Archive for 'My Books'

If you follow me on Twitter (@erictpeterson) you are likely already annoyingly aware that I rushed right out last week and bought Apple’s new iPad. I got the device for a few reasons but fundamentally it was because I’m a technology geek–always have been really–and despite knowing the iPad will only get better over time I was happy to shell out $500 to see what the future of computing and all media would look like.

Yeah, I see the iPad as the future of computing and all media. Bold, sure, but hear me out … and I promise I’ll make this relevant to web analytics, eventually.

I believe that all that the “average user” of any technology really wants is a simple solution to whatever problem they may have at the time. At a high level people look towards their operating system to simplify access to the multitude of applications and documents they use; at a lower level we want our applications to simplify whatever process we’re undertaking.

Proof points for my belief are everywhere, ranging from the adoption of speed dial on phones (simplifies calling your friends and family), power seats in cars (simplifies getting comfortable when you switch drivers), and even into web analytics where a substantial growth driver behind Google Analytics has been the profound simplicity with which important tasks such as custom report creation and segmentation are accomplished.

The iPad, and to some extent the iPhone and it’s clones, absolutely crushes simplicity in a way that is simultaneously brilliant and powerful. Want to read a book? Touch the iBooks application, touch the book you want, and start reading. Want to send an email? Touch the Mail app, touch the new icon, and start writing. Want to play a game or send an SMS or Tweet something? It all works exactly the same way … tap, swipe, smile.

Sure, the iPad is a little heavier than is optimal, and yeah it shows fingerprints and costs a lot of money and isn’t open source and … blah, blah, blah, blah. The complainers are gonna complain no matter what–you’re Apple or your not in this world I guess. But the complainers I think fail to grasp the opportunity the iPad creates:

• The iPad takes mobile computing to an entirely new level. With iPad you have a 1.5 lb device that will let you read, write, watch, and generally stay connected from just about anywhere for up to 10 hours between charging. What computer or phone does that? None that I know of, and so iPad gives us a simple answer to “I need to work but I’m away from the office.”
• The iPad enforces usability of applications, and this is a very good thing. The complainers complain that Apple asserts too much control over app design via their App Store acceptance processes. Apparently these folks haven’t used enough crappy software in their lifetimes and are hungry for more. Apple’s model and their application design toolkit gives us a simple answer to “I wish this software was easier to use.”
• The iPad changes media consumption forever. Despite the Flash-issue, one I suspect will become a non-issue very quickly thanks to the adoption of HTML5, the iPad is the most amazing media consumption device ever created. It is a portable, high-definition TV, it is a near-complete movie library, it provides access to hundreds of thousands of books, and it allows you to surf the Internet in a way that can only be described as “delightful”. By definition the iPad gives us a simple answer to “I wish I had a way to keep my books, my movies, my newspapers, my TV shows, … all of my media, in a single place that could be accessed anytime from anywhere.”
• The iPad changes education forever. I’m making a bet that by the time my first grade daughter hits middle school a significant number of children will carry iPads to school, not expensive, heavy, and immediately out-dated textbooks. Think about this for a second: interactive textbooks that can be updated as easily as a web site, think about young people’s media consumption model today, and think for just a second about why Apple would be motivated to provide “significant educational discounts” for the device. The iPad in schools gives us a simple answer to “How can we provide a common platform for learning that any student or teacher can immediately master and reflects our rapidly changing world?”

Think that last piece isn’t important? Have a look at the image at the right, sent to me by @VABeachKevin (thanks man!) where he has already translated all three of my books into the ePub format and placed them on his iBooks bookshelf! This collection gives any web analyst with the iPad instant access to hundreds of pages of web analytics insight, anywhere, anytime. How cool is that?

(And heck, these aren’t even Jim, Avinash, or Bryan’s books … I bet Kevin’s converting those as we speak!)

I suspect you cannot appreciate this until you have one in your hands but the iPad has or soon will remove the necessity to purchase printed books, newspapers, and magazines. More importantly it gives the holder the ability to work efficiently from nearly any location around the world–all you need is a Wifi connection today and later this month that will be augmented with a 3G option.

Yeah, I’m an Apple fanboy, and yeah, I’m lucky to be able to drop $500 on technology without giving it much thought, but wait and see … I bet the adoption curve on the iPad will very much mirror the iPhone which is essentially ubiquitous these days. And just wait until someone develops a full-featured web analytics data viewer that takes advantage of all the pinching, swiping, dragging, and zoom UI capabilities of the iPad, that will simply be awesome! Imagine:

• Scrolling along through time by simply swiping left or right
• Zooming in on data by tapping or dragging across several dates
• Adding metrics and dimensions by dragging them onto the existing graph or table
• Changing from graph to table by simply rotating the device

Total “Minority Report” for web analytics … and I bet we see this within nine months time. In fact, if you’re a Apple developer looking for an awesome project … call me! I’d love to help guide a team developing next-generation web analytics interfaces on tablet computers.

Why This Matters to Web Analytics Professionals

I said I would try and make this relevant to web analytics practitioners so here I go. The iPad matters to measurement folks for exactly the reason I outlined back in September, 2007 when I first wrote about mobile’s impact on digital measurement. Web Analytics 3.0, a term I coined at the time and one I still use, is essentially the addition of a completely new dimension for analysis: user location.

In a digitally ubiquitous world–again one I described in 2007 that has more or less come to pass (although the prediction was kind of like predicting gridlock in Washington or rain in Oregon in April)–where a visitor is accessing information from becomes increasingly important and adds potentially significant context to any analysis we conduct. Location coupled with the device they’re using will likely have a profound impact on their likelihood to transact or otherwise use your site.

For example, a visitor accessing your site from home will likely have different needs and goals than one in their car, in an airport, in a coffeeshop, or in one of your competitors stores. In a world where an increasing number of visits are “out of home/out of office” visits conducted using mobile devices our collective approach towards analysis needs to change, perhaps dramatically.

To be fair, this is not something you need to solve and resolve today. While our ability to discern and differentiate mobile visits is getting better all the time, our overall analytical capabilities for mobile including the ability to tie mobile, fixed web, and offline visitors together is still unfortunately complicated. On top of that, while applications are increasingly able to pass over geographic information, most web browsers are not, and so our ability to gather large quantities of this data are still limited …

… at least for the time being.

For now I stand by what I said back in 2007–digital ubiquity and location-awareness changes everything. Back then the devices and platforms were just an idea; now we have the iPhone and it’s clones, the iPad is about to usher in a new era of mobile computing, Google and Apple are both behind mobile advertising, and the full scope of our analytical challenges are just beginning to emerge. If  you’re struggling with how to measure your mobile investment and thinking about how that strategy needs to evolve please consider giving us a call.

What do you think? Do you have an iPad or do you refuse to purchase one? Why or why not? Have you already started to struggle measuring mobile devices or do you have it all worked out? Is this all as exciting to you as it is to me? As always I welcome your thoughts and comments.

The blogger Avinash Kaushik recently won an award for his post that largely echoed the content of my first book, Web Analytics Demystified. While I have never heard of the award, I am happy for Mr. Kaushik and excited because his repeated mention of my book’s title is driving incremental sales. Thanks Avinash!While I’m happy for Avinash, I have to wonder about his repeated insistence that “web analytics is easy.” I wrote as much in a comment I posted to his blog. The comment has not yet appeared (not sure why, maybe Avinash is on vacation) but I’m interested in your reaction to my position so I figured “hey, I have a blog …” and have published the comment below.

Basically I think that web analytics is hard — not easy or necessarily complex — but I think that this is very good news! “Hard” is something that all of us can overcome with determination and effort, just like the New York Giants did this past Sunday … all we have to do is recognize the level of effort and determination that is required and set expectations accordingly.

The verbatim content of the (missing) comment follows:

Avinash,

Congratulations on your award. I’ve never heard of the award but I don’t work nearly has hard on SEM/SEO as you do. Regardless I’m sure winning this award is quite an important accomplishment for you.

I also wanted to thank you. As the author of “Web Analytics Demystified” — the classic work you say your post pays homage to — it was interesting to hear your take on the subject. More interesting was how your post positively impacted sales of the book — direct sales were up nearly 40% from the month previous!

Perhaps your post reminded people that some of us have been around “demystifying” web analytics for a long time.

Either way, despite some people’s complaints that you were inconsiderate in your attempt to game my brand and copyright, I can assure you that I do appreciate your willingness to continue to bring awareness to my work, both as an author and as a consultant. And I sincerely hope you didn’t mind my tongue-in-cheek title for my AMA presentation …

Still, I wanted to ask you one question: Do you think the Giant’s thought that winning the Super Bowl was complex? Or do you think they thought it was hard?

I ask because you seem hung-up on my assertion that “web analytics is hard”, going out of your way to try and convince people that it is “easy but complex, not hard” and that somehow complex is preferred.

And while I’m not sure why you’re so violently opposed to my assertion, I do disagree with you — web analytics is hard, and that is fantastically good news! Web analytics is hard just like an underdog with a young quarterback winning the Super Bowl is hard. Nothing good is easy, but anyone, anywhere can do something difficult simply by being dedicated to the end product.

• Sacking Tom Brady is hard (hell, very hard) but the Giants defense did it again and again and again
• Converting on third down is hard, but Eli Manning and his receivers did it when it counted the most

There is nothing particularly complex about football, perhaps save contract negotiations, and there is nothing overly-complex about web analytics. In my experience the complexity that does come up in web analytics usually comes from “over-promise, under-deliver” and end-user needs for basic tools like segmentation and data integration that are lacking in some of the most popular applications, not from the practice of web analytics itself.

• Web analytics is hard, but anyone with enough motivation can overcome this obstacle and, in your own words, create amazing, magnificent, and wonderful success!
• Web analytics is hard, but simply by recognizing this and moving beyond the “web analytics is easy” hyperbole companies are able to create the right expectation about the effort required to be successful.
• Web analytics is hard, and that is excellent, excellent news. Because if web analytics were impossible there would be no need for Google Analytics or any of the other great applications available today, but if web analytics was easy, most of us would be massively under-performing.
• Web analytics is hard, but just like the Giants and every other Cinderella team in the history of sports, hard can be overcome through sheer determination, effort, and a well-formed plan for success: often the result is greatness.

I hope you’ll print this comment, and I know my thoughts will do nothing to dissuade you from your “web analytics is easy” mantra, but I had some time (ironically waiting to fly to New York where I hope to catch a Giant ticker-tape parade this week) and wanted to comment.

Again, congrats on the prestigious award! I’m sure that Stephan Spencer and Tamar Weinberg were quite bummed to have been nominated against you — I know I would be!

Sincerely,

…

Some have accused me of “over-messaging” on this point and pointing out the obvious. Perhaps, but as long as I keep seeing the relieved look on my client’s and audience’s faces when I tell this simple truth, and as long as people continue to come up to me and thank me for clarifying expectations about their use of measurement technology, I’m going to stay on message. “Web analytics is hard” seems to match well with people’s experience, and more importantly, nobody appears too perturbed about this statement (except for perhaps Mr. Kaushik and his business partners.)

What do you think? Is web analytics easy? Is it complex? Is it hard? Does it matter? Are you perturbed by my assertion? If so, why? What am I missing?! I’d love to receive your feedback …

[ I'm really happy to have my first "guest post" from blogger Robbin Steif from Lunametrics. Robbin really liked my "gradual building of context" post from awhile back and she and I have been discussing a related metric that she thinks builds nicely on my visitor engagement metric. Without further ado, Robbin Steif ... ]

On the one hand, I thought that Eric’s recent post, The Gradual Building of Context, was just awesome. Although every site has to define visitor engagement for itself, every site is still capable of pulling together similar numbers (which is why I loved it.)

On the other hand, I disagreed with Eric’s final conclusion, “I need to reach out folks like Matt, Marshall, and Clint and see if there is some way I can get them to more passionately advocate for my books in their weblogs. Given that their visitors are more highly engaged than the “average visitor’, I have to believe their is an opportunity to sell more books.”

I took one look at the numbers in the last chart and thought, well, that doesn’t make sense. Sure, Matt’s visitors (or Clint’s or Marshall’s) are somewhat more engaged than the average visitor, but their “start the purchase cycle” numbers are pitiful. If Eric were to put effort into this, the place to put effort in is where both those metrics are strong.

Eric was good enough to send me the spreadsheet, and I pushed the numbers. (Well ok, technically he and I pushed the numbers at the same time over the phone …) On the phone, he called it “Robbin’s Metric” and I left it that way. It is the product of his Visitor Engagement and Percent Buy Path Sessions:

[ Ugh! Yes, I know that image is hard to read! I will correct ASAP!!! ]

By multiplying the two metrics and then ranking all the referring blogs by that metric, you see where Eric should put in extra effort. I agree witrh the first conclusion that Eric already came to in his blog, i.e. that he needs to work out some kind of deal with Anil. However, the two blogs where he should put time/effort would be Justin Cutroni’s and ROI Revolution’s. Interestingly, they are both Google Analytic blogs, so there is a decent chance that the reader is newer at analytics and probably could really benefit from Eric’s books. I didn’t highlight Steve Jackson’s blog, Xavier’s or Aurelie’s because they are already converting well (if there is such thing as converting well.)

Finaly thoughts: An engaged visitor to a site that is also content rich, like Eric’s, doesn’t necessarily make a good customer. In fact, Clint did a survey on his blog and saw that many of his visitors already own many, if not all, of Eric’s books. When visitors go to the beginning of the checkout, we can actually see interest in the purchase, as well as interest in the content — and as direct marketers know, you should always pursue the customer who already has a propensity to buy.

[ Thanks to Robbin for taking the time to take visitor engagement to the next level! What do you think? Is Robbin on the right track? Did I miss the mark? As always, your comments are greatly appreciated! ]

I got an email last night from Eric Enge who writes for Search Engine Watch. A conversation about web analytics that we had last month was recently posted. Eric asked me a variety of questions about Visual Sciences, making decisions based on data, uniquely identified users, content groups, some of the challenges associated with page tagging, and Avinash Kaushik’s 90/10 rule (which I disagree with due to the rule’s impracticality …)

If you have the time and inclination, give the interview a read, and thanks to Eric Enge for interviewing me.

A few weeks back, Gary Angel from SEMphonic published an oddly-titled post called “Why 100% Conversion is a Very Bad Thing” in which he calls into question the whole notion that a key performance indicator (KPI) is only good if a change in the indicator suggests a specific action that can be taken. Gary calls this kind of thinking “the myth of actionability” and says:

“The myth of actionability is conventional wisdom in web analytics – and it suggests that you shouldn’t report on anything unless changes in the measured value can be directly addressed by specific actions. In other words, if you can’t answer the question “What would I do if the value changed up/down?” then you shouldn’t report on the measure.This criteria is designed to eliminate lots of useless data from report sets and insure that what is in report sets has substantive value.

Unfortunately, I believe the criteria of actionability is unsound in almost every way: being both wrong-headed about the purpose of reporting and impossible to actually satisfy in the real-world.”

Obviously Gary is not one to pull punches. Unsound, wrong-headed, impossible … yowch!

Gary calls the myth of actionability “conventional wisdom” and I absolutely agree with him. Everywhere you go, when people are working out key performance indicators and building dashboards, the basis for inclusion or exclusion is usually “is there some action that a change in this metric will encourage us to take?”

Where does this kind of thinking arise? Well, let’s look at page 10 of The Big Book of Key Performance Indicators by Eric T. Peterson. In the section titled “What is a a Key Performance Indicator?” under the subsection on “Action”, in 2006 I explicitly stated:

“Key performance indicators should either drive action or provide a warm, comforting feeling to the reader; they should never be met with a blank stare. Ask yourself “If this number improves by 10 percent who should I congratulate?” and “If this number declines by 10 percent who should I scream at?” If you don’t have a good answer for both questions, likely the metric is interesting but not a key performance indicator.There is enough data in the world already. What most people need is data that helps them make decisions. If you’re only providing raw data, you’re part of the problem. If you’re providing clearly actionable data, you’re part of the solution. If you discover you’re already doing the latter (being part of the solution), give yourself a hug.”

Hmmm, it seems like I am one of the sources of “the myth of actionability” Gary is railing against. But it gets worse; while I was at JupiterResearch I published and presented a number of times on the subject of key performance indicators, and every time I talked about the subject, I stated unequivocally that the “core” of a good key performance indicator was it’s ability to drive action.

Remember, Gary said “Unsound, wrong-headed, impossible …”

Now, I don’t feel the need to defend myself, not because I disagree with Gary, but rather because I think Gary (and perhaps other folks) have taken the interpretation of “needs to drive action” to an unreasonable extreme. Let’s quickly have a look at the history of Eric T. Peterson’s guidance on key performance indicators:

• In 2004 in my first book Web Analytics Demystified, I wrote in Chapter 15: Bringing it All Together Using Key Performance Indicators that “the most common complaint about Web analytics data and the applications that provide said data is that there is simply “too much information”; too many graphs, too many charts, too many options, too many variables—too much for the average user to understand and make use of.“
• In 2005, in my second book, Web Site Measurement Hacks, I wrote in Hack #94: Use Key Performance Indicators that “the best KPIs are those that, when people look at them and realize that they’ve gone down from week to week, make people freak out and call meetings.” I also said, relevant to Gary’s complaint regarding the establishment of which indicators to use, “if you’re thinking about a number but cannot think of any action you would take if that number absolutely tanks, set that number aside.“
• In 2006, in my third book, The Big Book of Key Performance Indicators, I wrote “key performance indicators should either drive action or provide a warm, comforting feeling to the reader; they should never be met with a blank stare. Ask yourself “If this number improves by 10 percent who should I congratulate?” and “If this number declines by 10 percent who should I scream at?” If you don’t have a good answer for both questions, likely the metric is interesting but not a key performance indicator.“

If I’m wrong, at least I’m consistent huh?

When I first started pushing the idea that indicators needed to be tied to some type of reasonable action, my statements were a direct response to the dominant paradigm at the time: that all the information you needed to run your online business was contained in the hundreds of reports all web analytics applications generate, all you need to do is find the right data and take the appropriate action.

The problem I saw with this was, well, almost nobody was being successful with this strategy. Not only were most companies hamstrung and suffering from data overload leading to analysis paralysis, senior managers were asking for relevant data from the web analytics systems but not getting particularly satisfying responses from the people running the systems. Relatively boring metrics like “page views” and “visits” were being pushed up the food-chain, but except in rare cases, an increasing number of page views and visits were only loosely tied to increasing business success.

And so I proposed an Occam’s Razor for web analytics reporting, one that mandated that companies actually carefully consider the metrics bound for widespread distribution, and choose those metrics based on their ability to generate some action.

I never said, and I’m not sure anyone really says, the “actions” that would be taken were as granular and spuriously precise as “if this metric declines, reduce your PPC spending by 10% per 3% point decline observed.” Web analytics just doesn’t work that way folks, and here I agree with Gary when he writes:

No single measurement can ever suggest an action – cannot, in fact, even be interpreted directionally as either good or bad. Only in the context of a complete view of the business system (and the knowledge that all other things are equal or heading in some specific direction) can a judgement be made about the meaning of single measure. I think this make it clear that no one measure can ever really be “actionable” when taken in isolation. And if no one measure is actionable, then surely the criteria of actionability is fruitless.”

So let me clarify my position, as I am perhaps the high priest of the “cult of actionability”:

1. At design time, key performance indicators should be included or excluded from a hierarchical reporting strategy as outlined in The Big Book of Key Performance Indicators based on the likelihood that the indicator will spur some type of action in the organization when the indicator unexpectedly changes.
2. The action the organization would take, when unexpected change occurs, is never precise. The action is nearly always “conduct additional analysis” at which time the indicator’s definition provides at least the nominal basis for the starting point of the analysis.

At the end of the day, my view on key performance indicators is that they are intended to promote the visibility of web analytics throughout the organization, especially to the upper echelons where it is increasingly unlikely that traditional web analytics reports will be given the attention they deserve.

By creating a reasonable set of metrics and indicators, derived directly from the site’s business objectives and supporting click-stream activities, and then delivering said metrics throughout the organization with serious thought to definition, presentation, and potential for action, companies have been shown to significantly improve the level of attention given to web analytics data.

All of this helps to directly combat Gary’s observation that he too is “often disappointed in the report sets [SEMphonic] generate[s].” At the end of the day, regardless of which side of the fence you’re on, I believe we all agree that the central goal of web analytics is to help the business make better decisions. We do this by continually refining the web analytics business process and striving to better educate decision makers about the actions they can take to improve the web site. We repeat as necessary and hopefully go to bed happy.

Anyway, I’m a huge fan of Gary Angel so I hope we can continue this debate. What do you think? Am I crazy? Is Gary crazy? Or, like so much in our industry, is the reality something between the lines?