As I was at Omniture Summit last week, I couldn’t believe that it had already been a year since I started talking about integrating Twitter data into Omniture SiteCatalyst!  Since I haven’t seen many updates about this integration come from Omniture, I thought I would share a few enhancements I have made over the year in case any of them are useful to those out there using the integration…

Competitor Twitter Share
When I first envisioned importing Twitter data into SiteCatalyst, my primary focus was tracking how often my brand was mentioned and importing the brand-related tweets.  This allowed me to monitor my brand usage and filter tweet reports to send the right tweets to the right people based upon search phrases.  However, the more I thought about it, the more I realized that this integration could be used to keep tabs on competitors as well.  Instead of setting one “Brand Mentions” Success Event, you could expand the scope of what is tracked and also grab tweets mentioning your competitors and set a second Success Event named “Competitor Tweets.”  This second Success Event allows you to trend your competitors and track them on the same SiteCatalyst dashboard you use to track your own brand:

This led me to another cool idea…Why not track overall “Competitor Tweet Share” in which you quantify the % of tweets your brand gets in relation to those of your competitors?  This would allow you to trend your “share of twitter” for your narrow competitive niche.  To do this, create a Calculated Metric as follows:

This results in a graph like this which allows you to see when spikes occur to see if local events or press releases move the needle:

You can also set Alerts based upon this Calculated Metric to be notified when you are spiking or tanking in relation to your competitors!

General Tweets
The next concept I thought about was “general tweets” that were related to a business.  For example, if you are Coca-Cola, you might want to keep tabs on tweets mentioning “soda” or “soft drink.”  However, you wouldn’t want these counted as “Brand Tweets” or “Competitor Tweets,” so instead you can set a third Success Event called “Twitter General Mentions” and specify a list of keywords that should trigger this Success Event.  This allows you to see if a list of “general” keywords related to your business is rising or falling over time to gauge the general level of interest in your category over time:

#Fail
Lastly, I decided that the #Fail hashtag was too good to pass up.  If your brand is mentioned in the same tweet as the #fail hashtag, you probably want your social media team (if you have one!) to be alerted at once!  To do this, all you have to do is create a scheduled report with #Fail in the search box and schedule it to run hourly.  Unfortunately, SiteCatalyst delivers hourly reports whether there is data or not (to stop this please vote for this idea) so you may need your social media folks create an Outlook rule to filter the alerts that say “No Data” in the subject.

In addition, you can perform the same exercise for your “Competitor Tweets” since your social media team may want to be notified when your competitors have a #Fail hashtag in tweets mentioning their brand name!

So there you have it…a few minor updates or enhancements to the Twitter – SiteCatalyst integration.  If you have other ideas, please leave a comment here…Thanks!

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.

One question I hear from time to time from Omniture SiteCatalyst users is:  “What are the paths visitors take on my site when they are successful in reaching one of my desired Success Events?”  Basically, on most websites, there are a few ideal paths that you wish all visitors would take.  Unfortunately, most visitors don’t adhere to your ideal path so you need to see what paths they are choosing to take.  Of course, you can use Pathing reports to see all of the paths that visitors are taking, but that can be very cluttered and hide what is really happening related to Success Events.  Therefore, one interesting analysis you can do is to focus only on paths that do lead to success.  I equate this to the old “cow path” story where architects would wait to create sidewalks in front of new buildings to see where people naturally walked and then build the sidewalks where people are already going.  In this post I will show you how you can do this in SiteCatalyst.

But I Don’t Have Discover or Insight?
When I raise this topic, the first thing people say is that they can’t do this because they don’t have Omniture Discover or Omniture Insight.  While those products are great and I highly recommend them, the good news here is that you don’t need those tools to see the paths that lead to success.  In fact, due to a current Discover limitation (more info on this later on), you cannot do this analysis in Discover, but you can do it easily in Omniture Insight.  The one thing you will need to perform this analysis, however, is Advanced Segment Insight (ASI).

So How Do I Do It?
The key to this solution is the Full Paths report in SiteCatalyst.  Normally, this report is a tad boring since there are so many unique paths on a site that beyond ENTER>>HOME PAGE>>EXIT, the rest of the percentages are usually pretty slim (i.e. .1% of all paths).  However, if you could look at this report for a small subset of your website audience, the percentages should go up dramatically.  This can be done with ASI, where you create an entire new data set for a specific segment.  Once you have created your segment and run your ASI slot, you have access to all SiteCatalyst reports, including the Full Paths report.  Hence, all you need to do is to properly identify a segment containing a Success Event, run your ASI slot and then look at the Full Paths report.

The way I start this is by identifying the Success Event that I care about.  Let’s say that you want to see a segment of “Purchasers.”  In this case the only Visits you want to include in the segment are those that have completed an Order within the Visit (feel free to review Segmentation  in my old post):

Once you have created this segment, you now create an ASI slot for, say, 30 days of data (amount of days is up to you).  When the ASI slot has completed processing, you can open the Full Paths report and see which paths are the most popular and include an Order:

I have found it fascinating to extract these paths and look for common trends.  It is often like finding needles in a haystack!  The best part, is that after you have learned what you want to learn, you can delete the ASI slot and re-create it for a different segment.  Here are a few examples you can create:

• View all paths that led to an Order, but only when the visitor was a first time visitor
• View all paths that led to an Order, but only when the visitor was a return visitor
• View all paths that led to an Order that was greater than $100
• View all paths that used a Product Finder and led to an Order
• Etc…

Just remember the formula.  Create segment, run ASI, look at Full Paths (Repeat).  The possibilities are only limited by your imagination.  I usually look at the top five paths for a bunch of different segments and then compare them to see what is common between them.

As I mentioned earlier, it would be much easier to do this analysis in Discover (where segmentation is instantaneous), but currently, there is no Full Paths report in Discover (see my idea suggestion and feel free to vote for it!).  I hope that gets into the product since then you wouldn’t have to wait a few days each time for the ASI slots to process.

What About Failure?
But wait…there’s more!  As Avinash Kaushik likes to say, one of the cool things about the web is that you can fail faster (and learn)!  Therefore, you shouldn’t just look at success, but you should also look at failure.  Why not create an ASI slot for visits where people did NOT succeed (create an Order in this case)?  Find out where people are most often taking wrong turns and maybe you can correct them.  Remember, when you perform normal Pathing analysis, you are seeing the good paths mixed with the bad paths, but with this solution, you can easily segment them out and analyze each separately.  Here is a sample segment definition you can use (notice “Exclude” – opposite of the first segment):

Well…there you have it, a quick and dirty way to see which paths lead to success (or failure).  Enjoy!

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.

Lifetime Metrics in Omniture SiteCatalyst are one of the most obscure and least utilized features in the entire product – and for good reason.  In their current implementation, they do not do all that much.  In this post I will explain what they are, how they are meant to be used and offer some suggestions on how Omniture can turn Lifetime Metrics into a more useful feature.

What Are Lifetime Metrics?
Before reading this post, I would hazard a guess that the majority of you reading this have never used Lifetime Metrics and that a good number of you haven’t even heard of them (at least based upon my experience when I was with Omniture Consulting!).  Most people who hear about them assume that they are metrics that are stored for website visitors for their entire lifetime (or until their cookie is deleted).  Unfortunately, that is not correct, as Lifetime Metrics have nothing to do with unique visitors or cookies…  When Omniture calls these “Lifetime Metrics” they mean the lifetime of the report suite (data set) in which the metrics reside.  For example, if you have a website Success Event for Form Completions, you use a regular Success Event to see how many Form Completions take place each day, week, month, etc…, but you would use the Lifetime Metric version of that Success Event to see the total number of Form Completions that have taken place since they were ever collected in the report suite.

So let’s say that in your main report suite, you started collecting Form Completions about a year ago and were segmenting those Form Completions by Traffic Source.  In the current month, you had 27 Form Completions driven by SEO, but going back until you started collecting Form Completions in the report suite, you had a total of 964.  In this situation, you would click the “Add Metrics” link and when you see the metrics selector window, you would use the drop down box (same place you go to use Participation or Calculated Metrics) and change “Standard” to “Lifetime” as shown here:

Once you have selected “Lifetime,” you should see a list of metrics that looks similar to what you would see under “Standard,” identical to what but with the word “Lifetime” in front of each (if you don’t see these metrics, talk to your Account Manager or ClientCare).  Simply select the appropriate Lifetime metric you desire (Lifetime Form Completes in this example) as you would any other metric and you would see a report like this:

As you can see here, the metrics for standard Form Completes is very different than the Lifetime Form Complete metric.  Again, this Lifetime metric has nothing to do with Cookies, but rather, it represents the sum total of all Form Completions that have taken place since the inception of the current report suite.

So What Can You Do with Lifetime Metrics?
Great question!  The truth is that these metrics are a bit limiting.  Here are the things I have seen done with these metrics:

1. You can use these metrics to see how you are doing in the current time period as compared with historical performance.  For example, in the report above, it might be interesting to note that SEO is greatly under-performing during the selected time frame (13.5%) as compared to its past performance (23.1% of Form Completes).
2. You can divide Form Completes by Lifetime Form Completes to see how the current time frame is contributing to the overall total.

I have really struggled to find other cool things you can do with these metrics, but I am hoping that maybe one of you can share how you have used them so I can learn new ways to use them (along with my readers)…

What I Would Do With Lifetime Metrics…
If you have read my posts in the past, you have heard me say that I don’t like to complain about something unless I can offer some potential solutions.  This will be no different.  I think that there is one simple change that Omniture can make to dramatically increase the usefulness of Lifetime Metrics… (drum-roll please…):

Give SiteCatalyst Administrators the ability to determine when Lifetime Metrics are re-started/expired

I know this subtle change doesn’t sound like it would accomplish much, but here is why I think it could:

Tying Lifetime Metrics to the date that data was collected in a report suite makes little sense.  Often times, you need to start a report suite or move to another one on arbitrary dates.  Therefore, these Lifetime Metrics make no sense in a business context.  If I use the same report suite for three years, why on earth would I want to see how my current month/quarter is doing compared to the last three years?  How would my users even know that Lifetime Metrics had been stored for three years?  It just doesn’t help make these metrics valuable.  However, if I could choose when Lifetime Metrics started over, I might re-start them on January 1st of each year and now I have a cool, easy way to see YTD information (i.e. how March is performing in relation to January-March).  As described above, I can also see how the ratio of SEO or SEM is performing against my YTD percentage.  Maybe I want to keep these metrics for two years, or re-start them when my company’s fiscal year starts – that should be my choice using the Admin Console.  While this will not propel Lifetime Metrics to MVP status of SiteCatalyst features, you could actually have something of use (of course, it would probably require a name change since Lifetime Metrics may not be appropriate) and bring this feature “back from the dead” so to speak…

Well…that’s it…just wanted to provide a bit of education about this little known feature and some suggestions on how it might be improved… If you would like to see the change I propose made by Omniture, click here to vote for this idea in the new Idea Exchange (requires an Omniture Account).

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.

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.

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.

In this post, I am going to talk about how Data Quality can kill an Omniture (or other Web Analytics) implementation.  I will share some of the problems I have seen and show some ways that you can help improve Data Quality…

Sound Familiar?
So you have been managing an Omniture implementation for a while.  You have your KPI’s lined up.  You have been sharing some dashboards and reports with people throughout your company.  People are starting to realize that they should talk to you before making website business decisions.  Suddenly, you find yourself in the executive suite to answer some key website questions.  Then, just as you are wrapping up your web traffic overview, an executive starts to calculate some numbers on a notepad and determines that the increase you show in Paid Search traffic doesn’t look right given other data they have seen from the SEM team.  She also questions the rise in traffic data for EMEA, knowing that his VP in the region told you traffic has been down over the last few months.  Suddenly, you are in a web analytics death spiral.  In a split second, you have to decide, do you defend your Omniture data and risk your reputation or do you back-pedal saying you will re-check the web analytics data and live to fight another day?

Hopefully this hasn’t happened to you, but it has happened to most of us who have been around the web analytics space for long enough.  Unfortunately, you only get so many chances to be wrong  about data you are presenting and even if your data is right, if you aren’t confident enough to stand by it, it might as well be wrong.

Minimizing Data Quality Risk
So how do you avoid this situation?  The first step is to realize that there is no way to be sure that all of your web analytics data is correct.  100% Data Quality is not only unattainable, but also not worth the time and effort it would take to achieve.  Therefore, I use a philosophy of risk minimization in which I try various techniques to minimize the key things that cause data quality issues.  The following will show you some of the ways to do this:

Ensure all Pages are Tagged
This is easier said than done.  As we all know, IT is usually used to deploy JavaScript tags and they often have more important things to do than to guarantee that every website page has a the [correct] JavaScript tag.  Fostering a good relationship with IT helps, but at the end of the day, new website pages are created all the time, and tags will be missing.

Use Technology
As you can imagine, where there is a need, there are technology vendors.  The main vendors that I have worked with or heard the most about are WASP and ObservePoint.  Not completely coincidental, ObservePoint was founded by John Pestana who was one of the co-founders of Omniture.  In a great blog post, John Pestana talked about getting rid of asterik’s in web analytics reports.  I am sure there are many other vendors out there offering similar products, but the gist of the technology is that it can spider your website and let you know which pages are missing JavaScript tags so eliminate any obvious omissions.

Blood, Sweat & Tears
Unfortunately, the main way that I have minimized web analytic data loss is by downloading data and looking for anomalies.  I normally do this by taking advantage of the Omniture SiteCatalyst Excel Client and downloading key data blocks by day or week and then using formulas to compare yesterday to the same day last week or last week to the week prior.  Once you have the data in Excel, you can do any type of statistical analysis you want on the data to see if anything looks “fishy.”  One thing I like to do is to use Excel conditional formatting to spot data issues.

The following is a screenshot example of using Excel to spot potential data issues.  In this example, I am looking at Page Views from one week prior to each day and if there is a change of more than 20%, I highlight it in red:

Uh-oh… It looks like our daily data quality report indicates that we may have lost a tag on Friday for the Login page and something suspicious took place related to the Search Results page the same day.  Obviously, the downsides of this approach are that it is extremely manual and that it is in arrears.  As you know, once you miss a time slot of data in SiteCatalyst, there is no easy way to get that data back.  While this approach can minimize the data loss to a day, it won’t help you get the Login Page data back in the example above.

Therefore, the way I employ this approach is to focus on the top items within each variable.  This means, I focus on the pages with the most Page Views, the Form ID’s with the most Form Completions, the Orders for the most popular products, etc…With the Excel Client, you can download multiple data blocks at once and then use conditional formatting to easily spot the issues.  Done intelligently, Data Quality for 80% of your data can be done in under a few hours each day.  By doing this, you can feel more confident when your VP questions your data knowing that if something were significantly off, you would have known about it ahead of time.

Special Cases
I have found that there are a few other situations that commonly lead to missing or bad data so I quickly wanted to bring them to your attention so you can apply some additional effort to ensure they are tagged correctly:

1. “Lightbox” pages where a new HTML page is often not loaded.  These often times are created as a window within a window and many times developers forget to put SiteCatalyst code within them.
2. Flash/AJAX pages where the page changes dynamically or you have an entire site/page developed in Flash.  By extra careful around these as they often are missing tracking code (especially when done by an outside agency!).
3. Dynamically generated content, such as a page that shows historical stock price data after a user enters a ticker symbol.  Often times, these dynamic pages are tagged as one single page, but might be better as unique pages from a web analytics viewpoint.

SiteCatalyst Alerts
If you have read my previous blog post on Alerts, you may figure out that you can use Alerts to help with Data Quality as well.  Alerts can be used to look for changes in key metrics by Month, Week, Day (or Hour in some cases).  These alerts can be handy to be notified when data is off  by more than x%.  However, I have found that if you want to look a more granular data (as in the example above), the current Alert functionality can be a bit limiting.  You can set alerts for specific sProp and eVar values, but not as easily as you can by using Excel.  Therefore, I would use Alerts as an early warning system an employ the previously mentioned techniques as your main defense against missing data.

Classification Data
Finally, when  thinking about data quality/completeness, don’t forget about SAINT Classifications.  If you have key reports that rely on SAINT Classifications, even if you have the source data collected perfectly, if you are missing key SAINT Classifications for that source data, your reports will be incorrect and indistinguishable from poor data quality in the eyes of your users.  You will know if you are missing SAINT Classification data if your classified reports have a large “None” row.  So how do you ensure your SAINT Classification data is complete?  What I do is create Excel data blocks for each Classification and isolate the “None” row for key metrics.

In the screenshot below, you can see that I have created a data block that looks for “Unspecified” Site Locale Full Names (the Excel Client doesn’t use None, but it uses “Unspecified” instead for some reason).  In this scenario, I store a 2-digit website country identifier in an  eVar and use a SAINT Classification to provide a full name.  I filter on “Unspecified”  where the metric is Visits, Form Views and Form Completes.

After running, you will see a succinct report that looks like this:

In this case, there are no Form View or Form Complete Success Events missing a Full Site Locale SAINT Classification, but there are some Visits missing the classification.  You can then easily go into SiteCatalyst or Discover, open the Full Locale Name report and break it down by its source to find out what values are left to be classified.

Finally, if you want to earn “extra credit” you can do this for all of your SAINT Classifications in one Excel workbook and make a summary screen like the one below which pulls the percentages that are unclassified into one screen so you can see how you are doing overall.  What is cool about this is that you can use the “Refresh All” feature of the Excel Client to check all of your Classifications while you get coffee and when you get back, you have a fully updated view of your SAINT Classifications.  In the above below, I have shaded some items in black that are OK if they aren’t fully classified, items in green that are acceptable and items in red that require attention:

Final Thoughts
As you can see, Data Quality is a HUGE topic so it is hard to cover it all in one post, but hopefully some of the pointers here will get you thinking about how you can improve in this area.  One last thing I will mention is that like most things related to web analytics, tools are good, but qualified people are better!  Therefore, I think that any serious web analytics team will have a resource who has Data Quality as one of their primary performance objectives.  Without this, Data Quality tends to fall by the wayside.  Try to do whatever you can to convince your management that having a full or part-time person devoted to Data Quality will pay hefty dividends in the future…

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.

This week I will round out my Pages in Conversion trilogy by discussing a # of Pages Viewed Counter eVar.  Two posts ago I discussed some of the benefits of setting a Page View Success Event and in my last post I showed some of the cool things you can do by setting a Page Name eVar.  While this post will not be as “meaty,” I wanted to share a quick tip that can help you out for a few cool analyses.  If you haven’t already, I suggest you read my last two posts as it might be helpful.

Counter eVar Refresher
About a year ago I blogged about what a Counter eVar was in the following Counter eVar post.  If you are unfamiliar with Counter eVars, I suggest you review that post before continuing.  In a nutshell, a Counter eVar allows you to increment an eVar with a numeric value (usually incrementing by one) when a specific action takes place.  For example, if you would like to count how many times website visitors conduct searches on your website prior to adding an item to the shopping cart, you would use a Counter eVar to store a numeric value in each website visitor’s cookie so that when the Cart Addition Success Event takes place, you can associate that number of internal searches with that Cart Addition.

# of Pages Viewed Counter eVar
OK.  So now let’s get into this week’s topic.  I often like to set a Counter eVar on each page of the website so I have a running count of how many website pages the current visitor has viewed.  Setting this is pretty simple as you only need to set a Counter eVar to “+1″ on each Page View and if you are setting a Page View Success Event it can be done concurrently.  So what does setting this # of Pages Viewed Counter eVar get you?  Well, no matter what Success Events take place on your website, it may be interesting to see how many pages the active visitor has/had viewed prior to that Success Event taking place.  For example, let’s say you are trying to drive website Lead Capture Form Completions and you want to know if Forms are being completed relatively quickly (after 1-3 pages) or taking more time (after 10 pages).  This is not easy to do with out-of-the-box SiteCatalyst reports.  You can see Average Page Depth of each Form Page, but I find that very limiting.  Using this Counter eVar, you have a simple, clean way to see how many pages visitors had seen prior to completing a Form (in this example):

However, you get more than just this.  Since all eVars break down all Success Events, this one Counter eVar will work with all of your Success Events so you can see any Success Event broken down by # of Pages Viewed.  All you have to do is add a different Success Event to the report above and you can see how many pages it took visitors to perform that action.  In the following example, we can now see how many pages visitors see prior to performing an Internal Search:

In this case, we can see that about 50% of all Internal Searches are taking place in the first four pages that visitors see.  This could be expected, but if your goal is to improve page content and navigation, this might be an indicator of how well your changes are doing over time…

Use with Subrelations
As they used to say in the commercials: “but wait…there’s more!”  The above reports only scratch the surface of what you can do with this new Counter eVar.  For example, let’s imagine in the first example above that we now want to see how many pages it takes to get visitors to complete a specific website form.  If you are capturing the name of the Forms on your website in another eVar and it has Full Subrelations, you can see the following:

Again, the same concept would apply to other Success Events so in the Internal Search example above, you can use subrelations to see how many pages website visitors had viewed prior to searching on a specific phrase.

Don’t Forget Classifications
One quick little enhancement to the # of Pages Viewed eVar is that you can use SAINT Classifications to bucket pages viewed into more manageable groupings.  For example, you can see the same Form Completions report above in more concrete buckets by using SAINT to see the following:

Final Thoughts
That is the quick overview of setting a # of Pages Viewed Counter eVar.  Here are a few final things to keep in mind:

1. As with all eVars, you need to determine when it will expire.  I tend to like to keep the # of Pages to an expiration that is longer than a visit so if a visitor comes back multiple times, you can see how many total Page Views they had done across more than the current visit.  You can use “Never” to see all Page Views or if you have one key Success Event, you can expire the eVar at that event and then start the counter over.
2. You can use the same SAINT Classification file for all Counter eVars so if you create it once, be sure to re-use 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.  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.

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.

Those who are familiar with Omniture SiteCatalyst come to learn that there is a big difference between Traffic Variables (sProps) and Conversion Variables (Events & eVars).  This separation can get in the way of many analyses unless you have access to Omniture Discover.  In this post I will describe one of the methods you can use to blur the lines between Traffic and Conversion variables by describing the use of the Page View Success Event.

Why a Page View Event?
In my experience as an Omniture Consultant, I found that most non-Media clients did not utilize a Page View Success Event.  However, there are great reasons why all Omniture clients can benefit from a Page View Success Event.  So what exactly is a Page View Success Event?  It is basically nothing more than setting a Success Event on every page of your site (kind of obvious huh?)!  Setting a Page View Success Event is very easy and can be done with minimal updates to your JavaScript file.  Once set, you will have a Page Views metric in your list of Success Events and this metric should, for the most part, be the same as the Page View metric you would see in the Traffic reports area.

OK.  So now you have the same metric you already had.  Doesn’t sound very exciting does it?  Despite its simplicity, it actually can be very beneficial.  Here are a few examples of what you can now do with this newly created Page View Event:

Basic Visitor Engagement
Let’s say that you are running a bunch of marketing campaigns and in addition to seeing how many purchases or leads each campaign generates, you also want to see how many pages on your site those arriving from each Campaign viewed.  Sounds easy right?  But how would you do this?  In the Traffic report area, there is no easy way to do this without using DataWarehouse, ASI or the Get&Persist Plug-in.  However, now that you have a Page View Success Event, you can open up your Campaigns report and in addition to your other site Success Metrics, you can add Page Views to see the number of Page Views visitors viewed on your site.  Having this metric is a [very] rudimentary way to view Visitor Engagement for Campaigns.

If you use the Unified Sources Vista Rule (or the JavaScript version known as the Channel Manager) to roll-up your traffic sources, you can use the Page View Event to see which Marketing Channel leads to the highest Number of Page Views on your site:

In addition, you can see how different Campaign Tracking Codes performed against each other with respect to Page Views by opening the same report at the Tracking Code level. For example, you can use this concept to see how many Page Views a particular Google Paid Search Keyword leads to on your site by finding that particular keyword in the Tracking Code report:

Internal Campaign Page Views
So earlier I mentioned that most Media clients set a Page View Event by default.  The reason they do this is that for most Media clients, Page Views represent how they make money!  They usually get paid for every Page View (through online advertising) so Page Views is one of their most important success metrics.  However, even if you aren’t a Media client you can use the same concept on your site.  Though you may not sell advertising on your site, you are most likely showing display ads for web promotions or to drive people to other areas of your site.  If you set an Internal Campaign code each time someone clicks on one of your on site promotions, you can use the Page View Event to see how many Page Views on your site each internal display ad leads to.

Basic Success Event Efficiency
Every once in a while, a client will ask me to do some analysis on how many Page Views it takes for visitors to complete website Success Events.  I have seen many clients try to answer this question by opening the Calculated Metric window and trying to create a metric that divides a particular Success Event by Page Views only to be puzzled why Page Views is not an option in the metric selector!  Why isn’t Page Views there?  Because Page Views is a Traffic metric and your Success Events are conversion metrics and you can’t mix those in SiteCatalyst.  However, if you have a Page View Success Event, you can easily create a Calculated Metric to see this.  Simply divide any existing Success Event metric by the Page View Success Event and you will be able to see a trended ratio that compares the two.  I call this Success Event Efficiency (at a high level, how many pages do visitors need to see for each Success Event) and it can provide an alternative view of how your site is performing.

Internal Search Term Influence
Ever wonder how many pages on your site people view after searching on a particular term using your site’s internal search?  How about seeing this for each internal search term?  While this sounds easy, it isn’t with an out-of-the-box implementation.  But if you have a Page View Success Event and are already storing internal search terms in an eVar, all you have to do is open the Internal Search Term eVar report and add the Page Views Success Event to the report.  This metric will show you how many pages were viewed on your site after each internal search term was passed to the eVar.

Sort by Page Views and you can see which internal search term led to the most site Page Views (keep in mind that the length of time you select to to expire the internal search term eVar will impact how many page views are shown, but most people expire this at the end of the Visit).  Another thing I have done is divide the number of Pages Viewed by the number of Internal Searches [Success Event] to see how many pages visitors tend to view after searching on each specific term (see 3rd column above).

Final Thoughts
As you can see, adding a Page View Success Event has many different uses and I have only touched upon a few here.  I encourage you to consider if you have a use for this for your SiteCatalyst implementation.  If you decide to do this, I would recommend the following:

1. Be sure to name the Success Event appropriately so you don’t confuse it with the Traffic Page View metric.  I tend to name the Page View Success Event as “Page Views (Event).”
2. Keep in mind that when you set other Success Events you need to have both in the s.events string separated by a comma (i.e. s.events=event1,event10).  You want to be sure you don’t lose your key website Success Events when you implement this!
3. Keep in mind that setting multiple Success Events can have an impact on latency so be sure to talk to your Account Manager if your site has a lot of traffic.
4. It is not recommended that you set a Page View event when using Custom Links.

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.