Interview: Analytics Tool Getting a Refresh with Crazzy Egg 2.0

A few weeks back I talked about Crazy Egg’s Confetti as a great analytics tool for data visualization and thought it worth some follow up.  Amee over at Crazy Egg came through with the inside scope on Crazy Egg 2.0 as well as some insights on data visualization.  To the left is the new drop down menu – some nice new options.

PMT – How have you seen the need for data visualization change/evolve in recent years?

CE – Because of the vast amount of data out there, it can be hard for companies to comprehend the data. Visualizations that provide an insight about users and more importantly actionable data, make it easier for companies to understand their data.
Similar to what some analytics companies are doing now, I think over the next few years companies are going to concentrate and create more useful visuals and not just pretty ones.

PMT – How do data visualization tools fit with typical analytics platforms like Omniture?  What’s the best way to create synergy between the two?

CE – Well, they help you understand the data in a different way. Some people are visual while others prefer crunching numbers. I think analytics companies are going to have to meet the needs of both type of users.

PMT – What’s new with the upcoming Confetti release?

CE – The best way to create a synergy is through deep integration. This way the user experience is seamless.
Crazy Egg 2.0:
• Completely rewritten from the ground up
• Improved stability, performance, and reliability throughout the whole system
• Reports are always available
• Reports load much quicker
• Improved tracking reliability
• Improved tracking accuracy
• Added many more dimensions of data to Confetti and Overlay, including custom user variables
• Higher-resolution heatmaps
• New snapshot creation UI
• Ability to fine-tune URL matching URLs for snapshots
• Ability to edit running tests
• Improved screenshots (better font rendering)
• Improved error handling and messaging
• Better tools for our users to diagnose potential installation/configuration issues
Coming soon…
• Regular expressions for URL matching rules
• Ability to handle template tracking
• Ability to track login-protected pages
• Export to CSV
• Downloadable Heatmaps
• IP Address blocking (existing 1.0 feature)
• Ability to track custom elements

To brush up on your analytics, pick up a copy of Web Analytics: An Hour a Day

Interview: Patrick Dicaprio of the Fantasy Pros 911

I caught up with sabermatrician Patrick Dicaprio of the Fantasy Pros 911 for this mini interview.  Patrick is a member of SABR‘s Statistical Analysis and Science of Baseball Committees and is a lifelong fantasy player. Patrick is also a practicing attorney, despite a degree from MIT.

PMT – How has the collection and analysis of data changed baseball in recent years?

PD – I don’t think that the methods in which data collection is done have changed much in recent years. Baseball has always been a statistics driven enterprise, and data collection has always been an integral part of that enterprise. But how that data is used and how people can access and distill the data has changed tremendously. And this is not just in the fantasy baseball realm. More and more teams have statistics experts on their staffs, and these experts are slowly getting more of a say in personnel decisions.  We have even seen the emphasis on more accurate statistics start to show up in traditional media such as TV and newspapers. These traditionally staid outlets are now starting to discuss more advanced baseball statistics and that is a huge boon to the analytical and baseball community.

PMT – Can some of these new measurement tools or ideas be transferred to better evaluate other activities?  I’m thinking of things like the job performance of a ‘regular’ person or the effectiveness of business investments?

PD – There is nothing in the use of baseball statistics, and by “statistics” I am now talking about in a mathematical sense and not in a baseball sense, that is any different than in any other business enterprise. The value of contracts and whether a team will profit form an individual player’s contract by comparing money spent to runs generated and marginal wins generated is an idea that cuts across any business investment.  As in any business enterprise or any evaluation, one must identify the proper metrics and analytical numbers and must then analyze them correctly. That process is one that should be universal but is not, and the businesses that do so, especially small “Mom and Pop” businesses undoubtedly have a leg up on their local competition.

PMT – What’s the one piece of data, baseball or otherwise, that you haven’t been able to figure out how to measure that could really be game changing?

PD – For me it is a way to measure defensive contributions of individual players. Guys have tried using regression analysis and the like to do so, but it has not been compelling. There is a synergy that exists between a pitcher and his defense; if a batter hits a hard grounder that the shortstop fields by making a diving catch, how much of that is the shortstop’s skill, how much is the player’s skill and how much is coaching and proper positioning? We have rough guides that are wholly insufficient to answer questions like this, but baseball analysts take the existing metrics as if they are gold, and they are simply not indicative of much. We are still barely at the point where we can verify whether a player is above average or not.

To learn more about the application of statistics in baseball pick up a copy of Moneyball: The Art of Winning an Unfair Game from Amazon.com.

Interview: Dan Kurani of Kurani Interactive

Here’s a mini interview with Dan Kurani, owner of the interactive agency KURANI Interactive.  Over it’s 9 year history the agency boasts clients like Nike, Mannington, and Fagor.  Visit their website at www.kurani.com or call Dan at his Red Bank, NJ location at 732-345-1700 to learn more about their services.

PMT: How do digital mediums differ from traditional branding and advertising programs in terms of measurement and accountability?

DK: Although I can see things changing as consumption and media cross-pollinates and integrates, today, a huge difference.  Whereas, offline primarily derives the underpinnings of analysis from qualitative sample groups (posing as quantitative results), digital “is” quantitative.  The toughest part of digital is ensuring stakeholders stay focused on KPIs instead of getting lost in the sea of data.

PMT: What are some new areas of growth or services you see Kurani Interactive taking on?

DK: Outside of our traditional services (digital marketing communications that includes social, websites, applications, email, search), we are starting to joint venture with select companies.  Basically, we are leveraging our digital expertise to unlock hidden or underachieving core values and managing the extension in a turnkey fashion.

PMT: In 10 years how do you think campaign and site performance measurement will change?

DK: Integrated measurement across all tactics, digital will be behind almost all MarCom.

To learn more about interactive advertising pick up a copy of The Online Advertising Playbook at Amazon.com

Interview: Evan LaPointe of Atlanta Analytics

In the first of a recurring series, here’s a miniview (mini interview) with Evan LaPointe of Atlanta Analytics.  I posed 3 rapid fire questions to Evan to get his take on analytics today.  Be sure to check out Evan’s blog www.atlantaanalytics.com.

PMT:  Since you’ve been “doing stuff” online for 15 years (about as long as I have), what is the most profound change that you’ve seen in the use of data in the digital space?
EL:  I think the most profound change I’ve seen is people FINALLY starting to reject data without context.  Just this week, I’ve been working on a client obsessed with exit rates.  But visitors have to exit somewhere.  Without the context of whether the page provides an appropriate circumstance for exit rates or not, they tell you nothing – and sometimes, dare I say, certain pages with insanely exit rates are GOOD!.  I’m glad to see the days of metrics without context slowly disappearing.

PMT:  What is your favorite KPI and why?  (please elaborate or this will be a really short interview)
EL:  Favorite metric? I hate to do this, but it’s got to be bounce rate.  Why? Because it is the ultimate “content rejection” metric.  When I use bounce rates in the context of inbound traffic sources, and especially keywords driving traffic to this page, it’s usually immediately actionable.  If we’re not offering clear calls to action based on what the user has already said they’re looking for, we’re running the wrong way around the track from the very second the gun is fired.  Making small changes to align the page with what visitors expect can have enormous revenue impacts.

PMT:  What do you think is the hardest thing to measure and analyze that could provide the greatest amount of value, especially if it were easy to track? (I’m fishing around the ‘engagement’ watering hole on this one so please try to come up with something new and totally mind blowing)
EL:  What is the hardest thing to measure that would have the greatest value? Well, you’re clearly shifting material that should be on my blog to your own, but I’m okay with that 🙂

I’d say that answering the “why” questions would provide tremendous value.  If we could have less-intrusive survey [qualitative] data to layer against web analytics [quantitative] data (like 4Q survey, but where we don’t just get polar love/hate participation), not only would it mean great data, but it would more importantly mean fewer arguments in the conference rooms which HAVE to account for millions upon millions of dollars of lost productivity every year before we even consider the performance impact on the site.  This industry is rife with terrible opinions and otherwise very talented executives who are clueless about online behavior, paired with a huge absence of data to help the enlightened to make their case definite.

How we get that data, I haven’t a clue.  Hopefully, everyone will begin trusting analysts’ assessments of why things happen and these arguments will be solved through multivariate testing rather than hours of blabber.  A few sites do surveys well, but participation is always going to be an issue, if I’m being realistic.

If we’re looking at measuring “engagement,” I’d just quit.  The only way to get something simple is to degrade the insight of each of the points that make up engagement.  A great example is Peterson’s effort to create this crazy ass engagement metric.  The formula looked like we were trying to predict the trajectory of the lunar lander, not help a web site.  The truth is that this metric is ultimately useless because we lose sight of the details that make it up – and details are what we’ll act on. Creating a mushed-up metric takes us backwards, in my opinion.  It’s like having a number to assess the performance of your car’s parts.  If that number drops, we are no closer to diagnosing and fixing the problem. We just know that something, somewhere is wrong – which is less helpful than it sounds.

To learn more about analytics pick up the Kindle edition of Web Analytics: An Hour a Day from Amazon.com!