One of the major complaints about my work on measures of Visitor and Audience Engagement is that unless you have Visual Site (= Omniture on Premise), Unica, Coremetrics, SAS, or a custom data warehouse solution you’re somewhat limited in your ability to make the calculation. Now, thanks to the recent upgrade to Google Analytics and the availability of session-level segmentation everyone can use my calculation to explore engagement patterns on their site.

Yep, free measures of Visitor Engagement from Web Analytics Demystified and Google Analytics!

It was a post from Alec Cochrane about engagement that got me thinking about the application of my calculation using Google’s segmentation features, thanks Alec! Heck, had I been paying more attention to his blog I would have noticed that even Avinask Kaushik (who persists in his dogmatic assertion that “engagement cannot be measured”) refers to GA’s ability to make the calculation.

Keep in mind, what I’m describing in this post is not a full-blown measure of Visitor Engagement for a lot of reasons. Still, as I’m kicking it around it appears to be a pretty good start and per my entire approach towards measures of engagement, I’d rather have all of you banging on the idea than work in a vacuum.

So how does it work?

Step 1: Gather Your Threshold Values

The first step is to determine what thresholds you want to set for your Click-Depth, Duration, Recency, and Loyalty indices.  You can get the first two from GA’s Visitors > Overview report (shown at right) while Recency and Loyalty come from Visitors > Visitor Loyalty > Recency and Visitors > Visitor Loyalty > Loyalty respectively.

Depending on your site you may need to be creative in how you set the Loyalty and Recency thresholds, especially since GA’s reporting on these measures is not super robust. Fortunately, since the segmentation tool is pretty flexible you can play with the threshold values once you’ve set them.

Step 2: Create Your Engaged Visitors Segment

The next step is to create a segment that lets you identify “engaged” visitors on your site. I’ll first describe the basic calculation, which is essentially the same as Audience Engagement only applied to click-stream data, and then expand in a follow-up post on the idea leveraging the Interaction Index, the Brand Index, and the Feedback Index.

Start by “creating a new custom segment” and adding the visitor dimension “Page Depth” (Google Analytics’s measure of Click-Depth during the session) setting the condition to “Greater than or equal to” the Click-Depth threshold value you discovered in Step 1:

Make sure to test the segment and confirm that things are working. In the example above you can see that about 25% of the sessions to my site last May were of at least three page views. Next you’re going to add the Duration Index by adding an “and” statement and dragging in the visitor dimension for “Visit Duration” and setting the condition to “Greater than or equal to” the time on site threshold determined in step 1:

Because you’re using an “and” statement we are getting the number of sessions that were both at least three page views and at least three minutes in duration; while this is imperfect compared to the visitor by session scoring strategy we described in the longer white paper the use of “and” ensures that we’re identifying visitors who are paying Attention as measured by clicks and session duration.

The next step is to roll in the Loyalty and Recency indices using the visitor dimensions “Count of Visits” and “Days Since Last Visit”.  As I mentioned above you may need to play with the thresholds here, perhaps creating a visitor segment of goal converters (purchases, leads, etc.) and examining the return visit behavior for that segment.  Also, when you set “Days Since Last Visit” be sure to use the condition “Less than or equal to” to capture visitors who have been to the site recently:

If your site is like mine you’ll see a noticeable drop in the number of matching visits when you add “Count of Visits” or “Days Since Last Visit” because of the use of the “and” operator.  But this is good and to be expected since if everyone coming to your site was truly engaged then you wouldn’t be reading this post, you would just be rolling in money.

All you have to do now is name and save the segment and you’re in business!  I called my segment “Engaged Visitors” which is not technically correct — really what I’m tracking is “Engaged Visits” — but when you see the final application of the segment below you’ll understand why.

Step 3: Mine Google Analytics for Engaged Visitors

Once you’ve created your “Engaged Visitors” segment you can start to apply it to the various reports in Google Analytics.  I recommend comparing the engagement segment against “All Visits” to get context — and GA does something nice here in calculating the percentage of segment members (= sessions where all four engagement criteria are met) for you.  Here you can see how this comparison looks in the Visitors > Map Overlay report:

While I’m only drawing a moderately engaged audience from Australia I am feeling the love from Spain! Probably since my good friend Rene Deschamps is Spanish or perhaps since I’m talking to a web analytics consulting group in Spain about coming over for a presentation and a big Web Analytics Wednesday event this coming Spring … who knows?

Now, I am pretty delighted with how easily these segments can be applied to the various reports in Google Analytics … hell, just the fact that the segment stays applied when I navigate from report to report is nice.  And yes, there are some obvious improvements that could be made but for a first effort this is pretty nice.

The same segment can be applied to reports that are more critical to how you run you business, for example the keyword report.  When I look at three top keywords driving traffic to my site you can see a clear pattern begin to emerge (and this is without adding the Brand Index into the engagement calculation):

Here you can see an obvious difference in the level of engagement associated with external searches for my brand’s name and “Web Analytics Wednesday.”  Even searches for Judah Phillips driving traffic to my site are bringing in a highly engaged audience (Judah, since I know you’re sensitive about this, nearly 30% of the visits associated with searches for you are scoring as engaged … nice work, buddy!)

If you’re willing to keep drilling down you can learn all kinds of wonderful things.  Here is a comparison of network traffic coming from WebTrends and Omniture:

Finally, if you’re using your one user defined field to capture some type of visitor identifier (hopefully doing so in line with your privacy policy) you can actually apply the engagement segment to individuals or groups interacting with your web site and actually begin to measure true Visitor Engagement.  Here you can see my very good friends Judah and June who are highly engaged at the Web Analytics Demystified web site, shown in stark contrast to another very active visitor who does not appear to be paying me any Attention at all:

This has become a long post so I’ll stop here for now and leave you with the following summary points:

• Google Analytics, like any session-based system, is not perfectly suited for calculating a true measure of Visitor Engagement;
• That said, given the recent availability of segmentation in Google Analytics, I would encourage those of you running GA to explore the use of my Visitor Engagement calculation;
• My belief is that you will begin to see for yourselves that this measure will help you identify opportunities not easily uncovered using traditional measures like average time on site and bounce rate;
• But you don’t have to take my word for it, do you? Play with the ideas I put forth in this post and let me know what you discover.  I would absolutely love to hear what you learn using this segmentation strategy or learn about applications of the segment that I haven’t thought of yet!

Last but not least, keep in mind that I have always put forth my work on Visitor and Audience Engagement as a hypothesis, one that is still being evolved and subject to testing and application in a variety of business situations. The thing I love about our community more than anything is the willingness that most of us show to explore new ideas and have an open mind.

As always I welcome your comments and feedback.

By now you are all well aware that the nice folks at Google wowed the web analytics world last week by announcing a suite of upgrades to Google Analytics at Emetrics.  Google’s “Analytics Evangelist” Avinash Kaushik — who was otherwise a no-show at the conference — made the flight out in Brett Crosby’s place to deliver a very energetic presentation describing the new features. More than anything after the talk I was left with this impression:

Google is serious about Google Analytics.  Period.

This is great news, at least for most of us, and I have to say after playing with some of the new features I am very impressed. Not that I didn’t expect to be — Brett and Paul’s team at Google has repeatedly demonstrated that they get it and that they have the programming talent to back them up.  With the addition of Kaushik as a full time product evangelist, especially given Avinash’s intensely competitive nature, the question wasn’t “will they improve the product” but rather “how much will they improve the product?”

This is a conversation I seem to have with folks who are tangential to the industry quite a bit, mostly because people who have invested a bunch into OMTR are justifiably nervous about whether Google Analytics has the potential to slow SiteCatalyst sales.  All along the arguement for OMTR was “Google Analtytics is nowhere near as powerful as SiteCatalyst and Google has no reason to improve Google Analytics, adding missing functionality like segmentation, customization, and data export functionality given the associated costs and the fact that Google Analytics already dominates the web analytics landscape with an over 65% marketshare across all sites with tag-based analytics deployed.”

Except it appears that nobody told Google this. Or, if they did, Google didn’t listen.

Now don’t get me wrong, the new features are not totally perfect.  The segmentation feature which is receiving the most hype within the web analytics community is not true visitor-level segmentation but rather session-based segmentation which severely limits an experienced practitioner’s ability to drill-down into the data. But I suppose this is a perfect example of “you get what you pay for” and since we’re not paying having multidimensional session-level segmentation that can be immediately applied to all historical data is pretty sweet.

On the upside, I was actually pretty surprised about Motion Charts which to me seemed like a tchotchky but after playing with it for just a little bit I’m inclined to agree with Yahoo’s Dennis Mortensen that Motion Charts have potential. I especially like the “Link to Chart” option that seems to allow us to share the visualizations we create with other Google Analytics users.

Here’s a Motion Chart that I’m rather enjoying the use of: Keywords by goal conversion rate by bounce rate sized by Percent New Visits colored uniquely with trails turned on.

The other features (AdSense integration, Management Console upgrade) are nice but decidedly less sexy.  Oh, except for the Data Export APIs which is easily the most exciting feature announced, and the one that has the greatest potential to reshape the web analytics landscape forever.  As I recently commented when talking about Yahoo Web Analytics, the availability of API-based access to web analytic data is the feature that has the greatest potential to change the way larger and more sophisticated companies think about free tools like Google Analytics.

Judah Phillips commented as much back in May of last year when Google updated Analytics the last time.  Bright guy that Judah.  Now he can use Google Analytics in his new position to pull freely collected data into the corporate Intranet … niiiice!

I suspect that before long we’re going to see some pretty cool applications taking advantage of the Google Analytics APIs which will erode the immediacy of need to invest in for-fee solutions.  When I ask my magic eight-ball if someone will develop something like HBX ReportBuilder for Google Analytics to allow companies to create custom reports in Excel and schedule delivery, or if we’re going to see vertical-specific web analytics applications like “Google Analytics for Real Estate Sites” and “Google Analytics for Law Firms” the response is always the same:

“Signs point to yes.”

It’s not that there isn’t still a gap between functionality provided by Google Analytics and that provided by Yahoo Web Analytics, SiteCatalyst, Coremetrics, WebTrends Web Analytics, etc., there definitely is. Custom data collection, data integration into the visualization interface, visitor-level data collection and analysis, custom dimensions and metrics, and the like are all features more-or-less required for advanced analytics.  But I think the fact that so few companies are doing truly advanced analytics coupled with the inevitable ecosystem that will spring up around the Google Analytics APIs will create some pain within the sales organizations among the for-fee vendors.

Especially in this uncertain economy, if I have to choose between spending between $20K to $50K on an entry-level SiteCatalyst/Coremetrics/WebTrends/Unica/Nedstat deployment or spending nothing to explore the use of segmentation, report customization, and Motion Charts while waiting for someone like DataLinks to port their application to the Google Analytics APIs so you can spend $995 to build totally customized key performance indicator reports in Excel … well, as a small business owner the choice is pretty clear.

WebTrends recent announcement about moving increasingly into BI, essentially as middleware between web data and traditional business analysis applications, is typical of the response I expect we’re going to see from the for-fee vendors. Some type of move up-market to continue to justify the expense of data collection, which will further limit opportunities for growth since I expect the end-user market to continue to mature at a much slower pace than the available technology set.

I mean, why pay for data collection and storage if Google and Yahoo are going to give it away? Especially in the context of those APIs and the low-cost applications we’ll inevitably see, I suspect the management teams at Omniture, Coremetrics, WebTrends, Unica, and Nedstat are looking suspiciously at their Q4 and Q1 2009 projections for SMB sales and global expansion trying to figure out exactly how much free web analytics will ultimately impact the business.

I know I would be.

It’s not to say they won’t figure it out — all of these guys are tough competitors with a lot of experience growing their business in an increasingly volatile market — but it will certainly be interesting to see how they go about it.  And I personally think it’s going to be a lot of fun to see how the market changes.  The best companies are doing absolutely outrageous things with web analytics, the mid-market is maturing more than ever thanks to an understanding of the right relationship between people, process, and technology, and the number of viable solutions is now approaching a very reasonable set reflective of the market’s maturation.

In summary:

• The new Google Analytics features are totally awesome and the crew at Google should get some kind of altruism award for making this level of functionality available for free;
• Once and for all we can agree that, without any doubt, Google is serious about Google Analytics and web analytics in general;
• While GA’s segmentation is limited to session data only, the implementation is brilliantly intuitive to use, especially at the best of all price points;
• Motion Charts are far cooler than I expected them to be, custom reporting is as brilliantly intuitive as I expected it to be;
• I still don’t think Google Analytics is appropriate for advanced practitioners, at least not as a system of record, but the number of truly advanced practitioners working out there today is still relatively small;
• I think the Data Export APIs are the most exciting aspect of this announcement and I’m looking forward to all the cool, new applications that will inevitably spring up based on these APIs;
• I think that Google has sucked the wind out of Yahoo’s sails, whether they intended to or not, but I still don’t think that Google Analytics and Yahoo Web Analytics are directly competitive;
• I think the vendor folks most impacted by this announcement are the teams responsible for SMB sales, the expansion into Europe and Asia, and anyone selling web analytics solutions at a sub-$50K price point;
• I expect the for-fee vendors to respond to Google Analytics not by picking on the features (remember: voters don’t like negative campaigning!) but rather by working to more aggressively take their existing suites and platforms up-market;
• I don’t expect this announcement to be a death blow to anyone. Rather it serves as yet another reinforcement of the inevitable commoditization of the web analytics data collection market and a wake-up call to any company with a ten-year plan to continue to make money counting page views.

Okay, thanks to Brett’s generosity I’m going to go back to playing with segmentation and Motion Charts. As always I welcome your feedback on my commentary and would love to hear from those of you also playing with the new features about your experience.

About six months ago the management team at comScore approached me with some questions about my Visitor Engagement calculation and the Web Analytics Demystified engagement framework. Their Chief Research Officer, Josh Chasin, had taken an interest in my work and wondered how it may be extensible across multiple properties using the comScore dataset.

It was an excellent question, and today I’m happy to give readers a preview of what we believe to be an excellent answer. Today we’re announcing a measure of Visitor Engagement that, thanks to comScore, can be used to compare levels of engagement across multiple properties in a similar category.

Brand Marketing’s New Measure: Audience Engagement

Audience Engagement is a simple modification of Web Analytics Demystified’s Visitor Engagement calculation that focuses on the core site behavioral attributes, measured through the comScore panel. If you remember, the Visitor Engagement calculation is:

Σ(Ci + Di + Ri + Li + Bi + Fi + Ii)

The components of the Visitor Engagement calculation are:

• Click Depth Index: Captures the contribution of page and event views
• Duration Index: Captures the contribution of time spent on site
• Recency Index: Captures the visitor’s “visit velocity”—the rate at which visitors return to the web site over time
• Brand Index: Captures the apparent awareness of the visitor of the brand, site, or product(s)
• Feedback Index: Captures qualitative information including propensity to solicit additional information or supply direct feedback
• Interaction Index: Captures visitor interaction with content or functionality designed to increase level of Attention the visitor is paying to the brand, site, or product(s)
• Loyalty Index: Captures the level of long-term interaction the visitor has with the brand, site, or product(s)

(More information about the measure of Visitor Engagement, including the details behind the calculation and several example use cases, can be obtained by reading the white paper that Joseph Carrabis and I recently published, Measuring the Immeasurable: Visitor Engagement which is freely available on this web site.)

The Audience Engagement simplifies Visitor Engagement by applying a “zero weighting” to the Brand, Feedback, and Interaction indices. By removing these values from the core calculation we are left with Click-Depth, Duration, Recency, and Loyalty:

Σ(Ci + Di + Ri + Li)

In English:

“Audience Engagement is a function of the number of clicks a visitor generates at a site, the amount of time they spent at the site, the frequency at which they return to the site, and their loyalty to the site as a member of the category for all of the sessions to that site during the reporting period.”

We’ve selected these four indices for one very simple reason: When scored using category-level thresholds (with the exception being the Loyalty Index, see below) comScore is able to automatically generate Audience Engagement values and engagement distributions across all of the sites they track.

The result is unique view into the relationship visitors have with the thousands of web sites comScore tracks around the globe. Now, for the first time ever, marketers and advertisers are able to gain insights into the level of engagement using a much more robust measure than session duration, page views, or recency alone.

Using Audience Engagement we can say with a high level of certainty that a greater percentage of Internet users find CNN more engaging than MSNBC and Yahoo! News:

More importantly we can also say that CNN has a larger population of “highly engaged” visitors to their site (22.5% of visitors at CNN versus 15% at MSNBC and less than 10% at Yahoo! News.) We believe that assessment of the audience distribution will provide advertisers an entirely new way to evaluate sites, focusing on audience quality over more simplistic measures of quantity.

This same type of analysis applied to popular network sports sites yields similarly interesting insights:

Here we can see that ESPN, while trailing Yahoo! Sports across all traditional measures (page views, sessions, minutes spent, active days) dominates Yahoo! from an Audience Engagement perspective. A closer examination of these two sites shows that ESPN’s dominance is driven largely by the frequency at which their audience members return to the site (Recency Index of 47.2% versus Yahoo! Sports at 27.0%) — an insight that has clear value to advertisers looking to create brand awareness and drive brand impressions across a sports-minded audience.

While comScore and Web Analytics Demystified are still working on how this data will be packaged and presented, another way of visualizing the relationship between two sites or a site and the category average is using a spider chart:

This chart visually tells the same story as the table above — ESPN has a higher level of Audience Engagement (bigger footprint) that is largely driven by Loyalty and Recency.

We believe that brand advertisers, advertising planners, and marketing managers will be able to use this data to make better decisions during the ad planning and media buying process. The whole debate over the definition of engagement manifest largely from advertisers desire to find more engaged audiences juxtaposed against a lack of faith in the simple measures being proposed as proxies for engagement. Thanks to comScore, these simple measures are about to become a thing of the past, giving way to a significantly more robust measure of the level of Attention audiences are paying at advertising powered sites around the world.

Interpreting Individual Data Points

In case you don’t want to spend the time reading the 50 page white paper I wrote recently on the subject with the mathematician and cultural anthropologist Joseph Carrabis, I’ll provide a brief summary of how the data comScore is reporting can be used.

Here is a sample of sites from comScore’s automotive category:

The first line in this table says that 42.8% of the audience to KBB.com is appreciably engaged with the web site. Engagement at KBB.com is largely driven by visitors clicking deeply into the site and spending an appreciable amount of time doing so, with nearly 85% of audience members exceeding the category Click Depth threshold and over 60% exceeding the duration threshold. Finally, using the distribution data, we can also see that 63% of the audience is highly engaged versus less than 3% who are only poorly engaged.

Audience Engagement data provided by comScore can also be used in a comparative context. Looking at the most and least engaging sites in this group, the data suggests that the audience going to KBB.com is over 400% more engaged than the audience going to About.com Autos (42.8% versus 8.5%.)  This is not to say that advertising at About.com Autos is a bad idea — over 90 percent of the site’s audience appears to be moderately engaged and in some instances a moderate level of engagement may be exactly what the campaign is looking for.

A Technical Note about Audience Engagement’s Loyalty Index

In the Audience Engagement calculation, the Loyalty Index is calculated differently than in the Visitor Engagement calculation because of an advantage conferred by the comScore system. Instead of simply counting the number of times a visitor has returned to the site as we’re forced to do using a site-centric data model, comScore allow us to better approximate loyalty as more commonly used: a measure of your likelihood to prefer a single site or brand over all others in the category. This model is essentially a “share of requirements” model used traditionally in the brand advertising industry and is calculated as:

Li(AE) = Visits to Site / Visits to All Sites in the Category

So, for example, if a comScore panelist is going only to eBay in comScore’s “Auctions” category, their Loyalty Index for eBay would be 100%:

Li(AE) = 10 visits to eBay / 10 visits in the “Auctions” Category

Conversely, if another visitor goes to eBay half the time and Bidz.com half the time, their Loyalty Index for eBay would be 50%:

Li(AE) = 5 visits to eBay / 10 visits in the “Auctions” Category

The result is a distribution of Loyalty Index scores for auction sites tracked by comScore in September that looks like this:

As you can see, eBay’s Audience Engagement component indices are higher than those of their competitors, but their Loyalty Index is much higher and tells us that nearly visitors in this category strongly prefer eBay to their competitors.

One of the challenges comScore and Web Analytics Demystified face regarding the Loyalty Index is the refinement of categories. Some categories like “Auctions” are well defined and represent logical competitors in a sector; others, like “News/Information” include diverse sites like Weather.com, Discovery.com, and Court TV Online. Over time we hope to refine these categories in partnership with comScore clients to provide the most accurate view of category loyalty possible. If you’re interested in participating in this work, please contact me directly.

Next Steps for comScore and Web Analytics Demystified

This is the first time we’ve been able to apply the Web Analytics Demystified Engagement construct to a syndicated audience data base.  We’re just announcing this work today, but we can already see possibilities for the measure’s evolution. Potential next-generation enhancements could include:

• Allowing comScore clients to provide a set of branded search terms to support the inclusion of Visitor Engagement’s Brand Index (Bi)
• Allowing comScore clients to provide a set of key site interactions designed to promote visitor Attention, supporting the inclusion of Visitor Engagement’s Interaction Index (Ii)
• Incorporating third-party data sources measuring more qualitative aspects of the audience relationship with the site, supporting the inclusion of Visitor Engagement’s Feedback Index (Fi)
• Allowing comScore clients to define their own competitive set in order to drill down into a more specific engagement profile in support of the advertising sales process
• Providing comScore clients access to the details behind the Audience Engagement calculation for their site and category
• Providing comScore clients custom access to Audience Engagement data, to provide a measure of Visitor Engagement in situations where the web analytic technology deployed does not support direct measurement

These are just a handful of examples of where this data offering can go. We’re presenting this model and starting the conversation because we want to hear from you. Regardless of whether you’re a current comScore or Web Analytics Demystified client, we would love your feedback regarding the calculation, the data, and the type of insights Audience Engagement is likely to provide to your organization.

Want to Know More about Audience Engagement?

Any reader of this blog knows that I have a passion for talking about the new measures of success on the Internet. I’m tremendously excited about this announcement and happy to talk if you’re interested in how you might be able to leverage Audience Engagement data.

Also, don’t hesitate to contact us if you have concerns about how we measure Audience Engagement or, in the extreme case, don’t think engagement can be measured at all. I firmly believe that the measures of Visitor and Audience Engagement I have proposed and the work I’ve done with Mr. Carrabis and now with comScore are only the beginning of the search for more useful measures of success on the Internet. Because these measures attempt to approximate something we agree is difficult to quantify, we believe that these measures will evolve over time; nothing is set in stone.

But we also believe that Visitor and Audience Engagement are better measures than “page views” and “average time spent” and far more useful to the measurement industry as a whole than simply sticking our head’s in the sand and exclaiming “engagement is an excuse” or worse, taking a Luddite’s view and declaring that complex measures are destined to fail.

For the time being, comScore is previewing additional details on the measure of Audience Engagement with their clients selectively.  If you’d like more information about how to be added to comScore’s list, or would like to discuss the measure of Audience Engagement with me, please email me directly and we can arrange a time to chat.

Those of you following me on Twitter and Facebook have probably noticed that I’m spending much of October on the road.  After delivering the keynote address at ForeSee Results excellent Digital Citizen 2008 conference for the public sector I hopped on a flight to London to deliver the keynote at Coremetrics European client summit.

While in London I was able to join over 170 bright, motivated, and extremely nice web analysts from Europe at what turned out to be the biggest non-Emetrics Web Analytics Wednesday event ever.  This event was everything that I have ever hoped that Web Analytics Wednesday would be — extremely well organized by the kind folks at SCL Analytics, featuring great  talks from senior folks from the vendor, practitioner, and consulting community, held in a fantastic location thanks to the generosity of Coremetrics.  An absolutely perfect evening!

Thanks again to Chris and the team at SCL, Renata and the team at Coremetrics Europe, and everyone who participated in the event.

I have one more private event on Friday but what I’m really, really excited about is getting to present (again) at Jim Sterne’s Emetrics Marketing Optimization Summit in Washington, D.C.  I am proud to say that, aside from Jim, I may be the only person in the world who has attended every single North American Emetrics.

Despite having heard it all and seen it all and started helping Semphonic promote and produce the X Change, I would never consider for a moment skipping this great event.  This year Jim was kind enough to allow me to present to a combined track in the big room on Tuesday so I will be delivering a brand new presentation titled “Competing on Web Analytics.”  Drawing on Tom Davenport’s great work in HBR and his own book, this presentation more than any I have given in the past brings our practice together and presents a clear, concise roadmap for success.

If you’re coming to Emetrics I hope you’ll join me Tuesday at 11:10 AM in Room Plaza ABC.

When I was describing my travel schedule to a friend last night he asked me point blank “Why do you do it? Why do you travel to so many Web Analytics Wednesdays and conferences, spending hundreds of days a year on the road to evangelize for web analytics and support the web analytics community?”

Easy. I love what I do!

Because I love what I do, it would never occur to me to skip an Emetrics. Sure, I’d love Jim to pay my speaker’s fee and yeah, I’d love a keynote speaker’s slot now and again. But after 10 years in this industry I’m clear that the web analytics sector is bigger than me, Jim, or any vendor, consultant, practitioner, author, or blogger.  Emetrics provides a twice-a-year touchpoint for a large part of our community, and Emetrics is the event that gave me, Avinash Kaushik, Bryan Eisenberg, Jason Burby, Jennifer Veesenmeyer and many more the opportunity to establish our personal and professional brands.

So for me, and I think this is true for most of my peers, it’s not a question of whether we’ll be at Emetrics, it’s only a question of what we’ll talk about.

Because of the things I’ve learned at Emetrics, I promote and support Web Analytics Wednesday to give back to the larger community.  By facilitating the Global Sponsorship, by supporting emerging events around the planet, by helping local hosts plan more engaging events, and by attending as many WAW events as humanly possible I am able to take much of what I’ve learned at Emetrics and put it into action on a larger scale.

The support of my friends, partners, and co-sponsors is allowing Web Analytics Demystified help to keep the web analytics community together when we’re not at Emetrics.  In 2008 we are going to beat our goal of 5,000 attendee, making Web Analytics Wednesday the largest gathering of web analytics professionals worldwide. Web Analytics Wednesday works because everyone’s intentions are pure — hosts want to have a nice event, participants want to network, and the sponsors want to support the WAW community.

Simple.

So I hope you’ll come see me at Emetrics next week, or at least join June, Jim and I at what will likely be the biggest Web Analytics Wednesday ever next Wednesday at the conference hotel.  Emetrics is the conference for everyone, so I look forward to seeing all of you there.

While Dennis Mortensen was kind enough to give me some advance notice that Yahoo! had officially rebranded IndexTools and was making it available to a wider audience, I have been so swamped with client projects I haven’t had a chance to comment on the news until now. I’m excited to see the company making forward progress towards making IndexTools available to the larger market, especially in the context of the vote of “no confidence” I keep hearing from the investment bankers I talk to from time to time.

Given that I was honored to break the story about the acquisition it is no wonder that some people have commented, “Hey, Peterson, you were wrong … it’s not free for everyone!” To this I can only comment that I would rather see Yahoo! take a measured and thoughtful approach towards the deployment of the application than be right.

But the one thing I have seen a lot of these past few days is the assertion that Yahoo Web Analytics is designed to compete with Google Analytics and that Yahoo! is somehow lame for being so late to the game. Wrong, wrong, wrong, wrong, wrong.

For those of you keeping track, when Yahoo! announced that they were waiving all fees for existing customers I commented the following:

“Finally, I would personally offer that Google Analytics and IndexTools are (in their current state) dramatically different applications targeting very different audiences.”

Now, I suppose I don’t expect traditional media to look any deeper into web analytics than necessary and so of course the logical conclusion is “Yahoo! and Google compete, egro Yahoo Web Analytics and Google Analytics are competitors.” I just hope the team at Yahoo! doesn’t start to believe this positioning as it is A) clearly wrong, B) minimizes the value of the acquisition, and C) only sets Yahoo! up to fail (something I suspect they have had quite enough of lately …)

In the midst of the media mini-frenzy I saw one quote that almost perfectly summarized why these two applications are unlikely competitors, published by the E-Commerce Times (emphasis mine):

“The data’s not aggregated — the data’s stored raw in our database,” Jitendra Kavathekar, vice president of Yahoo Web Analytics, told the E-Commerce Times.

“You basically get real-time reports and dashboards, allowing our customers to take immediate action rather than waiting half a day, or waiting a day, or waiting a week to get the information they need,” he explained.

That option, Kavathekar asserts, opens up a whole host of new options for end-users when it comes to data visualization and manipulation.

“The ability to drag-and-drop different filters — to be able to cut the data in different ways, in real-time, to get the data that you need, to get the insights you need — is something you don’t generally see out there in the market,” he said.

“The data’s not aggregated” is the difference between SiteCatalyst and Omniture Discover, WebTrends Web Analytics and Visitor Intelligence, etc. It is also the difference of tens if not hundreds of thousands of dollars, additional training and support, and the need for experience professionals in the operator’s chair.  

I said it before and I’ll say it again, just for emphasis: Game changing.

Regardless of the timeline — Christmas, Easter, Memorial Day, 4th of July, whatever — Yahoo! making a real-time raw data collection environment available to a widespread audience for free will change the web analytics market, especially if the company can get their arms around a reasonable GTM strategy. If Yahoo! can figure out how to get the application in the right people’s hands instead of pursuing the ludicris strategy of duplicating Google’s success,well, I stand by all previous assertions regarding who IndexTools hurts and who it helps.

Despite not competing, the wildcard of course is still Google. I don’t talk to Brett as often as I should but the rumors of new segmentation functionality coming soon are growing louder and the idea of Google Analytics APIs from Google (as opposed to a group of bright, enterprising individuals) is persistent. Hopefully some of this will come to light week after next at Brett’s Emetrics presentation, especially since his announcement at Emetrics San Francisco made us all yawn …

If Google is coming upmarket, driven by IndexTools or just their own internal strategy, a lot of the objections to deploying Google Analytics as a business standard start to disappear. Segmentation, custom variables, an API, better filters, etc. will all push GA up-and-to-the-right in the constellations, waves, and magic quadrants of the world. Couple that with Google Web Site Optimizer and the long-term view of the market’s evolution gets even cloudier.

One thing I keep forgetting to ask Dennis and my other contacts at Yahoo! is about the status of Rubix. Last I asked it was still on the table, something that only appears to be reinforced by Kavathekar’s statement about data visualization and manipulation. If you’ve seen Rubix, the “drag-and-drop filters” comment is especially telling, don’t you think?

In summary:

• Yahoo Web Analytics does not compete with Google Analytics because they are fundamentally designed to serve different audiences;
• Even if Google Analytics expands segmentation functionality, these applications are structurally differen;
• Provided the investment banking-types are wrong about Yahoo’s ability to execute, I believe that YWA will eventually emerge as a direct competitor in RFPs with SiteCatalyst, WebTrends Web Analytics, Coremetrics 2009, Nedstat, etc.;
• If Yahoo! figures out how to scale raw data storage and ultimately gives away access to Rubix, the competitive set expands to Omniture Discover, WebTrends Visitor Intelligence, Coremetrics Explore, Unica’s Affinium NetInsight, etc.;

Again, congratulations to Dennis, the team at Yahoo Web Analytics, and the folks at Yahoo who made the acquistion on getting a branded product out the door so quickly and opening the door to partners, developers, and Yahoo Store owners. Given all of the other news at Yahoo! and in the market in general this is no small feat.