Analytics Talk

Visit Vermont for Online Marketing BootCamp

October 30, 2007 by Justin Cutroni

On November 12-16 we’ll be holding our second Online Marketing BootCamp. This 5 day event is a series of talks and training sessions about online marketing and how to power your online marketing with Google tools. We have sessions ranging from the State of Online Advertising to Advanced Google Analytics Configurations. Can you guess what I’ll be speaking about? :)

We learned a lot from our first Boot Camp. Based on participant feedback we’ve re-tooled the format and the content. Even if you attended the first BootCamp you’ll probably find something new this time around.

I think one of the best parts of OM BootCamp is the format. Each day is focused on a specific part of online marketing. Interested in testing? Come to the testing day. Want to learn about analytics? Come to the analytics day. Come for a day or for the entire week; it all depends on what you want to learn.

Each day ends with an Ask the Experts session. These informal meetings provide a relaxed environment where participants can work through specific issues with speakers. Got a really hard GA question? I’ll be there to help. This is what I’m most excited about, working directly with people.

If you’re interested in OM BootCamp, or if you have any questions, email us at info -AT- epikone . com.

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Give Me What I Want and I’ll Do What You Ask

October 7, 2007 by Justin Cutroni

I’m not a testing guru. I love testing and think it’s a vital part of the web analytics process, but I’m still learning about the ins and outs. One thing that I have learned is that there is more to testing than changing the color of a button or the format of an email. It is equally important to test the offer that you’re making to the customer. Which works better, ‘20% Off’ or ‘Free Shipping’? Unless you test both you’ll never know.

This week I was reminded how important it is to test the offer when I received an email from Northwest Airlines. I don’t fly NWA much, but I have in the past. Anyway, what really caught my attention was, you guessed it, the offer.

I don’t know about you, but I’ll do almost anything for frequent flier miles. What a great deal, I can get 1,000 miles AND reduce my postal mail. Sign me up! The offer was perfect for me. Would I have taken to the time to subscribe to their email if they did not offer the frequent flier miles? Probably not.

There are so many things that NWA could have tested. First, they probably tested the offer. Then I bet they tested how many miles they needed to offer before someone would convert. Would I have enrolled for 500 miles? Probably not. I wonder if they tested the subject line of the email? I think more people would respond to the message if the offer was in the email subject line, but I could be wrong… Another benefit of testing the offer: understanding the financial impact, i.e. ROI, of the offer.

The bottom line is testing the message is just as important as testing your formats and layouts.

Tracking Email Conversions with Google Analytics

This post would feel naked if I didn’t mention something about GA. :)

The key to measuring the effectiveness of an email offer is identifying how many conversions occur. Measuring email conversions is pretty easy with Google Analytics. It all starts with link tagging. If you’re unfamiliar with link tagging then you may want to take a moment and review how it’s done. Testing emails with GA starts with creating different variations. Once the variations have been created you need to tag the emails so GA can identify each one.

Add a utm_campaign, utm_medium, utm_source and utm_content parameter to each link in each email. While the campaign, medium and source parameters can have the same values, each variation should have a unique content parameter. The following table lists the query string parameters for a simple A/B test.

Email Variation 1	Email Variation 2
utm_campaign=my-camapign	utm_campaign=my-campaign
utm_medium=email	utm_medium=email
utm_source=my-source	utm_source=my-source
utm_content=20-off	utm_content=free-shipping

After you’ve sent out the email, use the Traffic Sources > Ad Versions Report to measure the traffic volume and conversions generated by the message. The Ad Versions report shows a line item for each utm_content variable. Note: you should know that this report, by default, contains information from AdWords. If you’re using auto-tagging then GA will automatically pull in the title of the ad that the visitor clicked on. Just keep that in mind when you open the Ad Versions report and see more data than you expected. :)

You can also get creative with your link tagging. I like to add a lot of information in the utm_content variable. In the example above I added the offer that was different in each email. I could also add information that identifies which link in the email that the visitor clicked on. Here’s an example:

Email Variation 1	Email Variation 2
utm_campaign=my-camapign	utm_campaign=my-campaign
utm_medium=email	utm_medium=email
utm_source=my-source	utm_source=my-source
utm_content=20-off:top-nav	utm_content=free-shipping:main-image

Adding additional information to utm_content creates a lot of data and sometimes it is not useful. Plus, many email distribution tools will also report which link visitors click on, so this technique can create duplicate data. But the option is there if you want to try it.

So there you have it. Don’t forget to test different offers in your email marketing. And there is no better way to measure email conversions than with Google Analytics.

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Tip: Make Sure Your Site Works

September 2, 2007 by Justin Cutroni

I just read a great article by Bryan Eisenderg about Conversion Rate Basics. He points out some simple things that you should do to insure your site is converting visitors. This got me thinking about an experience I had earlier this week.

On Wednesday (August 29, 2007) I received a message from NetFlix regarding their video on demand service . I’m a big fan of on demand video so I decided to click on the email and view the offer. Imagine my surprise when I was greeted with the following message on the NetFlix website:

Now the site was not down long and this may have been an unforeseen problem. But the lesson is clear: make sure your site works. If it doesn’t you’re going to loose business.

Here’s a similar example. We started working with a client who uses their website to generate sales leads. While evaluating the website we found that their main lead generation form, if filled out incorrectly, would display a plain white screen to the visitor. No web page, no error message, no nothing. Just a plain white page.

How can you protect yourself from unexpected downtime? Try a site monitoring service. I’ve never used one but assume they all function the same way. At some given interval, say 2 minutes, the monitoring service makes a request to your website. If the web server returns an abnormal result then an alert is sent to the responsible party. The company usually charges a small monthly fee for this service. Does anyone out there have an experience with a site monitoring service they would like to share?

But what if the NetFlix issue was not unforeseen? What if the email blast was sent during the website’s scheduled maintenance period? To me, that indicates a lack of process. There should be been some type of process in place that stopped the email blast from going out while the website was down. From a web analytics standpoint, I always want to know when a client is sending out emails so I can insure that it is tagged for tracking. How about adding a step to the ‘email blast process’ to check the website status before sending out the email? I know it doesn’t seem complicated, but unless checking the website maintenance schedule is a documented step in a defined process it could go undone.

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Segmenting Members from Non-Members

August 29, 2007 by Justin Cutroni

Do you run a subscription based website? You know the type of site: customers pay you a monthly fee and you give them access to valuable content. I’ve worked with a number of clients with this business model and have noticed that many make a consistent mistake when setting up their analytics package: they fail to segment people who subscribe to the website (i.e. members) from those who do not.

Why is this so important? Here’s an example. The following image shows some real data that is not segmented other than the removal of internal employees:

Now, here are the same metrics with members removed:

Big difference, huh? Just image how this changes all those metrics that are calculated using Visits, like conversion rate, abandonment rate, etc.!

It doesn’t matter what analytics tool you use. If your website has some type of member’s area you need to segment out members to get an accurate view of your website performance and online marketing activities.

The Google Analytics Way

If you’re using Google Analytics the implementation is simple. Use GA’s custom segmentation feature to identify and segment members. Remember, the custom segmentation features uses a JavaScript function, __utmSetVar(), to set a cookie, named __utmv, on the visitor’s machine. The cookie is a persistent cookie and lasts for 6 months. You need to call __utmSetVar() when a member identifies herself. You can put it on a ‘thanks for logging in’. Here’s a perfectly good implementation of the code:

<script type="text/javascript">
__utmSetVar('member');
</script>

Remember, the above code snippet should appear AFTER the standard Google Analytics tracking code. The reason is that the __utmSetVar() function is in the urchin.js file. So if you try to call __utmSetVar() before the urchin.js is loaded by the browser then the visitor will receive an error.

Once the cookie has been set on the visitor’s machine you can use the custom segment value to exclude them from a profile. The exclude filter would look something like this:

Any profile that has this filter will only show data for those visitors that are not members thus providing a more accurate view of how effective the website is at converting visitors.

And let’s not forget about the members. You can create a profile that only includes members (the filter settings are almost identical to the filter above, just change the filter type from ‘exclude’ to ‘include’). By creating a profile specifically for members you can focus on their usage of the member’s area. For example, the Top Content report will identify the content that they find most engaging. You could also use some of the loyalty reports to see how often they use the website.

Tip: Tracking Different Subscription Levels

If your membership model has various level, like Gold, Silver and Bronze, you can include this information in the custom segment value. This allows for a more detailed analysis of each membership level. Just modify the value you pass to the __utmSetVar() function. For example:

<script type="text/javascript">
__utmSetVar('member-gold');
</script>

or

<script type="text/javascript">
__utmSetVar('member-silver');
</script>

or

<script type="text/javascript">
__utmSetVar('member-bronze');
</script>

After the custom segment cookie has been set you can create different profiles for each subscription level. Use the filter shown above, just change the value for Filter Field to match one of the values in the code above. Then you can use the profiles to analyze the member data and observe their habits.

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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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Tracking Google Audio Ads with Analytics

June 4, 2007 by Justin Cutroni

Today the Inside AdWords blog announced that the AdWords team has completed their beta test for audio ads. They are now in the process of rolling out access to all AdWords accounts. I was pleasantly surprised that my own personal AdWords account now has audio ads. Look out America!

Anyway, this got me thinking. What measurement capabilities have been built into the system? I haven’t done any audio ad analysis, but how different can this be from tracking other offline advertising using web analytics? It turns out that Google has integrated a call reporting system that can be used to measure the volume and geographic density of customer response to an audio ad. From the audio ads support docs:

Call reporting is an easy, free way to track customer responses to your audio ads campaigns. With call reporting you add a special phone number to your audio ads. When a listener calls the number Google records the time and location of the caller and forwards them on to your main business number.

This is all very good, but in today’s world of multi-channel business you need to combine the call data with web data. Not everyone is going to remember your phone number (unless you have a catchy jingle and repeat it over, and over, and over… Red Sox fans know what I’m talking about… 1-800-54-GIANT!) Luckily almost every analytics package on the market can help you identify the impact an audio ad has on your online traffic.

Segmentation is the Key

What better way to measure the impact of geo-targeted advertising than through the use of geo-segmented web data? Most analytics tools, including one that I have a soft spot for, lets you to segment your web data based on geographic location.

Obviously you should see a good bump in web traffic coming from the geographic areas where your audio ads are running. Make sure you segment the data by date/time to appropriately isolate the dates/times that your ads ran. Don’t just segmenting using geo-segmentation. You must continue to drill into the data using other segments.

If you can segment your geo-data by referral source you will gain even more insight into the effectiveness of the advertising. If your geo-data contains a large number of direct visits then it is probable that the visitor remembered the URL from your ad and typed it into the browser.

If your geo-data had a high percentage of organic search engine visits (probably using branded keywords) then it the visitors probably forgot the contact information from your ad but remembered your company name, or some other aspect of your brand, and used a search engine to locate your site.

It may be useful to analyze the non-branded keywords originating from the geographic region where your audio ads are running. This can provide insight into the overall message that your ad is generating among listeners.

Don’t forget to analyze the outcomes from this data. How many conversions occurred from the geo-segemented direct traffic or branded search traffic? Conversions are crucial to measuring the return for your audio ads.

You can also compare your web data with the call reporting data from Google to get a good picture of the overall impact of your audio ads. You could even create some cool KPIs for audio ads using the combined data set. For example, an audio response rate could be calculated using the following metrics:

Audio Response Rate = ( the number of web visits + the number of calls ) / impressions

Just for your reference, Google estimates the number of impressions using data from Arbitron.

Don’t forget to segment the above KPI using time, date and geographic location :) Then you can fine tune your audio ad buys.

A Better Way to Track

The one thing that bothers me about the above process is that it is fuzzy. Sure, the quality of web data stinks, but inferring that all traffic from a geographic region during a specific time, even if you know exactly when the audio ads were running, is a bit too loose for me. There is a more reliable way to link the offline world of audio ads with online tracking.

Using a vanity URL in offline advertising, including audio ads, is a better way to link offline advertising to online traffic. This technique is very common in print advertising. Vanity URLs are easier for people to remember and can be more indicative of your offer. I wrote a small blog post about offline campaign tracking which is a good primer. A better resource is Google’s Conversion University, which has a very good piece on tracking offline campaigns.

The concept of tracking an offline vanity URL is simple. When the visitor enters the URL into the browser they are redirected to a new landing page. During the redirect special query string parameters are added to the URL that indicate which ad the visitor is responding to. This method provides a more reliable way of linking an offline ad to a customer response. No more inferring that direct traffic to your site, from Mountain View, on a Thursday between 8 AM and 12 PM, was from a radio ad.

My Vision for the Future

Finally, how long will it take for Google to integrate audio ads with Google Analytics? I’m 99% sure it’s on the radar (just like integrating DoubleClick and FeedBurner with Analytics), but here’s how I would do it.

First, when you create an audio ad the system it will ask you if you want to activate call reporting (which is available now), web reporting (aka Google Analytics) or both. If you choose web reporting, the system will ask you for two pieces of information:

1. A vanity URL that will be used in the ad
2. The actual landing page that you want the visitor to see when they type in the vanity URL

After you submit the information the system will check the availability of the vanity URL. If it is already registered, and you own it, Google will confirm your request. If the vanity URL is not registered Google will register it for you. Then the system will check the actual landing page to make sure it is tagged with the Google Analytics tracking code. If it is not, then it will warn you that the page is not tagged and verify if this is ok. Who knows, maybe you want to use another analytics application to track your audio ads. If it is tagged then Google will confirm that the tracking is in place. That’s it. No other setup would be needed for tracking.

When a visitor types in the vanity URL Google will automatically redirect the visitor to the actual landing page. During the redirect the system will automatically tag the URL with the appropriate link tags to identify that the visitor originated from an audio ad. The system will embed critical information about the audio ad in the link tags such as:

• when the ad aired
• which market it aired in
• which station it was on
• the version of the ad

Essentially, this integration would be very similar to the AdWords auto-tagging feature that currently exists. It’s flexible enough to simplify the tracking setup for GA users and still lets non-GA users track their audio ads with other analytics applications. Obviously this is pretty vague, but it could be done.

Conclusion

In the end, it doesn’t matter what analytics tool you’re using. As long as you have some plan to track the performance of your audio ads.

So, what do you guys think? I’d love to hear from anyone out there that is actively tracking audio ads.

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Understanding the New Google Analytics Interface

May 8, 2007 by Justin Cutroni

I’m not going to sugar-coat this. The new Google Analytics reporting interface is radically different than the old reporting interface. It will take you some time to get comfortable using the new version. You may even be lost the first time you log in. Don’t worry, you’ll get used to it. In my opinion, understanding WHY the interface changed so much will help speed the learning process.

An Overview of the Concept

The new interface is designed to help you analyze your data. I know that may not seem possible, but that’s the reason. Let’s take a step back and think about analysis.

The key to analysis is to keep asking questions. Whenever you examine a metrics you should always ask a follow-up question. For example, let’s say you had 10,000 visits yesterday. That’s great, but you should be asking, “Where did they come from?”

The new user interface helps you answer those questions more intuitively. The data is presented AND CONNECTED in such a way that it almost forces you to ask the questions. It also provides the answers to those questions. This is really, really powerful because it will prompt, or force, people to ask questions about their data. When you get right down to it, the interface is holding your hand and leading you through a segmentation process.

Drilling Down: the process of Segmentation

Let’s look at an example.

Here is the Search report from the new GA. You’ll notice that the report shows ALL traffic coming from search engines. This includes paid and non-paid. If you want to segment the traffic, and separate paid and non-paid traffic, just click on the appropriate link at the top of the page.

Once we’ve segmented the data by paid and un-paid I can drill down even further using the segmentation feature. In the old GA the custom segmentation option was attached to each line of data. Remeber the little red chevron? In the new interface the segmentation option is a drop down box below the verbal description of the report. So, if I choose Landing Page, and yes you can now segment by landing page :), Google Analytics will segment the entire report by the landing pages used for non-paid search. After segmenting, the resulting data set is the performance of non-paid landing pages. If click on the ‘Paid’ link and instantly see how the landing pages for your paid campaign performed. People are going to love that feature! Talk about making a case for landing page optimization.

Let’s take a step back ‘up’ and segment the report by source. If I click on a search engine GA will display all the keywords for that search engine.

Context for your Data

Another really cool way that GA helps you understand your data is by providing context within the interface. You probably noticed that there are three tabs along the top of your report data. The first tab is the Site Usage tab. It displays the percentage of total that the current data set represents. For example, the previous image shows that Google sent 17,055 visits via search which was a total of 22.75% of all traffic. See, context for your data. It relates the current information to the big picture.

Segmenting by Success

The other two tabs let you perform a different type of segmentation. The Goal Conversion tab shows you the conversion rate for each line item in the report. AND, the column headers no longer say G1/Visits! They actually use the NAME OF THE GOAL!

The E-commerce tab displays revenue based columns for each line item in the report. The e-commerce tab will only show up if your profile has been configured to be an e-commerce profile.

Finally

The new Google Analytics uses your data to help tell a story about your website. The way the new reports are organized and linked together can literally lead you through an analysis and help you uncover answers as you browse the reports. It will take some getting used to, but in the end, this new presentation of data will help lots of people. I truly believe that the new interface will help a larger population of users tackle analysis and not just reporting.

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Get Ready for Testing with Website Optimizer

April 4, 2007 by Justin Cutroni

Ok, I’ll bite. I’ll jump on the bandwagon and post about Google Website Optimizer (WO). It seems that everyone is writing about it today so why not one more post? :)

We’ve been using WO for over a year and love it. It’s easy to use, very inexpensive (actually free) and provides tremendous value.

But what I’d like to stress is not the product, but the PROCESS. All of us know that testing is just one phase in our beloved Web Analytics process. Theoretically we should all be testing right now or else we’re just finding problems and not improving visitor experiences. The great thing about Website Optimizer is that it gives us all a robust testing platform.

If you’re new to testing then I urge you to learn about the testing process before diving into Website Optimizer. I know it’s tempting to jump right in and start using the tool, but read about the process first.

Why Process Matters

Testing, more than almost any other part of the web analytics process, needs to be structured. Why? Because if you do not methodically define what you are testing and how you will measure success, you may not know if your test actually worked.

Here’s something I rant about all the time…

Many people believe that all tests are measured using one simple metric: conversion rate. I disagree. While conversion rate may be affected by your test, there are many micro-actions that can, and should, be tested.

For example, let’s say you want to test your add-to-cart button color. You’re testing the color of the button to invoke an action from the visitor. What is the action? To get the visitor to click the button and add the item to the cart. Yes, the action of adding the item to the cart influences the overall conversion rate by moving the visitor through the conversion process, but when you design your test you need to know which action you want to measure. The goal of this test may be to increase the number of visitors who add an item to their cart by 10%, from 50% to 55%.

Where to Start

So, what are some good testing resources? How about Avinash’s blog. He’s got a great post entitled Experimentation and Testing: A Primer. Start there and then head over to FutureNow. They’ve got some great books about how to actually test. You can find two great starter guides at their online store. If you’re already familiar with the testing process then check out the Website Optimizer help section and start reading.

You’ll start to see more posts on this blog about WO and testing. Some posts will focus on the process and some about the tool. Kind of like my approach to web analytics and Google Analytics.

If you’ve been working with WO please feel free to comment, I’d love to hear you’re reaction to the product.

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An Analysis of My Data

March 5, 2007 by Justin Cutroni

I’ll be honest, it has been a long time since I looked at the analytics for this blog, I just haven’t had any time. Work has been flat-out busy since January 1. That’s also the reason that my posting has been very light.

Anyway, I logged into GA today to check some stats and was surprised by some of the data. I thought you all might be interested in the basic process I used to figure out what happened.

The Big Picture: What’s happened Since January 1

Since I haven’t reviewed the traffic data for a couple of months I started by adjusting the date filter to cover January 1 to March 4. Here’s the Executive Overview report:

Notice anything? What the heck happened around February 1st? Obviously some website drove a ton of traffic to the blog. Was it Digg?

Drilling Down: When did it Happen?

Before I get ahead of myself and try to figure out where the traffic came from, let’s determine exactly when it happened. I’m going to use the date filter to drill down and isolate when the date happened. If I hover my pointer over the data above GA shows that the spike occurred on February 1.

If I adjust the date filter one more time to cover February 1 we can see there was a big jump in traffic at 8 AM:

Now we’re getting somewhere. Now that I know when the spike happened I can start to figure out where the traffic came form?

Getting Closer: Where did they come from?

I’m trying to figure out where the traffic came from, so I’m going to look at referral information using the Marketing Optimization > Visitor Segment Performance > Referring Source report. This report segments the site traffic based on where it originated. When we look at this report we should immediately know where the traffic came from:

A ha! I was Stumble-Uponed! For those of you unfamiliar with StumbleUpon, here’s a description from their website:

People-Driven Technology:
Using a combination of human opinions and machine learning to immediately deliver relevant content, StumbleUpon presents only web sites which have been suggested by other like-minded Stumblers. Each time the ‘Stumble’ button is clicked, the user is presented with a high quality web site based on the collective opinions of other like-minded web surfers.

Based on this description I’m going to say that StumbleUpon drives qualified traffic to my site. We like qualified traffic, it usually converts better :)

Is there anything else to know?

What else can I learn about these people? First, they didn’t convert on any of my GA goals! I can see this in the above report. There is a 0% conversion rate for Goal 1 and Goal 2. This means that they didn’t do what I wanted them to do. (The goals for my website are to sign up for the RSS feed and to use the contact form). What’s disturbing is that this was qualified traffic! Is this indicative of a problem with my website? Why didn’t these people convert?

I’m going to dig deeper by cross segmenting the data in the Referring Source report. I’m trying to find out more about these people that came to my site from StumbleUpon. Did they come to the site before (i.e. how many return visits?):

Not too many return visits, almost all new visits. So I now know that StumbleUpon drove 136 new visits to my blog in about one hour and none of them converted. Wow, that’s a complete bummer.

Summing Up

I could dig a bit deeper, and look at how the visitors from StumbleUpon navigated the site. But, with an average number of pageviews below 2 I’m not going to discover too much. There are some lessons to be learned here:

First, I should have been paying closer attention to my reports. I probably don’t need to review them daily, but I should review them once a week. Also, I’m going to dig a bit deeper into my new visitor segment. I really think I may have a problem converting new visitors. But that’s another post for a later time :)

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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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