Cool to see Jim’s smile on my web browser. :) I wonder if LinkedIn showed me this because they figured I’d be interested (behavioral targeting) or because the profile mentioned analytics (contextual targeting)?

And it reminds me I should probably update my speaker bio, figure out my travel budget, connect with eBay PR to get on their approved speaker’s list, and all of that…

I’ve joined eBay.

eBay has many fabulous analytical tools already, both commercial and home-grown, for lots of different kinds of analysis. In addition, they are on a road to build out a whole new class of analytic capabilities based on Hadoop. They recently reorganized the data initiatives and groups to form a team that re-focuses the “many standalone tools” mindset to a “platform” for analytics. This holistic vision, and the “central data, distributed analysis” mindset aligns so well with my thinking and interests that I had to make the jump. As much as I love what Yahoo! is doing with analytics, the opportunity at eBay was too compelling to pass up. I mean, come on .. it’s the world’s largest online marketplace!

My discussions with the eBay leadership team told me two important things. First, they are ready to make significant investments in data capabilities to drive the next generation of eBay. Second, the new leadership over the last couple of years is bringing a change to the business, where the company will be much more technology- and innovation-driven than it has been in the past. Many of the leadership hires in the last 18 months are a testament to that. And I like to think I am another proof point.

Having cool technology and a leadership team that understands the value of data is a great start. But the icing on the cake is the level of data and analytics talent within eBay. It is, in a word, staggering. I am truly humbled by the opportunity to work with a group of this caliber.

And now, on a Saturday, I’m off to the ACM Data Mining Camp, hosted at eBay’s north campus…

Lest anyone think this means I’m down on the company — it’s quite the opposite! I’m more positive than ever about Yahoo!, especially the analytics. I am very excited about where the company is going with data. After a short but ill-advised set of changes that de-emphasized a coordinated approach to data and analytics, a new leadership team (read: Carol Bartz) recently reconstituted a central data and analytics group. You may even have heard or read Carol saying we’re looking for acquisition candidates in the analytics space. I’m very glad to see the return of executive leadership that sees the strategic value of data.

I’ve never been one to talk a lot about Yahoo! and I won’t start now, especially the internal goings-on, but there’s new leadership, a new commitment, a new focus, and frankly I’m really glad to see it happening. I am also jazzed about the 2010 and 2011 roadmap for our products, including Yahoo! Web Analytics, our advertising analytics products, and for a lot of internal products you haven’t heard of. Oh, and as I tweeted previously, the YWA team is hiring…

And with that, a chapter closes. Yahoo! has been good to me, and I like to think I’ve been good to Yahoo!. But even the good things don’t always last forever, and after almost five and half years, it’s time for me to say goodbye. I’m going to take a short break, decompress a little, and then gear up for the next thing. But that’s a story for another time.

Yahoo!

Last night I had an urge to participate. The timing couldn’t be better — the deadline was September 15! Not to worry, since I’m already attending the Summit, I don’t need a haiku pass. Unbound from the shackles of winning the contest, here are a few haikus for your consideration.

But first. Knowing Jim, I had this suspicion that he’s thrown in haikus as “easter eggs” in his “serious” writing, probably for years. Boy was I right. I found these, buried in some of his old (old!) articles:

They'll buy. And you will
   have done something positive
for the Internet.

— from The Internet Gift Culture (1996!)

The fact is, if you
   treat people with respect, you
can sell them more stuff.

— from Personalization and Privacy in Perspective (1999)

Variety. Choice.
   Excitement about what's
around the corner.

— from Customer Interface: Easy Doesn’t It (1996)

Smith, this is Sally
   at American Express.
How can I help you?

But what if gumbo
   recipes were exactly
what you had in mind?

— from Customer Interface: Do You Know Me? (1997)

And then my favorite: Mr. Sterne himself embedded in the haiku — quoted in an article by Wanda Loskot:

Jim Sterne: "The biggest
   mistake is going after
too large a segment."

— from What Makes People Click? – Targeting! (2000)

Magnificent! Emboldened and inspired by the ancient texts, I thought I’d try my hand at some original verse. While I don’t claim to have reached the pinnacle of haiku, I discovered that a little wine, a healthy disregard for tradition, and a willingness to expose one’s “creative analytical side” results in lyric such as:

Web analytics
   A great and noble journey
The long quest for truth.

(Tip ‘o the hat to Matt Cutler)

We use statistics
   thus we are never certain
of the snowflake's shape.

(er .. ahem)

The Twitter debate
   analytics or measure?
A freakin' hashtag!

(inspiration: Eric T. Peterson here)

Omniture, Webtrends
   Coremetrics and Unica
Google and Yahoo!

(note if you substitute “Adobe” for “Omniture” it still works! Coincidence?)

And finally, the topical entry.

Gary said it best:
   Adobe buys Omniture
What are they thinking?

(Gary Angel’s blog post)

I still think vertical analytics is bound to happen. Witness Atlanta-based Indie Music, whose service Band Metrics — “Analytics For The Music Industry™”, scored angel financing back in November. More than one press report about the financing used a variant of the phrase “Google Analytics of the music industry.”

Compared with some of the graybeards of Business Intelligence, the Web Analytics “industry” has not yet left adolescence. But I think many of the lessons learned in the greater web analytics field, combined with more powerful machines and a greater “popular culture” around number crunching, are going to lead to analytics for very specialized fields. At a minimum, it might move us away from generic tools that look at the Web to tools that have specific knowledge of a particular business — kinda like a specific solution for scheduling & billing for dentists vs. bringing in Oracle Applications and Accenture. What can be bad about that?

Could this be a new analytics growth opportunity, or perhaps just a land grab? Here’s a thought experiment: check out XXXanalytics.com (where XXX is whatever interesting business you can think of) and see if it’s already taken. I tried a half-dozen while composing this post and I was surprised how many were already claimed…

(Interestingly, XXXanalytics.com itself is not taken, nor is dentistanalytics.com)

I’ve been coming across new sites and new ideas for visualizing data, and thought I’d mention a few.

One of the things I love about the New York Times is their smart visualizations. The interactive graphic A Year of Heavy Losses was a huge hit last fall (even if the data was scary as hell) as the financial meltdown was unfolding. Treemaps can be difficult to understand, but this one nailed it.

Even the Times’ day-to-day infographics can be a pleasure to look at. Did you know that the NYT has a Visualization Lab where you can make your own visualizations? It uses the many eyes technology from IBM.

FlowingData explores many visual aspects of data. If you haven’t seen their visualization of Watching the Growth of Walmart Across America, (which uses the Modest Maps library) I highly recommend it — but the site has a lot more to discover.

Jeff Clark over at Neoformix continues to produce thought-provoking visualizations, many full of beautiful insight, like this contrast of two speeches, and some, like his visualization of Obama’s victory speech, are just plain “hang on the wall” beautiful (politics aside). I spend way too much time at Neoformix. Rather than single out one post, check out his Neoformix Review 2008 and see if you’re not intrigued. Jeff also links to other interesting visualization sites and projects.

Infographics should tell a story. Seeing a map of the US with red and blue states doesn’t really give the full scale of how the election went. Mark Newman, however, does a good job showing how using the geographic area is the wrong way to visualize the data, and coming up with better suggestions.

Tim Showers’ visualization discussions are worth checking out. I particularly liked his post on the challenges of visualizing multi-level data .

The TheStatBot does various dives into data that doesn’t normally get the spotlight, such as what post-processing software gets used on Flickr. Here’s a Twitter Wordle they did of Leo Laporte’s various tweets:

And .. if you like infoclutter (and we all do, sometimes, right?), check out this dashboard!

Finally, if you’ve made it this far: not really a data visualization, but a fascinating time-lapse movie of a four seasons in one 40-second video.

Have you seen other interesting visualization ideas?

This comes from our internal numbers; for “competitive reasons” I removed the legend indicating volume — but you can see the site was much busier than the previous week. Uniques, PVs, and PVs per unique all were way up.

TechCrunch showed some data from Hitwise on market share of visits for Nov 4. It’s a little strange that Yahoo! wasn’t listed in the TechCrunch graph, even though Yahoo! placed first overall. Also interesting that the Drudge Report was so high. Here are the top 10 .. for more, see Media Life Magazine .

I would say generally that baseball statistics are always trying to mislead you, and that it is a constant battle not to be misled by them.

…

We haven’t figured out anything yet. A hundred years from now, we won’t have begun to have the game figured out.

and to who should have a larger role in player evaluations, scouts or stats guys:

Ninety-five percent scouts, five percent stats. [...] the knowledge of who will improve is vastly more important than the knowledge of who is good. Stats can tell you who is good, but they’re almost 100 percent useless when it comes to who will improve.

I’m really jazzed about it. IndexTools is a great group that’s been laser focused on the stuff that customers care about. They have a very practical attitude towards their products. Because they started in 2000, they learned from the pioneers, and built a deep analytics system that really works well. That much was clear as soon as we popped the hood and poked around inside .. unlike a lot of their competition, they didn’t have an old and a new product that they bolted together.

So does this mean we’re going to do “Yahoo! Analytics”, and try to “steal” web sites away from Google Analytics or the commercial web analytics vendors? See, that’s not what this is about. Yahoo! has stated its desire to be a “partner of choice”, and as the new Yahoo! strategy began to sink in, it became clear that the new Yahoo! was going to need to offer a new level of products to its partners. We have many, many thousands of small and medium businesses partnering with us now, and we want to make sure they have the tools they need. We’ve already announced an open strategy where developers can take advantage of Yahoo! products and services; we want to make sure they get the analytics they need too. Yahoo! has so many partners in so many places that can benefit from this technology, it became clear — even obvious — it was now the right thing to do.

Yeah, we still have a team working on analytics solutions for our “owned and operated” world — Yahoo! is too big a customer for IndexTools, or any other commercial vendor for that matter. There’s a world of difference between massive scale for one huge customer, and massive scale for a huge number of small and medium-sized customers. Now we have both.

As for what this means for the web analytics industry, I’ll leave that to the pundits, analysts and fortune tellers.

Here’s some of the combined team after a day of meetings at IndexTools.

(and yes, that’s Dennis at the head of the table, farthest away from the camera.)

Some reactions from around the web:

• Dennis Mortensen
• Eric Peterson
• Rene Dechamps Otamendi
• Julien Coquet
• Michael Wexler
• Ian Thomas
• Anil Batra
• Marshall Sponder
• Lars Johansson
• Jim Sterne
• Chris Hill
• John Lovett

The web analytics is easy / hard discussion among various thought leaders has been interesting but I can’t help but think a little self-serving. I had a long preachy post ready to go but even I was bored by it. Instead, let me offer some observations:

Technology:

• Web data is messy. It doesn’t fit into cubes (think path analysis by segment) for instance. So it requires special handling.
• Web data is noisy. Think robots and cookie deletion.
• Web analytics is nonstandard. Despite the efforts of the IAB, WAA and others, nobody can say “we use the computation standard to determine this” – because there is no computation standard. Count web 2.0 for me…

If you want to chase the rabbit down the hole, you’ll decide that web analytics is hard. if you want to defer these kinds of things to a tool vendor who will sell you turnkey “best practices” then web analytics is easy.

Process:

• In business, speed of deployment is king. Thus it’s easier to look at pre-built reports than create them from scratch.
• Lack of integration with the business goals means lack of actionability. Most analytics is like driving by looking into the glove box – interesting but irrelevant.
• As a result of the first two, there’s an emphasis on quantitative over qualitative analysis — which means there very little “analytics” at all, just metrics trending.
• When you don’t first design your analysis from business goals, you grab as much data as you can, and pick and choose the data that supports your hypothesis — either you’re in report hell, or analysis paralysis. For a very visceral example of this, look at how most people do experimentation.

If you design your analytics to meet your strategy, and staff for it, the implementation is long (and complex, yes) but the resulting analytics are easy. If you want to defer to a tool vendor who will sell you turnkey “best practices” then web analytics is hard.