Web Analytics Demystified

Archive for 'Web Analytics 2.0'

The Most Important Post on Web Analytics You’ll Ever Read

When John Lovett joined Aurelie and I here at Web Analytics Demystified earlier this month an awful lot of people said, “Hey, nice job getting such nice guy on board,” “We love John, he’s great,” and “Man, what a great addition to your team!” Clearly John has the respect of the industry, but one thing that remained an open question in some people’s minds was “how will John make the transition from the ivory tower an analyst sits in to the ground floor where consultants actually do work?”

I admit, I wondered that too in a way, having made a slightly different transition myself years ago. It’s not easy to come away from a situation where you provide advice but are tasked with, honestly, doing very little real work. During my own tenure at JupiterResearch years ago I ensured my own connection to practical web analytics by writing my second and third books. But John had been an analyst for nearly 10 years … and so wondering how he’d hit the ground was a reasonable question.

Wonder no more.

While John has already contributed greatly to the businesses bottom line and helped out with one of our largest new retail clients, he absolutely floored me this morning when he published his post Defining a Web Analytics Strategy: A Manifesto. I asked him to elaborate on some comments he made at Emetrics where he essentially poo-pooed the use of so called “Web Analytics Maturity Models”, describing the almost religious zeal some people seem to have when talking about models and declaring himself as a “Model Atheist.”

Having written the original Web Analytics Maturity Model back in 2005, I have had first-hand experience with their failure to produce anything more than a generalized awareness that most companies simply don’t “get” web analytics, something that we more or less all know already. But honestly I was surprised when John took this position on the subject because, well, in my experience those that don’t do, teach, and models are a classic teaching tool.

I had assumed that as an analyst John was a teacher, not a do-er like I have been for years now in my capacity as a practice leader, consultant, and web analyst. Man was I wrong …

John’s “Manifesto” is perhaps the most lucid yet succinct explanation I have ever read detailing the steps required to make web analytics work for your business (as opposed to the other way around.) I almost asked him to edit the post for fear that he was opening our kimono too much, but if Social Media has taught us anything it has taught us that transparency is king. The fact that he managed to encapsulate what others have been trying to explain with long-winded speeches, tangential arguments, and downright rude behavior is a huge plus.

Some of you may read John’s manifesto and think “Gee, this seems to point to the need for outside consultants” which is a fair criticism. But before you react consider two things:

  1. Consultants (like us) have a tendency to, you know, recommend consulting. Everyone’s perspective arises from their own personal biases, regardless of how many times they declare the contrary. We are consultants, consultants who want to feed their children. Forgive us our bias and we will forgive you yours …
  2. Consultants in the Enterprise are like death and taxes, we are more or less inevitable. Often times an outside perspective is exactly what the business needs to actually start to act upon the message that otherwise great employees have been stating for years. Other times the business simply stops listening to their employees and won’t make a move until McKinsey, Bain, or Demystified come in and charge big money for insights that were already there. Either way, ours is the second (or is it third) oldest profession and it must be for a reason …

I would challenge you, dear reader, to spend some time reading John’s post and considering what he has to say. Think about how you could apply his ten insights to your business regardless of whether you turn to consultants for advice or not. Listen to your business partners needs, put away your models and roll up your sleeves, transcend mediocrity, establish your own waterfall and embrace change!

When I said “web analytics is hard” I meant it, I really, really did. But I wasn’t trying to box anyone in or establish myself as some kind of amazingly wonderful “guru”, I was simply telling you all the truth based on my dozen years of experience in the sector. Yes, getting started can be easy; yes, making Google Analytics do stuff can be easy; and yes, you can do an awful lot in an hour a day if you simply apply yourself to the task … but the problem is that within any business of size, complexity, or nuance — which is to say all businesses everywhere — the act of getting from raw data to valuable business insights that you can repeatedly take action upon is apparently so freaking difficult that almost nobody does it.

How is that “easy?”

You all know I love a good debate so if you disagree with my comments here please let me know. If, however, you have something to add to John’s manifesto, I would encourage you to comment on his blog post directly.

Happy Holidays, everyone.

Measuring success in Twitter: Influence vs. Participation

I was reading a post recently outlining a somewhat incomplete attempt to measure something called “Influence” as a measure of success in Twitter. Being a champion for complicated and easily misunderstood metrics based on cognitive and behavioral psychology I was immediately drawn to the article but walked away unsatisfied … that is, until I found Twinfluence.

Twinfluence is this nifty little Twitter tool that lets you explore a Twitterer’s “influence” based on their reach (size of their network and second-level network), velocity, social capital, and centralization (see the explanation page at Twinfluence for the details behind each.) For example, here are some of the people I follow in Twitter analyzed by Twinfluence rank:

  • Rank #19: Jeremiah Owyang (jowyang) from Forrester Research
  • Rank #660: Bryan Eisenberg (thegrok) from Future Now, Inc.
  • Rank #2,893: Marshall Sponder (webmetricsguru) from Monster.com
  • Rank #3,577: Avinash Kaushik (avinashkaushik) from Google Analytics
  • Rank #6,124: Anil Batra (anilbatra) from ZeroDash1
  • Rank #7,195: Aaron Gray (agray) from WebTrends
  • Rank #7,591: Jim Sterne (jimsterne) from Emetrics
  • Rank #11,209: Omniture (omniture) from, yep, Omniture
  • Rank #11,786: Dennis Mortensen (dennismortensen) from Yahoo! Web Analytics
  • Rank #11,940: Nick Arnett (nick_arnett) a social media blogger

Whee, what fun! I could Twinfluence my friends and folks I follow all night and day if only client work, my family, and copious powdery snow didn’t get in the way. In case you were interested I have a rank of #5,754 based on my nearly 700 followers who are followed by over 375,000 other people and a very resilient social network.

However, after a little while I started thinking that measuring someone’s “influence” in Twitter was the wrong way to think about success in social media in general. Especially since people who have been dubbed “influential” and successful in the blogosphere have a tendency to think about their popularity in somewhat ridiculous ways … say perhaps stating publicly that they’re going to charge to re-tweet content because they want to buy expensive stuff?

Anyway, when I went down this path I immediately thought “Hey, the two things I spend the most time on in Twitter is trying to find great people to follow and trying to share interesting ideas.” To find great people I use Tweetdeck and to a lesser extent MrTweet to find folks who are having a conversation I’m interested in. To share interesting ideas I limit the majority of my updates to the sharing of links on web analytics related topics.

These combined efforts have helped me find and share ideas with hundreds of folks in Twitter interested in web analytics. So I started thinking “So perhaps the true measure of success in Twitter is being as good a listener as you are a source of information!” Being a balanced participant in your efforts, not just a “social media rock star” who spends all their time talking at people, not to them …

Of course this line of thinking let me to Dave Donaldson’s Twitter Follower-Friend Ratio (or the Twitter Ratio for short.) The Twitter Ratio is dead simple: the number of followers you have divided by the number of people you follow — the perfect Twitter key performance indicator! Dave even provides benchmarks against which we can be measured:

  • A ratio of less than 1.0 indicates that you are seeking knowledge (and Twitter Friends), but not getting much Twitter Love in return.
  • A ratio of around 1.0 means you are respected among your peers. Either that or you follow your Mom and she follows you.
  • A ratio of 2.0 or above shows that you are a popular person and people want to hear what you have to say. You might be a thought leader in your community.
  • A ratio 10 or higher indicates that you’re either a Rock Star in your field or you are an elitist and you cannot be bothered by Twitter’s mindless chatter. You like to hear yourself talk. Luckily others like to hear you talk, too. You may be an ass.

(The emphasis on that last sentence is mine … I laughed out loud when I read that!)

I think Dave’s Twitter Ratio of 10 or higher is the same thing as Perry Belcher’s “Twitter Snob” (funny YouTube video if you have 5 minutes.)  Perry comments that if your Twitter ratio is super high you may not be participating in “social media” but rather “solo media” — perfect!  Perry’s point is why are you even in social media if you don’t have time to listen to the conversation?

If I apply the Twitter Ratio to all of the fine folks I analyzed still ranked using their Twinfluence score here is what we get:

  • Jeremiah Owyang earns a score of 2.95 indicating that Jeremiah “may be a popular person” and “people want to hear what [Jeremiah] has to say” plus he “may be a thought leader in [his] community.” Sounds pretty much perfect to me, but I like Jeremiah.
  • Bryan Eisenberg earns a score of 1.04 indicating that Bryan is “respected among [his] peers” (or that he follows his Mom and she follows him, but with 1,951 followers we can assume the former is the best explanation)
  • Marshall Sponder earns a score of 2.30 which is pretty similar to Jeremiah’s score against his 851 followers.
  • Avinash Kaushik earns a score of 105.5 indicating that Avinash is “either a Rock Star in [his] field or an elitist [who] cannot be bothered by Twitter’s mindless chatter” who “likes to hear [himself] talk” but “luckily others like to hear [him] talk too.”
  • Anil Batra earns a score of 1.27 putting Anil in the same category with Bryan above although with only 266 followers his reach is somewhat lower than Bryan.
  • Aaron Gray earns a score of 1.49 pushing Aaron more towards Jeremiah Owyang than Bryan Eisenberg, at least on Dave’s scale.
  • Jim Sterne earns a score of 17.48 which is in the same “Rock Star” range as Avinash (although an order of magnitude less rock-starry  than Google’s own analytics evangelist)
  • Omniture earns a score of 1.26 indicating respect among the company’s 247 followers
  • Dennis Mortensen earns a score of 13.85 showing that Dennis, like Jim and Avniash, is a true web analytics rock star!
  • Nick Arnett earns a score of 0.58 which indicates that Nick is trying but alas, “not getting much Twitter love in return.”

My own score is 3.13 against 697 followers which I’m pretty happy about (especially the part about not “being an ass!”) Incidentally Perry Belcher’s Twitter Ratio is 0.98 … about as balanced as it gets!  If you have 30 seconds you can go to Dave’s site and calculate your own Twitter Ratio.

What do you think?

Is “influence” the best measure of success in social media? Or should we pay closer attention to something like the Twitter Ratio as a measure of our likelihood to actively participate in the larger conversation? It’s not hard to imagine the Twitter Ratio combined with a measure of tenure or update velocity or even something like influence to come up with a system to help us better discover which members of Twitter are providing real and substantial value to the community.

I welcome your thoughts, comments, suggestions, and perhaps more selfishly, recommendations for great and interesting people to follow and tools to help with the discovery process.

Free white paper on the Web Site Optimization Ecosystem

I’m happy to say that my full-length white paper on the Web Site Optimization Ecosystem is now available from the fine folks at ForeSee Results (registration required for download.) I’ve been talking about the Ecosystem as a component of Web Analytics 2.0 for quite some time now and I believe this white paper does a good job of outlining:

  • The relationship between purely quantitative web analytics systems and more qualitative inputs such as those available via Voice of Customer (VOC) and Customer Experience Management (CEM) systems.
  • The necessity for all three measurement systems to create a truly robust visitor analysis environment.
  • The relationship between these measurement technologies and the “action” systems designed to support multivariate testing, behavioral targeting, and ultimately personalization.

Lee, Larry, and the entire team at ForeSee were great to work with on this document and I think some of the customer examples I discuss in the white paper are testament to the great work that companies are doing when combining web analytic and VOC data.

I hope you’ll take the time to register with ForeSee and read my work.

Free white paper on measuring multimedia on the Internet

This morning the fine folks at Nedstat in Holland published a white paper that Michiel Berger and I co-wrote titled Measuring Multimedia Content in a Web 2.0 World.  This free white paper explores the emerging direct measurement model for multimedia content by examining several common business cases for deploying video and provides a new set of definitions and key performance indicators (KPIs) designed to help companies effectively track their investment in video based content.

The timing is somewhat ironic because Judah has been writing a fair amount about Video Analytics over in his blog — I guess great minds think alike!

While video measurement has been around for awhile, the new social media certainly increases the complexity associated with determining the efficacy of video from a business perspective.  The folks at Nedstat are committed to helping their customers resolve these issues, and are generously making our white paper available without registration requirements.

You can read the press release about the paper’s availability or download your own copy right away.

Please attend my webinar on Web Analytics 2.0 and the Web Site Optimization Ecosystem

Thanks to Tealeaf I’m excited to be able to present a free webinar on December 11th titled “Who, What, Where, When, and Why: Understanding Visitor Interactions on the Internet.” I’ll be presenting my thoughts on Web Analytics 2.0 and discussing the Web Site Optimization Ecosystem fundamental to helping companies effectively measure and manage visitor and customer experiences in a Web 2.0 world. Plus, everyone who registers will get copy of a whitepaper I recently published sponsored by Tealeaf titled Customer Experience Management and Web Analytics: From KPIs to Customer Transactions.

When: December 11th at 9 AM Pacific / Noon Eastern
Register at: The Tealeaf web site

If you’ve ever wondered about Tealeaf and how their technology is best integrated with your existing web analytics practice I’d encourage you to attend this free seminar.

 
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