(Estimated Time to Read this Post = 5 Minutes)

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

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

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

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

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

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

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

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

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

…to see a report like this:

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

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

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

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

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

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

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

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

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

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

Last year I went to my first X Change conference and thought it was a great event.  For those of you who are not familiar with the conference, it is a truly different type of experience.  Instead of having many people sit through PowerPoint presentations, the conference is made up of small group “huddles” in which people who are knee-deep in web analytics share the good, the bad and the ugly (so to speak!).  I find that interacting with people holding similar roles at different organizations helps to validate some of the things you are doing and possibly comfort you that you are not alone in the challenges you face.  Because the X Change conference is only as good as the people who attend it, I wanted to take a moment to share my thoughts on it in hopes that a few of my blog readers might learn more about it and consider joining me at this year’s conference (Sept 21-22).

Why I Like X Change
Here are my top reasons for liking X Change:

1. Last year, there were great people in attendance and I really enjoyed hearing what people at top-tier companies were doing in the web analytics field
2. The folks moderating the “huddles” were very knowledgeable and helped get discussions going and kept them on-track
3. Since it is a smaller conference, it was easier to network with people and get to know them a bit better than I have traditionally been able to at larger industry conferences

My Huddles
Last year, I was privileged enough to lead a huddle on Social Media and it was fun to hear all of the ideas and things people were doing.  This year, I am leading two huddles on some new topics which I am excited about.  Here is a little info on the huddles I am leading:

Integrating Web Analytics & CRM
Since joining Salesforce.com over a year ago, I have spent a lot of time talking to people about integrating web analytics and CRM, including speaking on the topic at eMetrics San Jose.  I find this topic to be exciting because there are so many creative ways to do this and get value from combining website and sales data.  In this huddle, I hope to share some of the things I have done at Salesforce.com and at clients when I was with Omniture consulting, but more importantly, to facilitate a discussion about what others have done.  I hope to hear about how you all have created value for your company through these types of integrations and what challenges you have faced that others may have already solved!

Turning Around Troubled Web Analytics Deployments
Since all web analytics deployments are 100% perfect, this may be a sparsely attended session (wink, wink!)  One of the jobs I had at Omniture as part of the consulting team was to help clients who had “lost their way” with respect to their web analytics deployments.  Sometimes it was due to incomplete business requirements, other times it was a result of technical/training issues, but many times, it was due to employee turnover or new people in new roles.  Regardless of the reason, I have seen a LOT of mismanaged web analytics deployments out there and often times, people don’t know what they should do to turn them around.  In this huddle, I plan to share some of the techniques I used to turn around troubled deployments and hope to hear from others that have turned their own deployments around.  Even if you currently have a stellar web analytics deployment, I think many of the items we will discuss may help you make it even better or possibly prepare you for a future job where you are the new head honcho responsible for fixing an ailing deployment…

Other Huddles
Fortunately, I also get to attend huddles myself as a participant and here are some that I hope to get to:

• Defining and Executing a Global Web Analytics Strategy
• The Big Picture (for Most of Us): Conversion Optimization
• Test Yourself Rich! Multivariate and A/B Testing
• Managing Measurement for a Global Brand
• The Shift from “Reactive” to “Proactive”: Predictive Analytics

You can see descriptions of all of the huddles by clicking here.  I encourage you to check them out and see the diverse range of topics that will be discussed…

Please Come!
As I stated earlier, the X Change conference is only as good as the people who come so I hope to see you there.  If you register before July 20th, there is an “early bird” price so I encourage you to do your research now.  Registration information can be found by clicking here.  Thanks!

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

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

(Estimated Time to Read this Post = 2.5 Minutes)

From time to time, I hear people talking about Data Extracts in SiteCatalyst (especially on Twitter).  In this post, I thought I’d review them in case you are unsure of what they are and how they are used.

What Are Data Extracts?
The good news is that if you know how to use the SiteCatalyst ExcelClient then you are essentially an expert in Data Extracts, you just may not know it!  Behind the scenes, Data Extracts are really just a different way to access the engine that powers the ExcelClient data blocks with which you are already familiar.  The main difference between the ExcelClient and Data Extracts is that Extracts are normally used to have a report e-mailed on a regular basis without having to go into Excel (especially good for Mac users!).  Any report for which you can create a data block in the ExcelClient can also be accessed using the Data Extract icon in the SiteCatalyst toolbar:

If you cannot see the icon shown above in a SiteCatalyst report that means you cannot create a Data Extract for that report.  Once you click the icon, you will see a new screen that looks like this:

If you have used the ExcelClient, this should look familiar and you use this screen to choose how much data and what metrics you’d like to see.  Whatever settings you choose on this screen are what you will be stuck with (except for date which I believe is floating).  Finally, in the example below, notice that Data Extracts (and the ExcelClient for that matter!) have access to the same Classifications, Correlations and Subrelations that are available when using the normal SiteCatalyst user interface (click the green magnifying glass icon).  In this example, I am showing a correlation between Day of Week and Hour of Day:

Once you have configured your Data Extract, the last screen will ask you if you want to have it send via e-mail, added as a bookmark or both.  In a minute I will share with you why it is advantageous to store Data Extracts as bookmarks, but I recommend keeping any Data Extracts you create in an “Extracts” folder in case you ever need them again.

That’s it.  You’re done.  If you have e-mailed yourself the report, it will arrive shortly thereafter.  However, I have to explain something that often perplexes folks.  If you chose to add a bookmark, inevitably at some point you will open that bookmark using your bookmark toolbar and be facing a screen that looks like this:

If you are like me the first time I saw this, you might be a bit confused.  I expected to see the actual report, but that will never happen.  This screen is only to be used to modify your Data Extract and to open it so you can re-send it to yourself or others.  At first, I decided that this devalued my decision to store my Data Extract as a bookmark, but don’t despair because SiteCatalyst makes up for this by allowing you do something really cool with bookmarked Data Extracts.  If you open the ExcelClient and choose to insert a new Data Block, you can create a new one or you can choose from any Data Extracts you have created (or shared ones) as shown here:

Notice that the new Data Extract we just created appears here.  All we have to do is to click the “Insert” link and it will add the data block to our Excel spreadsheet and run the query:

This saves you having to re-create it in the ExcelClient and you can still edit it to suit your needs after it has been inserted.  The only bummer is that you cannot tie the Data Extract data block to cells in Excel so if you are ever looking for dynamic data blocks, start them in Excel, not as Data Extracts.

So that is pretty much all you need to know about Data Extracts.  One final note – it is my understanding that Data Extracts do not work with the new OmnitureReportBuilder, but perhaps something similar will be rolled out 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.  You can also hear Adam on the BeyondWebAnalytics podcast.  Please send questions and comments to adam@the-omni-man.com.

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

(Estimated Time to Read this Post = 2.5 Minutes)

In my last few posts I have been delving into Web Analytics & CRM (Customer Relationship Management) integration.  In my first post I described how you can pass Web Analytics Data to your CRM system to help your sales people.  In my last post, I described how you could pass CRM data like Leads, Opportunities and Revenue into your Web Analytics tool.  In this post, I will round out the trilogy by describing how you can use CRM data as Web Analytics meta-data to enhance your Web Analytics reporting.

My Golf Handicap Story
Since most people don’t often like talking about meta-data, I will begin by sharing an easier to understand story which first taught me how interesting integrating CRM and Web Analytics data could be.  Back when I managed the website for the CME, we had situation in which we were trying to sell tickets for a major golf tournament.  Unfortunately, the event was nearing and we still had lots of tickets to sell.  At the time, I recalled that, for registered website users, we had golf handicap as one of our CRM fields in our Salesforce.com system (our customers were traders and spent a lot of time golfing!).  I had recently worked on capturing each customer’s website ID in SiteCatalyst and also placing it in our CRM system.  Suddenly, the light bulb went on in my head…why not upload golf handicap as a SAINT Classification of the website ID I had in an sProps and eVar in SiteCatalyst?  I created a SAINT Classification table that passed in the raw handicap and also grouped it into buckets like this:

Whereas previously I could see what pages each website ID had viewed on the website, I could now expand that to see the same data for this new golf handicap Classification of that variable.  The result was a report like this, in which I could see the most popular pages for website visitors by golf handicap:

From there, all that was left to do was to target some ads on those pages and voilà, the tickets were soon gone!

For me, this was more experimental than anything else, but it was the catalyst (no pun intended!) which helped me see the power of  integrating CRM and Web Analytics.  Of course back then there were no API’s to help pass data between systems, but nowadays, this is much easier (i.e. Genesis integrations).  With this in mind, let’s take a look at a few more examples of how you can take advantage of this concept.

Examples of Passing CRM Meta-Data to Web Analytics
Now that you get the general idea, I’ll walk you through some other examples of enriching your Web Analytics data by bringing in CRM meta-data.  Let’s assume that you have done the steps outlined in my last post and have made a connection between your Web Analytics visitors and your known CRM prospects/customers.  Using the primary key described in my last post, you can export whatever CRM fields you care about from your CRM system and import them into your SiteCatalyst implementation as SAINT Classifications.  Here, you can see that I have decided to export Industry, # of Employees, Lifetime Value and a Lifetime Value grouping (to make my reports more readable) from my CRM system and import them using the following SAINT file:

Now that I have done this, I can open my Lead Gen ID report in SiteCatalyst and look at any of these CRM fields as Classifications.  Here is a view of some of my Success Events by Industry:

Here is the same data viewed by # of Employees:

Here is the same data viewed by Lifetime Value:

The same concept can apply if you are using other Web Analytics tools.  Here is an example of viewing reports in Google Analytics by Job Title (in this case filtering for CIO’s):

Final Thoughts
As you can see, once you have made the connection between your Web Analytics and CRM system, there are lots of creative things you can do with respect to augmenting your traditional web analyses.  I know a lot of people also do this in tools like Quantivo or Omniture Insight, but I hope this was helpful to see some of the ways to do this if you only have access to SiteCatalyst.

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

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

(Estimated Time to Read this Post = 5 Minutes)

In my last post, I explained a bit about CRM and how you could improve CRM by passing Web Analytics data into your CRM system.  In this post, I am going to cover the reverse angle  – passing CRM data into Web Analytics.  Since most of you reading this are web analysts, I think you will find this post more relevant, but I think it is important to understand both sides.

Why Pass CRM Data into Web Analytics?
As I mentioned in my last post, we web analysts get lots of great information about website visitors, but for many companies (especially B2B), the richest data resides in the CRM (Customer Relationship Management) system.  If you want to be relevant in your organization, it is always best to be as close as possible to the $$$ and that often means playing nicely with CRM systems.  Don’t get me wrong,  showing your CMO that you can lift form completion rates by 200% through optimization is awesome, but if you can show him the revenue impact of it right there in your Web Analytics tool, you will be a rock star!  Additionally, I will show that if you don’t have actual revenue-generating events on your site (eCommerce and Media sites have this easy!), then not doing this could actually result in Web Analytics data causing incorrect business decisions…

Passing Post-Website Data from CRM to Web Analytics
OK.  So there are many different ways to merge CRM and Web Analytics data including passing data from both into a massive Marketing data warehouse (or Omniture Insight), but just for the purposes of this post, I am going to assume that you are a SiteCatalyst person and want to get something done relatively quickly.  In this scenario, we’ll assume the following:

• You want to see which of your website visitors completing lead forms on the site evolve into Leads, Opportunities and Revenue
• Your CMO has charged you with capturing all of the different marketing channels and asked for your opinion on where the company should invest to get the most Revenue
• You are tracking the various sources of traffic you receive and using SAINT Classifications to roll each up into a high-level marketing channel (SEO, SEM, E-mail, etc…)

Given all of this, you might have a SiteCatalyst report that looks like this:

As a web analyst, at this point, it looks like we might want to invest more in our E-mail program since that seems to be converting the best.  Without CRM integration, that would probably be as far as we could go.  But let’s now dig a little deeper.  As I mentioned in the last post, when website visitors complete a form, we have a brief moment in time when we can connect our website data with our CRM data.  Most CRM tools allow you to capture leads and set a unique ID for each form completion.  At the same time, Omniture SiteCatalyst has a really cool feature (that many don’t use enough!) called Transaction ID.  I highly recommend you read my full post on Transaction ID, but at a high level, it allows you to set an ID to a special SiteCatalyst variable and then days or weeks later, upload [normally offline] metrics into SiteCatalyst.  The magic of Transaction ID is that when you upload these metrics later, they are tied to the eVar values (sorry – no sProps or Participation) that were present at the time the Transaction ID was set.  That means that if a website visitor had a City eVar value of Chicago, a Traffic Source eVar value of Paid Search and a Visit Number eVar value of 3, then any offline metrics you import will also be tied to Chicago, Paid Search and Visit Number 3 in the respective eVar reports.  This means that if you set the CRM ID associated with a website form completion, you now have a primary key (think Rosetta Stone!) that can connect your Web Analytics data to your CRM data!

So what does this mean to you?  Following our preceding example, let’s assume that you have made this connection and later imported all of the new leads your CRM system has seen along with the status (i.e. Qualified)  of each into SiteCatalyst (these new metrics would be Incrementor Events).  This gives you a new metric named “Qualified Leads” that you can now see in SiteCatalyst reports and since you used Transaction ID, these imported CRM metrics are correctly attributed to all eVar reports in your implementation.  The result is that you can now open a report similar to the one we saw above, but now it has “Qualified Leads” instead of Form Completes and a new Calculated Metric that divides these Qualified Leads by Visits:

The icons above the report show where each data point comes from and as you can see, the last column is truly magical in that it is combining data from two disparate systems (Cool huh?)!  Once we have this, we can see that even though E-mail looked to be the best channel a few minutes ago, it now appears that SEM is where we want to spend our money.  It turns out that E-mail generates form completions at the highest rate, but perhaps those form completions are all junk!

However, I like to go as far downstream as possible and nothing is better than cold, hard cash!  Applying the same principles, we can import Qualified Opportunities, Potential Pipeline, but the CRM metric that trumps them all is Revenue.  By uploading Revenue via Transaction ID, we can see how much $$ we got from each Lead Form completed on the website and tie it to any eVar value we have – in this case marketing channel/traffic source.  The following report shows the result of this:

Again, we see that some data is coming from SiteCatalyst and some is coming from our CRM system.  Our new Revenue/Visit Calculated Metric can be used to see that, in the end, it is really SEO that provides the most Revenue/Visit and maybe we should consider additional investment there.  Please keep in mind that these examples are simply meant to illustrate the concept and show the value in adding CRM metrics to your Web Analytics tool.  Finally, don’t forget that Transaction ID data is available in Omniture Discover so you can slice and dice this data even further there!

Targeting Based Upon CRM Data
Another really cool integration between CRM and Web Analytics is in the area of Test&Target.  For those not familiar with Test&Target, it is an Omniture tool that lets you test and dynamically target content to website visitors based upon what you know about them.  It is commonly used to optimize your website success metrics.  However, this can be extended by importing in CRM data so that your targeting is based upon both online and offline data.

Let’s walk through an example.  Imagine that a website visitor named Bill has been to your website a few times, looked at a few of your products and completed a lead form.  Next, Bill spoke to your sales representative and is at “Stage 3″ of the sales process (the discovery phase).  Over the next few weeks, meetings take place and Bill comes to the website occasionally (your sales team would know when and exactly what he is doing if you read my last post!).  But now let’s say that Bill is in sales “Stage 9″ which is the final stage before the deal is won or lost.  We know what products he wants, we know he is close to making a decision, we know how big is company is, etc…  If we knew all of this, what would we want to show him the next time he arrives at our website?  Here are a few things I would show to Bill on my home page when he (and only he) arrives on it:

1. Case studies related to his industry
2. ROI calculator for the product Bill is interested in
3. Links to community content to show Bill that he would be well taken care of if he were to be a customer
4. A time-sensitive offer (“Buy in the next 24 hours and get XX% off”) – You could even address him as “Bill” but that might freak him out!
5. etc…

The point is that if you can get the rich customer data related to Bill and multiply this to all of your prospects, each one could see more personalized content that helps move them further down the sales funnel.  You can even track how often they see these “recipes” and track the success of your intelligent targeting.  If you are interested in this type of CRM-based targeting I suggest that you contact @brianthawkins who is a Test&Target Jedi-master…

Final Thoughts
Hopefully this sparks some ideas about ways in which you can enrich your Web Analytics data by adding CRM data to the mix.  In the next post I will cover ways in which you can import CRM meta-data into your Web Analytics tool to augment your current web analyses.

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

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

(Estimated Time to Read this Post = 5 Minutes)

One of the areas of Web Analytics that I am passionate about is the integration of Web Analytics and CRM.  In the next three blog posts, I am going to share why I think this topic is important and some ideas on how to do it.

Why Integrate Web Analytics and CRM?
For those who are not experts on CRM, it stands for Customer Relationship Management and it generally involves using a tool to store all information you have about your prospects/customers.  This normally includes all contacts with customers while they were prospects, all customer service touches, what products they use and how much they pay for each.  However, the main thing to understand is that CRM systems contain pretty much all data about prospects/customers that takes place after you know who they are.  But before your customers fill out a form or call you, guess where many of them are going?  That’s right, your company’s website (and to social media sites more and more!).  Guess who knows the most about what prospects do before your company knows they are interested in you?  Your Web Analytics platform!

Last week, I presented on this topic at the eMetrics conference where I posited that the combination of Web Analytics and CRM is akin to the joining of chocolate and peanut butter in that they are both great, but even better together!  Often times, as web analysts we know a great deal about what happens on the website, but unless your website sells something or sells advertising, the true success event ($$$) often takes place off the website (especially for B2B sites).  Additionally, for all the great information we have about website visitors, most of it is anonymous – we don’t really know who they are so we can’t easily connect their website behavior to other interactions.  What if we could take all of that anonymous website behavior and somehow connect it with the known prospect/customer behavior stored in our CRM system?  Imagine if every time a prospect filled out a lead form on your website, the sales person who is routed the lead could see what that person had viewed on the website, what products they had looked at, etc…  That could lead to a much more meaningful conversation and help get things off on the right foot.  In this first post on the topic, I will cover ways in which you can improve your CRM system by passing it meaningful data from your web analytics tool.

Passing Pages Viewed
The first area I would like to cover is the concept mentioned above in which we pass data about pages viewed from your Web Analytics tool into your CRM tool.   So let’s say that you have a website visitor who navigates a bunch of pages on your website and then fills out a lead form.  At that moment, you have the opportunity to create a connection between that user’s website (cookie) ID (Omniture calls this a Visitor ID) and the ID used to record that lead form in your CRM system.  While it would take too long to go into all of the details on how to do this (Hint: read my old Transaction ID post!), at a high level, you can use API’s of both tools to tie these ID’s together.  Once you have made this connection, you can pass data bi-directionally between the two systems.  In this case, we are going to create a custom object in our CRM system that represents website traffic and import what pages this particular prospect on the website.  While this may sound hard, if you look closely, you will notice that the following screen shot is something I did between Omniture and Salesforce.com back in 2005 so it can’t be that hard right?

In this case, your sales team would know that this person is probably interested in Weather products so they might want to prepare accordingly for their first phone call or face-to-face meeting.

Passing Website Scores
In one of his post-Summit blog posts, Ben Gaines talked about a topic called Visitor Scoring (I prefer the name Website Scoring to avoid the whole Engagement debate!).  Basically, this involves storing a unique website score for each website visitor so you can see how active they have been on the website.  For example, you can set this up so if a visitor views a Product page they get 5 “points” but if they view a product demo video, they get 8 “points” and so on.  I tend to use Participation metrics or segments in Discover to determine which pages should be rating higher than others.  If you have implemented this, one of the cool ways you can use it is to identify the current website score of a website visitor who completes a web form and pass it to your CRM system.  Let’s say that your sales team receives hundreds or thousands of new leads each day.  One way they can determine which ones they should call first might be to see how active each has been on the website.  If one prospect comes through with a website score of “10″ and another with “54″ which one would you call?  While this isn’t meant to replace a full-blown lead management system, it is another data point that can be passed from Web Analytics to CRM.

Lead Nurturing
Unfortunately, there are most likely way too many visitors for your sales team to talk to and not all of them are truly qualified.  Therefore, one of the key strengths of CRM tools is that they can nurture or re-market to prospects via e-mail and other platforms.  For example, it would be common for a company to use its CRM tool to automatically schedule an e-mail to go to all prospects who are interested in Product X and have more than 500 employees.   However, what is often missing from these types of nurturing programs is the deep insights that can come from your Web Analytics tool.  Building upon the preceding scenario, if we have a connection between a particular prospect and their Website cookie ID, as they come back to the site and click on more things, we should be pushing that information into our CRM tool and having it then decide which re-marketing information the prospect receives.  For example, if the prospect above started clicking on items related to another CME product (say Eurodollars), the sales person may not have any plans in the next week to look at this person’s record so they would never know that.  But by automating the data exchange between the Web Analytics tool and the CRM tool, specific product flags could be triggered that would result in the prospect being intelligently nurtured with little human intervention.  If you are interested in Lead Nurturing, you can also look at tools like Eloqua which partner with CRM tools to provide this type of functionality.

Passing Key Website Metrics to CRM
The last concept I will cover in this post is the passing of key website metrics to your CRM system.  Most sales organizations use conversion funnels that are not unlike what we are used to in Web Analytics.  However, their funnels normally begin with new Leads and progress through different sales stages until business is won or lost.  The one flaw in this model is that it doesn’t account for the true potential of selling opportunities that exist.  A true salesperson would say that anyone who visits their company’s website is an opportunity for a sale so the way I look at it, they should include metrics like Unique Visitors and people who View a Demo or see a Lead Form as part of their sales funnel.  I also think that getting sales to think of their funnel in a larger context helps bridge the gap between Sales and Marketing and opens the door for increased cooperation.

Therefore, one of the ways I do this is to take the traditional sales funnel and add some of our Web Analytics KPI’s to it like this:

Final Thoughts
So covers most of the topics related to passing Web Analytics data into CRM.  In the next post I will cover the flip-side and show how you can pass CRM data into your Web Analytics tool.

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

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

(Estimated Time to Read this Post = 1 Minute)

Every once in a while, I will get questions about how often people are accessing Omniture SiteCatalyst.  In case this happens to you as well, I thought I’d write a (really) quick post with instructions on how to do this.  Currently, there isn’t that much you can report on (I have requested more here) so this will be one of my shortest posts ever!

Usage Reportlet on Dashboard
The only way I know of to get usage metrics is by adding a usage reportlet to a SiteCatalyst Dashboard.  To do this, open a new or existing Dashboard and add a “Usage” element.  Through this element you can get information on Users, Reports Viewed, Suites, etc… as shown here:

Unfortunately, you don’t get much detail and basically are stuck with one metric “Views.” (which I assume is similar to Page Views).  Once there, you can fill out the rest of the dashboard items. In the example below, I am adding a report that will show me the Top 500 users.

Once the reportlet is on the Dashboard, I tend to export it to excel and do some charts/graphs there.  Here is an example of how you can trend how often people are engaging with your SiteCatalyst reports:

Well, that’s it.  Short and sweet…

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

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

Recently, Omniture released its latest version of SiteCatalyst (version 14.7) in which there were a bunch of new features added.  Below are a few links to other blog posts that describe some of these new features:

• New Dashboards
• Day of Week Trending, New User E-mails, Default Dashboards, Transfer of User Settings

However, one of my favorite new features was the addition of Alerts on Classifications.  In the past, you could set Alerts on Success Events and on eVar and sProp values, but not on Classifications of those eVars and sProps.  While this new feature doesn’t sound all that impressive, it can be quite powerful.  In this post I will demonstrate how it can be used.

Example – Traffic Driver Type Classification
For the purposes of this post, let’s imagine that we have an eVar or Campaign variable that captures individual Traffic Drivers (Sources).  These sources of traffic might be SEO keywords, Paid Search Keywords, E-mail links or clicks from Social Media sites.  However, in this case, we don’t want to be notified every time there is a increase/decrease for a specific Traffic Driver, but rather, we would like to know if there has been a significant change to one of the higher level types (SEO, SEM, Social Media).  Before this new version, doing that would be basically impossible, but this is easy now if you have used SAINT to classify your individual Traffic Drivers.

Let’s say that your boss wants to be alerted if there is a significant change in Social Media referrals to the website from one week to the next.  To be alerted about this, you would simply open up the Classification version of the Traffic Driver report (we’ll call it Traffic Driver Type) and click the Alert icon.  Doing this brings up the screen below which is basically the same as the Alert screen you may have used previously.  Once here, you can give your Alert a name, choose the time frame, pick your metric and then select the specific item you want to be alerted about (in this case I have selected Social Media).  Next, you set the type of Alert – in this case I have chosen a percent change of over 15% and then tell SiteCatalyst how you woudl like to be notified (e-mail or mobile device).  That’s it!

Other Uses
There are an infinite number of ways you can use this powerful feature.  Here are just a few that I can think of off the top of my head:

• Classify internal search terms into buckets and be alerted when a specific type of keywords hits a threshold or changes significantly
• Classify countries or cities into regions and be alerted when a metric related to a specific one changes
• Classify search engine keywords into Branded/Non-Branded and be alerted when each changes significantly
• Classify videos viewed on your website and be notified when a video type changes significantly
• If you are using the Omniture Twitter Integration, all of the Twitter data points are based upon Classifications so you can set an Alert when a particular person Tweets or if a specific Twitter keyword experiences a spike

These are just a few examples, and I am sure you will find many ones unique to your business that can prove beneficial.

Now, if only Omniture could combine this new feature with this future idea, then we will really be in business!  In the meantime, if you think of some really interesting ones, feel free to leave a comment here…

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

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

In the Web Analytics space, we spend a lot of time recording and analyzing what people do on our website in order to improve revenues and/or user experience.  While this implicit data capture is wonderful, you should be supplementing it with data that you collect directly from your website visitors.  Voice of Customer (VOC) is the term often used for this and it is simply asking your customers to tell you why your website is good or bad.  There are two main ways that I have seen people capture Voice of Customer:

1. Page-Based Comments – Provide a way for website visitors to comment on pages of your site.  This is traditionally used as a mechanism to get direct feedback about a page design, broken links or problems people are having with a specific page.  Unfortunately, most of this feedback will be negative so you need to have “thick skin” when analyzing this data!
2. Website Satisfaction – Provide a way for visitors to rate their overall satisfaction with your website experience (vs. specific pages).  This is normally done by presenting visitors with an exit survey where you ask standard questions that can tell you how your website is doing and compares your site against your peers.

There are numerous vendors in each of these spaces and the goal of this post is not to compare them, but rather discuss how you can integrate Voice of Customer data into your Omniture SiteCatalyst implementation.  In this post, I am going to focus on the first of the aforementioned items (Page-Based Comments) and specifically talk about one vendor (OpinionLab) that I happen to have the most direct experience with (their headquarters was a mile from my home!).  The same principles that I will discuss here can be applied to all Voice of Customer vendors so don’t get hung up on the specific vendor for the purposes of this post.

Why Integrate Voice of Customer into SiteCatalyst
So given that you can see Voice of Customer data from within your chosen VOC tool, why should you endeavor to integrate Voice of Customer and your web analytics solution?  I find that integrating the two has the following benefits:

1. You can more easily share Voice of Customer data with people without forcing them to learn [yet] another tool.  People are busy and you are lucky if they end up mastering SiteCatalyst, lest you make them learn how to use OpinionLab, Foresee Results, etc…
2. Many Voice of Customer tools charge by the user so if you can port their data into SiteCatalyst, you can expose it to an almost unlimited number of users.
3. You can use Omniture SiteCatalyst’s date and search filters to tailor what Voice of Customer each employee receives.
4. You can divide Voice of Customer metrics by other Website Traffic/Success Metrics to create new, interesting KPI’s.
5. You can use Omniture SiteCatalyst Alerts to monitor issues on your site.
6. You can use Omniture Discover to drill deep into Voice of Customer issues

I hope to demonstrate many of these benefits in the following sections.

How to Integrate Voice of Customer into SiteCatalyst
So how exactly do you integrate Voice of Customer data into SiteCatalyst.  For most VOC vendors, the easiest way to do this is by using Omniture Genesis.  These Genesis integrations are already pre-wired and make implementation a snap (though there are cases where you may want to do a custom integration or tweak the Genesis integration).  You can talk to your Omniture account manager or account exec to learn more about Genesis.

Regardless of how you decide to do the implementation, here is what I recommend that you implement:

1. Set three custom Success Events for Positive Page Ratings, Negative Page Ratings and Neutral Page Ratings.  These Success Events should be set on the “Thank You” page after the visitor has provided a rating.
2. Pass the free form text/comment that website visitors enter into an sProp or eVar.  If they do not leave a comment pass in something like “NO COMMENT” so you can make sure you are capturing all comments.  If you are going to capture the comments in an sProp, I recommend you use a Hierarchy variable since those have longer character lengths vs. normal sProps which can only capture 100 characters.
3. Pass the actual page rating (usually a number from 1 to 5) into an sProp.  I also recommend a SAINT Classification of this variable such that you classify 1 &2 as Negative, 3 as Neutral and 4 & 5 as Positive.  This classification should take less than 5 minutes to create…
4. Use the PreviousValue plug-in to pass the previous page name to an sProp.
5. Create a 2-item Traffic Data Correlation between the Previous Page (step #4) and Page Rating (step #3).  This allows you to see what page the user was on when they submitted each rating.

All in all, this is not too bad.  A few Success Events and a few custom variables and you are good to go.  The rest of this post will demonstrate some of the cool reports you can create after the above implementation steps are completed.

Share Ratings
As I mentioned previously, you [hopefully] have users that have become familiar with the SiteCatalyst interface.  This means that they have Dashboards already created to which you can add a few extra reportlets.  In this first example, let’s imagine that you want to graphically represent how your site is doing by day with respect to Positive, Negative and Neutral ratings.  To do this, all you have to do is open the Classification version of the Page Rating report (can be an sProp or eVar – your call) and switch to the trended view.  You should have only three valid values and I like to use a stack ranked graph type using the percentage to see how I am doing each day as shown here:

This graph allows me to get a quick sense of how my site is doing over time and can easily be added to any Dashboard.

You can also mix your newly created Voice of Customer Success Events with other SiteCatalyst metrics.  For example, while you could look at a graph/trend of Positive or Negative Comments by opening the respective Success Events, a better way to gauge success is to divide these new metrics by Visits to see if you are doing better or worse on a relative basis.  The following graph shows a Calculated Metric for Negative Comments per Visit so we can adjust for traffic spikes:

Find Problem Pages
Another benefit of the integration is that you can isolate ratings for specific pages.  The first way to do this is to see which pages your visitors tend to rate positively or negatively.  In the following report, you can open the Rating variable report (or Classification of it as shown below) and break it down by the Previous Page variable to see the pages that most often had negative ratings:

This will then result in a report that looks like this:

Alternatively, if you want to see the spread of ratings for a specific page, all you need to do is find that page in the Previous Page report and break it down by the Rating variable (or its Classification) as shown here:

Share Comments
As noted above, if you capture the actual comments that people leave in a variable, you will have a SiteCatalyst report that captures the first 256 characters of the comments visitors enter.  This report duplicates scheduled reports from your Voice of Customer vendor in that it allows you to share all of the comments people are leaving with your co-workers.  However, by doing this through SiteCatalyst, you gain some additional functionality that some VOC vendors don’t provide:

1. You can create a Traffic Data Correlation between the Comments variable and the Previous Page variable so you can breakdown comments for a specific page.  Therefore, if you have users that “own” specific pages on the website, you can schedule daily/weekly reports that contain comments only for those pages so they don’t have to waste time reading all of the comments left by visitors.
2. You can use the Search filter functionality of SiteCatalyst to scan through all of the visitor comments looking for specific keywords or phrases that your co-workers may be interested in.  In the example below, the user is looking for comments that mention the words “slow” or “latent” to be notified of cases where the visitor perceived a page load speed issue:

Set Alerts
Another cool thing you can do with this integration is set automated Alerts in SiteCatalyst so you can be notified when you see a spike in Negative Comments on your site.  This allows you to react quickly to broken links or other issues before they affect too many visitors (and help avoid #FAIL posts in Twitter!).  Here is an example of setting this up:

Review Problem Visits using Omniture Discover
Finally, if you have access to Omniture Discover, after you have implemented the items above, you can use Discover to do some amazing things.  First, you can use the unlimited breakdown functionality to zero in on any data attribute of a user that is complaining about your site.  For example, if you had visitors complaining about not being able to see videos on your site, you might want to see their version of Flash, Browser, OS, etc… or even isolate when the problem took place as shown here:

Additionally, you can use Discover to isolate specific comments and watch the exact visit that led to that comment.  This is done through a little-known feature of Discover called the “Virtual Focus Group.”  This feature allows you to review sessions on your site and see the exact pages people viewed and some general data about their visit (i.e. Browser, GeoLocation, etc…).  While not as comprehensive as tools like Clicktale, it is good enough for some basic analysis.  Here is how to do this:

1. Open Discover and find the comment you care about in the custom sProp or eVar report
2. Right-click on the row and create a Visit segment where that comment exists
3. Save the segment in a segment folder
4. Open the Virtual Focus Group (under Pathing in Discover)
5. Add your new segment to the report by dragging it to the segment area
6. Click “New Visit” in the Virtual Focus Group
7. Click on the “Play” button to watch the visit

Now you can watch how the user entered your site, what pages they went to and see exactly what they had done prior to hitting the Voice of Customer “Thank You” page.

Final Thoughts
So there you have it, a quick review of some cool things you can do if you want to integrate your chosen Voice of Customer tool and Omniture SiteCatalyst.  This is by no means the only way to do this, but merely a few suggestions that I have found helpful over the years.  If you have done other cool things, please let me 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.  You can also hear Adam on the BeyondWebAnalytics podcast.  Please send questions and comments to adam@the-omni-man.com.

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

Thanks to Laura MacTaggart in the Omniture Consulting group, I just learned an awesome Discover time-saver I felt obligated to share.

Have you ever needed to pull a bunch of different successive reports in Omniture Discover?  Maybe you want to look at Pages, then Visit Number, then Campaigns, but for each you want to see the same metric columns.  If you are like me, you open a new report and then have to re-add all of the metrics that you want to see.  If you are looking at a lot of reports this is very tedious and can drive you crazy.  However, I just learned of a “hidden” Discover feature that can avoid all of this (maybe you all knew about this, but I certainly didn’t!).  Here is what you do:

1. Open the first report you want to analyze
2. Add the metrics you want to see
3. When you are ready to see the same metrics for a different report, simply right-mouse click on the name of the report (above the rows of values as shown below – in this report you would right-mouse click on “Pages (Traffic)”)
4. Select the “Change Report” option and select the new report that you want to see!

Presto!  You are now looking at a different variable report using the same metrics without having to re-add all of your metrics…Coolness!

In other good news, Laura MacTaggart and Derek Tangren from Omniture Consulting will soon be starting a blog on blogs.omniture.com to discuss all things Discover so be on the lookout for that!!

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

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