Analytics Talk

Breaking Up Is Hard To Do: GA Account Setup Tip

July 14, 2007 by Justin Cutroni

This post is for all you contractors and agencies out there that are setting up Google Analytics for your clients. I want to help your relationship. No, not the relationship between you and your significant other. The relationship between you and your client.

One of the biggest problems I see when working with companies is contractors that set up Google Analytics incorrectly. I’m not talking about poor configuration settings, I’m talking about Google Account issues.

Here’s the situation. You, as the contractor, decide to create a profile for each of your clients in a master Google Analytics account. This seems like a good idea because you can log in and have all your client metrics accessible in one location. Plus you can grant user access to each client so they can access their metrics. However, you can’t grant them admin access because each client would have access to ALL profiles (i.e. clients) in your account.

Here’s the problem. If you ever decide to part ways with your client there is no way to transfer ownership of their profile(s). They will have user access to their profile(s), that you created, FOREVER.

Why? When you create a profile it’s tied to a specific account. That means that the data physically flows into a specific bucket. Look at the tracking code for a profile

<script type="text/javascript">
_uacct = "UA-22222222-1";
urchinTracker();
</script>

The account number is right there for you to see. During data collection, the data goes into the bucket for the account number in the tracking code. If you change the account number in the tracking code the data goes into a new bucket but the historical data stays in the old bucket. See, there is no way to move the data.

Account Setup Tip

To avoid this situation, do not add client websites as profiles to a single Google Analytics account. Instead, create a new Google Analytics account for each client. Then, have the client grant you, the contractor, access.

This also pertains to those of you setting up GA for your companies. Do NOT create a profile for your employer in your personal GA account.

At EpikOne we have two primary GA accounts: an admin account and a reporting account. We ask clients to add these accounts to their GA account when a project begins. The admin account is only used by a few of us. We use it to make changes to a client’s GA settings. The second account is used for day to day access to the client data. We give analysts and other internal data consumers access to this profile so they can play with the data and we don’t have to worry about them breaking any settings.

If You’re Guilty

If you’re setting up client profiles in the above manner, I suggest you tell them immediately and start a migration process. Will it be painful? Potentially. But it’s in the best interest of the client.

See the Problem for Yourself

There are some folks that are probably thinking, “Just make the client an administrator, and then delete the contractor’s admin account.” That will work, but the client will then have access to all of the profiles that are in the contractor’s account. Furthermore, if the client deletes the other client profiles, they will be deleted from the contractor’s account as well.

I think it’s difficult to visualize this problem so you can test it out for yourself. I’ve create two GA accounts that you guys can play with. I’m not sure how well it will work, but I thought I would give this a try.

Account #1
username: ga-acct-contractor@cutroni.com
password: contractor

Account #2
username: ga-acct-client@cutroni.com
password: client

If you do add/delete profiles, please re-create them for the next user. Try to leave both accounts the same way that you found them.

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All About Google Analytics Goals

July 7, 2007 by Justin Cutroni

Google Analytics Goals are a way to measure conversions on your website. A conversion occurs when a visitor does something you want them to do. This could be completing some type of high value process or viewing a specific page on your website.

Setting up goals is one of the most important steps when configuring Google Analytics. Without goals, there is no easy way to measure conversions. If you’re unfamiliar with conversion, or the related metric conversion rate, please take a moment to read about why both of these metrics matter. In general, counting the number of conversions and tracking the conversions rate is a good way to measure the success of your website.

During this post I’m only going to cover how goals work and how to set them up. I’ll discuss how to use goals in my next post.

What’s A Goal (Technical)?

At its core, a goal is just a pageview. It’s could be a specific page on your website that you want the visitor to see or the page that is displayed when a visitor has completed a process. A goal is literally defined by the URL of said page. As GA processes site data, it increments the goal counter each time a pageview for the ‘goal’ page is found. It should be noted that if the goal page is found multiple times in a single visit then goal counter is only incremented once.

I’ll explain a little bit more about how goals work, at a technical level, at the end of this post. There’s a few things I need to cover before we get into the nitty-gritty tech stuff.

Creating A Goal

There are multiple ways to define a goal. The method you choose depends on the complexity of your website. The easiest way to create a goal is to copy the URL of your goal page from a browser into the Goal URL text field. So, if the process ends with http://www.epikone.com/thankyou.php, enter http://www.epikone.com/thankyou.php in the Goal URL field. Here’s another example. If the URL of the goal page is http://www.epikone.com/thankyou.php?submit=true then enter http://www.epikone.com/thankyou.php?submit=true into the Goal UL field.

A goal can also be defined using a regular expression. Rather than enter an exact URL in the Goal URL field you can enter a regular expression. This is particularly helpful if the website is dynamic. If the goal page contains a unique identifier then you can’t copy and paste a URL into the Goal URL field. Every goal URL will be different. You need to use a regular expression for the Goal URL. I’ll discuss this below in the Additional Settings section.

Goal Name
When defining a goal you also need to give the goal a name. There’s nothing special here. The Goal name will be used to identify the goal in the Google Analytics reports. Don’t use anything too long, it can make the reports difficult to read.

Activate Goal
The Activate Goal setting is an on-off switch. Switching the setting to ‘Off’ will stop tracking for the goal. Why would you want to turn a goal off? Google Analytics will calculate an overall website conversion rate using all of the goals you define for the site. If you create a goal that is temporary, say for a specific campaign, then it could artificially skew the overall site conversion rate if you leave the goal on after the campaign, ends.

Additional Settings

Each goal has an Additional Settings section that can help configuration in unique situations. It’s located at the bottom of the page under the Funnel settings. By the way, you do not need to create a funnel when you create a goal. Defining a funnel is optional.

Case Sensitive
The Case sensitive setting can be used with websites that have mixed-case URLs. So, if your Goal URL value is case sensitive then click the Yes radio button. However, profile filters can affect this setting. I’ll explain more at the end of this post.

Match Type

The Match Type setting is a powerful setting that can aid in goal tracking. For example, if each goal page contains a unique customer identifier then it will be impossible to paste a single URL into the Goal URL field without the use of the more sophisticated match types. Google Analytics has three different match types that can be used for Goals and Funnels.

Exact Match
When you choose Exact Match the value in the Goal URL field must exactly match the URL of the goal page displayed in the location bar of the visitor’s browser. This is the setting you want to choose if you copy the URL from the browser and paste it into the Goal URL field. If your website uses a unique identifier in the goal URL (like a visitor ID number or an order ID number) do NOT use an Exact Match. Use a Head Match or a Regular Expression.

Head Match
The Head Match is like a light-weight regular expression. You should use a head match when a small part of the goal URL differs from one visitor to another. With a head match, if the value entered into the Goal URL matches any part of the URL in the visitor’s browser then the goal will be counted. The Head Match will match both path data and query string variables.

For example, if there is a unique identifier in the goal URL then you can use the head match to define the goal. Let’s say the Goal URL for a visitor is http://www.epikone.com/thanks.html?submit=true&id=12345. The id query string parameter is a unique identifier that will change from one visitor to the next. So, I could use a HEad Match and enter the following into the Goal URL: http://www.epikone.com/thanks.html?submit=true. Because the Goal URL matches PART of the actual URL for the goal page, GA will count this goal.

Regular Expression
This setting defines a goal using a regular expression. If the regular expression entered into the Goal URL matches any part of the goal URL then the goal counter is incremented. Using a regular expression is particularly useful because it let’s ‘wrap up’ goal tracking so you track multiple goals in a single goal. You can track multiple goals using a single goal because a regular expression can match multiple URLs. For example, let’s say you want to create a goal that tracks and PDF file download. You could enter \.pdf into the Goal URL field. I actually wrote about using regular expressions to get more out of goals last year.

Goal Value

The final option in the Additional Settings section is Goal Value. Use this field to monetize non-e-commerce goals. For example, if each Contact Form submitted by a user is worth $100, enter 100 in the Goal Value field. Google Analytics will use 100 to calculate return on investment (ROI) and other revenue based calculations. If e-commerce tracking is active for a profile, and you would like to use e-commerce data for your goals, simply leave the goal value field blank. Google Analytics will pull in the e-commerce data.

One thing to note is that the Additional Settings are applied to both the values in the Goal URL and Funnel steps. I know I’m not covering funnels in this post, but this is a common mistake. It is not possible to use an Exact Match for your funnel steps and a Regular Expression for the Goal URL.

Tips, Gotchas & More

Let’s dig a bit deeper and learn how GA actually counts goals. During data processing the value you use to define a goal is compared to the Request URI value. You remember the Request URI, right? It’s part of the URL (everything after the .com, .net or .org). I know this seems strange especially because a goal can be defined by a complete URL, but this is how the data processing works.

It is important to understand that the Request URI is used during goal processing because if you create a filter that modifies the Request URI then it might break your goals.

Here’s an example. Let’s say the Request URI, in its original form, is /pages/html/index.html. You decide to modify this value using an advanced filter and it becomes /pages/index.html. If you define a goal using /pages/html/index.html then the goal will not work. The reason is that the Request URI (/pages/index.html), which was changed by the advanced filter, no longer matches the value entered as a goal (/pages/html/index.html).

How about another example? If you force the case of the Request URI to lowercase, and then define a filter using all uppercase characters AND specify that the goal is case sensitive, then the goal will not work. Get it?

I know this seems strange, especially when most people use an exact match to define their goals. But that’s the way goals work, honest! Don’t be alarmed by this. Using an Exact Match is a perfectly fine way to define a goal.

Here’s a tip. You can also define goals based on data created by urchinTracker(). Remember, if you pass a value to urchinTracker() then that data becomes a pageview in Google Analytics. These pageviews can then be defined as goals. You can read more about urchinTracker() in this series of posts. I’m using this technique to track RSS subscriptions on my blog.

And finally… A great way to debug goals is to use the Top Content report. Remember, a goal is just a pageview. If GA is reporting 0 goals, then check the top content report. Does the goal page appear in the Top Content report? If it’s missing, then there is probably an issue with your page tags. But, if the goal page is present in the Top Content report then there is probably an issue with your goal setup.

Wow… that’s a long post. Does it all make sense? Leave a comment and let me know!

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Writing More than Blog Posts

June 8, 2007 by Justin Cutroni

Over the past few years I’ve learned quite a bit about Google Analytics in my day to day job as a web analyst. I’ve tried to pass along much of what I know using this blog. Now I have a new way to share my knowledge.

The good people at O’Reilly Media have given me the chance to write a book. I can’t tell you how excited I am about this opportunity!!! I truly enjoying helping other people and this book provides another way for me to do that.

I’m not sure when it will be published, but it should be in the next month or so. The first draft is done and I’m waiting for the editor to rip it apart return her edits.

The book is part of O’Reilly’s Short Cuts series and is titled Google Analytics Short Cuts (how’s that for original?).

Short Cuts are PDF documents that spotlight one specific topic, usually in fewer than 100 pages. Whether it’s a first look at a brand new technology, a quick reference, or a thorough explanation of a narrow but crucial subject, Short Cuts bring you focused information in an easy-to-use, portable package.

I want to stress that this is not a ‘how to’ web analytics book. It’s a book about Google Analytics and is focused solely on the product. Sure, I take time to discuss how certain GA configurations can affect your data, but I don’t dive into topics like the long tail of search or the nuances of multivariate testing. I talk about things like cookie formats, getting third party shopping carts configured correctly and link tagging (among other things).

If you’re looking for great web analytics books I suggest the following (listed in no particular order):

Web Analytics: An Hour a Day by Avinash Kaushik

Actionable Web Analytics by Jason Burby and Shane Atchison

Web Analytics Demystified & The Big Book of Key Performance Indicators by Eric Peterson

Once I know the exact publication date I’ll post more information about the contents and a long list of thank-yous to those who are helping me through the process. In the meantime, check out the above books!

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New GA Feature: Segmented Widgets

June 3, 2007 by Justin Cutroni

I’m on a roll with GA Desktop Widgets :) Another really cool feature of the new GA dashboard is Segmented Widgets. This is very similar to the Sticky Filters feature that I wrote about last week.

With segmented Widgets you can add a segmented report to your dashboard. Here’s an example. I can choose a keyword from the keyword report, segment it by City, and then have the resultant data placed on my dashboard.

First, choose a keyword from the keyword report:

Then, segment the data for that keyword:

Finally, after GA has segmented the data, add the report to your dashboard:

This feature will work for any report that you segment. I really like this feature, especially for AdWords analysis. I can segment the AdWords Analysis report by geographic area and place the result on the dashboard. Then I have instant data on how my geo-targeted AdWords campaign is performing.

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New GA Feature: Sticky Filters

June 1, 2007 by Justin Cutroni

This is a pretty cool feature that most people don’t know about. I’m not really sure if it’s officially called ‘Sticky Filters’, but that’s the term I’m going to use.

If you apply a filter to a report, and then add that report to a dashboard, the filter will be applied to the data in the report widget. Here’s an example. Let’s say you have a list of keywords, and you only want to see brand keywords. Go to the Keyword report and apply a filter to isolate your branded keywords.

Then add the report to your dashboard. When the report widget appears on the dashboard it will contain only the keywords that match the filter.

What’s really cool is that you can create multiple widgets, each with a different filter. So, if there are multiple groups of keywords tat you want to see on your dashboard, you can create multiple widgets. Just keep applying different filters to the keyword report.

What would be even better is if GA let me choose what integer value is displayed in the widget. So, rather than see visits, I could see conversions, or pageviews. What do you think Google?

‘Sticky’ filters work for all reports. Here’s another example. Let’s say you want to see geographic data segment by north american city. You can filter the Map Overlay report by city and then add the report to your dashboard. (I know this is technically segmentation and not filtering, but the results are similar).

Not only does this add more detailed information to my dashboard, but it also let’s me access a segmented Map Overlay report with one click.

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Tracking Clicks with GA Pt. 3: Advanced Implementation

April 9, 2007 by Justin Cutroni

Welcome to Part 3 of Tracking Clicks with Google Analytics! Last time I discussed the process and theory behind tracking visitor click data in GA. This technique is primarily used to track non-HTML files and outbound links. In this post we’ll discuss a quicker, easier way to implement the click tracking. Please make sure you’ve read Part 2 before reading this post.

Overview

Whenever we need to track clicks we use the following JavaScript code. This code automatically adds the urchinTracker function to appropriate part of your HTML at the appropriate time. With this script there is no need to change the HTML in your pages. You simple add this script to all the pages on your site and it does all the work for you.

You’re probably wondering how this all woks. I’m not going to get into the nuts and bolts, but this uses the DOM or Document Object Model. Using the DOM in the code gives us the ability to modify the HTML in real time.

About the Script

This script will only track clicks on anchor tags. It will not track clicks on images or other HTML elements.

If the anchor tag points to a different domain then urchinTracker() is executed before the visitor leaves the site and a pageview named ‘/outbound/<url>’ is created in Google Analytics. The <url> part is replaced with the value from the HREF attribute in the anchor tag.

If the anchor tag points to a non-HTML file then the scrip creates a pageview named ‘<path>’ where <path> is the value in the HREF attribute of the link.

Here’s an example of the script in action. The link below will take you to a test page where you can click on links to other domains and files Rather than send the data to GA, the script has been modified to display a message (note: a new window or tab will open in you browser).

GA Click Tracker Test Page

To view the code just look at the source of the above page. Right click on the page and choose ‘View Source’.

Installing the Script

Installing this script is simple. Copy and paste the code from the test page and place it in your web page. I place it before the closing BODY tag. After the script has been installed you can configure it to work with your site. Also, make sure that the Google Analytics tracking code is installed on the page.

Customizing the Script

There are a few customizations you can make to the code.

First, there is a variable named debug. When it is set to 1 the script will display a pop up window when a link is clicked. Set debug to 0 to disable the pop up. By default, debug is set to 1 (on).

Next, you can define the types of non-HTML files that this script will track. Find the variable named fileTypes. The value should look like this:

(".doc",".xls",".exe",".zip",".pdf")

To track additional file types just add the extension to the list. Make sure you match the text-formatting of the existing list.

Finally, you can change the way external links appear in the GA reports. By default, all external links will be preceded by ‘/outbound/’. If you would like them to appear differently change the extIdentifier variable.

Summary

There are lots of scripts like this. This is just our version. I hope it gives you some idea of what is possible and inspires you to create one of your own or modify ours. Just remember that this script will create additional data in your GA profiles. You many need to add a filter to deal with the extra data.

Please feel free to use and modify this script. The only thing we ask is you share the changes with others.

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Top 5 Google Analytics Resolutions for 2007

January 3, 2007 by Justin Cutroni

Happy New Year! I hope everyone enjoyed some quiet time during the holidays. Looking at my visitation data for the past 2 weeks it looks like many off you stayed off-line. I know I did!

I’d like to take a second and thank all of you who take the time to read this blog and provide feedback. I’d also like to thank the web analytics community for all their support and encouragement. Thank you, I appreciate it.

Here’s a light post to start the new year, a review of some important Google Analytics topics that I covered in 2006. I think that all of the posts listed below are very helpful to a new or experienced GA users. Without further ado, my Top 5 Google Analytics Resolutions for 2007.

5. I will always test my Google analytics settings using a test profile

Remember, an incorrect filter of goal setting can ruin the data in your Google Analytics reports. Bad data means bad analysis. Test all of your settings using a duplicate profile before changing the settings on a ‘production’ profile.

6. I will always tag my advertising links

One of the most useful features in Google Analytics is its ability to track online marketing campaigns. We all know that GA works great with AdWords, but it can also be used to track banner ads, CPC ads and even your off line ads. If you do any online advertising you should track the performance at the most granular level.

4. I will export data from Google Analytics and create my own key performance indicator and reports

I’m lazy :) I expect all the data I need for an analysis in one place. I don’t want to hunt through 4 or 5 Google Analytics reports to find the data for my analysis. I define key performance indicators for a site and monitor then using a single report. Take the time to export data from Google Analytics and into some other application (like Excel or PowerPoint) so you can instantly gauge the health of your website.

3. I will avoid the most common GA configuration mistakes

Getting Google Analytics set up correctly will insure the quality of your data. I’ve seen lots of GA setups, some good and some bad. I’ve got a series of posts describing some of the most common problems people make when setting up profiles:

Google Analytics Configuration Mistake #1: Missing Default Page
Google Analytics Configuration Mistake #2: Query String Variables
Google Analytics Configuration Mistake #3: Third Party Domains

Not sure if you have GA set up correctly? Here are a few ways you can identify configuration mistakes.

2. I will exclude myself (and my employees) from Google Analytics reports

While the data quality in Google Analytics may not be 100% accurate, you should try to make it as accurate as possible. One such way is to exclude all the traffic that you and/or your employees generate. If your office has a static IP address you can use a simple exclude filter. But, if you have mobile users or a rotating IP address you need another solution. I suggest excluding visitors using the Google Analytics custom segment technology.

1. I will understand that Google Analytics is a tool and Web Analytics is a process

Google Analytics provides data about how people find your website and how they use it. This data needs to be part of your normal business decision making process. Should we spend more on AdWords? Check the data. Should we change our checkout process? Check the data. Get the picture? You should have a process in place to use the data generated by your website. Even better, you should use the data generated by your website to identify new business opportunities.

Did I miss something? Feel like I don’t know what I’m talking about? Leave a comment.

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Answers to Your Google Analytics Questions… ON VIDEO!

October 14, 2006 by Justin Cutroni

Ok, here we go! I finally got around to answering some of your questions… ON VIDEO! How fun is this! My co-worker, and good friend, Mike helped me pull this off. Actually Mike did ALL the work. He shot the video, edited it and compressed it.

Today I answer the first three queststions in my queue. All have to do with Google Analytics.

1. Louis Kessler asks about third party shopping cart tracking
2. Robin Steif asks about viewing a statistical distribution of data
3. Rob asks about tracking site specific cookies

If I did not get to your question I will get to it soon.

I will say this… I look TOTALLY stiff in the video! I have way more personality, HONEST! Hopefully I’ll meet a few of you at eMetrics next week where I can prove it.

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Google Analytics: How to Tell When Something is Wrong

October 12, 2006 by Justin Cutroni

I’ve written about some of the most common Google Analytics configuration mistakes. But how do you know if you’ve made one of these mistakes? What can you do to insure that a profile is set up correctly after it’s collecting data? Here are a few things you can check to make sure everything is running smoothly:

1. Compare your GA data to another source

Comparing the data in Google Analytics to the data in another application is helpful. I prefer to compare GA data to data from other types of applications BUT not other web analytics applications. A transactions system, a CRM system or any other system that collects data can be used. If the data is off by more than 10% to 15% then there is probably a problem.

Today I was working with a client that had a large discrepancy between the number of goals in GA and the number of ‘goals’ in their internal order system (60% delta). After looking at the profile we identified an issue with their configuration which was causing the problem.

I don’t like comparing GA data to that of another web analytics application. Why? Primarily because each application tracks data in a different way. This makes it very difficult to identify if there is a problems with Google Analytics or if the discrepancy is due to the differences in the applications.

2. Look for ‘(other)’ in your reports

If you see a line item for ‘(other)’ in some of your GA reports (like the Top Content report) then there is something wrong with your profile.

Each Google Analytics account has a data storage limit. That means that your account will only hold so much information. Once you reach that limit Google Analytics will continue to collect data BUT it will be recorded in a nondescript record named ‘(other)’.

Here’s an example. Let’s say that GA limits you to 10,000 records in each database table*. One of those tables records unique pages. Your website is huge, it has 200,000 unique pages. Obviously something has to give. You can’t fit 200,000 records into a 10,000 row table.

What happens is GA tracks the first 9,999 unique page views correctly. When GA tries to record the 10,000th page view it stops because it knows that it’s about to record the 10,00th record and that will be the last record in the database table. Rather than record the data, GA creates a ‘bucket’ to catch all subsequent data. This bucket is called ‘(other)’. So, for every unique page greater than 10,000, the counter for ‘(other)’ is incremented by one. GA is still tracking the total number of unique pages, it’s just not identifying them uniquely.

This means that perfectly valid page views will be missing from your reports. It also means that any features, like goals or funnels, that depend on these page views will also malfunction.

If you see ‘(other)’ in your reports check your profile configuration. You’re probably filling your database with bad data. You may need to exclude some query string parameters. Read Google Analytics Configuration Mistake #2: Query String Variables or the official Google Analytics help docs.

* DISCALIMER: I have no idea how much data a GA account can hold. I picked the number 10,000 randomly.

3. All your e-commerce referrals come from your domain

If you have an e-commerce website, and all your transaction referrals are from your own domain, then there is a problem. Or, if you have e-commerce data but no values for $Index then you may have a problem. These are two symptoms of the same problem.

I usually see this problem when people have not followed the configuration instructions for a third-party shopping cart. The GA tracking cookies are not transferred correctly between the two sites causing the report data to be incorrect.

You can read the official Google Analytics support instructions or read my post about third party domains.

One more thought about Google Analytics data…

Don’t freak if there are huge chunks of data missing from your Google Analytics reports. From time to time the Google Analytics team updates the GA system. This can cause your reports to loose data. Be assured that your data is still there. The system is probably just slow in processing the data.

If Google is NOT updating they system then you should worry :)

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Configuring Google Analytics for Business Success

October 10, 2006 by Justin Cutroni

A couple of weeks ago I wrote about the two types of Google Analytics configurations: the technical configuration and the functional configuration. I’ve been explaining the technical configuration with a series of posts called ‘Top Google Analytics Configuration Mistakes’. Now I’m finally going to tackle the functional configuration. Don’t worry; I’ve got more posts about GA configuration mistakes coming!

The Google Analytics functional configuration is where we make sure Google Analytics will collect the data that an organization needs. During this process we spend less time working with GA and more time talking to individuals within an organization. Remember, Google Analytics is just the tool that collects the data for our analysis. It’s one part of the web analytics process.

I like to think of the functional configuration as a melding of GA knowledge and organizational needs. Knowing which metrics are used by an organizations drives the data that needs to be collected by GA. Knowing which data needs to be collected drives how we set up GA. See how it’s all connected?

How you actually go about defining what the data needs are for your organization takes time. Set up meetings, talk to people and learn. Some may not think that the process is worth it or understand the value. Believe me, this process is very important. If you can’t measure success how will you know when you reach it?

Here are a few things to consider when thinking about the functional configuration:

1. Find out who is going to use the data.

Different people in different parts of an organization will want different information. Take the time to sit down and see how they use analytics. Think about what they’re asking for and how GA works. Can GA deliver what they need?

Here’s an example. I like to report the Depth of Visit and Time of Visit for various marketing activities (email campaigns, AdWords campaigns, etc). By default, this info is not available in a standard GA profile. To solve this problem I create a profile specifically for the marketing activity (using an include filter based on the campaign name). All the reports in this campaign specific profile, including the Depth of Visit and Time of Visit reports, are for one marketing activity.

2. Don’t think in terms of GA reports, think in terms of equations.

Learn how your user’s metrics are calculated. If the report they need is not in GA can it be created based on the raw data in some other GA report? Personally, I always extract data from GA and create my reports using other tools. This method lets me create the exact metrics I need for a client.

3. Set expectations.

This is very important. Google Analytics may not be able to provide all the information you need. It’s just a simple fact of life. But remember to be creative when addressing someone’s data needs. I never say ‘no’ without thinking about a problem. I always try to use the functionality within Google Analytics to ‘craft’ a creative solution.

4. Think about the future.

One of the biggest challenges in using Google Analytics is you can not re-process data. This limitation has some implications. For example, there is no way to segment your data using a custom variable after the data has been processed. If you can plan ahead, and anticipate what data you organization may need, then you can configure GA to meet those needs.

I can’t tell you how many times a client contacts us and complains about their GA setup. After we spend a few minutes with them we realize that there is no problem with their configuration. They simply don’t know what data they need. Take the time to understand how GA data fits into your organization. Talk to people. You’ll save yourself time in the long-run.

There you have it. What I’ve learned from working with many, many clients. Do you have some experience with GA that you’d like to share? Or do you think this post is junk? Your feedback is always appreciated.

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