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.

Recently out on Twitter, someone had asked how you can calculate Bounce Rate for various Traffic Sources.  In the past I have shed light on how you can create Bounce Rates for campaign elements, visitor types, etc…, but I failed to share how to see Bounce Rates for SEO, SEM, E-mail, etc…  In this post I will share the way to do this. If you are reading this post, odds are you know what Bounce Rates are, but quickly, it is the percent of visitors who saw one thing (normally page or section) and then went no further.  If you need a refresher on Bounce Rates, you can look at my old Bounce Rate post, or better yet, check out Avinash’s post on Bounce Rates.

Why Traffic Source Bounce Rate?
Often times, marketers want to see how each of their disparate online marketing channels are doing when compared to each other.  Most will rate them by how well they perform against the website KPI’s.  However, due to its popularity, may want to see the Bounce Rate for these online traffic sources.  While my Segment Pathing post showed you how to see the bounce rate for a specific traffic source element (i.e. SEO Google keyword going to your home page), what if you want to see the total Bounce Rate for SEO or SEM?  Unfortunately, that doesn’t come out of the box in Omniture SiteCatalyst (though you can derive it in Omniture Discover).  I am not going to tell you whether the Traffic Source Bounce Rate is a valid metric as that depends upon your business objectives, but the next section will outline how to implement it.

Implementing Traffic Source Bounce Rate
So how do you implement Traffic Source Bounce Rate?  Like any Bounce Rate metric, you need to be able to calculate Single Access and Entries.  In SiteCatalyst, that means you need Pathing to see these metrics, so you know right off the bat we are going to need a Traffic Variable (sProp).  Once you have identified which sProp you are going to use and had Pathing enabled for it by ClientCare, you need to find a way to get the various Traffic Sources that you use into that sProp.  The ones I commonly use are:

1. SEM
2. SEO
3. E-mail
4. Display Ads
5. Affiliates
6. Social Media
7. Other Websites
8. Typed/Bookmarked (a.k.a. the rest)

The key to this solution is that you need to find a way to identify the Traffic Source of the first click to your site.  This can be done manually in your JS file or semi-automated using the Unified Sources VISTA Rule or the similar Channel Manager Plug-in.  Regardless of the method, what I try to do is to find something that uniquely identifies each online marketing channel.  Usually the best way to do this is through a query string identifier.

Here is how I do this:

SEM – If a click to your website comes from a Search Engine, you should have an identifier (i.e. ?s_kwid=) in the URL.  If you do, you know the Traffic Source is SEM.

SEO -  If the click comes from a Search Engine, but doesn’t have that identifier, it is SEO!

E-mail – When you send e-mails, you should be tracking the inbound clicks with a query string parameter.  If so, set it to something unique for e-mails (i.e. ?eid=) so you know that if you see that identifier in the URL, the Traffic Source is E-mail.

Display Ads – In a similar manner, if you are buying Display Ads, you normally get to choose the destination URL.  Therefore, you can set the destination URL on your site to have another unique identifier (i.e. ?displayid=) so you know which clicks have come from Display Ads.

Affiliates – See Display Advertising (i.e. ?affID=)

Social Media – This one is a bit trickier, but what I do is make a list of the key Social Media sites I want to track and when I see the referring URL contains one of those URL’s, I set the Traffic Source to Social Media.

Other Websites – If all of the above criteria have not been met, but there is a referring URL, set the Traffic Source equal to “Other Website.”

Typed/Bookmarked – If none of the preceding conditions have been met and there is no referring URL, set the Traffic Source to “Typed/Bookmarked.”

Phew!  It sounds difficult, but you should be using different query string parameters anyway in your campaigns area and any good JavaScript developer can do this somewhat easily.  It does require coding (which I don’t do myself!), but maybe Omniture will provide this out of the box one day…

But Wait…There’s More!
Believe it or not, you are not done yet!  Once you have found a way to distinguish the Traffic Source and are passing that into an sProp on the first page of every visit, you are 90% of the way there.  The last step is a bit confusing (techie alert!).  In order for SiteCatalyst to know if a visitor made it beyond their first page of the visit (hence, did not “Bounce”), it needs to see a different value in the sProp at some point during the Visit.  If it doesn’t see another value passed to the sProp, it will assume they didn’t see any other pages and exited the site (your boss won’t want to see a 100% Bounce Rate for every channel – trust me!).  Therefore, when a visitor navigates to a second page in the visit (any page – doesn’t matter which one), you need to force a “dummy” value into the same sProp that you previously passed Traffic Source.  My clever developer, passes in the value “Did Not Bounce” as the dummy value.  I will let those more technical than me discuss the best way to pass this dummy value, but once you have done this, you will have a new sProp that has one value for each of your Traffic Source Types and one extra one for the dummy value.  Since this sProp has Pathing enabled, you will have a Single Access and Entries metric for each of your Traffic Sources and can now calculate Bounce Rate (I recommend using Advanced Search to hide the dummy value and save it as a Custom Report so you don’t confuse your users).

For the most part , this sProp won’t have much value beyond calculating the Bounce Rate since it is really only set on the first page of the visit, but here are some additional goodies:

1. Use Trended reports to monitor Traffic Source Bounce Rates over time
2. Enable Daily, Weekly, Monthly, etc… Unique Visitors on the sProp to see Uniques for each Traffic Source
3. Correlate it to any other sProps that are most important on the first page of the visit (i.e. Referrer, Visit Number, etc…)
4. There is one more cool thing you can do with this, but it is so cool, I need to do a full post about it so stay tuned for my next post…

Final Thoughts
Well there you have it.  I wish it was not so convoluted, but don’t shoot the messenger!  If anyone else knows an easier way to do this, I am all ears.  I apologize for this being a bit more technical/complicated than most of my posts, but I don’t know of a non-technical way to explain this.  Let me know what you think…

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 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.

In my last post, I discussed a topic which I called Segment Pathing, which allows you to see how Pathing on your site differs by Visitor Type or Campaign Tracking Code.  In this post I will build upon this concept with one of the most popular topics in the Web Analytics field: Bounce Rates.  While I am not as enthusiastic about Bounce Rates as many others in the field, I do understand their importance and why people like them them.  However, one of my gripes with the Bounce Rate metric (which I have always defined as Single Access/Entries) is that there is not an easy way in SiteCatalyst to see Bounce Rates for different types of visitors or Campaigns.  Unless they have Omniture Discover or are experts at ASI Segments, most of the Omniture clients I worked with were primarily looking at Bounce Rates for the entire population.  While this is OK, I think we can do better than that.  In this post I will show you how I create Segment Bounce Rates.  However, to get the most out of this post, I strongly encourage you to read my prior post on Bounce Rates and my previous post on Segment Pathing before reading this post.

Segment Bounce Rates
As I just described, my goal when looking at Bounce Rates is to be able to tell my peers how visitors are bouncing off key pages based upon both the page and the segment.  In my previous post, I highlighted two segments that I commonly use: 1) Visitor Type (i.e. Customer vs. Non-Customer) and 2) Campaign Tracking Code (i.e. visitors from Google keyword A vs. Yahoo keyword B).  If I can dissect how each segment bounces off pages, I can determine if I need to create different versions of pages for each Visitor Type or Campaign Code or I can use this information to build future A/B Tests using a tool like Test&Target.  As I mentioned in my last post, this is a moot point if your organization already has Omniture Discover, but as is always the case in my blogs, my goal is to show you how to do things if you only have access to SiteCatalyst.

Implementing Segment Bounce Rates
The good news is that if you have already followed my instructions from my previous post on Segment Pathing, you are 95% of the way to being done with implementing Segment Bounce Rates!  As a quick recap, in my last post I described a process in which you concatenate the Page Name with another Traffic Variable (sProp) that contains a segmentation that you care about (i.e. Visitor Type).  Once you have these values concatenated on every page, you enable Pathing so you can see paths or pages by segment.  However, when you enable Pathing on this new sProp, you immediately gain access to the two metrics that you need to calculate Bounce Rate: Single Access & Entries.  Therefore, without even knowing it, by implementing Segment Pathing, you have also implemented Segment Bounce Rates!  All you need to do is to create the Bounce Rate Calculated Metric (which hopefully you already have as a Global Calculated Metric) and you are done.

So how do you see the results of your work?  All you need to do is to open the new concatenated sProp and add the Bounce Rate metric to the report.  In the example shown below, I will use the Campaign Pathing sProp which shows Campaign Tracking Codes concatenated with Page Names.  I will add Visits, Single Access, Entries and Bounce Rate to the report:

As you can see, the Bounce Rate for each Tracking Code/Page Name combination is displayed and you can sort by any metric you wish.

As a best practice, I like to conduct a text search filter to isolate one Page Name so I can see how the Bounce Rates differ for the same page with different Campaign Tracking Codes.  In the following example, I filtered on the phrase “:Home Page” and limited my results to see only Home Page Entries and the associated Bounce rates of each Campaign Tracking Code:

Keep in mind that I am only showing a few simple examples here and that this functionality can be extended to any segment of your choosing.  If you want to get really advanced, you could even concatenate multiple items together, such as Visitor Type + Campaign Tracking Code + Page Name.  This would allow you to see how different Visitor Types, coming from specific Campaign Tracking Codes, landing on specific Pages, navigate your site or Bounce off pages (i.e. Customer:ggl_1:Home Page).  Just don’t go too crazy since there are character limits on sProps and you don’t want to exceed the 500,000 monthly unique limits on sProps.

Final Thoughts
As you can see, you get a “two for the price of one” deal if you do all of the steps in this post and the previous post.  If you don’t have access to Omniture Discover and want to see how people navigate through your site or bounce off your site pages by specific segment, I suggest you give this a try and see if it helps you.

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.

I know many Omniture clients that spend much of their time using SiteCatalyst for SEO and SEM tracking.  If you are one of these clients, the following will show you a fun little trick that you can use to improve your Search reporting by setting custom Search Success Events.

That Darn Instances Metric!
As a Search marketer, you tend to spend a lot of your time in the various Paid and Natural Search Engine reports within SiteCatalyst.  While in those reports, you would normally use the out-of-the-box “Searches” metric for most of your reporting.  If you stay in the Search reports, life is good, as you can use the Searches metric and any other Success Event to see what success takes place after visitors arrive from a particular Search Engine or Search Keyword.  For example, here is a report that shows Searches and Form Completions coming from various Search Engines:

However, as I blogged about a while back in my Instances post, the Searches metric is really a really a renaming of the dreaded SiteCatalyst “Instances” metric.  Why is that bad?  It means that if you need to see Searches in any other Conversion Variable (eVars) report, you are out of luck.  For example, let’s say that your boss wants to see a report that shows Searches and Form Completes (and possibly a Calculated Metric that divides the two) by Site Locale (each country in which you do business).  To do this, you would open the Site Locale eVar report and add Form Completes, but guess what…there is no “Searches” metric to add to the report since it only exists in the Search Engine reports!  Rats!

Let’s say you are an eternal optimist and you say, darn it, I can solve this!  I’ve read all of Omni Man’s blogs and there has to be a way to do this.  After pouring over past blogs, you finally arrive at the perfect answer!  I can use Conversion Subrelations to break the Search Engine report down by Site Locale while the Searches metric is in the report!  So you go back to the Searches report shown above and realize that all you have to do is use the green magnifying glass icon to and break the report down by the Site Locale eVar (which BTW will only work if Site Locale has Full Subrelations enabled).  I’m a genius, you think to yourself!  Then you wait for the report to load…brimming with anticipation only to see this…

Yuck!  What’s up with all of the “n/a” values?  Foiled again by the darn Instances metric!

Don’t Panic!
Don’t be so hard on yourself since if you got that far, you are ok in my book!  Just consider this a well earned lesson on why you have to be careful around any Instances metric (don’t fall for the same thing with Product Views!).  As always, I don’t like to just present problems since the Omni Man is all about solutions!  To solve this enigma, we have to find a way to get around the Instances metric.  At a high level, the solution is to set custom Success Events when visitors arrive at your site from a Search Engine.  I usually set a Natural Search, Paid Search and Paid + Natural Search metrics.  This can be done in several ways, but the easiest way is through the Unified Sources Vista Rule or the JavaScript equivalent known as the Channel Manager Plug-in (I recommend talking to Omniture Consulting about implementation details).  Regardless of how you implement it, once you have true custom success events set when visitors arrive from a search engine, you can use these success event anywhere within Omniture SiteCatalyst which means that you can now create the report you were looking for above like shown here:

The following are some other advantages of using a custom success events for Searches:

1. You can use these metrics in Calculated Metrics (i.e. Shopping Cart Additions/External Natural Search) without having to rely upon the ExcelClient
2. You can create Alerts on Paid or Natural Search metrics
3. You can add some cool SiteCatalyst Plug-ins or advanced features to the new Custom Search success events that make them even better than the out-of-the-box Searches metric (i.e. Avoid back button duplicate counting by using the getValOnce plug-in or Event Serialization).
4. You have an easy way to create a metric report for Searches (see below) and add it to a SiteCatalyst Dashboard

The only caveat I will give you is that the new custom Search metrics will probably never tie exactly with the out-of-the-box metrics, but in many cases you can make them more accurate and useful.  If SEO/SEM is something that is important to your organization, I suggest you talk to Omniture Consulting and give it a whirl…  Let me know if you come up with any other cool uses for this functionality…

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.