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Eric T. Peterson has been working in web analytics for over ten years and has built up an incredibly rich body of knowledge about the subject, knowledge Mr. Peterson works to share every week here in his Web Analytics Demystified weblog. Whether you're new to the subject or the most experienced practitioner, you should join the thousands of people around the globe already subscribing to Peterson's blog and start reading today.

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New data on the state of web analytics in 2009

Those of you who were unable to attend the webcast I did with Coremetrics and the Direct Marketing Association in December titled “Create Your Web Analytics 2009 Action Plan” are in luck — the nice folks at the DMA recorded this web analytics event and it is freely available for your listening pleasure.

Click Here to Watch the Webcast!

Also, we conducted a poll on the call asking about planned 2009 investment in technology and human resources for web analytics, in part because of the amazing response to my post about Web Analyics being recession proof?  For the 251 responses we got, here is what we heard:

Regarding investment in technology and tools:

  • 36 percent said they planned to spend more in 2009 than they did in 2008
  • 50 percent said they would be spending about the same in 2009 as they did in 2008
  • Only 14 percent said  they would be spending less in 2009 than they did in 2008

Regarding staffing and resources for web analytics projects:

  • 26 percent said they would be increasing staffing levels in 2009 compared to 2008
  • 70 percent said staffing levels would stay about the same in 2009 as they were in 2008
  • Only 4 percent said they would be decreasing staffing levels in 2009 compared to 2009 (phew!)

Finally, regarding web analytics in general in their organization:

  • 47 percent said that senior management considers web analytics a priority investment
  • 29 percent said that senior management considers web analytics a discretionary investment
  • 24 percent said that senior management had poor visibility into their web analytics efforts

Now I’m a little suspicious of these numbers, especially the 47 percent saying that senior management considers web analytics a priority investment which sounds high to me by about half.  Keep in mind that there is clearly bias in this sample since respondents were DMA members with an expressed interest in web analytics …

If you believe these numbers it certainly sounds like 2009 will be somewhat stagnant in the industry compared to the last few years of rocket-like growth.  And while reading that 47 percent of senior managers “get” the value of web analytics, the reality is that 53 percent don’t which is still bad news no matter how you spin it.

What do you think?

Do you believe that senior managers in nearly half the companies out there consider web analytics a priority investment? Does your management team consider web analytics a priority investment? Or are you still trying to explain to the bosses what web analytics is capable of doing for your organization? I’d love to hear your thoughts, and feel free to use a pseudonym and “anon@anon.com” as an email address to post without your boss knowing how you really feel ;-)

Thanks again to everyone who attended the webcast and participated in this informal poll.

Our Vendor Discovery Tool is Back Online

I have to admit I was a little surprised at how many people howled at me when I took the Vendor Discovery Tool offline a few weeks back, but I wanted you all to know it is back online. If you had the tool bookmarked you’ll have to update your bookmark and you may want to get in the habit of accessing it via the Research section of this site.

Why is that you ask? Funny story.

While the Vendor Discovery Tool is designed to be used by individuals researching the deployment of web analytics tools across the Internet, thanks to analytics I was able to identify a few folks who were abusing the script by running it via a what very much appears to be a bot.  Unfortunately the bot appears to have been accepting cookies and executing some tracking JavaScript but not all of it (e.g., I do not observe the same pattern in my Google Analytics or IndexTools deployments!)

Not naming any names, but here is the data data I’d been working from in Omniture Discover on Premise:

Gotta love analytics, huh?

I have since blocked the offending IP address range and continue to monitor the situation.  In the meantime, if you need web analytics vendor distribution data and don’t have the patience to run the script manually, please contact me directly since I’m easily able to do custom dumps of the data and typically don’t charge for the service.

Anyway, thanks to everyone who wrote me asking when the VDC would be back online and again, I’m super sorry for the inconvienience!

Web Analytics is Recession Proof?

For the past few weeks I have been thinking about the economy and trying to reconcile two seemingly contradictory observations:

  1. The economy sucks, and it doesn’t seem likely to improve anytime very soon
  2. The web analytics sector is reportedly recession-proof and, in fact, predicted to grow in 2009

While I hardly need to provide any proof of the first observation, evidence for the latter has been emerging from a variety of voices in our community for the past few months.  Case in point:

In the E-consultancy report, the organization’s head of research Linus Gregoriadis was quoted as saying: “The profile of Web analytics continues to grow as it becomes more integral to business decision-making and organisational strategy. The credit crunch is putting the spotlight on analytics as organisations work harder to understand where they are getting the best return on investment and where real value is being added.”

Recently, Josh James, the CEO of Omniture said something similar during the Q&A portion of the company’s Q3 earnings call in response to a question about whether businesses saw web analytics as discretionary:

“Every dollar that a marketer has, I think everyone has in every organization is under pressure right now and certainly marketing spend is where CFOs like to look and see if they can cut. But, what we’ve seen with our customers is their online channels are the ones that are performing the best. Their online channels are the ones that are giving the most direct impact within that quarter that spend is also taking place.

In terms of the way that they think about Omniture, even if they cut let’s say 10% of their marketing spend, they’re going to use us to a) identify the 10% they’re going to cut and b) use us to optimize the other 90% to try to get back up to the same results as they had with the 100% the year before. These kinds of times actually drive usage of our product.

When things are good it’s a lot easier when you want more sales just to throw more money at the top of funnel and to generate more leads and go through the process. When things get bad people try to focus on of everyone that’s already coming to our store, what can we do to keep them more attracted? What can we do to get them to look at other things? What can we do to get them to read additional articles? All of those behaviors drive uses of our product.”

All of this sounds absolutely spectacular. Except for one thing …

I’m not sure I believe any of it.

I think that we are collectively starting to suffer from the echo chamber effect, essentially reiterating that web analytics will be fine in this lousy economy because, unsurprisingly, we are all making money off of web analytics and we would very much like to continue doing so. The WAA, IQ Workforce, my friend Jim, E-consultancy, Omniture, me … our collective businesses are all more or less explicitly tied to continued investment in the sector. So why wouldn’t we look for data that suggests that the picture continues to be rosy and the future bright?

Why indeed.

In terms of the data presented above, as a former researcher I would offer this assessment: many of these surveys appear to suffer from sample bias. Asking the Yahoo! group, members of the Web Analytics Association, or the audience attending Emetrics about their interest, investment, or organizational focus on web analytics is kind of like asking your average Democrat in Portland, Oregon how they feel about Barack Obama.  The problem is not the audience, the problem is the interpretation: I think it is misleading to extrapolate the responses from a non-random sample of businesses and business people to the larger audience.

This kind of sampling leads to claims like “52% of online marketing managers are currently engaged in A/B or multivariate testing …” Fifty-two percent implies that tens of thousands of online marketing managers are testing. Which sounds great, except that when Offermatica and Optimost were acquired by Omniture and Interwoven they had a few hundred customers between them, and Stephane Hamel’s WASP tool reports that 0.4% (zero point four percent) of the Top 500 online retailers are using easily detected A/B or multivariate testing tools.

Don’t get me wrong, I too have been guilty of sampling biased audiences, although in the past year I have stopped conducting primary research due to both the sampling issue and the plethora of free research that suddenly appeared in the marketplace.

Ultimately I’m suspicious of this optimistic data that we’re seeing, especially in the context of statements like this one made by Mr. James made on the earnings call referenced above about the effect the economy is having on Omniture’s ability to forecast Q4 and 2009:

“Towards the end of September however, it became apparent that the challenging macroeconomic and financial environment may have some impact on our business going forward although it remains difficult to quantify the uncertainties specifically.”

Mr. James and his CFO specifically don’t want to talk about 2009 on the call. Which makes sense to me, since here are some other data points:

  • The economy sucks, and without belaboring the obvious, it appears that this suckiness will stay with us for quite some time;
  • While I don’t question Mr. James assertion that his best customers make excellent use of web analytics, in my personal experience this is not universally true;
  • Some of the largest consumers of web analytics products are starting to struggle;
  • Despite the conventional wisdom that dictates that brilliant analysts are safe when times are tough, I am getting more and more calls from brilliant analysts who are being laid off or being offered severance packages to walk away.

It is this last point coupled with something I learned at Emetrics that has me the most concerned.  In D.C. at Emetrics I heard Liz Miller from the CMO Council say that most CMO’s are a few years away from fully understanding the value of web analytics. If Liz is right, and her credentials are impeccible when it comes to the CMO’s office, then given the anecdotal evidence that continues to come in I wonder if web analytics is slightly more discretionary than we’d like to believe.

Don’t get me wrong, I sincerely hope to be wrong in this assessment. As an author, public speaker, evangelist, consultant, and conference co-producer focusing on web analytics I honestly hope to be able to write a follow-up post in six month saying, “Wow, I was really super-wrong about where the web analytics industry was going …”

But what can you do if I’m more right than not? What if you work in an affected sector or work for a company known for their web analytics acumen that is suddenly faced with bankruptcy or worse? What if the folks you work for who profess a great love for data-driven decision making are really HIPPOs in their heart and when the real bloodletting begins are just as likely to look for savings in areas that can be easily cut (human resources, for example) as opposed to those that would require breaking contracts?

What indeed.

If you’re in any way concerned about the current economy and your personal employment situation, here are five tips that I would offer to help you best prepare for the worst.

Tip #1: Focus on Increasing Profits, Not Minimizing Spend

My friend W. David Rhee just published a great response about the relationship between web analytics, sales, and marketing in a down economy.  To paraphrase Dave, if the bosses begin to panic, you don’t want to be in a situation where you appear to be an expendable marketing cost that can be cut.  It is far better to be focusing your analytical efforts on how the organization can be increasing profits, even if you have to fight to spend more time conducting analysis and less time generating reports.

Essentially you want to take Mr. James statement above to heart and work your butt off to optimize the lower-levels in your conversion funnel, working with what you already have, not what you might be able to attract.  The good news is that the technology supports this analysis; the bad news is that more often than not, the deeper you get in the funnel, the more difficult optimization becomes for a variety of reasons, not limited to the business, IT, and “the way we’ve always done it!”

Be a profit center, be big picture, become truly invaluable.

Tip #2: Don’t Be a Report Monkey

The unfortunate reality about web analytics work is that far too many smart people spend far too much time generating far too many reports that far too people actually read and even fewer actually derive real value from.  Sound familiar?  When I started the conversation about process in web analytics in 2006 at Emetrics, over 80% of the audience said they spent too much time on “reports” and not nearly enough on “analysis” … sadly I’m not confident that things have changed much in the past two years, especially on a percent-of-practitioners basis.

There are any number of great posts about why reporting is over-rated and how the real value in web analytics comes from careful, business-focused analysis of the data, there are still too few companies that have put the hub-and-spoke model into practice and are able to effectively leverage web analytical resources.

My advice to to step-up and find the real value in your data, even if you have to conduct the analysis on your own in the wee hours.  It’s not as if you can just stop generating reports (tempting as that may sound) but if you’re a good analyst, taking the time to figure out where the real opportunities to increase revenue are is the work you want to be doing anyway.  Taking the initiative to make data-powered recommendations and presenting them is a good way to demonstrate your skills and commitment to the business (but don’t stop doing the job you’re being paid to do!)

Analysts conduct analysis and make recommendations. Be an analyst.

Tip #3: Start Watching the Job Boards

Even if you feel pretty good about the situation you’re in you have to admit that the most accurate term to describe the current economy is “dynamic.”  In situations like this the worst thing you can do is be caught off guard and so I would offer that spending a little time surfing the Web Analytics Demystified Web Analytics Job Board (also see the WAA’s version) would be time well spent.

According to the nice folks at SimplyHired the number of job postings looking for “web analytics” experience of some kind continues to increase:


Assuming these postings are all accurate and still open, this is fantastic news since it contradicts my thesis that our sector is at risk.  The only thing that concerns me is that when I add a major market to the search, the trend graph starts to look substantially different. Here is the trend of jobs in SimplyHired for “web analytics” jobs in San Francisco:

Not quite as encouraging, huh? Now I might be using SimplyHired incorrectly but the general trend observed in the Bay Area makes me wonder if job growth in the sector is as strong as the first graph shows. Plus, anecdotal evidence suggests that an increasing number of companies are imposing hiring restrictions and outright freezes, meaning that many of these postings are effectively “inactive.”

By no means am I suggesting that any gainfully employed web analytics practitioner should jump ship in this economy unless you are absolutely confident about the situation you’ll be moving into.  But keeping your eyes, and your options, open makes increasingly good sense in my opinion.

Be smart about your current employment situation.

Tip #4: Think About Your Skill Set

I recently interviewed Corry Prohens from IQ Workforce and asked Corry about requirements for web analysts and what he looks for when trying to place folks. I recommend you read the entire interview, but here is what Corry had to say about what IQ Workforce looks for:

“In general we look for someone that has tool expertise, communication / interpersonal skills (these jobs are increasingly front-office), analysis & presentation skills and some complimentary kicker (testing, SAS, SQL, search marketing, development skills, search marketing skills, etc.) based on what our clients need at the moment.”

I went on to ask Corry about what two criteria he believed would help practitioners land a great job in this economy:

“If I were a web analyst I would learn how to use SAS to manipulate data & models.  I would also try to pick up experience in  testing/optimization.  Having one (or both) of these would open a lot more doors than a straight WA skill set.”

Real analytics experience and a focus on testing and optimization.  Great advice, even if the former is somewhat non-obvious (perhaps that’s why it’s such great advice!)  And while you may not be able to implement testing technology on the job, Google Analytics and Google Web Site Optimizer are free and easily implemented on a personal blog.

Push yourself and expand your skill set. Move ahead of the market.

Tip #5: Network, Network, Network

In my experience one of the most valuable things you can be doing during uncertain times is expanding your network of contacts.  Fortunately the web analytics industry is pretty well set in terms of opportunities to meet other practitioners, both locally and globally.  Here are a few networking opportunities that I highly recommend:

  • Attend or host a Web Analytics Wednesday event.  Web Analytics Wednesday is the world’s only local social networking event for web analytics professionals and it has helped dozens of folks find their next new job.  Take advantage of the many events happening before the end of the year or, if you don’t see an event in your town, contact me directly about getting a chapter started where you live!
  • Join the Web Analytics Demystified group at LinkedIn.  A few years ago I started a LinkedIn group for web analytics professionals.  Now the group has nearly 1,300 members worldwide and is open to anyone interested in getting connected via LinkedIn.
  • Join the Web Analytics Association.  The WAA is the only association we have and is actively working to create great value for their members around the world.  Joining the WAA gets you discounts to great conferences, access to their job board, and plugs you in to an increasingly vibrant community.

At the end of the day, despite the great demand for our skills and long-term opportunity afforded to all of us, a web analytics job is like any other job.  Your professional growth and development is as much a function of the people you know and your relationship to the community as your native analysis skills.

Get to know your peers. Have fun while you do it!

What Do You Think?

This has become a ridiculously long post considering that I could have just said, “I think there is more risk than we realize.  Be prepared.”  Most of us working in the web analytics arena have become quite used to the good times rolling and have every faith that they will continue to roll.  Only now, budgets are shrinking, jobs are being lost, and the general fear is that the President-Elect will create a business climate that is somewhat less friendly than most would like.

Still, my firm belief is that if you’re great at what you do and if you’re working for folks who clearly “get” the web analytics value proposition you have nothing to worry about.  All I would caution is that you not assume the latter is true, again especially in the context of the conversations I have constantly about senior-management not really understanding the art and science of digital measurement and analysis.

So now it’s your turn.  Do you think I’m way off base?  Do you believe the data I was somewhat critical of earlier in this post?  Does your boss “get” web analytics?  Are you optimistic like Mr. James that your company will be able to leverage your investment in Omniture (or whatever) to optimize your marketing spend?  Or are you worried about your job, or worse, have you been laid off?

I normally don’t allow anonymous comments but given the somewhat sensitive nature of this post and the feedback I’d love to hear, as long as the comments are appropriate I’ll approve them.

Visitor Engagement + comScore = Audience Engagement!

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.

Forrester acquires JupiterResearch

I wanted to say congratulations to David Schatsky and the team at JupiterResearch, as well as the fine folks at Forrester Research, on the news of FORR’s acquisition of JupiterResearch announced this morning.  Forrester has acquired a great asset and a great group of analysts, researchers, and operational staff, and it was very encouraging to read David Schatsky’s post on the subject, especially:

“Jupiter’s employees are also going to benefit from the combination with Forrester. Forrester execs have enthusiastically expressed to me their respect for the quality of our staff and are eager for us to become part of the expanded company. Jupiter folks will reap the benefits of being part of a larger organization, with its rich resources, track record of effective execution, and commitment to employee growth and career development.”

Somewhat ironic that FORR has been actively looking for someone to cover web analytics since Megan Burns (who will be at the upcoming X Change conference) has transitioned to cover customer experience more broadly.  John Lovett, in my humble opinion, will make a great Forrester analyst and was almost certainly the best candidate for the job … <grin>not that Mr. Colony should have paid a $23M bonus to his current employer.</grin>

While I am excited for all involved, this combination of companies does raise one specific concern within the web analytics sector: Instead of three independent voices in the community providing an objective assessment of the competitive landscape that can be compared and contrasted over time, now there will be only two, Forrester’s view and Gartner’s view.

Don’t get me wrong, I have a tremendous respect for all involved here — otherwise I would never have advocated for inviting Megan, John, and Bill to keynote the upcoming X Change 2008 conference I’m a partner in.  But I do have some small concern that the market’s view of the vendor landscape will soon be defined by one fewer data points, especially since Gartner has not done a formal Magic Quadrant on the sector recently (although Bill did publish a market note on web analytics on July 3rd that I assume is available to Gartner clients.)

I suppose my fears may be unfounded, but given the unusual (and perhaps unreasonable) amount of weight vendors, consultants, and companies alike seem to put on these constellations, waves, and magic quadrants, the loss of one-third of the available information may have implications that won’t manifest for quite some time.  In the context of the consolidation our industry has gone through in the last 24 months, I think technology buyers are even more likely to look for that “objective” viewpoint and rely on published research.

Wait and see, I guess, but I have a few new questions to ask Megan, John, and Bill in a few weeks at the X Change!

Regardless, I’m excited for the folks at Forrester and JupiterResearch and sincerely hope the acquisition proves fruitful for all involved.

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