Analytics Talk

Surprise! New Google Analytics Features

December 13, 2007 by Justin Cutroni

It looks like the team at Google Analytics has surprised us all with some new features. What a great way to celebrate the holiday season. Many of these new changes were actually announced by Brett Crosby at Emetrics and are just now getting rolled out to all of us.

New Multi-Line Graph

Google has added a new features to help with analysis. It’s called multi-line graphing. We now have the ability to graph multiple lines of data in the data-over-time graph that appears at the top of each page. There are two ways to use this feature.

First, you can compare two metrics in the graph. This is a great way to determine if there is a correlation between the two numbers. For example, let’s say you want to see if conversion rate stays the same if visits increase. Now you can do that.

The second way to use the multi-line graph is to compare a specific segment of data to the overall site data. This helps you analyze how much the segment of data affected the larger set of data.

The graph below shows AdWords visits (blue) and the total site visits (gray). We can clearly see that there was a big bump in traffic but it was not caused by AdWords.

I’ll have a more in-depth post on this tomorrow.

New ga.js Tracking Code

The new ga.js tracking code is now live. For those of you that don’t know, Google created a new version of the tracking code that supports many new features, primarily event tracking.

The new tracking code is very different. Many of the functions that exist in urchin.js do not exist in ga.js. Things like urchinTracker() and __utmSetVar() are gone. Don’t worry, they’ve been replaced with new methods like _trackPageview() and _setVar().

You don’t need to migrate to the new ga.js, you can continue to use the old urchin.js. However, Google will not update urchin.js in the future. If you want to take advantage of new features you must upgrade.

Check out GA.JS: New Google Analytics Tracking Code for more information about why the basic page tag has changed, how it has changed and if you should upgrade to the new tracking code.

To help facilitate the transition, Google has published a migration guide to help you transition from urchin.js to ga.js. It’s a great resource that does a good job of mapping old tracking code settings to new tracking code settings.

How do you get the new tracking code for your site? For existing websites, there is a new tabbed interface that provides the urchin.js tracking code or the ga.js tracking code. Just click on the “Check Status” link for a profile and you’ll see the tabs. Google will automatically supply the new ga.js tracking code when you create a new profile.

Caution: do not use the new tracking code and old tracking code on the same page. However, you can use the new tracking code on some parts of your site and the old tracking code on other parts of the site.

Subscribe:

10 Comments »

Event Tracking Pt. 3: Reporting & Analysis

October 16, 2007 by Justin Cutroni

This is part three of a three part series about event tracking in Google Analytics. You can find more information in these other posts:

Event Tracking Pt. 1: Overview & Data Model
Event Tracking Pt. 2: Implementation

I wrote this post before having access to the new events reports. As a result, I don’t have any screen shots for you guys! Sorry I don’t have anything to show you guys, but I will try to explain as much as possible.

The new event reports section will have specific reports for objects, actions and labels. If you have not read my post on the event data model then I strongly suggest that you do so. The data model is the driving force behind the structure of the reports.

Event reports will let you see summary information at an Object level, action level and value level. Here’s an example using Google Maps. If we create a ‘Map’ object then we will get a unique count of how many times the map object has been created. We can then drill into that event and see the actions and values of those actions.

Map
|_ Click Map View
|_ Satellite
|_ Hybrid
|_ Map
|_ Traffic
|_ Street view

This drill-down functionality is very similar to the drill down that you can do with campaign tracking.

The interface will also show you the values of each label. Remember, Satellite, Hybrid, Map, Traffic and Street view, are all labels and they have an associated value. GA will total up the value and show a unique count of how many times each action happened, the total value and the average value.

This is fantastic information because we can now measure what people are doing on our media rich pages. We no longer need to rely on Average Time on Page to gauge the success of our content.

I know this is really high level, and I’m sorry I don’t have any screen shots, but I’ll try to get some soon. Hopefully you got a taste of what is possible with the event reporting.

Subscribe:

6 Comments »

GA On Site Search Pt. 2: Reporting & Usage

October 16, 2007 by Justin Cutroni

This is part two in a two part series about the new GA on site search reports. In part one I discussed the setup.

There is a tremendous amount of information in the new Site Serch reports about ow your visitors interact with your search engine. But it goes way beyond measuring how many searches occurred for a keyword. The new reports actually tie outcomes to searches providing insight into what product sand content your site visitors are looking for. But enough babble, on to the screen shots.

What Reports are Available

First and foremost there is the Usage report. This reports helps you understand if visitors are using site search. If you’re trying to push site search as a navigational tool for your visitors, and only 2% of site traffic is using site search, then your navigation may not be working. You may want to change the visibility of the search box.

The Usage report is pretty good, but everyone wants to know what people are searching for. The Search Terms report contains all of the search terms that visitors entered into your on site search. One thing you should know is that GA is reporting UNIQUE searches. This means that duplicate searches, made in the same visit, are excluded. So it is not a count of how many times a term was search for, but rather how many VISITS contained a search for a specific term.

Take a look at the narrative at the top of the report. It contains a number of new metrics to evaluate on site search. Total Unique Searches indicates what search terms people are entering. % Search Exits indicates what percentage of visitors are leaving immediately from the search results page. This could indicate that visitors are unhappy with the search results. Time after Search and Search Depth indicate the engagement of the visitor after using search.

Google Analytics does not normalize the search terms. This means that misspellings and similar searches are not grouped together. So the search terms ‘red sox’, ‘red socks’ and ‘Red Sox’ would appear as individual line items. You’ll need to review your data and manually normailze it using filters.

Another really cool report is the Site Search Start page. This report shows where your site searches originated. It identifies the page that the visitor was on when the seach occured. This can help identify issues with navigation or the data architecture.

Now we know where people started their searches, but what about where they end up? The Search Destination Report shows which pages people navigate to directly from the search results page.

What’s really cool is if we click on a destination page that is listed in the above report we can see all the search terms that drove people to the page. Here’s what happens if I click on one of the results in the previous report:

There are other reports that do a good job of illustrating how visitors use site search. If you select a search term in any reports you can do a really deep analysis using the analyze drop down. One option is the Search Navigation report. This report shows where someone started their search and where they went after the search.

What about peple who search multiple times? Another analysis option is to use the Search refinement report. This report shows how people refine their search terms during their visit. So, in the image below, visitors began by searching for dog. Then they refined their search using one of the terms in the report.

Ok, one more thing about the Search Reports. Notice that the standard Goal Conversion and Ecommerce tabs exist on most reports. These tabs provide information about which searches lead to conversions and, if you’re an e-commerce site, the revenue that each generated. Pretty darn cool is you ask me.

What’s Missing

The one report that is missing from Google Analytics is the ‘0 Result’ searches. It’s really important to know what on site searches are producing 0 results. This is an indicator of missing site content. You can artificially create this data by creating an event or a pageview (I suggest event) in Google Analytics. I’ll write more about how to do this in another post. But be aware that the new reports to not contain this data.

In Summary

There is a ton that you can do with the new on site search reports. Not only can you analyze what people are looking for and optimize your content, but you can also identify how visitors integrate search into their visit.

Have fun with these reports!

Subscribe:

3 Comments »

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.

Subscribe:

5 Comments »

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.

Subscribe:

7 Comments »

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.

Subscribe:

2 Comments »

Poor Landing Pages: My Experience Tonight

March 9, 2007 by Justin Cutroni

I’m pretty excited. I’m buying one of those super cool flat screen TVs. I’m going to get a Sony and hook it up to an AppleTV. I’ve got about $1,500 to spend and am ready to act.

Imagine my surprise when I opened my in-box and found an email with the following subject:

Sweet! Not only did I get an email from an electronics retailer, but one focused on a product I am currently shopping for. The email subject even mentioned the brand I am most interested in! Good job email marketing guys, you got me to open your email. Here’s what it looked like:

Great! Right at the top of the email is a banner advertising Sony HD TVs. Again, nice job. I’m going to click on that banner and get me a TV! I can’t wait to watch The Office in HD!

Here’s the landing page on Fry’s website:

Um…. Ok… I see the same banner, but where are the Sony HD TVs? Actually, I don’t see any TVs. Well, maybe I need to click on the banner again. So I clicked the banner again and nothing happened. I get the same page. After a few seconds of looking around I left the site.

Fry’s did a great job at getting me to their website. BUT, once I was there I didn’t find what I wanted. The message they presented in the email did not match what I received on the website. So I left. This is the consept of ’scent’. As Bryan Eisenberg explained in a 2004 ClickZ article:

What I find most exciting about current information-scent research is it forces the question, “What’s most relevant to the customer?” The end result can only be a Web site that contains not only the relevant product or solution but also the relevant scent and content to get the customer to it. That smells really good to me.

How could they have made it better? Well, if you’re going to advertise Sony HD TVs, then show me Sony HD TVs. It’s not rocket science.

Let’s take this one step further. How could a Fry’s analyst discover this? Use the following data points:

• Number of Emails Sent
• Number of Emails Opened
• Number of Click Throughs
• Number of Landing Page Bounces

With those simple numbers an analyst could illustrate the experience I went through. Here’s how I would do a simple analysis. Pull the numbers and put them in a table:

See that drastic drop off at the landing page? 90% of people that click through from the the email bounce when they get to the landing page. That’s REALLY high!

The point is, see how I can quickly gauge what’s wrong with my campaign using some basic metrics.

Hopefully someone at Fry’s is reading this :)

Subscribe:

1 Comment »

Google Analytics Cross Segmentation: Something You Should Know

March 6, 2007 by Justin Cutroni

Google Analytics has a great feature called Cross Segmentation. Using this feature you can ‘drill down’ into your data to gain more insight. However, there is one thing that all GA users should know. Sometimes cross segmenting data does not produce the desired result.

Example

I’m a big fan of bounce rate. I think it’s a vital metric that explains a lot about the online sales channel. One things I like to do is measure the bounce rate for marketing campaigns. Using bounce rate I can tell if the marketing message that drove a visitor to the site matches the message shown to the visitor when they land on the site. Nothing revolutionary here…

I start with the Content Optimization > Navigational Analysis > Entrance Bounce Rate report. Here it is in all it’s glory:

To get the data I want, the bounce rate for a specific page coming from a specific source, I need to cross segment the above report. Usually there is a special landing page (or multiple landing pages) for the campaign, but in this case we’ll look at /blog/index.php. Cross segmenting row 1 in the above report yields:

See how the report columns have changed? We can no longer see the bounce rate. We only see the visits, pageviews, conversion rate and revenue per visit. Honestly, I don’t need that data, I really need to know the bounce rate for each source. Unfortunately I can’t get that data using the cross segmentation feature.

Another Example

Here’s the Marketing Optimization > Visitor Segment Performance > Referring Source report.

** Please Note: I initially posed the wrong image above. The image should contain referrals from Web Analytics Demystified. If it shows data from StumbleUpon then you may be viewing a cached image. Sorry. Now, back to our story. **
Thanks Eric for all the traffic :) Let’s cross segment row #1 by ‘Content’ and see what happens:

You may think that we’re segmenting by the content on my site, but we’re not. This isn’t the same content from the ‘Top Content’ report. What we see here are the pages on Eric’s site where people clicked on links to my site. How can I be sure? All the pages on my site start with ‘/blog/’.

So why is this happening? It’s just the way that GA is storing data. It’s not a bug, it’s just the way that GA works. Don’t worry, there is a work around :)

The Solution

The solution comes down to two things: planning and knowledge. Know the exact metrics you need for your analysis and make sure Google Analytics can deliver them. If you can not cross segment a report to produce the desired data, then try creating an additional profile (using filters).

Here’s how I get around the bounce rate issue above. I use a filtered profile to generate the bounce rate. I create a new profile and apply an include filter based on the campaign, medium or source, that I want to analyze. When the filter is applied to the profile then all the reports in that profile will be specific to the campaign, medium or source, specified in the filter. Obviously this is practically impossible if you are doing an analysis on the fly, or if you need to filter on a piece of data that is unknown when you set up GA.

As a rule, I always create specific profiles for major marketing campaigns. Here’s an example of the filter I might use:

The above filter only includes data coming from a single campaign named ‘Important-Campaign’. That means that the the data in the Entrance Bounce Rates report is only for the ‘Important-Campaign’. I’m essentially cross segmenting when Google Analytics processes the profile data.

Conclusion

I truly believe that GA can provide most of the metrics you will need for a thorough analysis. However, you must plan ahead. As the above example shows there are some anomolies, but they can be mitigated with a logical plan for analysis.

Subscribe:

3 Comments »

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 :)

Subscribe:

7 Comments »

Google Analytics Campaign Tracking Pt. 3: Reports and Analysis

March 4, 2007 by Justin Cutroni

In Part 1 of this series I explained link tagging, the technology that Google Analytics uses to track on-line marketing campaigns. In Part 2 I discussed how to tag your links and posted a tool that I use to quickly tag large numbers of marketing URLs. Today, in Part 3, I’ll start to pull this whole thing together by walking through a very basic analysis.

How I Start

I like to start my marketing analysis using the Marketing Campaign Results reports. Using these reports I can immediately identify any campaigns that are under or over performing. They’re a great launching pad for further analysis. You can find them in the Marketing Optimization > Marketing Campaign Results section.

The reports segment the data based on where the visitor came from using the values from the campaign tracking variables. So, for each of the major campaign variables we discussed in Part 1 (utm_campaign, utm_source and utm_medium) we have a corresponding Google Analytics report. Here’s the mapping of campaign variable to GA report:

Campaign Variable	Report Name
utm_campaign	Campaign Conversion
utm_source	Source Conversion
utm_medium	Medium Conversion

This means that the values you used in the campaign variables will be pulled directly into the reports. Exciting stuff, huh? :)

Campaign Conversion Report

Let’s start with the Campaign Conversion report.

This report segments the traffic based on campaign name. It contains information from tagged URLs (using the utm_campaign variable) and un-tagged URLs. How does it get data for the un-tagged URLs? If you’re using the auto-tagging feature in AdWords then Google Analytics will automatically pull in the Campaign names you create in AdWords. All other un-tagged URLs get put into the following buckets:

1. (direct): visitors that entered your website address directly into the browser
2. (organic): visitors from an un-paid search engine listing
3. (referral) : visitors that clicked on an un-tagged link
4. (not set) visitors from links that were tagged but were missing some information. For example, if you are looking at the Campaign Conversion report, and see that there were 10 visits from ‘(not set)’ this means that the utm_campaign variable was missing from the tagged link.

Ok, so what does this report tell us? It helps us quickly understand how well our campaign is performing using some basic metrics:

• Visits: How much interest did the campaign generate?
• Goal Conversion Rate (G1/Visits): Did the visitors from this campaign do what we wanted them to do?
• Transaction Average (T/Visits): How many transactions were generated by this campaign?
• Revenue per Visit ($/Visits): How much money did we make from each visit in the campaign?

It’s important to realize that each metric gives you a bit more insight into what is going on. For example, let’s say a campaign has a very low conversion rate. Why? Look at the number of visits. Is the campaign generating a lot of traffic? If there are a high number of visits but a low conversion rate there may be a disconnect between the marketing message you’re sending and the content the visitor sees when they land on the site. Dig deeper, Try checking the bounce rate for the landing page.

Again, this is a good starting point for a deeper analysis. And analysis means segmenting the data to gain more insight.

Segmenting Campaign Data

Notice that the first column in the report is named ‘Campaign/Source’ and not just ‘Campaign’? The reason is that this report let’s us drill down into our campaign and view the sources associated with the campaign. If we click on the plus sign for the ‘Ongoing’ campaign we can drill into the data and see the associated sources.

This tells us is there were three sources of traffic in the ‘Ongoing’ campaign: Squidoo, Wikipedia and MySpace. This is real data from a company using social networking and viral sites to drive traffic. The value in the brackets (Social_Networking and viral) is the medium (which we’ll get to later).

Remember from Part 1 of this series, the source is the ‘who’ part of the campaign. ‘Who’ did we partner with to distribute our message? By drilling down into the data we can find out. Drilling from the campaign level to the source level revealed a lot about our campaign. It looks like this business should dump MySpace and focus more on Squidoo! Not only do they get more traffic, they get far better conversion.

But let’s take a different look. It could be that these sources are used in multiple campaigns. Maybe MySpace did really well in a different campaign. Let’s use the Source Conversion Report to get a different view.

Source Conversion Report

The source report shows us how all of our various sources are doing. It does not matter which campaign the source belongs to, they are all listed in this report. This report is very helpful because it shows, historically, how well a source performs. It may be that a source just under performed for a specific campaign. We can see above that Squidoo, which performed very well in the Ongoing campaign, does not crack the top 10 sources. MySpace is no where to be found. This probably means that MySpace performs poorly across the board, not just in the Ongoing campaign.

Next to each source we can see the medium associated with that source. Again, I like to think of the medium as the mechanism that we use to push our marketing message out. Was it email, CPC, banner, print, etc. Google Analytics has pulled the medium value from the utm_medium variable and placed it in the report.

Medium Conversion Report

Looking at the medium we can evaluate how well the mechanism is working for us. Let’s see how well the Social Networking ‘mechanism’ is working.

Interesting. We can see that the ‘Social Networking’ medium doesn’t get a lot of traffic, but it gets attentive traffic (high number of pageviews per visit) and what appears to be an average conversion rate (for this site) for Goal 1.

The medium report is good at identifying dependencies. Are you too dependent on a particular way of getting traffic? If all your conversions come from organic, and the search engines drastically change their ranking algorithms, then you could loose a lot of traffic and a lot of money!

Other Reports

In addition to the Conversion reports, there are also three ROI reports. These reports are very similar to the Conversion reports. They segment the data in the same way (based on campaign, medium and source). The difference is the metrics reported. Rather than conversion rates, these reports show cost, revenue and ROI. If you have an e-commerce site and are collecting revenue, or have monetized the values of your goals, then the revenue generated by each campaign will be displayed.

A warning about this report. GA will only pull in cost data from your AdWords campaigns. Do not be alarmed if you see no other cost data in this report. GA is a closed system, you can not import cost data from other sources. This means that the ROI calculations will be incottrct for non-AdWords campaigns.

The referral conversion report is another fantastic report :) This report lists all of the un-tagged, non-organic and non-direct links that drove traffic to the site.

Drilling down into this report will show you where on each referral domain, the visitor originated. I find the referral report enlightening. The web is a wacky place. And people reference content in so many different ways. This report will help you hunt down all the sources of your traffic.

Some Final Thoughts

You may notice that some of the reports above have multiple lines for the same items. For example, the Medium Conversion report has two line items for social networking:

• Social_Networking
• social_networking

The reason the item is listed twice is that the person tagging the links specified two different values for the utm_medium variable. That’s why it’s important to use a standard naming convention when tagging your links.

Well, that wraps up this Part 3 of our Campaign Tracking series. What did you think? My ultimate goal is to make you all marketing measurement wizards. Am I doing a good job?

Subscribe:

8 Comments »