Bounce Rate vs Avg. Time on Page – The true meaning

It has become a mantra that a good user experience signal is a low bounce rate and a high avg. time on page.

A user who is enjoying the site won’t be abandoning the page but spend quite a good amount on it. Ergo: low bounce, high time on site.

But…is this always the case?

In my opinion, this is not (always) the case. And I’ll explain why.

Pages are born different. Some pages are more important than others, and different page categories have different scopes. Blogs, videos, products, checkout, log in…they have designed with a different goal in mind.

Bounce Rate vs Avg. Time on Page – What’s their value telling us?

The homepage

Let’s consider a homepage. Would we consider a homepage with high time on site successful? Probably not as its main purpose is to encourage visitors to browse and explore the site. Conversely, would we consider a blog page successful a low time on page? Most likely not, as a blog main purpose is to drive users to consume the content (from texts to images and videos).

So, how do we measure bounce rate and average time on page to establish successful marketing? We measure those metrics based on the page main purpose. We expect pages that are more like gate-keepers -such as the homepage, the category page, the login page – to have a low bounce rate, but also a low average time.

Blog and informative pages

Blog and informational pages – including videos and even product pages- are expected to have a high bounce rate but also a high avg. time on page. Users might read the blog, get the information they are after and then leave. However, I would also expect these pages to have a high percentage of returning users and work well as landing pages.

Product pages

Product pages are a bit tricker. Before making a purchase, a user might need to come back to the product several times before committing. In an initial discovery phase, users might come back several times. In this case, I would expect a high bounce rate and a low avg. time on page. During the decision process, users might spend more time on the product page, looking for more details regarding the product.

In this instance, I would expect a high bounce rate but also a high avg. time on site. However, users might decide to explore more pages in case the product is linked to additional resources (i.e. a tutorial). In this scenario, the bounce rate will be low.

Finally, at the purchasing phase, users will spend little time on the product page and go directly to the check-out page. In this instance, I would expect both metrics to be low.

Not all pages are expected to score the same bounce rate and avg. time on page values. Also, some pages must be scoring poorly on either or both values to deliver a successful marketing effort.

But how do we define High & Low?

Now, the real trick is to establish what constitutes a high and low value. The easiest solution would be to look at benchmarking in Google analytics.

In summary…

Both bounce rate and avg. time on page values is an indication of marketing success depending on the page main purpose. If in doubt, we expect a high bounce rate and:

  1. Low time on page for new users or occasional visitors
  2. High time on page for returning users and for informational pages

Or, a low bounce rate and:

  1. Low time on page for customers and for gatekeeping pages such as the homepage and the category page
  2. High time on site for loyal customers

For any questions regarding this blog, feel free to contact me:

How to add Campaign Cost in Google Analytics – Step by step guide

  1. Login to your Google Analytics account
  2. Open the Administration pageMaster View Admin Page
  3. In Property, click on Dd Data Import
  4. Click on CREATEGA - Data Import Create
  5. Select in SUMMARY DATA IMPORT Cost Data. Click Continue.GA - Summary Data Import
  6. Name your campaignGA - Name your campaign
  7. Click the Enabled Views in which your DataSet will be available. Click Continue.GA - Enable Views
  8. Select Cost (ga:adCost) & Campaign (ga:campaign) as minimum required parameters
  9. Click SAVE
  10. Click on Get schemaGA - Get Schema Data Import
  11. Fill in the Excel File with your data – Keep in mind that Google Analytics is case sensitive and therefore “Campaign” is different from “campaign”.
  12. Click UPLOAD FILE in Google Analytics
  13. Navigate to Conversions > Attribution > Model comparison tool – You can now track Profit

Who else wants to set up Google UTM tags for Pardot tracking?

As a digital analyst who knows the importance of efficiently recording and reporting marketing activities, there are moments where you feel overwhelmed.

You know that tracking is at the core of every marketing strategy (Avinash Kaushik anyone?), but at the same time, you are often full of doubts. Does this product update need a brand new campaign? Does this Facebook update belongs to the Social Media Campaign or the Product Launch Campaign? Possibilities are endless, your patience…a little less.

The frustration that I just described can become even more unbearable when results are expected to happen fast. Perhaps, when you joined a new company and want to impress your senior manager or when you want to pitch a new client. Or when you realized your predecessor never bothered tracking anything or that their tracking strategy took inspiration from the Memento plot!

Unfortunately, there is no choice, but taking a deep breath and start putting reason into the digital madness.

Luckily for you, I have already slain the dragon, and I’m here to show you how you can do the same. In few easily repeatable steps, you’ll always be able to track any campaign and effectively report your results to any client, manager or stakeholder.

Tracking and reporting will never be the same again.

Step 1: Set up your campaign structure

Independently from the business, you will run a certain number of marketing campaigns throughout the year. Those might include:

  • Product launch [to introduce a new product to the market]
  • Newsletter [to communicate to your clients]
  • Seasonal promotion [offers and discounts]
  • Product promotion [to promote a product that is not selling]
  • Events and workshops

I would recommend having a brainstorm at the beginning of each financial year, to determine how many types of campaigns the team will be running. To come up with ideas, I would suggest to include questions such as:

  • Will we be running discount & promotions?
  • Will we be launching new products?
  • Will we be attending social events?
  • Will we be running affiliate programs?

Continue reading Who else wants to set up Google UTM tags for Pardot tracking?

Track your social media efforts in Google analytics…today!

We all know the power of social media for driving well-targeted traffic to website. Social channels are great platforms for connecting with niche-related industries, generating brand awareness, finding new leads and learning more about potential customers.

Possibilities are limited only by our imagination.

As we also know, no digital marketing strategy would be complete without a tracking system in place. The number of clicks, likes and re-tweets are a good indication of the success of digital marketing efforts, but not enough for understanding how much they contribute in generating qualified traffic to our site.

What we want is to be able to calculate how many leads, conversions and eventually sales are generated by social media campaigns. What we want is to be able to calculate social media ROI.

To do this, Google Analytics comes to our rescue (surprised?). Google Analytics provides information on the role of social channels and specific platforms in referring users to a website’s traffic.

Let’s dig deeper…

Acquisition > Social > Overview: The social value

Social media menu google analytics

The social media menu provides information regarding the role of social channels in referring users to the website. By default, the Social Overview report shows total conversions and conversion value, that is the sum of all ecommerce and goal metrics.

These values are displayed in the social value graph and the numeric report (image below). Both reports compare total goal completions and ecommerce monetary value to those generated by social media.

Specifically, Google Analytics distinguishes two types of social conversions:

Last Interaction social conversion = people that converted in the same session that has been generated by the social referral.

Contributed social conversions = people that returned from a social referral and convert during a following session.

Based on the example below, 5.1% of all traffic came from a social referral [calculated as (785/15,381)x100]. In terms of conversions, 37% of all visitors converted [calculated as (5,742/15,381)x100], 4.3% of which was coming from social media marketing [calculated as ((191+59)/5,742)x100].

The effect of social media marketing might seem pretty low (4.3% on the total number of conversions); however, if calculated based on the number of visits generated by social media  (785), the percentage of conversions becomes 31%, in line with the site’s average.

Image result for social graph google analytics
Source: Kissmetrics

Acquisition > Social > Goal Overview

As stated in the previous paragraph, the social media menu can focus either on goals completions or ecommerce  conversions. When focusing on goal completions, a better understanding on the role played by social media marketing comes when each goal is displayed individually. This is because the impact of social referral might vary significantly among goals;  to give an example, social media marketing might work well to bring people to webpages such as photo galleries, blogs or vlogs, but not in driving users ready to purchase at the first visit.

To display single goals:

  1. Click on Conversions drop-down menu (top-left)
  2. Leave only the goal of interest checked

As result, the social value graph and the numeric report show only the conversions -total or social- associated to the goal of interest. Based on this narrower focus, the percentage of social media referral that contributed to goal completion can be calculated as shown in the above example:

  • First, calculate the percentage of visits that converted:
    • Sessions / Conversions = Goal conversion rate
  • Then, calculate the percentage of social sessions that converted:
    • Sessions via social referral / (assisted+last) social conversions = Goal social conversion rate

If the social marketing is performing well in driving qualified traffic, it is expected that the social conversion rate would be similar to the total conversion rate. To give you an example, if the goal conversion rate was around 10%, we would expect the goal social conversion rate to be in the range of 8-12%.

The same can be applied to quantify ecommerce conversions:

  • Total conversions/Total sales = Total ecommerce rate
  • Social conversions/Social sales = Social ecommerce rate

Acquisition > Social > Network Referrals

The Acquisition > Social > Network Referrals menu shows how much each social media channel contributed to the number of all sessions. The line charts allow to compare the number of sessions generated by social referral to the number of total sessions. As the two graphs can also be displayed in different scales, comparing the impact of social referral to generating sessions can be quite tricky.

Image result for social network referral charts

The table at the bottom is much more useful as it shows traffic generated by single social channels. In addition to sessions, the table can display quantitative data such as:

  1. Pageviews
  2. Average session duration
  3. Pages/Sessions

From each channel, it is possible to extract qualitative data such as:

  1. Types of pages visited
  2. Types of traffic

Acquisition > Social > Conversions

The Acquisition > Social > Conversions report shows the monetary value associated to social network referrals. Compared to Acquisition > Social > Goal Overview, the social conversion report shows the monetary value that resulted from conversions generated by every single social channel.

Conversion menu of Google Analytics

As before, the default setting shows all the social conversions. The best approach is to either focus on ecommerce values or on specific goals by selecting a specific conversion from the Explorer tab. The new graph will display the total number of conversions or the monetary value that all social channels generated. Beneath the new graph each social channel displays the number of conversions or monetary value that generated individually.

To better understand the number of conversions that each channel generated, it is necessary to combine the values of the Acquisition > Social > Conversions with those of the Acquisition > Social > Overview.

The percentage of conversions that each channel generates is calculated dividing the number of conversions from the Conversions menu with the number of sessions from the Overview menu. In short, we divide the number of conversions by the number of sessions (Conversions /Sessions) for each channel. The first value is found in the conversion menu, the second one in the overview menu.

However the story does not end here. It is important not only to understand how many conversions each channel generates but also how much monetary value each channel brings as fewer conversions might not mean a lower monetary value.

Therefore, in addition to the percentage of conversions, it needs to be calculated:

  • How much monetary value each session generates
  • How much monetary value each conversion brings

The first value is calculated by dividing the conversion value by the number of sessions for each channel. In short:

  • Average Conversion $ / Session
  • Average $ / Conversion

The last insight comes from looking into Assisted Versus Last interaction. The table shows how many users purchased on the first visit, that is when they are referred to a social media channel, or on a following visit.

Conclusion

The social media menu is a great Google Analytics tool, extremely useful to better understand social media marketing. Besides making it easier to understand how each social channel works to bring users to your site, the social media menu offers that insight that helps you generate more social leads and conversions.

However, the points covered here are just an introduction; ongoing analysis into the social media data will help you uncover the power of social media behind marketing and what resonates with your social users. By looking more into social media data in Google Analytics, you can make your content marketing more potent and generate more sales.

Google Analytics Acquisition menu: How to track your campaign

Sale Offer
Source: Freepik

You are running a digital business and you decide it is time to run an offer, a special sale to increase sales, brand awareness or get rid of old stock.

Independently from your business goal, every time you promote a special offer, a discount or any other form of marketing you want to be able to track your efforts: whatever it is the promotion and the medium you are using (social media, email, blog post), you are sending your visitors or potential customers to a specific -landing- page.

In addition, it might be that you are using multiple sources for delivering your promotion. If that is the case, you also want to determine which one is the most successful in driving people to conversion so that you can increase ROI and plan future strategies effectively.

As always, Google Analytics comes in our aid.

Why you should add a tag to your campaign links

In Google Analytics, if you do not add a tag to your campaign, GA refers to campaign traffic as “Direct Referral” (the same category in which are listed users that type the page URL directly into a browser).This means that you won’t be able to determine how much your campaign generated in terms of revenue. Conversely, by adding a tag, GA can more precisely track how a user came to the site and therefore determine how successful a campaign is to generate traffic.

How to generate a link tag manually

Every time you run a campaign, you send your visitors to a specific landing page. This landing page is a link advertised via email, social media or blog post. Generally, it would look something like this:

<a href=http://www.yourdomain.com/landing-page.html>Click here</a>

In order to generate a tag, you need three parameters:

  1. utm_source (the marketing vehicle, such as Facebook, newsletter, guest blog post)
  2. utm_medium (the digital medium, such as social media or email)
  3. utm_campaign (your campaign name)

A real example would look something like this:

  1. utm_source = Facebook
  2. utm_medium = Social Media
  3. utm_campaign = Summer Sale

This example would turn your landing page link into this link:

<a href=http://www.yourdomain.com/landing-page.html?utm_source=

facebook&utm_medium=social_media&utm_campaign=summer_sale>Click here</a>

How to add a tag using GA developers help

Luckily for GA, you do not need to generate a link tag manually, as GA provides a convenient software that allow you to generate a code containing all the required information. You can easily create a link tag for your campaign at URL builder, Analytic help (https://support.google.com/analytics/answer/1033867?hl=en).

Track your campaigns

In the Acquisition > Campaign > All Campaigns, you will find how much the campaigns contributed to the overall traffic in the specific time frame (You can change it by selecting dates from the right-hand side top corner).

Google Analytics Campaign Menu
Google Analytics Campaign Menu

Below the Explorer Summary graph, GA lists all the running campaigns for the specific time frame and how much they contributed individually to Acquisition, Behavior and Conversion. Next to the Summary  menu,  you can switch to Site Usage and E-commerce data (if you have generated any Goals, they will be listed as well). By selecting any of these options, you should be able to answer questions such as:

  1. Which one was the most successful campaign?
  2. How many new users were captured by this campaign?
  3. Was the site engagement better? Lower bounce rate?
  4. Was the revenue increased by the campaign?

In the Site Usage, you discover more about user engagement such as number of pages viewed or bounce rate, while in the E-commerce menu, more about the revenue that the campaign contributed to.

As we stated at the beginning, you also want to know which aspect of the campaign contributed the most when you are using different media and sources to promote your campaign. To do that, you need to go back to the Summary page and click on one specific campaign. If all your sources possess the same tracking code, they should all appear under the same campaign. If that is the case, social media, email marketing, blogs and any assisting pages (those that drive to the conversion page) should all appear when you click on a specific campaign from the Summary menu. Finally, to discover more about each single source, you can switch to Site Usage and E-commerce menu.

Follow up on Campaigns

Let’s assume that people that came from social media pages, spent more time on your site but converted less, while people that came from the blog pages converted more but where less engage. If that was the case, you could follow up by using social media to nurture your leads and/or turn our first visitors into leads by creating engaging content. Conversely, people that come from your blog where readier to convert and showed a higher ROI in the E-commerce menu. If that was the case you can start by sending people from your social media to your blog as it seems that people that regularly visit the blog convert more often; for instance, Flow Charts could help you in setting up a follow-up strategy based on the data you collected.

Conclusions

In conclusion, tracking your campaign efforts is fundamental in understanding which sources/medium works the best to deliver ROI and how the visitors behave after reaching the landing page. All the collected information will also be vital to design future campaigns and follow ups.

Google Analytics: The hidden power of goals and custom segments

As mentioned in previous posts, tracking your SEO and marketing efforts is fundamental to understand if your efforts (aka, money and time) are delivering the expected ROI. What you do not want is to spend hundreds of hours on implementing a strategy that will deliver poorly. If that was the case, you would like to discover at the earliest stage.

Google Analytics offers several options to track how well your efforts  are delivering to ROI; for instance, the conversion menu allow to set up specific goals that people need to accomplish to deliver ROI, while segment creation is a powerful tools to understand user behavior at a deeper level and therefore how it can be addressed to make those user convert.

Today, I will show you how to create a segment based on conversions.

At this point you might be asking the reasons why you should generate a segment based on specific goals you have already implemented on your site. Would goal A not report enough information already? The answer is yes and no.

Why you need a custom segment

Let’s assume you want to track people that visited pages related to a specific offer (offer X) or a specific topic (topic A); for instance, you are offering free delivery for the next 48h (offer X) or you are writing a guide on how to save money on energy bills (topic A).

To begin with, you create a new goal in GA called “Visited Offer X Page” OR “Read Topic A Pages”. In addition, you want to know if people changed their behavior after visiting these pages; in specific if more people took advantage of that offer after visiting the page describing the 48h free delivery offer or spent more time on your site after reading your guide on how to save money on energy bills.

To do this, you need to create a custom segment to determine if goal conversion influences future behavior such as taking advantage of an offer (Offer X) or spending more time on site after reading specific content (Topic A).

How to create a custom segment in Google Analytics

A custom segment can easily be created using goal metrics:

  1. Go to the Acquisition Overview and click on + Add Segment
  2. Select +New Segment
  3. Give it a name such as “People that did not visit OfferX/TopicA page”
  4. Click on (Advanced) Conditions option
  5. The selection of this option brings up the Conditions page
  6. Pulling-down the Ad Content you find the Goal Conversions option (almost at the end)
  7. Make sure the Conditions are set to Filters > Sessions > Include
  8. By opening this option you can view all the goals you created
  9. Select your goal (Offer X or TopicA)
  10. Set 1 to Per Session option
  11. Click Save
Add a second segment as control:
  1. Go to the Acquisition Overview and click on + Add Segment
  2. Select +New Segment
  3. Give it a name such as “People that did not visit OfferX/TopicA page”
  4. Click on (Advanced) Conditions option
  5. The selection of this option brings up the Conditions page
  6. Pulling-down the Ad Content you find the Goal Conversions option (almost at the end)
  7. Make sure the Conditions are set to Filters > Sessions > EXCLUDE!
  8. By opening this option you can view all the goals you created
  9. Select your goal (Offer X or TopicA)
  10. Set 1 to Per Session option
  11. Click Save

How to check your tracking

Now that everything is set in place, you can start tracking your custom segments: Do people that visited Offer X or Topic A page converted more that people that did not visit those pages?

First you can check the Audience > Overview page to determine the percentage of people that visited the pages you are interested in (Offer X or Topic A page). In the page summery those people are listed under the custom segments you have just generated.

After checking that at least some users visited the conversion pages, you can open Behavior > Site Content > All Pages to determine if the behavior of the custom segment that visited the selected pages changed compare to the behavior of the control segment (people that did not visited the conversion pages).

Finally, check the Conversions > Ecommerce > Overview to determine if more users purchased your products because they visited the 48h free delivery offer page or read the guide on how to save money on energy bills. Based on the results you can determine if your conversion pages are helping people to purchase or not.

Google Analytics: an easy lesson on how to track your downloads

If you are like me, a blog writer, web developer and marketing analyst you know how important is Google Analytics to understand your business.

However, if you have spent more than a little time on GA you know how frustrating is to dig deeper into metrics and dimensions reported values. As SEO experts or well-established marketeers we might end up wondering if the bounce rate is too high, how the conversion rate could be improved or what percentage of business the organic traffic is bringing to the business.

Why tracking downloads?

Today I want to focus on how tracking downloads could offer a better view on how the visitors are interacting with our site. If we assume that people visiting our site are downloading mostly a PDF on a specific topic (let’s call it topic A), we can assume that most of our visitors are interested in topic A (and not in topic B, whose PDF gets rarely downloaded). Therefore, we can make decisions regarding:

  1. The type of content we should be producing to keep users coming back
  2. The type of email marketing campaign we should be focusing on
  3. The pages we could be using to drive users along the funnel that leads to conversion

Tracking downloads might also help solving a problem regarding single page visits. As you might know, Google Analytics cannot track how much time a user spent on your last page as it calculates the session duration as the exit page timestamp – entry page timestamp. However, if they concise, it cannot calculate the time the user spent on a single page and therefore GA sets it on zero.

This could be particularly frustrating as those page are calculated as having a high bounce rate even if a user spent even a long time reading our content! So, how can we know if a page with a high bounce rate is effectively a great page or not? The solution is asking the user to do something, such as:

  1. Sharing the page on social media
  2. Clicking a Thumb up button
  3. Visit another page
  4. Download a file!

To understand a little bit more how GA metrics values could be misleading, please read the next paragraph.

Engagement Metrics: Problems with Google Analytics Reports

In addition to more traffic, a website owner wants people to visit more pages and spend on average more time on a single page as they lead to an increase in engagement, conversion and (potentially) sales. To measure changes over time we might refers to GA metrics such as:

  1. Time spent on site
  2. Number of pages viewed
  3. Lower bounce rate

In Google Analytics Time on Page and Session Duration are quite often misunderstood metrics as Google can’t measure the time a user spent looking at the last page as Google uses the time of the next page view to determine time you spent looking at the current page. Therefore, if the Time on Page is unknown, it gets recorded as zero.

This means that for each exit page, the Time on Page is zero. Google takes into account this flaw when calculating the Avg Time on page:

Avg Time on Page = Time on Page / ( Pageviews - Exits)

However, only if a page does not have a high exit rate (% Exits), then the Avg Time on Page is a pretty good reflection of the real average. This means that the Avg time on Page could be grossly underestimated. Avg Time on Page is a good metrics only if exit rate is low. This metric is particularly frustrating for bloggers as visitors tend to read an article and then leave without visiting a second page.

The Session Duration metric cannot ignore the effect of exit pages: every session has an exit page, and if there aren’t many pages in the visit, the loss of that last page timing can have a massive impact on the total: in the “Bounce” case, the Sessions count is 1 but the Session Duration is 0!

Avg Session Duration = Session Duration / Sessions

The Avg Session Duration as a key performance indicator is not recommended as fluctuations in the number of pages viewed per session, the number of bounces, and the number of sessions can all influence the metric.

In summary: the Avg Time on Page calculation removes the effect of Bounces (Exits), but the Avg Session Duration calculation includes the Session count for those Bounces which reduces the average.

Track Events and Downloads: more accurate GA metrics

A solution -as mentioned before- is to ask users to perform a task such as downloading a file. This means that every user that downloads a file is associated to a session whose duration is now calculated based on the time the user performed the download. In conclusion, an interactive type of page could help to better calculate how much time users are spending on specific pages as GA is able to track downloads in a similar manner to pageviews.

How to track downloads: JavaScript tracking code

First, you need to locate your downloads in a well defined directory; something that represents what the folders contain so that you can easily find their reference in GA; something like app/subdirectory/folder_download_name/filename.pdf. Second, to find out if these folders have been visited, go to Behavior> Site Content > Content drilldown. From here you can learn:

  1. Which PDF was downloaded the most
  2. Which pages the users visited after the download

Third, in order to allow GA to track downloads, you need to add this tracking code to the <head>, inside the section of the HTML pages that contain the downloadable files:

function download(file)

{

ga('send', 'pageview', file);

alert("Thank you for your download.");

(window.location="http://www.yourdomain.com/subdirectory/filename.pdf"+ file);

}

Now that you tracking code is in place, you can finally start tracking your downloads.

Track your downloads via a text link

In case you are using a text (“Click Here”) to allow people to download a file, you need to make a change to your text to make it trackable via GA:

  • FROM <a href=”subdirectoty/filename.pdf”>Click here to download file </a>
  • TO <a href=”javacsript:download(‘/subdirectory/filename.pdf)”>Click here</a>to download more information.

And that’s it! Happy tracking!

Tracking your downloads via an image link

Source: CodeCanyon

At times, you might prefer to use an image (a button, a photo, a PDF vector) instead of a generic text (such as “Click here”) to encourage visitors to download your files. In HTML language, it means that you now need to track a <img> instead of <text>.

The way you achieve this is very simple: it is exactly the same principle used to track downloads via text. You only change the <text> with a <img> file and you are done!

  • FROM <a href=”subdirectoty/filename.pdf”><img src=”images/filename.jpg”></a>
  • TO <a href=”javacsript:download(‘/subdirectory/filename.pdf)”><img src=”images/filename.jpg”></a>

And that’s it! You are now all set to track your downloads via images!

How to report a Goal: The Conversion Menu and the Multi Channel Funnel

In Google Analytics (GA) the term Conversion indicates that a goal has been achieved by a user. A goal is defined by the webmaster of GA and depending on the type of website, a goal could be -for instance- the purchase of a product, the streaming of a video, or the download of a brochure. A goal could even be defined as time spent on site (a conversion that is particularly useful for bloggers). In GA menu, the sub-menu Conversions contains four options:

  1. Goals
  2. E-commerce
  3. Multi-Channel Funnels
  4. Attributions

Conversions > Goals 

If we click on the first option Goals, it contains five clickable options:

  1. Overview
  2. Goal URLs
  3. Reverse Goal Path
  4. Funnel Visualization
  5. Goal Flow

Conversion Menu
Conversion Menu – Overview

The Overview shows how many users have completed the defined goals (27), the total value associated to each goal (in this case zero), the percentage of users that converted (19.71%). The total abandonment rate is always equal to zero as users have completed the goals. In addition to these four set metrics, the Overview shows how many users have completed each goal (Goal 1 Completions). In the above example there is only one set goal. If we had more than one goal, the first four parameters would be the total sum of each goal plus two more metrics showing how many users completed each goal. In this last instance, the Overview would be:

  1. Goal Completions (Total Users that completed Goal 1 and Goal 2)
  2. Goal Value (if set it would express the total monetary value of Goal 1 and Goal 2)
  3. Goal Conversion Rate (Percentage of users that completed Goal 1 and/or Goal 2)
  4. Total abandon rate (always zero)
  5. Goal Conversion 1 (total users that completed Goal 1)
  6. Goal Conversion 2 (total users that completed Goal 2)

In this case the values are summative and therefore do not give any insight regarding how each goal is performing. For instance, Goal completion does not indicate if the number of users that convert is high or low. Conversely, Goal conversion rate does not indicate if a Goal is performing well or poorly. To have a better insight on how each goal is performing, we should look at the Goal Completion Location, which lists all the terminal pages for each conversion.

Goal Completion Location
Conversion Menu Overview: Goal Completion Location

In the above example, Goal 1 is equal to social shares. If we look in detail, among the 27 users that converted, 8 users completed the goal on /Post and 3 users on /Albums. In this case, as there is only one goal defined, it is easy to find a correspondence between goal and final page URL. However, when there are many goals it is difficult to determine which terminal page corresponds to which goal. To gain a better insight, it would be worth selecting only one or a sub-group of goals from the All Goals menu. The on goals would appear in underlined blue and the off goals in grey.

Goal URLs
Conversion Menu : Goal URLs

The Goal URLs shows all the terminal pages URLs and the number of conversions for each page. In case there are more than a single goal set, each terminal page will show the total number of users that converted; therefore, for each page it is impossible to tell how many users completed a specific goal (Goal 1 or Goal 2 for instance).

Goal URL and previous step
Conversion Menu : Goal URLs with Previous Step

By clicking on any specific URL, we do not get any additional information; only how many users converted and the monetary value associated to it. However, by selecting from the menu Secondary Dimension the option Goal Previous Step -1, we can find out which pages the users have visited before the terminal page. The same information can be visualized using the Reverse Goal Path.

Conversions > The multi-channel funnel (MCF)

The multi-channel funnel provides additional information regarding the steps visitors and users took before converting. The Time Lag shows the time that passed between a user visiting th site for the first time and the conversion. In case you have set up multiple goals, you can select and deselect specific goals from the top hand-left side menu. The Path Length option indicates how many steps a user took before converting.

If the conversion path is on average quite long, the website structure might not be optimized for users conversion. Options could include more visible call-to-actions buttons, more links that lead to the conversion page.If that is not the case, visit the pages that your users visited before converting to better understand their behavior.

Learn how to create a segment in Google Analytics

Segmentation is the process of dividing heterogeneous data into homogeneous smaller groups. Segmentation could -for instance- divide users between users that purchased a product from out ecommerce site and users that did not. Classification variables which are used to generate a segmentation, are variables selected from any of the available Google Analytics dimensions and metrics.

Segments can be generated to track trends, goals and new opportunities to promote the site; for instance, the success of new products (trend), the percentage of visitors that convert after landing on a specific landing page (goal), the impact of webinars in promoting the site’s visibility on social media (site’s promotion).

How to +Add a Segment

Segments can be generated from any GA page and in combination to any dimension and metric available on GA. The easiest segment that can be generated is a single segment, that is a segment with only one dimension and one metric. Let’s say you are interested in the behavior of your users; in this case you would focus on the Behavior Menu > New vs Returning of GA. In addition, let’s assume you you have just launched a brand new mobile version that makes the mobile navigation much easier for tablets. In this case, you would not be interested in all the visitors, but only to those that used a tablet device to visit the site.

GA - ALL Segments
Google Analytics: How to Apply a Segment to the current view

First, select Audience > Behaviour > New vs Returning. If you click on “+Add Segment” next to “All Sessions 100%“, a new window opens up. Now, select “Tablet Traffic” among the available options and click “Apply“. A new trend-line will appears on the graph showing all the sessions. If you want to exclude “All Sessions 100%“, deselect the “All Sessions” button.

How to +Add a System Segment

When selecting +Add a Segment, the new window shows that segments are divided in five different groups:

  • All (All available segments)
  • System (predefined in GA)
  • Custom (created by the webmaster of GA)
  • Starred (preferred custom segments)
  • Selected (applied to the current view)

System segments are built in segments provided by GA, which cover the most common types of users’ characteristics and behaviors. These types of data restrictions are particularly helpful to better understand sessions and users. Let’s assume that you are interested in analyzing how many users convert (perform a specific action or goal) among your visitors. In this case, you should:

  1. Select the Dimension you are interested in (in this case, Behaviour > New vs Returning)
  2. Click on +Add Segment next to All Users, 100% Sessions
  3. Select System from the left-hand side menu
  4. Select any of the available predefined options (in this case, Converters)
  5. Deselect All Sessions if you want to visualize only Converters
  6. Click Apply

GA - System Segment
System Segment: Behaviour of Converters

How to +Add a Custom Segment

Custom segments are segments created by the GA webmaster/user. Let’s assume you want to identify how many users utilize Safari Browser when visiting your site to determine if it would worthwhile investing in optimizing your site for Safari Browsers. To create this type of custom segment, you need to:

  1. Select the Dimension you are interested in ((in this case, Behaviour > New vs Returning)
  2. Click on +Add Segment next to All Users, 100% Sessions
  3. Select +Create New Segment
  4. Give the segment a Name (for instance, Safari Browsing)
  5. Select Technology among  the available dimensions indicated on the left hand-side:
    1. Demographics
    2. Technology
    3. Behaviour
    4. Data of First Session
    5. Traffic sources
  6. Select Browser which contains Safari
  7. Click Save

GA - Custom Segment
Behaviour Custom Segment – Technology

Custom Segments could also be defined by multiple conditions. Let’s assume for instance that you are interested to know how many visitors that come from social media use mobile devices. If a site sees a lot of incoming traffic from social sites, it might be worth investigating if the site needs to be optimized for mobile devices.

  1. Select the Dimension you are interested in ((in this case, Behaviour > New vs Returning)
  2. Click on +Add Segment next to All Users, 100% Sessions
  3. Select +Create New Segment
  4. Give the segment a Name (for instance, Social Media and Mobile Traffic)
  5. Select Technology
  6. Select Mobile (Including Tablet) Yes
  7. Select Traffic Sources 
  8. Select Medium contains Social
  9. Click Save

If you now visit the Custom Segments, you’ll find listed all your new generated segments. You can now apply or remove Custom Segments. By clicking on Action, you will be able to Edit, Copy, Share or Delete your segment.

GA - Custom Segment List
Google Analytics Custom Segments