that must be met in order for the alert to be triggered. Begin by configuring the traffic conditions and site usage parameters (images condensed for illustrative purposes):

Then, from the drop-down menu to the right, choose the general conditions that must be met:

Finally, give your custom alert a name, save it, and you’re done!

5. Comparing Historical Traffic Trends

Many Google Analytics users are only concerned with current traffic patterns, but identifying patterns based on past traffic can provide useful insights into how traffic may change over time. One of the best ways to examine this data is to use the Compare to Previous Period tool in the date range dialog box:

After you’ve specified the required date range (and the previous period to compare it to), you can use this filter to see how your traffic compares from one time period to the next – in this case, from April 12 to May 12, and March 12 to April 11 (the previous period):

Have you noticed how the valleys of one plotted line (April 12-May 12 in blue) correspond fairly closely to the peaks of the second plotted line (March 12-April 11 in orange), and vice versa? This is due to discrepancies in the days of the week specified when comparing recent traffic data to a previous date range.

Defining Custom Date Ranges in Google Analytics

For example, if you applied this filter to a weekly view, you might assume that a Monday-Sunday week view would perfectly match the previous period – but it does not. Instead of corresponding days from the previous week, Google Analytics defaults to the number of days in the specified period. Let’s see how this works in practice:

The first date range is Monday, May 5 to Friday, May 9. This covers the entire five-day workweek for the given time period. However, when we select “Compare to Previous Period,” Google Analytics retrieves data from the five-day period preceding the first date range, rather than the previous five-day work week, implying that the data included in the graph is actually comparing completely different days of the week, resulting in the (misleading) graph below:

However, if we specify a custom date range (where the days of the week match exactly), we will notice that the two graphs are nearly identical. Please keep in mind that in order to accomplish this, you will need to manually enter the desired date range in the appropriate fields rather than clicking on a start day and allowing Analytics to fill in the blanks:

As you can see, there is still some minor variation in traffic – but nothing out of the ordinary, and certainly nothing like the significant variance we saw in the misleading graph above.

6. Enhancing Your Reports with Annotations

The final (but certainly not least) Google Analytics tip is about good housekeeping. Perhaps you are not the only one in charge of monitoring your Google Analytics account. If this is the case, you’ll need a method for tracking why and when things occurred. Was a media mention responsible for a massive increase in traffic? Did a downturn coincide with a less-than-successful email marketing campaign? Annotations can help you remember everything you need to know in Analytics. Annotations are simple notes that can be added to an Analytics reporting graph to explain traffic increases or decreases, notify other account managers of promotional campaigns that launched on a specific day, and pretty much anything else you want to keep track of directly within Analytics.

Speech bubble icons represent annotations along the bottom of an Analytics graph. Notice how many of the peaks in our Pageviews graph in the image above have accompanying annotations.

Adding Annotations in Google Analytics

To read annotations, simply click the downward arrow tab icon directly beneath the graph. You’ll see a list of all annotations made during the specified time period, as well as information about who created the annotation and their email address. Annotations can be set to “Public” or “Private,” giving you control over who sees what. To make a new annotation, simply click “Create new annotation” to the right of the existing annotation authors’ email addresses:

Mastering Your Traffic

Whew! That concludes our list of the top six Google Analytics tips. I highly advise utilizing these strategies to leverage your reports for deeper insights into your traffic, conversion funnel, and visitor behavior on your site.