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All joking aside, there’s no telling what is going to happen on Monday when Google completes the system-wide migration to Enhanced Campaigns, but we do know one thing, with the power of Google Analytics we can watch it happen and adjust as we see the story unfold.

Using Google Analytics custom reports we are able to keep a close eye on all areas where we have the option to place a bid multiplier. We can easily track data based on device, geo, day of the week, and hour of the day. By applying this report we can easily look at emerging trends at a granular level and quickly apply optimization changes to bid multipliers to head off any potential threats.

We can keep an eye on per visit value and revenue trends in accounts with eCommerce tracking set up and apply fixes based on this information at the device level. We can also see potential trouble with increased visibility on tablets and begin adjusting bids accordingly.

We can also start to look at how things are affected by geography in both eCommerce and lead gen accounts. We can then apply geographic bid multipliers if we see certain geographies start to over spend or perform better as compared to the same period last year or the same amount of time prior to the enhanced migration.

We can’t predict the future, but we can prepare ourselves to battle what may come. Until the rumored enhanced campaign reports show up in Google Analytics, download these custom reports and adjust them for your campaigns prior to Monday’s system-wide migration.

Monday morning and for the next several weeks, I’ll be keeping a close eye on these reports as well as all paid traffic. We’ve already started to see these changes leak into the PPC ecosystem beyond Google into Bing and I’m sure there are more ripples to come.

Hold on to your butts!

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Install Google Analytics With Google Tag Manager

🚨 Note: Since Google Analytics will be sunsetted on July 2023, we recommend starting the GA4 migration process.

Are you looking for a quick and easy way to start using Google Analytics through Google Tag Manager?

In this guide, we’ll learn the step-by-step procedure to install Google Analytics tracking on your website with the help of Google Tag Manager.

Here are the steps to install Google Analytics with Google Tag Manager:

So let’s jump right into it!

Create a Google Analytics Tag

We’ll start this tutorial with a demo shop with Google Tag Manager installed. If you don’t already have it, we suggest installing Google Tag Manager as the first step. 

It will also show all the different Tags and triggers set up for the website from the Google Tag Manager account. Currently, we don’t have any Tags running. 

The first step in building your Google Analytics Tag is to access the Tracking ID from the Google Analytics account for your website. 

Under this Admin section, navigate to Property → Tracking Info → Tracking Code. 

You’ll see that the Tracking Code will deploy on all the pages of your website for Google Analytics to function correctly. 

We will not use the Global Site Tag for this guide. Global Site Tag code is an all-in-one code that will directly deploy Google Analytics tracking on our website. 

Since we’ll be deploying everything via Google Tag Manager, we just need to copy the Tracking ID instead of the code.

Once the Tracking ID is copied, we’ll come back to Google Tag Manager. 

We’ll need to create a new Tag on Google Tag Manager to configure the tracking ID. 

In your Google Tag Manager account, you can use the Tracking ID to create a new Tag.

Open a new Tag with Google Analytics: Universal Analytics as the Tag type. 

Google Tag Manager provides different tracking templates so we don’t have to manually implement any kind of code. We just choose a template from all the options. 

Once we choose a template, it will give us some fields to fill out. The first field is the Track Type. What kind of interaction do we want to send over? 

In our case, it would be Pageview tracking that we want to deploy on all the pages.

Next, we’ll choose our Google Analytics Setting Variable. Variables will contain our tracking ID. 

Configure a Google Analytics Settings Variable

In case you already have any variables set up in the past, then you can use them. However, we’ll create a new Google Analytics Settings Variable for this Tag. 

This is where we will need our Tracking ID. But we don’t have anything available here yet, so we’ll select New Variable.

On the variable, we’ll add the Tracking ID that we copied. We won’t make any changes to any other fields. 

Next, we’ll add a Name to the Variable. A good practice is to add the tracking ID itself as the name. 

This way, if you have more than one account, you can easily access tracking ID variables for each account. 

Once the variable is set up, we’ll also add a trigger to deploy the Tag. 

Attach a Trigger to your Tag

A trigger defines when you want to deploy the Tag. You can choose to deploy it on all pages or only on certain pages. 

In this case, we’ll choose the pre-defined trigger named All Pages. 

Hence, we’ve configured an All Pages trigger to a Page View Tag. So, we’ll track whenever a user views any of our pages on the website. 

Before we go any further, it’s best practice to test this implementation to make sure everything is working correctly. 

Test Your Tag Implementation

From your Google Tag Manager account, enter Preview mode. 

We’ll refresh Google Tag Manager and our website so our Tag gets uploaded. 

If the installation is done correctly, our Pageview – All Pages Tag will fire on the website. 

Additionally, you can also open any random page on your website to make sure that the Tag fires on all pages. 

At this point, we’ve already fired the Tag. However, we also need to make sure that this information is carried along to our Google Analytics account. 

There are two easy ways to make sure that Google Analytics is receiving data from this Tag.

The first step is to use an extension in Chrome called the Tag Assistant Legacy by Google. We can see under the Tag Assistant Legacy extension which tags have fired. 

In this case, the extension shows that Google Tag Manager and Google Analytics tracking codes have been fired on this page. 

Also, some users might see the Non-standard implementation option in blue instead of green. That’s fine. 

Google Tag Assistant simply shows the information that was sent over to Google Analytics or any other tools. 

Therefore, we’ll also be able to see the same information on the Google Analytics interface. 

Let’s open our Google Analytics account. 

On the home screen, we’ll open Real-time → Overview. 

Whenever a user opens a page or any other interactions take place, we’ll get the results on this page. 

🚨 Note: If you’re using Google Analytics 4, the process will take longer since GA4 batches data. 

Your page path for the Active Page will also change accordingly. 

🚨 Note: If you see pageviews appearing twice in your reports when you should only see one, check for other Google Analytics implementations. 

You may have a Gtag or other implementation hard-coded into your website, which would result in double-tracking and bad data. 

Make sure to check your website theme files for unwanted code or extra tracking implementations. 

In case you aren’t able to see any visuals on the Overview page on your Google Analytics account, it might be because your account is fairly new to report any results. 

There may also be problems with the implementation of the Tag or tracking ID of Google Analytics. 

But it may also be due to any filters you may have added to your Google Analytics interface for better optimization. 

Moreover, our installation isn’t complete yet. We still need to publish the changes we made to the website in the preview mode so our Tags become live for other users. 

Publish GTM Changes to Your Live Site

You can also give a Version Description that describes the changes made in this update. 

Each time you publish, you’ll create a new version of your website. The number of the version will appear on the screen along with the name of the version. 

So, that’s how you can install Google Analytics with Google Tag Manager.

What can I do with any implementation done beforehand?

Here is one frequently asked question related to implementations on Google Tag Manager. 

If you have any plugins installed on your website or your WordPress accounts, or if you have GTag or Google Analytics installed in your theme files of the website, we recommend you uninstall them. 

Currently, we’re deploying our tracking through Google Tag Manager. We won’t necessarily need the previous implementation anymore. 

If you have both the implementations intact, then it might fire the Google Analytics Tag twice. 

In this case, you’ll get double results for your website tracking, and such an issue can also hamper your Google Analytics reports. 

Therefore, we recommend you remove any hard-coded implementation of GTag or Google Analytics tracking script. 

It’s recommended to deploy everything through Google Tag Manager. 

FAQ What is a Tracking ID, and where do I find it in Google Analytics?

A Tracking ID is a unique identifier associated with your Google Analytics property. To find the Tracking ID in Google Analytics, go to the Admin section, navigate to Property → Tracking Info → Tracking Code. Copy the Tracking ID displayed on that page.

How do I create a Google Analytics Tag in Google Tag Manager?

To create a Google Analytics Tag in Google Tag Manager, you need to create a new Tag and choose “Google Analytics: Universal Analytics” as the Tag type. Configure the Track Type as “Page View” and select or create a Google Analytics Settings Variable that contains your Tracking ID.

How can I test if my Google Analytics Tag implementation is working correctly? Summary

This is a simple method to configure Google Analytics with Google Tag Manager. With this, you can start tracking your pageviews without writing any code. 

This is recommended because instead of adding various codes to monitor each type of tracking on our website, we can do it directly through Google Tag Manager.

Additionally, once you start analyzing the data through Google Analytics, you can also learn to set up goals in Google Analytics for better website performance. 

🚨 Note: Want to make the most of your tracking with GTM? Make sure that you’re tracking your popups and form fields.

Build A Google Analytics Dashboard With Google Sheets

🚨 Note: All standard Universal Analytics properties will stop processing new hits on July 1, 2023. 360 Universal Analytics properties will stop processing new hits on October 1, 2023. That’s why it’s recommended to do the GA4 migration.

Google Analytics dashboards are not always comprehensive—which is why digital analysts prefer exporting their data into other tools, like Google Sheets. 

Google Sheets is a great option to create a Google Analytics dashboard using the GA Reporting API. It is free, flexible, and can help you with quick analysis.

In this guide, we’ll learn how to import Google Analytics data into Google Sheets to create meaningful dashboards. We’ll also use a Google Sheets plugin called Supermetrics to import and visualize data. 

An overview of what we’ll cover:

So let’s start!

An Overview of Reporting Tools

Google Analytics is one of the best tools to track your website traffic. 

However, it is not flexible enough to create custom reports or data visualization dashboards that can be sent to clients.  Without data visualization, your clients may not be able to understand the data you’ve collected, no matter how thorough it is.

This is why many digital analysts prefer to export their data to different tools. 

For example, you can use the tool Klipfolio to display your data in a more comprehensive manner.

Klipfolio has a few different products and different pricing tiers, including one that is free. It’s great if you are confident in your coding so that you can customize your reports, but it can be challenging if you don’t have that experience.

Similarly, if you require more data visualization and analysis, you can use Tableau. 

Tableau is a well-developed software with huge data processing capabilities, although it’s a steep learning curve for most users. It also doesn’t have a free tier, although you can customize your paid plan and maximize cost-efficacy for your needs.

R projects are easy to connect to Google Analytics accounts and fetch data, but it’s quite the time investment to learn.

But sometimes, all you need is a basic analysis of your data—which you can accomplish with MS Excel or Google Sheets.

Google Analytics already has a functionality that allows you to export data directly using the Export option. With this function, you can transfer all of your data directly to Excel or Sheets.

A better way to import data from Google Analytics is using something called the Reporting API. 

Let’s see how this works!

The Google Analytics Reporting API

The Google Analytics Reporting API is the interface that collects and manages your tracking data. By working directly with the reporting API, you can simplify several aspects of your data analysis workflow—including data exports.

First, you’ll need to go to the Core Reporting API and log in with the Google account that you use for Google Analytics.

This view will be the same as the one you’d see in the Home tab of your Google Analytics account. 

Next, you can select the Query Parameters that you want to import. For example, let’s try to recreate the Source/Medium report of Google Analytics. 

In the Query Explorer, select the start-date and end-date that you want for your report. You can also select the metrics from the drop-down menu. 

To generate the Source/Medium report, we’ll select sessions as metrics and sourceMedium as dimensions. 

You’ll see the Source/Medium report from the fetched data. 

There are several other parameters such as segment and filters that you can select. You can also define your samplingLevel.

One great thing about this is that it’s available even in the free version of Google Analytics. It gives you a sample of free data from your Google Analytics account via the API. 

If you want, you can also write a script in Python or PHP to connect to the API and fetch data. Or, you can use plugins in Excel like Analytics Canvas or Axon Analytics to import data and analyze it.

But in my opinion, Google Sheets is an easier option to create reports and dashboards. 

Let me show you why. 

Pros of Using Google Sheets for Reporting

To start with, Google Sheets is a free tool, and it’s easy to share your files with clients and collaborators. All they need to do is open a link—no need to download files or use special software. 

As a reference for you, I have created a dashboard from scratch that contains data of an e-commerce website directly from Google Analytics. 

You can download this dashboard template to create your own reports and customize it according to your requirements. 

This tool allows you to connect your Google Sheets directly to the Google Analytics Reporting API and pull the data directly into the correct cells. 

From there, you can format, analyze, and present the data for more insights. It’s my favorite tool for fast, easy data analysis and presentation. Let’s take a look at an example.

Pulling Data from Google Analytics Using Supermetrics

To launch Supermetrics in Google Sheets, go to the Add-ons → Supermetrics → Launch sidebar. 

Make sure to connect your Google Analytics account to the add-on.

Next, we’ll go to Data source → Select views. Under the Select Dates option, we’ll select This month to date to fetch data from last month. 

Going further, we can Select metrics. Let’s go with Sessions and Users. 

The next option is Split by. You can split your data from rows as well as columns. In our example, the rows are already split into Sessions and Users. But we’ll split the columns by Month. 

Then you can select any Segment that you’ve defined in your Google Analytics account, or you can use the Filter option to refine your data. 

Lastly, you can explore the Options tab. This gives you an option to avoid data sampling (which is usually a problem with the free version of Google Analytics). If you use this feature, Supermetrics will fetch your complete, unsampled data bit by bit.

For this example, we’ll keep it unchecked to speed things up—but it’s a very useful tool if you have tons of data. 

We’ll see the Sessions and Users data for the current month up to this date. 

If you want, you can also add some basic Excel or Google Sheets calculations on this data. For example, we can enter a formula to find the number of sessions per user in this Sheet (done by dividing the number of sessions by the number of users). 

Lastly, we can connect this data to our final dashboard by using this cell address (‘Raw Data’!C4). 

But there’s much more you can do with the Supermetrics tool. It has both a free and a paid version, and which you can select based on your requirements.

Not sure what you need? Let’s break down some of the most important features.

Supermetrics Features

The paid version of Supermetrics has the ability to schedule updates to Google Sheets reports automatically and send those reports out using emails.

To access this feature, go to Add-ons → Supermetrics → Schedule refresh & emailing. 

This automation saves a lot of time, especially while working with multiple Google Analytics accounts. You can also send regular reports to your clients. 

The basic version is free for Google Analytics. It can also connect to a number of other tools including AdWords or YouTube to import data into Google Sheets. 

However, you can only import data up to 100 rows. If you want to import more data, you’ll need to pay the price starting from €99 per month for these integrations. 

Depending on your requirements, you can choose different plans. Additionally, if you want, you can also create a custom plan for your business that will be charged according to the data sources you choose. 

FAQ How do I import data from Google Analytics into Google Sheets? Can I create custom reports and dashboards with Google Sheets and Google Analytics?

Yes, you can create custom reports and dashboards using Google Sheets and Google Analytics. After importing the data into Google Sheets using Supermetrics, you can format, analyze, and present the data according to your requirements. You can also customize the dashboard template provided in the blog post and tailor it to your specific needs.

Do I need to migrate to GA4 for using the Google Analytics Reporting API and Google Sheets integration?

No, the Google Analytics Reporting API and Google Sheets integration can be used with both Universal Analytics and GA4 properties. However, it’s recommended to migrate to GA4 as Universal Analytics properties will stop processing new hits on July 1, 2023, and 360 Universal Analytics properties will stop on October 1, 2023. Migrating to GA4 ensures compatibility and access to future enhancements in Google Analytics.


That’s it! This is how you can build a Google Analytics dashboard using Google Sheets and the Supermetrics add-on.  

Google Sheets is a free tool that provides customizability and flexibility to analyze data. It also has various plugins to import data. Supermetrics is definitely my favorite way to pull data into Google Sheets, but you also can learn other ways to export data from Google Analytics to Google Sheets in this guide.

How To Create Custom Utm Parameters Via Google Tag Manager

Did you know that you can track the audience’s movements with the help of the URL they use to access your website? 

The URL has a string attached to it which contains various UTM parameters that can track and send information to the servers. 

An overview of what we’ll cover: 

So, let’s start!

What are UTM Parameters?

UTM Parameters are encoded messages that are added to the URL of the user in the form of query strings. 

These parameters are readable by the search engines and sent over to our analytics accounts. They can help us in tracking the user activity on our web pages and analyze that data. 

Let’s learn more about what they can do!

UTM Campaign

In this guide, you’ll learn to create a custom UTM parameter. 

This means we’ll create parameters other than the existing standard Google Analytics campaign parameters.

🚨 Note: If you’re using Google Analytics 4, check out our handy guide and learn how to track UTM codes in GA4.

We have created a demo newsletter for mailing our audiences. 

Each different link provides a different discount rate. 

The URL parameters of these links are readable by Google Analytics. They further transfer this data into the campaigns. 

You can also track the exact source of the traffic from your campaign data in the Google Analytics account. 

You’ll need to navigate to Acquisition → Campaigns → All Campaigns. You’ll find all your active campaigns in this section. 

You can use various parameters including the keyword or also the Source/Medium campaigns. 

For this campaign, we have used the Google Analytics Campaign URL Builder tool to create the URL. 

You’ll need to fill out the required fields: Website URL, Campaign Source, Campaign Medium, and Campaign Name.

In addition to that, you can also add the Campaign Term and the Campaign Content to the URL. 

Which Three Campaign Parameters Are Recommended to Manually Track Campaigns? 

The three recommended campaign parameters to manually track campaigns are Campaign Source, Campaign Medium, and Campaign Name. 

The campaign source parameter allows you to track the source from which the user accessed your website. 

The campaign medium allows you to track the medium that the user used to access your website. 

Lastly, the campaign name gives you information about the particular campaign that enables the user to access your website. 

There are three standard Google Analytics campaign parameters, utm_source, utm_medium, and utm_content. 

As the name suggests, these parameters are used to track the source of the user, the medium user used for accessing our website, and the content that the user accessed on our platform. 

However, in this guide, we’ll learn to create a new parameter to track the user activity on our website manually. 

🚨 Note: If you want to know your traffic’s initial source before landing on your website, you can find it out with GTM.

This happens when you have already exhausted all the parameters and still need a custom parameter to track any particular user movements on your webpage. 

We can create such custom parameters with the help of Google Tag Manager, and forward this data to Google Analytics account, so we can analyze it. 

Let’s see how! 

How to Create Your Own UTM Parameter

Let’s take the example of the URL links we added to our newsletter. 

We have different discounts on the basis of different links in the newsletter. 

Unfortunately, no such parameter is available in the URL builder that can give us custom discounts based on the URL. 

This is where we need to create our own UTM parameter. 

Let’s say we add our own parameter of discount=90. 

Refresh the page and see if Google Analytics picks up the data. 

Unfortunately, Google Analytics can’t interpret the parameter as it is going beyond the set of the parameters defined to it. 

We’ll learn to create a new UTM parameter, and send this data to Google Analytics so it can interpret and understand the data. 

We already have the value of 90 for the keyword discount. 

We already have a Tag for PageView. We’ll need to create a new custom variable to make this data available for Google Analytics to read. 

Let’s see how! 

Building a New Custom Variable in Google Tag Manager

We’ll choose the Variable Type as URL. Our Component Type will be Query. 

We’ll use the Query Key of discount. The query key is the keyword we use before the equal sign on the query string. 

You can understand how to use query strings and parameters before setting up custom parameters. 

We’ll refresh our preview and debug mode, as well as refresh the website to see how the variable works.

We’ll check the Variables section for the PageView event. 

We can see that the url – discount holds the value of 90. 

Let’s also check whether this value is dynamic. We’ll add a discount value of 50 in the URL this time instead of 90, and reload the page to see the results. 

We can see that as the page loaded, the value of 90 changed to 50. 

Once we have captured this information into the variables, we’ll send this to Google Analytics by using a custom dimension. 

Custom Dimension

On your Google Analytics account, navigate to Secondary dimensions, you’ll find all your Custom Dimensions here.  

Let’s learn how to configure them! 

Open the Admin Settings and navigate to Custom Definitions → Custom Dimensions → New Custom Dimension. 

We’ll add a Name to the dimension, and use the Scope as Session because our UTM parameters are also scoped to sessions. 

We’ll keep the status as Active only. 

Next, we’ll need the dimension value of the dimension we just created. In our case, the value is 3. 

Let’s now configure this into Google Tag Manager! 

We’ll need to build the custom dimension into the PageView Tag in the Google Tag Manager account. 

Then open More Settings → Custom Dimensions. 

The Index number will be 3 in our case, and choose the Dimension Value as url – discount. This means dimension number 3 will be filled with the URL discount as its value. 

This is how we added a dimension to one Tag. However, we can also add it to all the Tags by directly adding the dimension to the Google Analytics Settings variable. 

This is the recommended method. 

Google Analytics Settings Variable

Let’s open our Google Analytics Settings Variable. 

We’ll again navigate to More Settings → Custom Dimensions → Add Custom Dimension. 

The Index number is 3 in our case, and choose the Dimension Value as url – discount.

We’ll Save it once done. 

Let’s refresh the website and also the page from the preview and debug mode. 

We can see that the Tag has fired correctly. Let’s check the Tag details in the Google Tag Assistant. 

In the Pageview section, we’ll open the Custom Metrics. We can see that the custom dimension of 3 was fired, with a value of 50. 

Let’s now learn to analyze these results from the Google Analytics account. 

Acquisition Reports

We’ll open Acquisition → All Traffic → Source/Medium. 

You can see the newsletter/email source mentioned. 

Once that’s done, the custom dimension of discount will be added to the reports. 

The data might take some time to populate. We recommend giving a few hours’ time for the data to load completely. 

Additionally, you can also add this parameter to any other session-based report to verify the discounts availed by the users. 

All we did here is that we just extended the dataset of Google Analytics with another dimension that is customized to our needs. 

In the end, you’ll need to submit this as a version to make the data live for all the users from the Google Tag Manager. 

FAQ What is the purpose of accessing campaign data from the source/medium reports in Google Analytics?

Accessing campaign data from the source/medium reports in Google Analytics allows you to analyze the performance of different marketing campaigns and identify the sources and mediums that drive traffic to your website. It helps you understand which channels are most effective in driving conversions and enables you to make data-driven decisions for your marketing strategies.

How do I configure the discount custom UTM parameter in the report section of Google Analytics?

Configuring the discount custom UTM parameter in the report section of Google Analytics involves setting up a custom dimension. Once you have created the custom dimension for “discount,” it will be added to your reports. This allows you to track and analyze the discounts availed by users based on the UTM parameters in your marketing campaigns.

Can I use custom dimensions for purposes other than tracking discounts?

Absolutely! Custom dimensions in Google Analytics provide flexibility to track various aspects of your website and marketing campaigns beyond discounts. You can create more than 20 custom dimensions to capture and analyze specific data points such as user behavior, campaign performance, content engagement, or any other metrics relevant to your website’s goals and objectives.


So that’s how you create your own custom UTM parameters via Google Tag Manager. 

This is just one of the examples for customizing the Google Analytics installation to accommodate your needs. 

You can add more than 20 custom dimensions to your Google Analytics account and track various things to optimize the installation according to your website needs. 

Google Analytics : Branding And Packaging Results

Google Analytics : Branding and Packaging Results

Google has scored a major coup with the release of Google Analytics. In the spirit of helping webmasters and search marketers move site visitors into converted site users, Google is offering its enormously useful site analytics tool, Urchin, free of charge under the re-branded name Google Analytics. The software is designed to help webmasters and marketers understand site visitors and their behaviours. Last year, it cost almost $500/mth to subscribe to.

According to the basic information provided on the features page, Google Analytics can help you, “Learn how visitors interact with your website and identify the navigational bottlenecks that keep them from completing your conversion goals. Find out how profitable your keywords are across search engines and campaigns. Pinpoint where your best customers come from and which markets are most profitable to you. Google Analytics gives you this and more through easy-to-understand visually enhanced reports.”

Yesterday, the system ground to a near halt as millions of webmasters rushed to sign up. Google will be receiving a wealth of consumer and marketing information from sites using the software, information that will be incorporated into Google’s understanding of how users travel through sites found in its index. That kind of information is worth its weight in Google shares.

Separated into three general user types, Executive, Webmaster, and Marketer, Google Analytics shows up to the minute information on over seventy essential elements, giving decision makers a lot of data to work with. The internal system is set up around a left-hand side dashboard of expanding drop-down menus for each of the general user overlays, each of which displays a series of reports. Users can also select a drop down display that expands to show the full range of elements to analyze.

Having said all that, it isn’t really possible to give a full review of the data generated by Google Analytics as we have just inserted the tracking-script into documents on our site this morning. It will take about twelve hours for information to accumulate.

On the surface, it appears as if Google has taken some of the best elements of other analytic programs and integrated AdWords/AdSense conversion support features. The layout is easy to use and there is a good mix of information and supporting graphical elements to ease the headaches commonly associated with statistical analysis. The first overlay provides an at-a-glance dashboard with gauges indicating site visitors, unique visitors, top documents, top keywords, and other user-specific information sets.

Account access can be shared with other Google Account holders, a feature that will allow SEOs and SEMs to share information directly with their clients. While it is a violation of the Terms of Service agreement to charge clients for access to data generated by Google Analytics, a service helping them interpret and understand the stats and information seems a natural evolution for search marketing professionals.

Jim Hedger, Search Engine News Writer – Jim Hedger is a writer, speaker and search engine marketing expert working for StepForth Search Engine Placement in Victoria BC. He has worked as an SEO for over 5 years and welcomes the opportunity to share his experience through interviews, articles and speaking engagements.

Customising Google Analytics For Your Business – 6 Key Types Of Customisation

Google Analytics is a fantastic tool from the moment you arrange to have the tracking code installed and you experience the thrill or anxst of your first reports appearing showing how real people are interacting with your business.

Every business now needs a Google Analytics customisation strategy

You can certainly get a lot of value from reporting and analysis using the standard setup, but to really drive results for your business, you’re better off spending some time on customisation.

Retweets previously

recommending this post

before Smart Insights


With each passing month there are more customisation options available in Google Analytics, so I believe you really need a strategy of what to customise, particularly if there are several team members using the account. This post gives my ideas on a customisation strategy based on consulting work I have done and typical usage of Google Analytics by attendees on  Econsultancy training Site  Optimization with Google Analytics – the length of the post shows that there are lots of customisation options available.

I’ve published it as the pre-read for marketers attending the training course and hope it’s useful for others who pass this way. I plan to update it as the need for new customisations appear.

If you’re on my next course, “Hi and I look forward to meeting”. Don’t worry if you don’t have time to go through all the links(!), it’s just intended to give you a flavour of some of the main concepts we cover so you can ‘hit the ground running’. It will also provide a reference after the course.

We’ll cover each of these concepts on the course, but  we spend most time on using analysis of reports to get better results rather than configuration and setup – that’s what I find interests people most!

Customisation options for Google Analytics

From several years experience of using GA, I recommend reviewing these six types of setup or configuration for Google Analytics to customise the reports you view. Some may need some tech assistance, but most can be completed by any business user, if you know where to look!

A recently published companion to this post is Brian Clifton’s Book Advanced Web Metrics with Google Analytics which explains how to implement the setup in more detail than possible here

So, from easiest to hardest, the six customisation options are:

1. Working with reports in a smarter way

3. Creating custom reports and dashboards within Google Analytics

4. Setting up marketing campaign tracking

5. Modifying profile setup within “Google Analytics Settings”

6. Customisations that require server modifications

Resources for finding out more about Google Analytics customisation

Most Google Analytics users will have used the Google Analytics Help System which is functional, but I find that many don’t know about the excellent “Google Conversion University” which as the name suggests is a much better way to learn.

The Google Conversion University is designed to help analytics specialists take the Google Analytics Individual Qualification.  I worked my way through the GAIQ back in September 2009 and I can recommend it if analytics is a big part of what you do. But even if they’re not, I can recommend some of these lessons as a great way to learn about Google Analytics. I’ve highlighted the most useful ones here. Here’s an example:

I’ve also linked to relevant posts within Avinash Kaushik’s Occam’s Razor blog. Avinash is analytics evangelist for Google and thinks deeply about how GA can be best applied to benefit businesses. As well as his recommendations, suggestions of other users about customisations make this an excellent place to learn.

There will naturally be future updates as Google enhances it’s Analytics services. To help here, I’ve created a Google Analytics update wiki where I add a short note on the latest, most significant, changes as they happen.

1. Working with reports in a smarter way

The most basic customisation you can do is to change the way default reports are displayed. For example, changing or comparing time periods or variables or the number of results displayed. Most readers will be doing this already because the system is intuitive and you have to use it for basic analysis.

But it’s worth checking out this lesson on Interface Navigation in the Conversion University since it also shows how to compare different metrics to review correlation and how to do a quick segmentation within a report to drill down to the detail.

There are also some newer features in Google Analytics to help with report analysis which aren’t included yet in the Conversion University, so here’s the low-down on these:

Google Analytics Intelligence

What is it?

The Intelligence feature of Google Analytics currently gives you automated or custom alerts of changes in visitors from different sources like an individual country, search engine or another site.


Ideal for overlaying a reminder of the start of new marketing activities to jog your memory or to share with colleagues. Annotations are overlaid on the graph on each report. For instance, you can show new campaigns, new content or new publicity and relate it to changes in traffic or conversion.

Using Advanced Segments is essential if you want to find how different groups of visitors behave and then work out how well your content, messaging, offers and navigation is appealing to them.

The most useful standard segments to apply are:

Paid and natural search traffic

First time visitors or returning visitors

I’ll write more about custom segments in a later post, but for me, the most useful are:

Visits from brand and non-brand searches

Visits from social media

Visits from key markets or country

Visits involving different conversion types

Engaged visits, etc

Read more Advanced segments:

3. Creating dashboards and custom reports within Google Analytics

When you first log-in to Google Analytics, you start with the dashboard screen for your selected profile. This is arguably less easy to configure than dashboards in other analytics systems. You can move, add or subtract reports. You add additional standard report widgets through using the “Add to Dashboard” option.

Motion charts can be customsied in reports where the “€œVisualisation”€ option is available at the top of the screen.

Tip: Add additional standard or custom reports to your dashboard and then add then schedule a daily, weekly or monthly email.

Read more on custom reports:

Read more about Bubble charts and motion charts

4. Setting up marketing campaign tracking

Many companies will track AdWords because of it’s automated integration enabled from Google AdWords, but they may not track other codes or have a standard notation which needs to be defined and then added to all links involving media placements.

Google Analytics uses 5 standard dimensions for a campaign which need to be incorporated into the query string of the URL for each ad placement as this example shows:

The campaigns report in Google Analytics will then enable you to compare media.

The table explains each of these 5 dimensions which refers to this example:

Variable Explanation



The name of the marketing campaign, e.g. Spring Campaign.



Media channel (i.e. email, banner, CPC, etc).

What is the ‘distribution method’ that is used to get our message out to our clients?



Who are you partnering with to push your message. A publisher such as chúng tôi or for paid search, Google, Yahoo, Live Search, etc



The version of the ad (used for A/B testing) or in AdWords. You can identify two versions of the same ad using this variable. This is not always used and is NOT included in the above example.



The search term purchased (if the link refers to keywords).

This is not always used and is NOT included in the above example.

The Google URL builder can help with creating these links.

Note that in the major Fall 2008 upgrade to Google Analytics, Advanced segmentation provides some standard source codes for campaign types such as paid search.

Tip: Defining a standard set of online marketing source codes is essential to determining the value of different referral sources such as ad campaigns or email campaigns.

Tracking offline campaign referrals

Many companies will reference promotional URLs or so-called vanity URLs (we hate that term) in offline Print ad, Direct Mail and TV campaigns to make it easy for the customers to fulfil the offer.

Of course, they also want to track the effectiveness of different promotions.

Best practice in such offline or multichannel tracking has been explained well by Avinash in his post: Multichannel Analytics: Tracking Online Impact Of Offline Campaigns.

As with digital campaign tracking, offline campaign tracking should use standard codes for medium, source and campaign name.

5. Modifying profile setup within “Google Analytics Settings”.

The Google Analytics settings section is more likely to be used by analytics specialists who have experience of previous setup, but some of the changes are quite straightforward. We we will cover the 4 main types of settings changes most businesses will need to make:

A. Setting up conversion goals.

Visitors to a site do not have equal value to a company, they engage to different degrees as indicated by the types of pages they visit.

A visitor who has visited a product page, registered for an e-newsletter, bought a product or visited the contact page is clearly more engaged – in web analytics we call these “value events”.

Tip: Setting up value goals to report $Index Value and Goal Value per Visit

This is another really powerful option I find isn’t used much eventhough you can apply it to the many non-Ecommerce sites (this post by Brian Clifton author of  Advanced Web Metrics with Google Analytics explains how. But the approach of assigning value to goals is incredibly useful since you can compare how successful different pages, referrers and journeys are in influencing conversion goals and generating value.

In Ecommerce sites, value from sales transactions are used to automatically populate $Index values and you can also report on Revenue per Visit.

Even for non-transactional sites, you should set a nominal value on each value event such as a newsletter signup or lead-generation form since you can then see which traffic sources or pages influence success.

Arguably the best use for this is to exclude visitors who are not engaged at all i.e. poor quality traffic which isn’t well targeted. I suggest greater than 10 seconds  and greater than one or two pages per visit.

Avinash Kaushik has a great post on the rationale and examples of conversion goals.

B. Setting up conversion funnels

Funnels representing the different steps in a checkout process are an essential piece of configuration for retailers. After these have been setup up you can then visualise the drop-off or attrition at each stage. But you can set up funnels for most types of site.

Tip: Setup Higher-level conversion funnels. They can also be setup for sites showing how many people engage with different parts of the site such as browsing or searching for products, viewing product content which then contribute to a lead or a sale.

C. Setting up on-site search

On site search is not setup as often as you would expect  in my experience, but is usually easy – you simply specify the search parameter which is a text string used to tell the search engine what the query term is. For example, my sites use the Google custom search engine which like chúng tôi uses the search parameter ‘q’.

Analysing the volume and types of searches completed by site visitors can pay dividends to find the type of content visitors are looking for and whether they can actually find it or leave the site frustrated!

These types of insights are available:

If you are using a Google appliance for search or Google custom search for providing on-site search configuration is straightforward. But other search engines can be integrated through specifying the query string parameters to Google Analytics.

D. Setting up Filters and profiles

The granularity with which you collect and report data should be consistent with the way the organisation is structured since different people in the organisation will likely NOT want to review the results for the entire site, but instead you will want to separate out data for part of the company or a particular product, service or audience they are responsible for. Common options which you should consider to report separately on include:

To report separately on domains, sub-domains or sub-folders you need to apply the concepts of profiles and filters within Google Analytics. You may even want to have different accounts with different unique tracking codes for different countries, particularly if they operate as separate entities and you want to apply different currency and time zones to the report. Each account will use a different unique tracking code, but you will need to remember to include an aggregrate tracking code to report all the sites together.

A Google Analytics profile will typically be used to produce reports for different sites , subdomains or subfolders. Google Analytics Help on Profiles.

So, on my site I have a master profile that is unmodified for the entire site other than a filter for excluding my IP address together with other profiles for particular types of content such as blog content or visitor segments such as returning visitors. You should specify your default page for the profile, e.g. index.html.

A Google Analytics filter is applied to modify data from a particular profile so that it shows a subset of data within the profile. A filter will often be used to show visitor interactions with product information stored in a sub-domain or subfolder. Google Analytics Help on Filters.

In this example I have a filter which is applied to my Right Touching blog which only includes visitors who go to that sub-folder.

For example, a filter could restrict results to first time time visitors or returning visitors. With the Advanced Segmentation feature in Google Analytics you are effectively provided with several default filters, such as all visitors from

So you can see this is complex! You need to get this right from the outset of collecting data since profiles and filters cannot be applied retrospectively, applying filters incorrectly will introduece errors and introducing new profiles will lead to employee confusion.

Excluding employees from report.

This configuration is relatively simple! You don’t want visitors from a company skewing the results, so these should be excluded unless you want to artificially boost your visitor numbers and have difficultly understanding visitor behaviour.

A filter should be created to exclude a range of IP addresses for company employees and contractors working in different offices.

Alternatively, if staff have a range of IP addressses or dynamic IP addresses then using the _setVar function call on a page used by staff only (e.g. Intranet home page) to update a cookie to filter staff out. Both strategies are explained below:

6. Customisations that require server modifications

There are 5 main types of customisation that may be required which involve changes to the tracking code that will need to be configured or coded within the content management or Ecommerce system.

A. Ecommerce Tracking

E-retailers will need to enable E-commerce tracking for their Profiles since this isn’t enabled by default. Ticking the tick-box will be straightforward.

The reports summarising E-commerce transactions and revenue within require inclusion of additional tracking code on the checkout completion page specifying order and product information.

Including the transaction information about the order and product(s) will be less straightforward, but many popular E-commerce systems will support this.

If you are coding this or inserting manually (e.g. for event tracking), in addition to the standard tracking code, the _addTrans() and _addItem() Javascript functions need to be included as in this example from Google:

  var pageTracker = _gat._getTracker(“UA-XXXXX-1”);    pageTracker._trackPageview();

  pageTracker._addTrans( "1234",                                     "Mountain View",                          // Affiliation     "11.99",                                    // Total     "1.29",                                         "5",                                            "San Jose",                               // City    "California",                                  "USA"                                          pageTracker._addItem(     "1234",                                         "DD44",                                         "T-Shirt",                                      "Green Medium",                  // Category     "11.99",                                        "1"                                          pageTracker._trackTrans();

Google Analytics E-commerce Help Documentation

B. Event Tracking

In Google Analytics, Events apply to interactions with content made by visitors, so if they are setup, they are found within the Content reports section of Google Analytics.

Event tracking allows you to track additional types of events other than page views. The most important are:

Video or rich media interactions

Outbound or external links.

This is a good example of a link/downloading tracking script:

For video tracking an additional script isn’t required, see Google announcement of final rollout of Event tracking June 2009:

This shows that Event Tracking can be specified with these parameters to the _trackEvent() method values of which then appear in the Analytics Reports interface under content:





implicit count

This is an example from Google help:

In this scenario, the reports for Events would display Videos as the Category, Play as the Action, and Baby’s First Birthday as the Label. The rest of this document describes these components in detail. Bear in mind that when you implement Event Tracking, you can use this data model as a guide, or you can simply use the _trackEvent() method to segment user interaction in any way that works for your data.

C. Custom variables for visitor segmentation.

Custom variables apply to Visitors, so they are found within the Visitor reports section if specified.

Custom variables were originally specified through a call to _setVar, but are set through _setCustomVar. They are most often used for defining specific segments based on the profile detail identified through a form or consuming particular content.

Options for setting custom variables including:

Customer vs non-customer

Different customer segment (or demographic profile variables like male or female). For example, Econsultancy has Bronze, Silver, Gold and Platinum member segments

Segmenting visitors according to landing page

Recording referral source attribution

Categorising different content types

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