You Asked, We Acted.
Today we launched a few improvements to WebTrends Tag Builder. Based on input from this blog we were able to quickly make some changes to a couple of issues you called out.

•   We didn’t update referrer appropriately when off-site links were clicked. Now these are passed with every off-site click.
•   We were a little too picky about file extensions. File extensions you specify on the Click Event Tracking tab are now case-insensitive.

Auto Detection of Paid Search for AdWords
Are you interested in tracking paid search for Google AdWords in your WebTrends reporting without having to deal with additional setup? Now our tag detects if referrals from Google originate from paid or organic placements without requiring you to set an additional parameter. This does require that you have the “Destination URL Autotagging” option enabled in your AdWords account. We will keep you posted as we automatically detect other engines in the future.

Integrated Tagging for Quantcast Publisher
Tag Builder now includes Quantcast as an option when you are setting up your WebTrends tagging. Quantcast is a no-charge solution that provides access to detailed geographic, demographic and lifestyle data about visitors to your site (including age, race, sex, income range, children status and other sites visited).

With WebTrends and Quantcast you can:
•    Compare your traffic acquisition strategy to competing sites
•    Get insight into how your competitors are getting traffic
•    Use insight on high-value populations to move ad dollars
•    Adjust your ad buy mid-stream – see what demographics are responding

For more details check out the Quantcast site.

Please keep the feedback coming. We are listening! Whether you are a software or On Demand customer, we’re always working hard to improve your experience with WebTrends.  Let us know how we’re doing -  from within the products,  here on the blog, user forums, Twitter or contact any of us directly.

More than a month ago we started the search for a communications company that could integrate, and make stronger, our vision of PR, AR, and Social communication being a single effort. Our marketing goals, much like our customers, are focused on growing our business and delighting our customers using Digital Marketing, Traditional Marketing, Sales, PR, AR, and Social communications collaboratively. Of course, like our customers, we want to do so objectively with data. We wanted to work with a team that, collectively, understood the rules of the traditional communication world, but had experience with new media and share the same passion for turning data into insight that we do.

Today, we are extremely pleased to share today that we’ve concluded our search and selected our new communications partner Voce Communications.

About Voce

Voce is a 50+ person firm with offices in San Francisco and Sunnyvale with people in Orlando, Portland, and Ketchum. They cut their teeth in PR and have since added AR, social media, and more comm skills. The deciding factors for us was their knowledge of the tech space, impressive skills in social media, use of technology, and passion for data. Voce has successfully grown the bottom line for companies like NetApp and using their integrated communications approach, and we’re looking to benefit from their experience.

About our plans

We have some exciting plans we’re rolling out including increased executive participation in our our local  community here in Portland, social media (extending our support and sales team into Twitter as an example), and a few big ideas that we’ll share as they develop.

Stay tuned,

Jascha

@kaykas

For our IP5 sponsor video we made a parody of the Star Wars opening scene with the yellow text that scrolls up the screen. When searching around, we came across an awesome tutorial. It turned out the tutorial was on how to use a Mac program that generated the title scene! The program is magically, but it is a little convoluted. We were able to figure it out by following this tutorial, so we’re sure many of you can figure it out too

Some things we learned:

• Figure out your copy before you render. Rendering takes a while and you don’t want to do it 4 times.
• The generator spits out individual files, which you have to compile into a single movie file. Buy Quicktime Pro to do that. It’s much easier than trying to do it with iMovie.
• To add audio, you’ll need to use a video editing program after you spit out the merged file from Quicktime.
• You can get the theme song here.

Here’s a screenshot of the program:

If you make one of these title scenes, send us a link in a comment below!

At one point or another, all of us have dismissed the need to share information because we assume that its common knowledge or simply intuitive.  When we slow down to think about (or someone else points it out), we realize that we have something to offer to help others.  That said, we’ve just released some best practices for reports and starting points in Visitor Intelligence.  WebTrends, along with our customers, have learned a lot about creating, sharing, publishing, and organizing reports and starting points in Visitor Intelligence.

With a powerful ad-hoc, multi-dimensional tool like Visitor Intelligence, there are so many ways and options that it can be overwhelming.  So, we’ve compiled some best practices that will help report creators design and publish more usable, consumable reports.  Also, we’ve included some tips to help report viewers create and manage their own reports and starting points.

The best practices are now included in  ‘Using Visitor Intelligence’ a chapter of the Marketing Warehouse User’s Guide, available in the product Customer Center.

Happy analyzing!!!

Welcome Ignite Portland followers! Here’s our sponsor video:

[youtube=http://www.youtube.com/watch?v=lHmxmjjdQY8&hl=en&fs=1]

About Our Space and Availability

Sixteen stories above Pioneer Courthouse Square on the top floor of our building, we have a space that can accommodate groups as large as 250 or as small as 16. It has a patio with grand views of the West Hills and two grills for summer time BBQs. Here’s a little more about the rooms and their amenities:

This space can hold up to 150 people. It has a kitchen and large projector screen, as well as a flat screen TV. You can access the patio from this main room, which can hold 20-30 people. Tables are available for seated events as well.

This space can hold up to 40 people comfortably. The speaker has a lectern that faces the room with a projector screen.

The classroom has room for 32 people to have deskspace (16 spots come with computers). All of the seats face a projector screen, which can be controlled by a speaker/teacher sitting at the workstation in the front of the room.

If you have a large event, the walls between the rooms retract into the walls providing a large, open room that can easily hold 250 people.

Reserve a room

If you are interested in holding an event in our space, please drop us a comment below and we will email you at the address you enter in the comment form. We’re just getting started here, so the process at the moment will be that we will work out the details over email. In the future, we may have something like a calendar and more formal rules, but for now it’s casual. Our plan is to offer the space for free to free events and to charge for paid events. If you have more questions, feel free to ask in our comments below as someone else likely has the same question.

Follow us

WebTrends employs over 300 people, many of whom are on Twitter (we have an official WebTrends Twitter account), Facebook, and more. Over the next couple of months, we’ll be rolling out more executive participation, so be sure to follow our CEO Alex Yoder and VP of Marketing Jascha Kaykas!

How did you make your IP5 sponsor video?

So, you liked the Star Wars title screen concept and want to make your own version? No problem. We’ll post a tutorial on that tomorrow.

Hi Everyone,

Last week I had the pleasure of listening to Eric Peterson speak not once, but twice. The first time was during a Coremetrics webinar on campaign attribution and the second later that evening at the local Web Analytics Wednesday where Eric delivered a longer presentation that included the same attribution material. And while I have a great deal of respect (and even friendship) for Eric and an equal amount of respect for Coremetrics, I feel a need to challenge the content.

For awhile I’ve been speaking about the emergence of the third generation of web analytics, as I call it. For those that haven’t heard me present this before, the first generation was characterized by IT departments measuring web site activity via software installations of log file analysis tools. The second generation was dominated by marketing departments utilizing hosted solutions and page tagging. The primary value these two generations of solutions provided were aggregate reports, along with rudimentary ad-hoc analysis capabilities (rudimentary, that is, compared to modern business intelligence systems).

Whereby the first two generations were characterized by reports, the third is certainly about the data – the open access to un-aggregated visitor detail data and the endless forms of true analysis that can be performed with it. Knowing that Coremetrics is one of a few major vendors to store un-aggregated data in an industry-standard database (along with WebTrends) I was expecting a thoughtful discourse on statistical modeling. Alas, what we were told was to utilize not one, but three flawed attribution models (last, first and equal), in hopes that three wrongs would make it right I suppose.

Since our high school statistics classes we have been taught the difference between correlation and causality. Statistics show that as ice cream sales increase, so do drowning deaths. Therefore, ice cream causes drowning, right? Of course not – it is the onset of warmer temperatures that indirectly leads to both. As trite as this example may seem, it is no different than the fallacy that a campaign’s inclusion in a visitor’s click-path prior to conversion means that it had a causal affect on the conversion, or that it belongs in our campaign portfolio. The same campaign may have been clicked on by many more non-converting visitors … at substantial expense.

True, if a visitor clicked on a campaign prior to conversion, it’s certainly more likely to have had a causal impact. That’s especially true for the last campaign. But if we’re going to finally break away from the flawed last-click attribution model, why not do it correctly? We have the data – let’s use a statistical model.

Now for the less-than mathematically savvy user of web analytics, no, this doesn’t mean your solution will be more complicated. Quite the contrary. Before credit card companies implemented mathematical models to detect fraud, we consumers would first learn of fraud only after we received our statement. And then after weeks arguing with our vendor we might have gotten the charges removed. Today we get a phone call within hours of the questionable transaction and a new card sent overnight to us, no questions asked. Math made our lives easier.

So will it be for campaign attribution. Imagine a campaign report that tells you, in a statistically valid way, which campaigns and campaign attributes actually had a positive contribution to conversion and to your campaign budget, versus those that didn’t. Then imagine that same report telling you how to improve results. I propose the following report:

Don’t sweat the details – I just punched some example data into a spreadsheet. Instead, focus on the bigger picture of having a report that shows you how your campaigns truly performed and recommends to you an adjusted mix based on the current set of campaigns. Then imagine the data for auction-based networks being automatically passed to an automated campaign optimization system. Now that would be progress towards true optimization of campaign budgets while also making the marketer’s job much easier.

Note that at the moment WebTrends doesn’t provide the above report either (but we do have the requisite data in a readily accessible format). My point is that it’s time to embrace the third generation of this industry and start truly leveraging the data in mathematically and scientifically valid ways.

- Barry

P.S. Please send me your thoughts on the dream campaign report.

Hi Everyone,

Last week I had the pleasure of listening to Eric Peterson speak not once, but twice. The first time was during a Coremetrics webinar on campaign attribution and the second later that evening at the local Web Analytics Wednesday where Eric delivered a longer presentation that included the same attribution material. And while I have a great deal of respect (and even friendship) for Eric and an equal amount of respect for Coremetrics, I feel a need to challenge the content.

For awhile I’ve been speaking about the emergence of the third generation of web analytics, as I call it. For those that haven’t heard me present this before, the first generation was characterized by IT departments measuring web site activity via software installations of log file analysis tools. The second generation was dominated by marketing departments utilizing hosted solutions and page tagging. The primary value these two generations of solutions provided were aggregate reports, along with rudimentary ad-hoc analysis capabilities (rudimentary, that is, compared to modern business intelligence systems).

Whereby the first two generations were characterized by reports, the third is certainly about the data – the open access to un-aggregated visitor detail data and the endless forms of true analysis that can be performed with it. Knowing that Coremetrics is one of a few major vendors to store un-aggregated data in an industry-standard database (along with WebTrends) I was expecting a thoughtful discourse on statistical modeling. Alas, what we were told was to utilize not one, but three flawed attribution models (last, first and equal), in hopes that three wrongs would make it right I suppose.

Since our high school statistics classes we have been taught the difference between correlation and causality. Statistics show that as ice cream sales increase, so do drowning deaths. Therefore, ice cream causes drowning, right? Of course not – it is the onset of warmer temperatures that indirectly leads to both. As trite as this example may seem, it is no different than the fallacy that a campaign’s inclusion in a visitor’s click-path prior to conversion means that it had a causal affect on the conversion, or that it belongs in our campaign portfolio. The same campaign may have been clicked on by many more non-converting visitors … at substantial expense.

True, if a visitor clicked on a campaign prior to conversion, it’s certainly more likely to have had a causal impact. That’s especially true for the last campaign. But if we’re going to finally break away from the flawed last-click attribution model, why not do it correctly? We have the data – let’s use a statistical model.

Now for the less-than mathematically savvy user of web analytics, no, this doesn’t mean your solution will be more complicated. Quite the contrary. Before credit card companies implemented mathematical models to detect fraud, we consumers would first learn of fraud only after we received our statement. And then after weeks arguing with our vendor we might have gotten the charges removed. Today we get a phone call within hours of the questionable transaction and a new card sent overnight to us, no questions asked. Math made our lives easier.

So will it be for campaign attribution. Imagine a campaign report that tells you, in a statistically valid way, which campaigns and campaign attributes actually had a positive contribution to conversion and to your campaign budget, versus those that didn’t. Then imagine that same report telling you how to improve results. I propose the following report:

Don’t sweat the details – I just punched some example data into a spreadsheet. Instead, focus on the bigger picture of having a report that shows you how your campaigns truly performed and recommends to you an adjusted mix based on the current set of campaigns. Then imagine the data for auction-based networks being automatically passed to an automated campaign optimization system. Now that would be progress towards true optimization of campaign budgets while also making the marketer’s job much easier.

Note that at the moment WebTrends doesn’t provide the above report either (but we do have the requisite data in a readily accessible format). My point is that it’s time to embrace the third generation of this industry and start truly leveraging the data in mathematically and scientifically valid ways.

- Barry

P.S. Please send me your thoughts on the dream campaign report.

Hi Everyone,

Last week I had the pleasure of listening to Eric Peterson speak not once, but twice. The first time was during a Coremetrics webinar on campaign attribution and the second later that evening at the local Web Analytics Wednesday where Eric delivered a longer presentation that included the same attribution material. And while I have a great deal of respect (and even friendship) for Eric and an equal amount of respect for Coremetrics, I feel a need to challenge the content.

For awhile I’ve been speaking about the emergence of the third generation of web analytics, as I call it. For those that haven’t heard me present this before, the first generation was characterized by IT departments measuring web site activity via software installations of log file analysis tools. The second generation was dominated by marketing departments utilizing hosted solutions and page tagging. The primary value these two generations of solutions provided were aggregate reports, along with rudimentary ad-hoc analysis capabilities (rudimentary, that is, compared to modern business intelligence systems).

Whereby the first two generations were characterized by reports, the third is certainly about the data – the open access to un-aggregated visitor detail data and the endless forms of true analysis that can be performed with it. Knowing that Coremetrics is one of a few major vendors to store un-aggregated data in an industry-standard database (along with WebTrends) I was expecting a thoughtful discourse on statistical modeling. Alas, what we were told was to utilize not one, but three flawed attribution models (last, first and equal), in hopes that three wrongs would make it right I suppose.

Since our high school statistics classes we have been taught the difference between correlation and causality. Statistics show that as ice cream sales increase, so do drowning deaths. Therefore, ice cream causes drowning, right? Of course not – it is the onset of warmer temperatures that indirectly leads to both. As trite as this example may seem, it is no different than the fallacy that a campaign’s inclusion in a visitor’s click-path prior to conversion means that it had a causal affect on the conversion, or that it belongs in our campaign portfolio. The same campaign may have been clicked on by many more non-converting visitors … at substantial expense.

True, if a visitor clicked on a campaign prior to conversion, it’s certainly more likely to have had a causal impact. That’s especially true for the last campaign. But if we’re going to finally break away from the flawed last-click attribution model, why not do it correctly? We have the data – let’s use a statistical model.

Now for the less-than mathematically savvy user of web analytics, no, this doesn’t mean your solution will be more complicated. Quite the contrary. Before credit card companies implemented mathematical models to detect fraud, we consumers would first learn of fraud only after we received our statement. And then after weeks arguing with our vendor we might have gotten the charges removed. Today we get a phone call within hours of the questionable transaction and a new card sent overnight to us, no questions asked. Math made our lives easier.

So will it be for campaign attribution. Imagine a campaign report that tells you, in a statistically valid way, which campaigns and campaign attributes actually had a positive contribution to conversion and to your campaign budget, versus those that didn’t. Then imagine that same report telling you how to improve results. I propose the following report:

Don’t sweat the details – I just punched some example data into a spreadsheet. Instead, focus on the bigger picture of having a report that shows you how your campaigns truly performed and recommends to you an adjusted mix based on the current set of campaigns. Then imagine the data for auction-based networks being automatically passed to an automated campaign optimization system. Now that would be progress towards true optimization of campaign budgets while also making the marketer’s job much easier.

Note that at the moment WebTrends doesn’t provide the above report either (but we do have the requisite data in a readily accessible format). My point is that it’s time to embrace the third generation of this industry and start truly leveraging the data in mathematically and scientifically valid ways.

- Barry

P.S. Please send me your thoughts on the dream campaign report.

Why Twitter? I Don’t Get It! If you’ve asked that question yourself or heard it from others – This NYTimes article on the Brave New World of Digital Intimacy helps to explain the transformation on tapping the collective consciousness. Personally – I have a love/hate relationship with Twitter and I’d bet many of you feel the same way.

Love that I can keep up with many of my friends and coworkers so that when I see them in person, know a bit more of what is going on with them and we automatically start our conversations at another level. 

Hate that many people, including folks I’ve never met, know more about my day-to-day life than my sister who lives a few states away.

Love that when I have something that I think is interesting to say, I can find the right 140 characters (or less) to express my thoughts.

Hate when I don’t have time to keep up with those that I do follow.

I spend too much time checking Twitter updates.  I don’t have enough time to keep up with Twitter updates.  I installed the TwitterFox plug-in for Firefox and Twitterberry on my Blackberry because I feel like I need to keep up with what’s going on.  But I uninstalled Tweetdeck because there is way too much going on.  I’m usually pretty decisive about things, but not Twitter.  I love it, I hate it, I have a strong opinion that changes fairly often.

But here’s the thing: it doesn’t matter what I think about Twitter. And it doesn’t matter what you think about Twitter. As a product manager I live every day by the saying that while my personal opinion might be interesting, it is completely and totally irrelevant.  It doesn’t matter what we think about Twitter.  What does matter is that your customers, prospects, supporters, and detractors are all using it.  They are saying good things, they are saying bad things.  People who want to learn about your company are using Twitter to learn more about your company’s products and services.  And from these 140 character snippits, they are going to your web site.  Think about that – they are going to search.twitter.com (formerly Summerize), typing in a keyword or phrase that you’ve worked really hard at getting to the top of Google search, and finding a ton of information about your company on a site full of 140 character microblogs.  And by the way, you don’t necessarily have a lot of control about what’s being said.

At WebTrends – not only is there Twitter talk, there is Twitter listening.  We spend a lot of time using all of the new, modern, social media tools out there so we are better marketers ourselves. While some of us think we’re doing some really cool, modern things regarding social media – it also freaks some of us out.  We know we have to do our best to measure our effectiveness and we know how hard it can be to measure that effectiveness. (just ask our own social media team how they are tracking the space)To make that measurement easier we employ a social media tagging strategy and the newly available Twitter tracking.

Click for Full Size Screenshot

We recently added tracking Twitter as a search engine in WebTrends Analytics reports.  It’s already in our On Demand offering, or if you use our software you can download an installer to upgrade your installation.  It’s probably not going to be at the top of your search engine reports, but you can use our reporting’s search feature to see what keywords and phrases people are using to find your site – what they are saying on Twitter.

Now -  if I could just sum up all these thoughts up in 140 characters …  If I only had the time.

Although the field of web analytics has slowly broadened its reach, it’s still far short of a household word. As an analyst or administrator of WebTrends, this lack of familiarity with analytics can become a huge stumbling block, especially if the decision makers in charge of budgeting and resources are among the uninformed. Our clients are often unhappily surprised to find that a sound installation and a plan for moving forward sometimes aren’t enough to get analytics data adopted enterprise-wide, nor to get the attention drawn to their area that will guarantee adequate resources and funding.

In a past job, I was the proverbial lone voice in the wilderness, preaching the benefits of using analytics data to drive decision-making, but unable to gain enough support internally to move us forward. Perhaps you’ve felt like that, too. Simply providing the data doesn’t guarantee you’ll be able to get decision-makers to start using it; you have to build a culture of data-driven decision making so compelling that it spreads throughout your organization. That is a tall order for a single analyst, or even a single department. The only way to succeed is to find allies. Preferably, allies with influence, decision-making power or organizational clout.

One way to find such allies is to look among your “squeaky wheels”. If there is one manager or executive who consistently cross-examines the data and finds it wanting, that’s the person you want to recruit as an ally. Why? Because a true conversion story always carries weight. If you can convert that complainer into your advocate, then everyone in your organization  is going to take notice. Here are some tips for winning him or her over: (more…)