(Estimated Time to Read this Post = 5 Minutes)

Unless your website is very basic, odds are that you use some sort of navigation to help visitors find website content.  Usually navigation is in the header or left side of web pages.  Inevitably, there will be times when you are asked how often and in what ways visitors are using navigation.  In this post I will cover some common navigation questions and how to answer them.

Common Questions
So what are the common questions you may get around navigation.  Here are some that I have been asked over the years:

1. Which individual navigation links are clicked the most?
2. Which navigation areas are clicked the most?  This is usually related to the main section area, not individual links.
3. From which pages are visitors using each navigation link?
4. For what percent of website visits is navigation used?
5. In what order do website visitors use navigation links?
6. Which navigation links lead to key website success milestones being accomplished?

The following will show how to answer each of these questions:

Which individual navigation links are clicked the most?
In this scenario, people are looking to see which detailed navigation links are clicked the most.  In the image below, this would represent such links as “Sales Cloud 2,” “Service Cloud 2,” “Custom Cloud 2,” etc…

To answer this question, you should have your developer write code that will pass the name of the link to a Traffic Variable (sProp) when a visitor clicks on each link in your navigation.  In addition, I highly recommend that you have them include the high-level navigation area in the value passed to the sProp.  For example, when a visitor clicks on “Sales Cloud 2″ in the example above, I would pass the value of “products:sales cloud 2″ (I always use lower case since sProps are case-sensitive) to the sProp.  Passing the high-level area will ensure that your data is clean as there are times when the same link can occur more than once in a navigation structure.  When this is complete, you can view a report that looks like this:

Which navigation areas are clicked the most?
In this question, people are generally asking to see (in the example above) if the “Products” section is clicked more than the “About” section and if so, by how much.  The good news is that if you have done the previous step correctly, you can answer this question by creating a SAINT Classification which rolls up the values in the preceding report into higher-level buckets.  You can create this classification easily by exporting the above report to Microsoft Excel and splitting the column by the separator and using the first part as the high-level navigation name.  Here is what your SAINT file might look like:

After you create and process this SAINT file you will be able to see a new high-level navigation report that looks like this:

From which pages are visitors using each navigation link ?
In this scenario, people at your company may want to know what is the most common top navigation link clicked from the home page or from another page on your site.  To see this, you need to have setup a Previous Page sProp.  This sProp passes the name of the previous page to the current page which allows you to create Traffic Data Correlations between it and any other Traffic variable.  In this case, once we have a Previous Page sProp, we can correlate it to the Top Navigation Link sProp shown above to see what navigation links are clicked from each page.  For example, I can open up the Previous Page sProp within a report suite and then break it down by the new Top Navigation sProp…

…to see a report like this:

In this case, we can see that the “customers:india customers” Top Navigation link was only clicked 482 times from the home page.

In addition, since this uses a correlation and correlations are bi-directional, you can also use this to find out all of the pages from which visitors clicked on a specific navigation link:

In this case, we can see that the “customers:india customers” link was clicked a total of 957 times and then see the breakdown of pages visitors were on when they clicked it.  This can help your content people understand when visitors are reaching for the navigation…  Finally, if you look closely, you can see that the “SFDC:in:homepage” shows the same 482 clicks referenced above, but in this case we can see that it accounts for 50% of all clicks this link gets across the entire website…

For what percent of website visits is navigation used?
In some cases, you may be asked how often website navigation is used (in general).  One easy way to figure this out is to look at the the total Page Views from the first SiteCatalyst report shown in this post and divide it by the number of website Visits.  This can be done easily using the ExcelClient where you can pull a Visits data block and the report above and divide the two.  However, if you think you might need this on a recurring basis and if trending is important, I will show you another way to do this.  When visitors click on navigation links, in addition to passing the link name to a Traffic Variable as shown above, set a “Navigation Clicks” Success Event.  Once you have a Success Event, you can create a Calculated Metric that divides Navigation Clicks by Visits as shown here…

…which will allow you to see a report like this:

In what order do website visitors use navigation links?
If you are redesigning your navigation, a useful piece of data is the order in which visitors click on navigation links.  Do they always click on the first items in the list?  The ones that are farthest to the left?  Fortunately, if you have implemented the items above, you can see this by simply enabling Pathing on the new Navigation Links sProp created above.  This will allow you to view the Pathing reports including a Next Page Flow and Previous Page Flow just for navigation items:

Which navigation links lead to key website success milestones being accomplished?
Finally, I will occasionally be asked which navigation links are contributing to success.  To answer this question, all you have to do is enable Participation for your key metrics on the Navigation links sProp described above.  This will allow you to add a Participation metric to the first report shown above to see which links were in the flow of your key website Success Events.

Final Thoughts
Well, there you have it.  Everything you wanted to know about tracking your website navigation, but were afraid to ask!  If you have any comments/questions, use the form below.

Adam Greco is the Director of Web Analytics at Salesforce.com.  You can read his previous Inside Omniture SiteCatalyst blog at http://blogs.omniture.com/author/agreco/ and can follow him on Twitter at http://twitter.com/adamgreco.  You can also hear Adam on the BeyondWebAnalytics podcast.  Please send questions and comments to adam@the-omni-man.com.

Please note: I am no longer an employee of Omniture and the content/views expressed here are my own and not those of Omniture.

(Estimated Time to Read this Post =3 Minutes)

I believe that every SiteCatalyst implementation should have a Previous Page sProp.  There!  I said it (I feel like I am channeling Avinash!).  In past blog posts I have touched upon the use of a Previous Page sProp, but I feel like I have not done it justice and wanted to take time to explain it in greater detail.  In this post, I will describe why I think this variable should always be set and provide some examples of its use.

Why You Need a Previous Page sProp
I find that in the web analytics world, I often receive the following question:

“What page was the visitor on when he/she _______?”

You can fill in the blank with many things.  Here is a list of the ones I have been asked:

• …searched for this phrase in our internal search box…
• …clicked on a button to go to a web lead form…
• …downloaded a white paper…
• …added products to the shopping cart…
• …clicked on a banner advertisement…
• …started using the ROI calculator…
• …clicked to fill out a website survey…

I could go on for days and never come to the end of these types of questions!  People want to know this information because it helps them get inside the head of their visitors.  Often times it leads to navigation or content changes.  Regardless of the reason, I assure you that you will be asked this question at some point and the truth is that it is not easy to answer with out-of-the-box functionality (i.e. Pathing).  The good news is that setting the Previous Page sProp is easy and will pay great dividends down the road…

How To Set the Previous Page sProp
Setting the Previous Value sProp could not be easier.  All you have to do is use the Previous Value JavaScript Plug-in to pass the previous page name to a new Traffic Variable (sProp).  You can even see a detailed description of the code for this in Ben Gaines’ great Summit blog post.  If you need help, call your Omniture Account Manager, Omniture Consulting or ClientCare.

Once you have your JavaScript setup to pass the Previous Page Name to the sProp, you need to enable a Traffic Data Correlation to any sProp for which you want to create a breakdown.  For example, if you want to see what pages visitors were on when they searched for a particular internal search term, you would correlate the Previous Page Name sProp with the Internal Search Term sProp…

…so you can see a report like this:

In addition, if you are familiar with correlations, you may recall that they are bi-directional, so in addition to seeing the pages people searched for specific terms from, you can also see the converse.  In this case, that would mean seeing all of the internal search terms visitors searched for on a specific page:

As you can see here, we see the same “4″ searches for the phrase “chatter” from the selected page as we saw in the first internal search term report (in this case I am just using Internal Search as an example, but if you want to learn more check out my Internal Search post).

One Is Usually Enough
However, one word of caution, I have seen many clients implement several Previous Page sProps and I am not a fan of doing this as I will now explain.  Let’s say you want to see what page people were on when the searched on a specific search term (as described above) and you also want to see what page they were on when the downloaded files on your site.  A lot of people will set two Previous Page sProps in this situation – one for the search term and one for the file downloads.  In my opinion, this just wastes a variable, wastes correlations and causes confusion for your users.  The truth is that all you need is one Previous Page sProp to answer both questions.  Since on each page there will be one and only one Previous Page value, there is really no reason to do this multiple times.

I have seen some clients who have chosen to pass the Previous Page Name to an eVar.  There are some interesting uses of this.  For example, if you want to see what pages visitors were on when they added a specific product to the shopping cart, you can pass the Product Name to the Products Variable, set the Cart Add Success Event and the Previous Page Name to an eVar.  The main issue you will run into is that Conversion Subrelations are an “all or nothing” proposition so you can only do breakdowns by eVars that have Full Subrelations.

One final tip that I will throw out there is to consider having your developer pass a value of “[NO PREVIOUS PAGE AVAILABLE]” (or something similar) to the Previous Page sProp on entry pages (or any other time no Previous Page is available).  I find that this is easier than dealing with questions around “Unspecified” in correlation reports and it is easier to remove this value using the search box than it is to hide the “Unspecified” values.

Final Thoughts
As I mentioned in the beginning, I highly recommend that you have a Previous Page sProp for all of your key report suites and add correlations as needed.  If you have any questions/comments, feel free to leave them here…

Adam Greco is the Director of Web Analytics at Salesforce.com.  You can read his previous Inside Omniture SiteCatalyst blog at http://blogs.omniture.com/author/agreco/ and can follow him on Twitter at http://twitter.com/adamgreco.  You can also hear Adam on the BeyondWebAnalytics podcast.  Please send questions and comments to adam@the-omni-man.com.

Please note: I am no longer an employee of Omniture and the content/views expressed here are my own and not those of Omniture.

[Warning: Some elements of this post are meant for advanced SiteCatalyst users so read at your own risk!]

Last week, Ben Gaines (@OmnitureCare) wrote a great blog post about the getPercentPageViewed JavaScript plug-in, which he had demonstrated in his Summit presentation.  This plug-in is very fun and I have enjoyed using it.  While this topic is fresh in people’s mind, I wanted to throw out some additional/advanced uses of this plug-in in case they are relevant to those out there using it or thinking about implementing it.

Beyond % of Page Viewed
When I first started using the aforementioned plug-in, my goal was like most, to see the total % of each website page that my visitors viewed.  I found the Browser Height report to be too limiting (shows pixels, not % of page viewed) and this plug-in helped provide some additional insight.  However, after using the plug-in, and correlating % of Page Viewed to pages, I realized that there were a few more things that could be done with this concept.  The next question that popped in my head was “I wonder what % of the page, for each website page, can be attributed to scrolling?”  After all, the % Page Viewed plug-in really only shows you how much of the page they saw in total, but not how much of the page they initially saw vs. saw because they scrolled.  This line of thinking drove me to ask what else could be learned from this plug-in such as:

1. Total % of Page Viewed by Page Name
2. % of the page that users tend to scroll by Page Name
3. Initial % of Page visitors tend to see before they start scrolling (to get around the pixel limitation of the Browser Height report)

As I mentioned earlier, Ben’s post covered item #1 above, so in this post, I will show you how to solve items #2 and #3.

How Much Are Users Scrolling on each Page?
To see how much visitors are scrolling on each page, I asked my developer if he could calculate the actual % of the page that users scroll through the plug-in.  Through his supreme awesomeness, he told me that he could.  That meant that we would have the total % of the page that was viewed and the % representing scrolling (both available on the next page as described by Ben).  From there, we decided that we would concatenate the two values into an sProp.  This means that the sProp Ben described would be slightly different such that instead of having raw number values (i.e. 100, 95, 56, etc…), it would have two values concatenated together as shown below [TOTAL % OF PAGE VIEWED]|[TOTAL % VISITOR SCROLLED]:

(Before you get scared, bear with me as I will show you how to deal with these strange looking values in the next few paragraphs!)

Once you have these concatenated values in the sProp, it is time to classify them using SAINT Classifications.  To do this, you create the following classifications of this sProp:

• Total % Page Viewed.  This is the first of the two values and this classification replicates what Ben blogged about.
• Scrolling %.  This is the second value and represents the % of the page the visitor scrolled to see.

When you are done with this, you can see the report Ben showed in his post, but can now see the following additional report:

Through this clever classification, you can see how often people on your website tend to scroll.  In this case, it looks like 73.2% of visitors don’t reach for that scroll bar!  However, as Ben stated, all of this data is more valuable when viewed by Page Name.  Since this Scrolling % report is really a classification of an sProp that is correlated to the Previous Page Name sProp, any classifications of it will also be correlated to Previous Page Name (if you understand that in one reading you are a true SiteCatalyst ninja – if not, re-read it a few times).  This means that you can break the above report down by Page Name, or in other words, you can look at any page on your website and determine how often visitors are scrolling.  To do this, simply open your Previous Page Name report, find the page you care about, and break it down by the Scrolling % (classification of the Percent of Page Viewed sProp).  In the following example, we can see how much visitors scroll when looking at the Home Page:

In this case it looks like about half of the time visitors are scrolling on the Home Page.  Finally, if you want, you can bucket these Scrolling percentages into more meaningful groupings by adding additional SAINT classification columns as Ben described.

What % of the Page Do Visitors See Upon Page Load?
So the other thing I wanted to see was the percentage of the page that visitors see before scrolling.  I don’t like looking at Browser Height pixels, but would rather simplify things and see the exact % of the page my visitors are seeing – period!  Unfortunately, there is not an easy way to do this in SiteCatalyst.  However, when I was looking at the above items in this plug-in, I realized that the answer to this question was a side-benefit of doing the SAINT Classification shown above.  Think about it…we have the Total % of the Page Viewed and the Total % that visitors scrolled, both concatenated in an sProp as shown above.  If you subtract these two values, you are left with the percent of the page that visitors saw before scrolling (in other words, upon page load)! For example, if the value in the sProp is “58|10″ (see first row of example above), then we know that the visitor saw a total of 58% of the page and they scrolled 10% of it, so they must have seen 48% of it initially (good thing web analysts like math!).

Therefore, when you are classifying the sProp shown above, you can add a new Classification of the Percent of Page Viewed sProp named “Initial % of Page Viewed” and simply subtract these two values and add that as a new classification (no new data to collect!).  When you do this, you end up with a new report that shows you the total % of pages visitors tend to initially see like this:

Here we can see that, in general, about 60% of visitors are essentially seeing the entire page without having to scroll.  Again, we can group these values into more meaningful buckets using SAINT, but the real power is seeing this Initial Page Viewed % classification by a specific Page Name.  Again, using the Home Page as an example, the following report shows how much of the Home Page most visitors see before scrolling:

What’choo Talkn ‘Bout, Willis?
OK…I know this sounds complicated, but really all you need to do is slightly modify the code (see below) that Matt Thomas  (of Omniture Consulting) created and that Ben alluded to in his post to add one concatenated value (% Scrolled).  The majority of the hard work is in building the SAINT classification file to get all of these cool, new reports.  Well the good news there is, that I have already created the file which you can use as a starting point for these extra reports.  All you have to do is to download it by clicking here (save .TAB file to your hard drive).  Simply save this file and add the values to your own SAINT template after you have created the Classifications mentioned in this post.

So there you have it…a few additional ideas for you to ponder while you have % of Page Viewed on the brain…  If you have other ideas or questions, please leave a comment here…Thanks!

FOR OMNITURE GEEKS ONLY!
Here is the “enhanced” JavaScript code that modifies the great code that Matt Thomas (from Omniture Consulting) created and is in the Omniture KnowledgeBase.  This is not currently supported by Omniture so use at your own risk!

Adam Greco is the Director of Web Analytics at Salesforce.com.  You can read his previous Inside Omniture SiteCatalyst blog at http://blogs.omniture.com/author/agreco/ and can follow him on Twitter at http://twitter.com/adamgreco.  You can also hear Adam on the BeyondWebAnalytics podcast.  Please send questions and comments to adam@the-omni-man.com.

Please note: I am no longer an employee of Omniture and the content/views expressed here are my own and not those of Omniture.

Those of you who have read my blogs for a while know that I am a big proponent of using as many SiteCatalyst features as possible.  However, in this post I am going to venture into uncharted territory by suggesting reasons to NOT use a SiteCatalyst feature – File Downloads.  While you may be skeptical about this, I ask that you hear me out on my reasons and alternative approach before passing judgment!

How Does the File Downloads Feature Work?
Before dismissing the File Downloads functionality, let’s take a minute to understand what it does.  Like most web analytics programs, SiteCatalyst provides out-of-the-box functionality for File Downloads such that when a website visitor clicks to download a file, it captures the file name in a special File Downloads report.  In reality, file downloads are treated a lot like Exit Links as far as SiteCatalyst is concerned.  The File Downloads report is very handy since you can open it and see which files are downloaded most like this:

Why I Don’t Like Using The File Downloads Report
As I have become more sophisticated in how I approach SiteCatalyst, I have found several flaws in the File Downloads report.  Here is a quick summary of my issues with it:

• One of my pet peeves of the File Download report is that it stores the path of the file with both an http:// and a https:// so you often times have the same file represented twice in your reports.  This throws off your data and it can confuse users.  You can modify this by tweaking your JavaScript file, but I wish there were an out-of-the-box option to do this.
• There is no easy way to see how each file download impacts website Success Events.
• Often times, I want to see where the website visitor was when they downloaded a particular file, especially if the same file can be downloaded from different pages on my site.  In the past, I have worked around this by modifying my JavaScript file to pass the file name to a custom sProp and then enabling the Previous Value Plug-in to store the previous pagename and enabling a Traffic Data Correlation between file name and Previous Page.  This provides a way where I can choose any file name and then break it down by pagename to see the ranked order of pages it was downloaded from.  Net Result – Out of the box File Downloads report doesn’t get me what I want.
• However, the real reason I don’t like the File Download report is that it ruins my Pathing reports.  I love pathing.  I like seeing where people go backwards and forwards through my site.  But when I look at the Next Page Flow report or the Next Page report, I am not getting an accurate picture if there are File Downloads on a page.  There are many cases where the most clicked element on a web page is a PDF that visitors download.  However, when I look at my pathing reports, this file is nowhere to be seen.  I can see it in the ClickMap report, but not in my SiteCatalyst pathing reports.  Therefore, when my users look at the next page report, they are looking at incorrect data due to the fact that 10% of visitors downloaded that PDF.

So What Should You Do…
I don’t like to complain without offering alternative solutions so the following outlines what I would do instead of using the File Downloads report.  Per my list above, at the end of the day, I have the following requirements for understanding File Download activity on my site:

• Easily see which files have been downloaded the most (and only once per file regardless of http or https)
• Understand from which pages visitors are downloading files
• See how each file download impacts my KPI’s
• Ability to see file downloads in my pathing reports so I can see what is really happening on each page

Seems reasonable enough right?  So here is how you accomplish all of these without using the File Download report:

1. Work with your developer to treat every file download as if it were a web page on your site such that it is passed to the Pagename variable (s.pagename)
2. Ensure that when passing the file name to the s.pagename variable, you strip out the http or https so you just get the raw file path (you can also strip out your domain to make the pagename shorter)
3. When creating this pagename, be sure to insert the phrase “file|” or “file:” in the pagename (or something similar)
4. Remove the File Download code from your JavaScript file (so you don’t get double-charged server calls)

So that doesn’t seem so hard does it?  But what does this actually get you?  Let me extol the countless benefits:

• Passing the file download name to the s.pagename variable means SiteCatalyst sees file downloads the same way it sees any page on your website.  This means you can see file downloads in Pathing reports so your next page and previous page reports will be accurate.
• If you remove the http or https you will only have one pagename for each file so you avoid the duplicate file issue I mentioned earlier.
• If you insert a file identifier (“file:”) then you can recreate the current File Downloads report you have today by just opening the Pages report and doing an advanced filter on “file:” in the Search area area.
• If you want to see which page visitors were on previous to downloading a specific file, you no longer need to use an extra sProp nor enable a correlation.  All you have to do is find the file in the Pages report and open the Previous Page pathing report.
• If, by chance, people link directly to your file downloads, you can also calculate the Bounce Rate of each File Download since it is now part of the pagename variable which has pathing (and thereby Single Access & Entries) by default.
• Anyone want to see Daily, Weekly and Monthly Unique Visitors for each File Download?  You just did it if you have those enabled on your Pagename variable (which most people have by default)!
• As I mentioned above, it is not easy to see how often each file on your web site “participates” in your key success events?  This is because you cannot enable Participation on the File Downloads report.  However, now that File Downloads are part of the Pagename report, you can easily enable Participation on the s.pagename variable (which you should already be doing) to see how often each file download impacts your key KPI’s.
• Last, but not least, if you have any correlations to the Pagename report (which is very common), you now have those correlations to every file on your website.  For example, if you have Pagename correlated to Visit Number or GeoSegmentation Country, you now have all file downloads correlated to these as well without having to pay for any extra correlations or variables!

All in all, you can get a lot of bang for your buck with this handy trick.  I think it can easily save you a few sProps, correlations and unique visitor CPM increases (I make no money on this blog so feel free to send contract savings my way )!

Final Thoughts…
Well there you have it.  These are the reasons why I have chosen to take an alternative approach to the File Download report and I think it makes a pretty compelling argument!  I will be curious to get your thoughts and see if you agree or disagree with me on this…

Adam Greco is the Director of Web Analytics at Salesforce.com.  You can read his previous Inside Omniture SiteCatalyst blog at http://blogs.omniture.com/author/agreco/ and can follow him on Twitter at http://twitter.com/adamgreco.  Please send questions and comments to adam@the-omni-man.com.

Please note: I am no longer an employee of Omniture and the content/views expressed here are my own and not those of Omniture.

Last week I shared a way to capture the various traffic sources (i.e. SEM, SEO, E-mail, etc…) so you could calculate the Bounce Rate for each of these Traffic Source types.  In this post I am going to build upon this and show you another cool way you can leverage this to have what I call Cross-Visit Traffic Source Attribution.

What is Cross-Visit Traffic Source Attribution?
As an online marketer, one of the things I want to see is how each traffic source leads to online success.  Within a visit, it is relatively easy to see which Traffic Source types lead to success.  Normally this is done by capturing the various campaign elements and using SAINT Classifications to roll these up into Traffic Source types.  However, what many marketers want to see is the overall mix of Traffic Source types that lead to success over several visits.  For example, maybe Paid Search is always the last thing your visitors are doing before placing an order, but maybe the first thing they did was to click on an SEO keyword.  I touched upon this a bit in an old blog post on Cross-Visit Participation which you can review here.  If your organization has a desire to see a high-level view of which combinations of Traffic Source types lead to success, then Cross-Visit Traffic Source Attribution may be your answer.

Implementing Cross-Visit Traffic Source Attribution
If you have followed the instructions I laid out in my last blog post, then you have already done much of the work required to enable this feature in your SiteCatalyst implementation.  Now that you have an sProp that contains the Traffic Source type set on the first click of each website visit, all you have to do is the following:

1. Pass this value to an eVar (Most Recent Allocation)
2. Implement the Cross-Visit Participation plug-in
3. Have the eVar expire when your primary success event takes place (i.e. Orders)

As a refresher, the Cross-Visit Participation plug-in stores a list of elements, in this case Traffic Sources, with each visit so when a Success Event takes place, you can attribute the success to the current string of cross-visit values.  For example, if someone comes to your site three times, first from SEO, second from E-mail and third from SEM and then places an order, the current value in the eVar would be “SEO|E-mail|SEM.”  As time goes by, and you have more website visitors, the combinations that occur most frequently will rise to the top (web analytics darwinism?).  Usually the single Traffic Sources will be at the top (i.e. SEO by itself or SEM by itself), but what I look for are the combinations that are at the top of the list.  I sometimes even hide the individual items using the advanced search feature (Tip=Show if it Contains “|”) so I can see only multiple session Traffic Sources:

The only warning I will give about using this functionality is that it might burst the bubble of some of your co-workers who think that their Traffic Source type is the “end all, be all” of success.  In my experience, many people bounce around quite a bit and the results can surprise you!

First Touch, Last Touch
When it comes to attribution, many talk about First Touch, Last Touch and All Touch, meaning which Traffic Source was the first that visitors saw in a sequence leading to success, the that visitors saw last or a list of all of the Traffic Sources that influenced the success.  In SiteCatalyst, the easiest way to implement First Touch and Last Touch is to use two separate eVars.  Both capture Traffic Sources, but one has Original Allocation and a long expiration (never or say 6 months), while the other eVar is set to Most Recent Allocation and expires at the Visit.  However, you can also use the new Cross-Visit Traffic Sources eVar shown above to do this.  Simply download the above report to Excel and then isolate the first Traffic Source or the last Traffic Source and add up the Orders (or use a Pivot Table) to see the total for each Traffic Source.

Traffic Source Influence (All Touch)
For me however, I am most interested in seeing the total influence of a specific Traffic Source (All Touch).  While this is not readily available in SiteCatalyst (since Linear eVar Allocation only works within one visit), you can use the new eVar mentioned above to quantify the potential impact/influence of a specific Traffic Source Type.  Here is how you do it:

1. Download the report above to Excel (you decide if you want to include the single Traffic Sources or only when multiple exist – as shown above)
2. Use an Excel Formula to set the Traffic Source Type for a specific Traffic Source Type (i.e. SEO) in all rows where it is found (see green column below)
3. Create a Pivot table off this new column (i.e. SEO) and look at the total Success Events (Orders in this example) that are associated with a row that contains the Traffic Source Type you chose in step two (in this case 754,328)
4. Take that total (i.e. SEO Influenced Orders in this case) and divide it by the Total Orders (in this case 76.07%).  This will show you how much SEO influenced Orders such that SEO was involved in a visit that ultimately led to an Order.

Finally, if you want to see Cross-Visit Attribution of individual Campaign elements (Tracking Codes) instead of Traffic Sources, you can apply the same principles shown in this post and my last post.

Hopefully, between this post and my last post, you will be able to answer the nagging Traffic Source questions that come up from time to time and help your organization better understand where it should use its precious marketing dollars…

Adam Greco is the Director of Web Analytics at Salesforce.com.  You can read his previous Inside Omniture SiteCatalyst blog at http://blogs.omniture.com/author/agreco/ and can follow him on Twitter at http://twitter.com/adamgreco.  Please send questions and comments to adam@the-omni-man.com.

Please note: I am no longer an employee of Omniture and the content/views expressed here are my own and not those of Omniture.

One of the holy grails of online marketing teams is to find a way to track and measure a company’s Brand Awareness.  There are many different approaches to do this including the use of products like comScore, Compete, Twitter, but more often than not, it takes place offline in research studies.  While this trend is not going to change anytime soon, as a web analyst, you may be looking for data that you can collect to provide an estimate of your Brand Awareness.  Therefore, in this post, I wanted to share a “quick and dirty” way to use online data to see and trend the popularity of your company brand.  While this will not be a comprehensive approach, it might provide a basic starting point into the larger “Brand Awareness” puzzle.

Why Track Brand Awareness?
There are many schools of thought on whether it is even worthwhile to try and track Brand Awareness.  While people like us try to track everything, sometimes, there are things that are just not meant to be tracked.  If you own a website that sells stuff, then there is so much you can do with Web Analytics that tracking Brand Awareness is probably way down on the list.  However, there are many companies (i.e. B2B) that don’t sell products directly and inevitably the question arises:

“What is the true purpose of my website?”

If you are part of one of these companies, the above question is often followed with a spirited debate about whether success should be judged by lead counts, unique visitors, visitor engagement, etc…  At some point one Marketer will say that the website should be used to build Brand Awareness so success should be judged by increasing Unique Visitors, only to be countered by another saying that Unique Visitors don’t mean anything if they aren’t the right types…After about an hour of this, there is rarely a consensus on how to judge the success.  Soon you can see why this is not a popular topic in Web Analytic circles!

Amid all of this confusion, I think that people sometimes forget the real reason that people care about Brand Awareness.  At the end of the day, you want to measure how often consumers that are interested in a product/service that you provide think of you when the time comes to research or buy that product/service.  If you are doing a really good job at branding your company such that you are top of mind when consumers are at this stage, then one way or another you have done something right.  This is why I think there is some value in trying to quantify this and trend it over time.

So What Can Be Tracked?
So building upon the previous section, let’s assume that you don’t sell a product directly on your website, but that there are consumers out there who need your product/service (and have a blank checkbook in hand!).  Do you think they would:

1. Come to your office and ask to see your salespeople?
2. Pick up the Yellow Pages and give you a call?
3. Mail you a letter asking for information?

Maybe in the 1980’s, but not today!  Most are going to go to a Search Engine and a few savvy ones will go to Twitter.  So if the bulk of these will go to a Search Engine, and you are truly “top of mind” from a branding standpoint, they would probably search for your company name or the name of one of your products.  For example, if the consumer is looking for a “CRM” product they might search for “CRM.”  But if you are doing your job and have an awesome brand such that the first thing people think of when they think about “CRM” is your company brand (I don’t know…maybe something like “salesforce.com” ), then you would know that your brand is alive and kicking!

Following this logic, you can see that one interesting way to track your brand awareness is to quantify how often people are coming to your website from a list of “Branded” keywords of your choosing.  This list of keywords would include your company name, product names, key executive names, etc…  If you can aggregate these SEO keywords (I wouldn’t include Paid Search Keywords), then you have a number that you can trend over time.  Keep in mind that this is not an exact way to track brand awareness, but the logic behind it is that the more people [organically] search for your key brand phrases, the more pervasive your brand is out there.  In my consulting experience, I have often found that the number of SEO Brand Searches has a direct correlation with other key website success metrics.

So How Do I Implement SEO Branded Keyword Tracking?
In a perfect world, it would be great if there were an easy, reliable way to track how often your brand keywords were searched on all of the major search engines.  Companies like comScore try to estimate this, but it is not always accurate due to the panel-based methodology.  Another way I have tried to get at this data is through Google Trends, but I have not found ways to automatically export that data through API’s (if you know how please let me know!).

That being said, if you want to use SEO Branded Keywords to track your brand, take the following steps:

1. Work with your Marketing team to identify the list of keywords that everyone agrees are “Brand Keywords.”  In order to not distort the trend, it is important that you not continually add to the list so try and get an exhaustive list and stick to it for an extended period of time (i.e. readjust yearly).
2. The next step is to isolate these Branded Keywords in your SEO reports.  One way to do this is to add each one to the advanced search criteria for your SEO Keywords report (in the interface or ExcelClient), but if you have a lot this can be difficult.  My preferred approach is to pass SEO Keywords to a custom eVar.  Once you have done this, you can use SAINT to classify these keywords as “Branded Keywords” and then use the trended view of reports.  If you are using the Channel Manager plug-in or the Unified Sources Vista Rule, you should already have the data you need in a custom variable.
3. Once you have these branded keywords isolated, you can create a report that looks like this:

In addition, if you have specific products that are brands of their own, you may want to apply the same technique to the SEO Keywords that represent those brands and chart the Brand Awareness of your different products amongst each other (maybe inspire some competitiveness?).  For example, at Salesforce.com, we group our products into “Clouds” so you might chart the SEO Keywords related to the various “Clouds” on a graph to see how each is doing (shown with sample data here):

Don’t Forget About Twitter!
As mentioned earlier, another way to look at how your brand is doing is to look at Twitter.  This can be done using the Omniture Twitter Integration I proposed last year.  Implementing this provides you with a way to see how often your brand is being talked about so you can see a chart like this:

If you want to get fancy, you can even measure how your brand compares to the brand of your competitors on Twitter.  The graph below shows what I call “Twitter Competitive Share” and is calculated by the following formula:

Branded Tweets / (Branded Tweets + Competitors Branded Tweets)

The result is a chart that looks like this:

Final Thoughts!
Well there you have it, definitely not world peace, but if you are looking for some different ways to leverage your web analytics data, hopefully these ideas give you some food for thought.  If there are other ways that you are using web analytics data to track Brand Awareness, please leave a comment here as I’d love to hear about it…

Adam Greco is the Director of Web Analytics at Salesforce.com.  You can read his previous Inside Omniture SiteCatalyst blog at http://blogs.omniture.com/author/agreco/ and can follow him on Twitter at http://twitter.com/adamgreco.  Please send questions and comments to adam@the-omni-man.com.

Please note: I am no longer an employee of Omniture and the content/views expressed here are my own and not those of Omniture.

While most of you reading my posts are focused on your public website, in this post I am going to share how you can leverage your web analytics skills internally at your organization.  Company Intranets are often times larger than the public website and using the tips I will share here, you can get some big visibility internally and become the hero of your HR team!

Why You Should Care About Your Intranet
Companies often spend a LOT of $$$ on building Intranets.  Unfortunately, not everyone at the company uses the Intranet.  If you can help your internal team show what is working and what is not working on the Intranet, you can help them to save a lot of money.  In addition to the altruistic reasons to track what happens on the Intranet, there are the following selfish reasons:

1. Tagging Intranets is a great way to try new things and get better at web analysis in a safe environment
2. Intranets often have low traffic volume so it is a great way to help cost-justify increased budgets for web analytics (“Mr. CEO, not only does this money go towards tracking the website, it also allows us to track our entire Intranet!” – Just don’t tell them that tracking the Intranet costs all of $1,000 in server calls!)
3. Showing people what is happening on the Intranet does wonders for people inside your organization understanding what the heck you do for the public website!

I have seen situations where a web analytics team has killed themselves trying to get senior executives to see what is taking place on the website and what improvements could be made based upon solid web analysis, only to see the same team get promoted or more budget after spending 2-3 weeks showing what takes place on the Intranet (something that they actually use)!  It sounds completely illogical, but I guess if you can’t beat them, join them!

Tracking Intranets
So what should you track on Intranets?  The following are my best practices learned working with a few large clients.  The one caveat to everything below is that you have to be sure to track all of this data in a different report suite than all of your other website data!

Employee ID
Depending upon the security policy of your company, ask if you are able to track down the the Employee ID level.  I tend to not do this since it can be a bit creepy, but it is technically possible and you can replace the Omniture Visitor ID with your own unique employee identifier.

Non-Personally Identifiable Employee Info
On each Intranet page, I recommend that you pass Department, Region, Business Unit, Office Location, Employee Band Level (i.e. VP, Manager), etc… to variables.  This will allow you to break down all Pages by these data points.  I generally pass these to an sProp and an eVar (save some time setting both through this post) and also recommend you put your top five of these into a 5-item Traffic Data Correlation.

Pages & Sections
Obviously, you want to pass in a unique page name for every Intranet page like you would any other website.  In addition, you should pass the Intranet section to the Site Sections (Channel) variable.  As always, I recommend that you enable Pathing on the Channel sProp so you can see how employees are navigating between Intranet sections.

Internal Search
Just like a public website, Internal Search is usually important on Intranets.  You should track Internal Search on the Intranet just as you would on a public website.  You can apply the same principles I mentioned in this Internal Search post.  This includes tracking what search terms people are looking for, but the beauty here is that you can see these by Department, Region, etc…

Timeparting
Many of my Intranet clients were keen to see when employees were accessing the Intranet, so I recommend you implement the Timeparting Plug-in.  This allows you to see what day of the week and time of the day employees access the Intranet.  Don’t forget to create a correlation between these sProps and your other ones so you can see when each page/section is accessed most often.

Internal Promotions
Much in the same way that I described Internal Campaigns in the past, Intranets may have promotional areas that try and entice employees to click.  You can track these the same way you would a public website.

Intranet KPI’s
The following are the types of KPI’s I have seen used for Intranets:

Page Views/Visit & Average Time Spent/Visit
Depending upon whether your goal is to get employees in and out or get them to spend more time reading Intranet content, you can use this calculated metric to see how you are doing.

Page Views (Event)
As I described in this post, I would recommend that you set a Success Event on each page.  Why?  Well let’s say you want to see how many pages on the Intranet a specific internal e-mail led to.  You can open the Campaigns report, find the e-mail and then see how many pages were viewed.  You can then use an eVar Subrelation to break this down by page name (as long as you pass Pagename to an eVar) to see the exact pages viewed.

Internal Searches
As you would on a website, you should track and trend the # of Internal Searches taking place on the Intranet.

Logins
If employees have to log into your Intranet, you can capture that as a KPI to see how you are doing at getting them to access the Intranet.  This can also be used for segmentation (i.e. show me all users who have not logged into the Intranet in the past 30 days…)

Custom KPI’s
Many times, Intranets are used to get employees to fill out forms, surveys, etc…  Each of these key actions should be captured with a Success Event and in the case of Forms, you should capture the Form Name in an eVar so you can break it down appropriately.

Employee Profile Views
As we march down the road of internal social media, it is fun to track how often each employee’s Intranet Profile is viewed.  Using new tools like my company’s upcoming “Chatter” product (see shameless plug video below!), we may be moving to a world where employees get “followers” so you can track how often people are looking at or following other employees.  This allows you to see who your employees think are important (which may not always align to the org chart!).

Final Thoughts
As you can see, if you know what you are doing for tracking a public website, tracking an Intranet uses many of the same principles.  If you are just getting started in web analytics, feel free to apply the above items on your Intranet as a testing ground before you tackle the public website.  If you have some other cool things you have done to track your Intranet, please feel free to leave a comment here…

Adam Greco is the Director of Web Analytics at Salesforce.com.  You can read his previous Inside Omniture SiteCatalyst blog at http://blogs.omniture.com/author/agreco/ and can follow him on Twitter at http://twitter.com/adamgreco.  Please send questions and comments to adam@the-omni-man.com.

Please note: I am no longer an employee of Omniture and the content/views expressed here are my own and not those of Omniture.

A few weeks ago, Ben Gaines (@OmnitureCare) wrote a great blog post about tracking Internal Search.  In this post, I am going to add a few additional tips I have learned over the years…

Correlate Internal Search Term & Page Searched From
Knowing what people searched for on your site is certainly valuable, but knowing the exact page they searched for each term from is even more valuable.  Having this allows you to see what content visitors think they should be able to find on each page.  This is like gold to your content folks who can look for terms that are consistently searched for on a specific page and make a case that they need to add or improve content.

Setting up SiteCatalyst to do this is very simple.  All you have to do is pass the Internal Search term to a Traffic Variable (sProp) (as Ben showed) and then set a second sProp with the previous page name value (use the Previous Value plug-in) and create a Traffic Data Correlation for these two sProps.  When you are done, you will be able to see two cool things:

1) What terms are searched for on a specific page:

2) For any given term, what pages are visitors searching for that term:

Group Internal Search Terms
In Ben’s post, he discussed how to eliminate duplicate terms by taking upper/lower case out of the equation.  In addition to this, there are times when you might want to group specific keywords together into buckets since they represent the same type of search.  For example, if you manage a travel site, you might want to group all City internal search terms by State and Region so you can supplement your analyses.  This is easily done by taking advantage of SAINT Classifications which allow you to bucket your internal Search Keywords however you would like.  Here is an example of a SAINT File you could use in the preceding example:

Use Compare Feature to find differences between Dates
Once you are tracking internal search terms, you can use the Date Comparison feature in SiteCatalyst to see how the same internal search terms perform in two different time periods.  You access this feature from within the SiteCatalyst Calendar window.  Below is an example of looking at how the top internal search terms for September perform in October:

As you can see, by using the date comparison feature, SiteCatalyst will show you the difference between the two time periods so you can be aware of significant changes.  Simply click the difference column and you can see the search terms that changed the most/least (depending upon whether you sort ascending or descending).

Use Compare Feature to find differences between Report Suites
In a similar manner, if your implementation has multiple report suites (or ASI Segments), you can use the Compare feature to see how internal search terms vary by suite/segment.  For example, if you have a Customer Segment and a Non-Customer Segment, you can see what internal search terms each group is looking for:

In the above report, we can see that Non-Customers are more apt to search for careers, while Customers are more interested in detailed product information.

One cool thing you can do with this is to combine this data with Test&Target by FTP’ing the most popular search terms to a Word Cloud program and having Test&Target show the appropriate Word Cloud based upon a cookie value indicating customer status.  That is a great way to proactively use your web analytics data to create a better experience for your users!

Trend Search Page Exits
One way to see how good or bad your internal search results are is to look at how often visitors exit your site on the search results page.  While this isn’t a guarantee that your search results are bad, most of my clients agree that search results page exits are not normally an indicator of success!  Therefore, I like to trend this and set alerts to monitor this.  Here are the steps to do this:

1. Open your Pages report and find your Search Results page in the list
2. Click on its name and in the sub-menu choose Paths – Next Page report
3. Unfortunately, Exited Site might be one of your highest next pages, but in this case it is a good thing since you that makes trending it easier (I haven’t figured out how to trend it id it isn’t in the Top 5!).  Once you are looking at your list of Next Pages, click the “Trended” link to see the top five next pages trended.
4. From here, I usually refine the report to only show the Exited Site and Home Page (for some reason SiteCatalyst won’t let you see just “Exited Site” so you need to have one other value – not sure why – so I normally choose Home Page)
5. Finally, change your date range and View by (i.e. day, week, month) and you will see a report like the one below where I am trending Exits and clicks to the Home Page by percent over time.  You can now add this graph to a dashboard to monitor it over time…

Use Counter eVars!
There are two ways you can use Counter eVars with internal search.  First, per my last blog post, you can use the # of Pages Counter eVar concept to track how many pages visitors view prior to doing a search to see how your website design is functioning.  I showed this in my last post:

Second, you can track the # of internal searches in a counter eVar so you can see how many internal searches each visitor has done prior to completing your desired success event.

Track Recommended/Filtered Search Results
Many companies provide internal website searchers with recommended search results or filtered results based upon the search term as shown here:

You can use SiteCatalyst to track whether the visitor clicked on your organic links or the recommended/filtered links.  All you need to do is add a query string to links in each distinct area and capture that in an eVar when visitors click on these links.  For example, the eVar values may be “organic link click” or “filtered link click” which will show you the distribution.  You can take it further by passing this to an sProp and correlating it to the search term to see which internal search terms lead to visitors clicking each type of result.

These are just a few of the fun things you can do with internal search tracking…

Adam Greco is the Director of Web Analytics at Salesforce.com.  You can read his previous Inside Omniture SiteCatalyst blog at http://blogs.omniture.com/author/agreco/ and can follow him on Twitter at http://twitter.com/adamgreco.  Please send questions and comments to adam@the-omni-man.com.

Please note: I am no longer an employee of Omniture and the content/views expressed here are my own and not those of Omniture.

In my last post, I described some of the benefits of using a Page View Success Event.  In this post I will continue along the same theme by describing the benefits/uses of a Page Name Conversion Variable (eVar).  I recommend you read my last post on the Page View Success Event prior to reading this post as the two go hand-in-hand.

Setting a Page Name eVar
Setting the Page Name in an eVar, while somewhat nontraditional,  can be used for many different purposes.  In this post I will cover just a few, but I am sure those reading this can come up with many more.  The implementation of this couldn’t be easier.  Simply pass the s.pagename value to an eVar and you are done!  The following sections will outline how I use this variable once it is set.

Campaign Pages
Let’s say that you are running a bunch of online marketing campaigns and you want to see how many pages on the website people coming from each Campaign Tracking Code view.  In SiteCatalyst, the main way to figure this out would be to use DataWarehouse, ASI or Discover unless you read my last post and had set a Page View Success Event.  But now let’s take it a step further.  What if you want to see the pages that visitors from each Campaign Tracking Code viewed on your website.  Easy right?  Not so fast.  There is really no easy way to see this in SiteCatalyst using out-of-the-box reports.  One way to do this would be to use the Get&Persist Plug-in to pass the Campaign Tracking Code to a Traffic Variable (sProp) on each page of the visit and then use a Traffic Data Correlation to correlate this new sProp with the Page Name variable, but that is a lot of work!  The other way is to use a Page Name eVar.  By default, your Campaign Tracking Code report will store and persist the Campaign Tracking Code for multiple page views (you choose your time frame in the Admin Console) so if you begin to store Page Names in another eVar, you will have an intersection between Page Name and Campaign Tracking Code on each page.  That allows you to use a Conversion Variable Subrelations report to see all Pages viewed by visitors coming from each Campaign Tracking Code  You can see this by opening up the Campaign Tracking Code report, selecting the Page View (Event) metric and clicking the icon next to a specific Tracking Code to break it down by the Page Name eVar.  Once you have done this, you should see a report like this:

Channel Pages Tracking
If you role up your Campaigns to higher-level Marketing Channels using SAINT Classifications you can use the concept from the Page View Event post to see how many pages are viewed on your site after visitor arrive from each Marketing Channel.

You can then break this report down by the Page Name eVar to see the most popular pages for each Marketing Channel:

While this is not as granular as viewing Pathing by Campaign (as I demonstrated in this post) , it can give you a high-level view of what pages are popular for each different marketing channel.  If you are using the Unified Sources DB VISTA Rule or Channel Manager plug-in, it gets even better as you can see what pages people coming from another website or SEO are viewing on your website by breaking down a particular SEO keyword or external website link by Page Name:

Internal Search Follow-On Pages
If you are properly tracking Internal Search on your website, you should have Internal Search Terms stored in an eVar so you can use this concept to break down Internal Search Terms by this new Page Name eVar (while using the Page View Event) to see what pages visitors view after they search on each specific Internal Search Term:

What Page Does Success Take Place?
Another side-benefit of setting a Page Name eVar is that you can see on which page a Success Event takes place.  For example, if you set a “File Download” Success Event and a file is available on several pages, you can subrelate each file name with the Page Name eVar to see which page is the most popular for downloading each file.

Conversion Variable QA
Finally, there is a completely different use for the Page Name eVar – Quality Assurance.  Often times, you will run into situations where you have eVars that have bad data or no data at all (the dreaded “None” row!).  Often times, these issues are hard to troubleshoot.  However, if you have a Page name eVar, your life is much easier.

Let’s say that you have forms on your website and when visitors complete a form, they are required to enter a “Company Size” field which is stored in an eVar.  However, there are many cases where you are seeing the Form Company Size eVar with no data.  This might mean that IT forgot to make the field required on some of the Forms (would never happen right?).  How do you figure out which forms are causing the issue?  All you have to do is the following:

1. Open the eVar report that has data issues with a relevant Success Event metric (Form Company Size and Form Completes in this example)
2. Find the row that has bad data or no data (“None” row)
3. Click the breakdown icon to break the report down by the Page Name eVar
4. The resulting report (see below) will show you a list of Page Names where SiteCatalyst set the Form Complete Success Event, but did not have a corresponding Form Company Size eVar value

You can then send this report to your IT team to help them find pages where there may be tagging issues.  You could even schedule this as a recurring report to you and IT so you are alerted when similar issues arise in the future, which helps with overall data quality.  Keep in mind that this will only work if the eVar you are looking at has Full Subrelations or you add Full Subrelations to the Page Name eVar (see below).

Final Thoughts
As you can see, there are many different uses of this functionality.  The following are some final pointers related to this topic:

1. As previously noted, if you plan to use the Page Name eVar extensively for testing, I would recommend that it have Full Subrelations so you can QA all eVar reports, not just those that already have Full Subrelations.
2. In one of the rare times I ever tell clients to do this, I would recommend that you set the Page Name eVar to expire at the Page View in the Admin Console.  Expiration beyond that will probably add little value and only slow down reporting.  There are some special things you need to do here if you use Custom Links so I would advice you speak to Omniture  Consulting about this.
3. Consider Classifying the Page Name eVar by Page Type, Page Product Category, etc… to increase the value you get from this eVar.

Adam Greco is the Director of Web Analytics at Salesforce.com.  You can read his previous Inside Omniture SiteCatalyst blog at http://blogs.omniture.com/author/agreco/ and can follow him on Twitter at http://twitter.com/adamgreco.  To be alerted to new blog posts, I recommend subscribing to this blog via e-mail using the tool provided on the top-right of this page.  Please send questions and comments to adam@the-omni-man.com.

Please note: I am no longer an employee of Omniture and the content/views expressed here are my own and not those of Omniture.

By default, most Omniture SiteCatalyst clients are tracking their external Marketing Campaigns using Campaign Tracking.  These reports allow you to see how many Success Events take place on your site for each type of Campaign you run (i.e. E-mail, Paid Search, etc…).  However, I am surprised how rare it is that Omniture clients are tracking their Internal Campaigns (also referred to as Internal Promotions) to the same extent.  Most websites promote products or content on their site through the use of display ads, buttons or links.  These Internal Campaigns should be tracked in the same way as external campaigns.  While I have touched upon this concept a bit in the past in the Conversion Variable post and the Products Variable post, in this post, I will provide the basics on Internal Campaign tracking.

Why Track Internal Campaigns?
So why should you track Internal Campaigns?  At most organizations, there is constant debate about which website promotions perform better than others.  This is especially the case for high-profile pages like the Home Page.  For example, the screen shot below shows four distinct Internal Campaign Promos:

While you can try to see how often visitors are clicking on each promotion item by looking at Pathing reports (look how many people went from Page A to Page B where you had a promotion on Page A), this takes a lot of time and won’t help you if you have multiple links to this same destination page on the same page.  You can try to use the ClickMap feature of SiteCatalyst, but in my experience, ClickMap data is not wholly accurate.  If you have a tool like Test&Target then you can easily test and promote content that is proven to be the best in each content area, but if you don’t, you can use Internal Campaign tracking to provide some basic information.

How to Track Internal Campaigns?
Tracking Internal Campaigns is done through an eVar.  As I have pointed out in the past, the s.campaigns variable in SiteCatalyst is really nothing more than a predefined eVar with Full Subrelations.  Therefore, you can track Internal Campaigns in the same way.  I tend to do this using the getQueryParameter plug-in which captures a code placed in the URL and passes it to the Internal Campaigns eVar.  These codes can be whatever you like, but the parameter identifier should be different from what is used for external campaigns.  In the fictitious example shown here, a user has clicked on a website banner and the destination URL has a “pid” parameter which passes the code “home_hero_112″ to the Internal Campaigns eVar:

As you can imagine, the hardest part of Internal Campaign Tracking is adding tracking codes to each promotion link on your site.  However, this can be built into the process of banner/promo creation and done on a going forward basis if needed.  All you need to do is to come up with a logical naming convention or if you want, you can even just use numeric codes and use SAINT Classifications to add meta-data later.  When using SAINT for Internal Campaigns I tend to use the following Classifications:

1. Page on which the promo banner was shown
2. Location on page of promo banner
3. Format (i.e. GIF vs. Flash)
4. Creative Copy (i.e. $50 off vs. 10% Discount)
5. Owner of the Promo

How to Use Internal Campaigns?
Once you are passing Internal Campaign codes to an eVar, it is time to use the data for analysis.  The most basic way to do this is to open the Internal Campaigns eVar report and look to see how many of your website Success Events take place after a visitor clicks on one of your Internal Campaign elements.  You can see an example of this in the following report:

In this example, I have set an additional “Internal Campaign Clicks” Success Event to track each time a visitor clicks on an Internal Campaign promo item.  You could rely on the “Instances” metric, but as I have stated in this post, I am not a big fan of this.  This new “Internal Campaign Clicks” metric is an internal equivalent to the Clicks metric set by default for External Campaigns.

However, there is one difference between Internal and External Campaigns to keep in mind.  Unlike External Campaigns that usually have one value per visit, visitors can click on multiple Internal Campaigns within one session.  Therefore it is important that you understand the principles of eVar Allocation so you understand which Internal Campaign element will get credit for website Success Events.  If you want to go really deep with Internal Campaigns, you can even set multiple eVars such that you have the following:

1. One eVar to store the first Internal Campaign clicked in a visit (First Value)
2. One eVar to store the last Internal Campaign clicked in a visit (Most Recent)
3. One eVar to store all Internal Campaigns clicked in a visit (Linear) [remember that Linear Allocation is only Visit-based!]
4. One eVar to store all Internal Campaigns clicked across multiple visits using Cross-Visit Participation

One of my favorite reports to run is one in which I look for synergistic effects between External and Internal Campaigns.  Since the External Campaigns eVar comes with Full Subrelations, you can automatically break it down by the Internal Campaigns variable.  Doing this allows you to see which combinations of External campaigns and Internal Campaigns lead to success.  For example, it may be the case that a particular Paid Search Keyword, when combined with a specific Internal Campaign promo converts above the average for the site.  These hidden gems can help you boost overall conversion and are found by simply opening a Subrelation report between the two variables as shown here:

Finally, another benefit of tracking Internal Campaigns is that it enables you to improve your building of DataWarehouse Segments to include visitors who have/haven’t seen a particular Internal Promo.  This information can be valuable to re-marketing efforts in general.

Adam Greco is the Director of Web Analytics at Salesforce.com.  You can read his previous Inside Omniture SiteCatalyst blog at http://blogs.omniture.com/author/agreco/ and can follow him on Twitter at http://twitter.com/adamgreco.  To be alerted to new blog posts, I recommend subscribing to this blog via e-mail using the tool provided on the top-right of this page.  Please send questions and comments to adam@the-omni-man.com.

Please note: I am no longer an employee of Omniture and the content/views expressed here are my own and not those of Omniture.