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.

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.

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 sie 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.

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.

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.

A few weeks ago, fellow Omniture SiteCatalyst blogger Jason Egan described some ways to take advantage of the Menu Customization feature in SiteCatalyst.  I wrote about how to use the Menu Customizer in this post, but recently I have been wanting to do something new with the feature that doesn’t appear to be possible.  In this post I will describe what I am trying to do in hopes that someone else out there knows of a way to do it or if nothing else to get it on the radar of the SiteCatalyst product management team…

Why Classifications Mess up the Menu Customizer
For those of you who are savvy enough to understand SAINT Classifications, you will quickly realize how powerful they can be in a SiteCatalyst implementation.  In addition to the normal function of rolling up data into groups, SAINT Classifications are great in cases where the root source of the data is not as “clean” as you would like.  For example, imagine a scenario where you are trying to capture two character text strings for US States into a Traffic Variable.  Unfortunately, your developer has passed data in using both upper and lower case (i.e. CA and ca).  While this can be fixed going forward, there may be reports you need to show that group these together.  Therefore, you would create a SAINT Classification and lump both of these values into a value of “California” in the classified report.

So far so good.  But what if you wanted to show only the Classification report, but not the source report (the one with the “CA” and “ca”)?  Believe it or not, this is actually possible by 1) creating a custom report for the Classification version of the variable and then 2) using the Menu Customizer to put this custom report in the right spot and 3) hiding the original report that was classified.  However, there is one major drawback of this approach.  If you ever need to have a user perform a break down by that classification, for say a Traffic Correlation, you are completely out of luck since hiding the source report disables the ability to break it down.  So in this case, if you had an Internal Search Term report and wanted to break Internal Search Term instances down by state (either the “CA” version or the “California” version), you cannot do it once you have hidden the source report.  The same limitation applies to classified Conversion Variables (eVars) and Conversion Variable Subrelations.

Proposed Solution
While the example above is somewhat basic, there are many cases where you might want to show a classified version of a report, but not show the source report of the same variable. Unfortunately, since you cannot even see Classifications in the Menu Customizer yet, I am not optimistic that this will be addressed anytime soon, but in an ideal world, it would be possible to do the following:

1. See SAINT Classifications in the Menu Customizer as they appear in the regular SiteCatalyst menus and have the ability to hide/move any of them or the source of the Classification.  Currently, most of my Classification data appears in a 3rd level fly-out from the menus and it would be great if I could move these reports anywhere I’d like as I can with non-classification reports.
2. In cases where the source of the Classification is hidden, still allow users to breakdown Traffic and Conversion reports by the classified versions of the source variable
3. If a Custom Report is created using a variable that has Classifications, allow users to have breakdowns of that report in the same way they would if they were looking at the regular version of that report (i.e. don’t punish users for using the Custom Report functionality!)

If anyone out there has come up with a work-around for this, 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.  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.

Thanks to all of you who took the time to complete my SiteCatalyst quiz.  I hope it was a fun way to put your knowledge to the test.

So for the rest of this post, I will show how people answered the survey and point out what answers I was looking for.  When looked at as an entire population, if I include anytime someone got the correct answer, the majority of people got 10 correct answers out of 15 (66.67%).  However if I just look at just those responses where the exact right answer was given (no incorrect answers included where you could check off multiple boxes), the average score went down to about 6 out of 15.  However, please bear in mind that I am not an educator so if you interpreted a question differently than I did and gave a different answer, it is probably my fault not yours so don’t lose any sleep over it!  On the bright side, one (anonymous) individual in Europe got 14/15 correct (I am resisting the urge to find you by IP address and hire you!).  Either way, I strongly encourage you to look at your answers and see which ones you missed and read the linked posts below so you can become a SiteCatalyst Ninja!!

Question #1 (Correct Answer=Traffic Variables (sProps))
This first question was intended to be an easy one.  Think of it as a way to build engagement and not scare you off.  Most of you got this answer correct, but I was surprised to see that 33% of you thought that you could enable Pathing on more than just Traffic Variables (sProps).  Keep in mind that one of the main reasons to use sProps is to enable Pathing.   If you need a refresher, please check out my past posts on Traffic Variables (sProps) or on Pathing.

Question #2 (Correct Answer=True)
For many of these True/False questions, it is hard for me to tell if you got the right answer based upon knowledge or luck, but I am going to give you the benefit of the doubt!  In this case 75% of you were correct in saying that it is possible to share a segment with other users in your company.  I show how to do this in my past post about the Admin Console.  Keep in mind that you can only share a segment within one report suite so if you have multiple report suites you are out of luck.  If you really need to share segments across multiple report suites, the only way I know to do this is to create them under a shared Omniture User ID and give that ID to multiple users so they can see the segments owned by that ID.

Question #3 (Correct Answer = ZERO)
This question is admittedly a difficult one.  To get this one right, you would have had to really been in the trenches with SAINT Classifications.  Those who have ever tried to classify a variable that has a value of “0″ in the Key column have probably learned this the hard way.  While you can classify a value of “1″ or “43,” there is no way to classify a Key value of “0″ in SiteCatalyst.  Therefore, you need to pass in a text value for “0″ so you can classify it later on.  Therefore, the best answer to this question is the 3rd answer below “ZERO.”

Question #4 (Correct Answer=When a Success Event takes place or after a specified Time Period)
You guys knocked it out of the park on this one.  The correct answer here is that an eVar can be expired when a Success Event takes place or based upon a time period.  This happens to be one of my pet peeves since I really wish you could expire an eVar based upon a Success Event or a time period (whichever comes first).  There are many cases where having this ability would have saved me a lot of time.  Maybe in a future release (or all of you can help me by requesting this as a feature request!).

Question #5 (Correct Answer=True)
Most of you got this one right as well.  One of the cool things about classifying Conversion Variables (eVars) is that if you have paid for full subrelations on the eVar it is based off of, you get full subrelations on all of the Classifications.   This can save you time and money!

Question #6 (Correct Answer= All but Conversion Variables (eVars))
This question was a hard one and another one of my pet peeves.  The correct answer is the second one “Conversion Variables (eVars).”  The security features in the Groups area of the Admin Console are very good and a much better way to hide reports from select groups of users than the Menu Customizer.  However, for some unknown reason, you can hide pretty much everything in SiteCatalyst except Conversion Variables (eVars), which are some of the most critical reports!  I am not sure why this one thing was omitted and I have been asking for this for some time.  Hopefully it is on the product roadmap.

Question #7 (Correct Answer=None of the Above)
This question probably caused some confusion due to the wording, but the correct answer here is “None of the Above” since I was looking for the best way to assign credit across multiple visits.  Most of you fell for the trap I set here and chose “Linear Allocation.”  Many people I talk to think that Linear Allocation of an eVar works across multiple visits, but it does not.  Linear Allocation only works within a visit (for the most part, but the details are a bit confusing!).  Therefore, the real best answer for this question was Cross-Visit Participation which I covered a while ago.  Cross-Visit Participation is the only real way to assign credit to an eVar across multiple visits.  If you are not familiar with Cross-Visit Participation, please review my previous post.

Question #8 (Correct Answer=None of the Above)
Importing offline or external data via Data Sources is a more advanced topic, but many of you look like you are familiar with it.  The majority of you got this one correct since none of the options provided here will allow you to back out data sources metrics.  For this reason you have to be extremely careful when importing Data Sources data since there is really no going back if you make a mistake!

Question #9 (Correct Answer=False)
This is one of those questions you used to get from your teacher and absolutely hate them afterwards when they told you the answer, so I will apologize in advance.  The key phrase here is “the only difference” so the correct answer here is “False.”  While the difference cited here is correct, there is one really big difference between Correlations and Subrelations that you need to know.  That difference is that you can correlate two sProps, five sProps or twenty sProps with each other, but with Subrelations it is an all or nothing proposition.  It would be great if you could Subrelate just two eVars together, but that is not currently possible like it is for sProp Correlations.  This is a key thing that every SiteCatalyst Ninja must know!

Question #10 (Correct Answer=Unique Visitor Counts an Pathing)
Most of you got this one correct.  The key disadvantages of Roll-ups are that they don’t de-dup uniques and you cannot do Pathing analysis.  But hey, they don’t cost a lot!  Personally, I tend to not use Roll-ups since I can duplicate a lot of the info they provide using the ExcelClient and I like Pathing and de-duped Unique Visitors so I tend to favor Multi-Suite tagged sites.

Question #11 (Correct Answer=Calculated Metrics)
Great job on this one as most of you got this one correct!  In my post about Conversion Funnels I explained all of the ways they can be used and highlighted what, in my opinion, is an oversight of the functionality that you cannot add Calculated Metrics to them.  I hope this ability will be available at some point in the future, but in the meantime, you should keep this in mind when determining whether you should pass in a metric organically or rely on a calculated metric.

Question #12 (Correct Answer=Page Views)
In this question, I allowed you to choose from the following metrics.  While most of you got this correct that the Page Views metric is available in Traffic Variable Correlations those of you who also said that you could add Visits, DUV’s and MUV’s were not correct.  Please keep in mind that only Page Views are available when using Correlations.

Question #13 (Correct Answer=Classifications cannot be used in DataWarehouse Segments)
I had a hard time figuring out how to word this question, but if you really understand SAINT Classifications, you should have been able to get this one right by the process of elimination.  As you can see, most people had a hard time with this one, but the correct answer did emerge in the end as the only true statement below is that Classifications cannot be used in DataWarehouse Segments.  We can deduce this by understanding that 1) Classifications can be used in correlations/subrelations, 2) Classifications can be used in Omniture Discover and 3) Classifications cannot have pathing enabled in SiteCatalyst (You can, however, apply Pathing to classifications in Omniture Discover, which you can read about in this post on Page Type Pathing).

Question #14 (Correct Answer=False)
While I have been using Advanced Segment Insight (ASI) segments for many years, I only recently figured out that you can change the ASI type from recurring to time slice and vice versa if you know what you are doing so the correct answer below is actually False (the whole double-negative thing!).  If you have a static ASI that has run for say last month, you can use the “Add Data” link to bring up the ASI segment set-up screen, change the type to Daily Recurring and make the start date the day after your ASI last ran.  Just be sure to uncheck the box that asks if you want to remove existing data or you will lose your past ASI data.  If the ASI you already have is a Daily Recurring, simply wait until it has finished its daily processing and click the “Cancel” link.  Once you have cancelled it, you can click the “Add Data” link, make the type “Time Slice,” select your dates and set it to run.  Again you have to be sure to uncheck the remove existing data checkbox.  I am not sure if this is “officially” supported, but I have done lots of testing on it and so far it has worked fine…

Question #15 (Correct Answer=>!)
This last question is one of those “inside secrets” that only true SiteCatalyst Ninjas know.  Unfortunately, only 32% of you got this one right as the correct answer is “>!” which is a way to tell if a value exists or not in a specific variable when using the segment builder.  I covered this in my Tips & Tricks are of the Segment Builder post so if you didn’t get this one correct, check out that post which has lots of goodies in it.

Well, there you have it.  Hopefully this was a fun way for you to see some of the things that SiteCatalyst Ninjas know.  If you keep reading my blog posts, I can (almost) guarantee you will learn everything that there is to know…

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.

While there are many great out-of-the-box reports in Omniture SiteCatalyst, there is one key limitation to them that can cause problems from time to time.  This limitation is that you cannot apply  SAINT Classifications to out-of-the-box reports.  In this post, I will demonstrate why this can cause issues and how I get around this limitation.

What’s The Big Deal?
So you cannot classify some out-of-the-box reports.  What’s the dig deal?  Let me show you a real-life example of where this limitation comes into play.  Let’s imagine that your boss tells you that he needs to see a weekly report of the top 25 Natural Search Keywords leading to Site Registrations.  No problem!  Simply open the Natural Search keywords report, add the Site Registrations Success Event and schedule the report for delivery (easy enough!).  However, the life of a web analyst is never that easy.  Next your boss says that he needs to see the same weekly report, but broken out by Branded vs. Non-Branded Natural Search Keywords.  Uh oh!  Now you have a problem.  Your first thought is to use the ExcelClient to download the Natural Search Keywords report and then use a pivot table to group each Keyword into Branded vs. Non-Branded buckets.  However, you soon realize that this will soon become a maintenance nightmare as you will have to manually do this each week and there isn’t an easy way to distribute the report to all Omniture users like you can through a SiteCatalyst Dashboard.  So next, you recall reading a [brilliant] blog post about Classifications and realize that the easiest thing to do would be to classify the top 200-300 Natural Search Keywords and then add the Branded vs. Non-Branded Classification version of the report to a SiteCatalyst Dashboard.  This would only require a one-time work effort and barely any maintenance.  Problem solved!  However, when you go to the Admin Console to add a Classification to the Natural Search Keywords report, you soon discover, that there is no way to do this (why, Omniture why?).  The inability to classify this report can have a real negative impact on end-user adoption, which is why at times, this can be a big deal.

But this is not the only place where this limitation can haunt you.  Another common example, is the Visit Number report.  It is pretty cool that you can look at the Visit Number report and add a Success Event metric and see what percentage of success takes place within the first visit, second visit, etc…  But if your site has a “long tail” it may take many visits for success to take place.  How would you like to present your boss with a report about Internal Searches that looks like this:

While not the worst thing in the world, this report does not provide an easy way to perform analysis, nor does it “tell a story” at an executive level due to its level of granularity.  However, if you could classify the Visit Number report, you could create a more functional report like this:

Here we can more easily see that the bulk of Onsite Searches are being conducted by first timers and those who have been on the site many times which can lead to follow-on questions.

The following are some of the places where I have run into this limitation:

1. Search Keywords
2. Search Engines
3. Visit Number
4. Referrers/Referring Domains
5. GeoSegmentation Country, Region, City, etc…

The Workaround
So if this limitation has affected you or you could see how it might in the future, how do you get around it?  Thankfully, the solution is very easy if you know what you are doing.  To get around this problem, all you need to do is to use JavaScript (or in some cases a VISTA Rule)to copy the values stored in these out-of-the-box reports into regular Traffic Variables (sProps) and Conversion Variables (eVars).  By duplicating this data into custom variables, which can be classified, you can use the Menu Customizer to steer your users to the custom versions of each report (which contain the Classification) instead of the out-of-the-box versions.  I have seen this quick/easy solution help clients turn otherwise unused reports into versions that are popular amongst SiteCatalyst end-users.

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.  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.