This chart shows the incremental contribution - on a percentage basis - of each Twitterer who participated during eMetrics. Note that I have removed myself ("Omomyid") from the data as I was the host and my behavior could be considered to skew the data.

As you can see, Bob Page was the top TwIt with 25.6% (53) of all Tweets - way to go Bob!

There’s quite a large gap between Bob and the second rated TwIt - June Dershewitz who contributed 11.1% (23) of all Tweets. June was followed closely by Marshall Sponder at 10.1% (21).

There’s another small break in contribution and we get to Dave Rohrer and Eric T. Peterson who contributed 8.7 and 7.7% respectively.

Next, we have Vannesa Fox and Dean Burris adding 5.3% and 4.8%.

Finally, we have Rene Dechamps and Gradiva Couzin chipping in another 3.9% and 3.4% of Tweets and that gets us to 80.7% of all Tweets being driven by 9 individuals (36% of active #eMetrics twitterers.)

Here’s another take on the same data … basically just a chart of the raw counts. In this case it’s a little easier to see how more active Bob was than everyone else and the relative groups that were discussed above.

In addition a more striking grouping is visible in this chart:

1. Uber-Twitterers - From Bob Page to Eric T. Peterson, this group is responsible for 131 tweets covering 63.3% of all tweets. This group averaged 26 tweets per person, 17.9 per day and almost 3.3 tweets per person per day.

2. Engaged Twitterers - from Vanessa Fox to Jim Sterne, this group tweeted 43 times and contibuted 20.8% of the tweets. This group averaged 8.6 tweets per person 5.4 tweets per day and 1.1 per day

3. Casual Twitterers - this group, from Laura Forrest to Ian Thomas had 19 total tweets in 8 days. They averaged 3.8 per person, 2.4 tweets per day and 0.5 tweets per person per day. Casual Twitterers contributed 9.2% of tweets.

4. Sometime Twitterers - from u_m to Phil Sheard this group had a total of 8 tweets which works out to 2 per person and 1 per day. They contributed 3.9% to the twitter-stream.

5. One-Tweet Wonders - this is the largest group with 6 members each had just one tweet to #emetrics (2.9% of total) in the 8 days between May 1 and May 8, 2008.

So what’s all this telling us? Well, I’m not sure beyond the fact that there were discreet and obvious levels of engagement in the back channel.

I haven’t done a qualitative assessment of the tweets themselves - sure would to love to see that. But my general sense is that this backchannel was used more for status and social communication (e.g. ‘I’m at the lobby bar’) than as an idea space like I saw at Media Re:Public.

John Peltier (See Comments) gives us this Zipf test chart on the distribution of tweets:

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I’ve been on Twitter for quite a while but never found much value beyond the amusement and entertainment until I went to Media Re:Public where I and a bunch of others were tweeting tidbits from the sessions. Turned out to be a great and fun way to get a sense of all that was happening.

There are lots of tools that you can use to keep track of Twitter but my current favorite is Twemes.com - you can see their widget at the right with the emetrics tweme (Twitter-meme). Mostly because it’s using the same idea that I had back in November ‘07 - although I can’t take credit for the idea it is still cool.

So, IF you are going to be at eMetrics in San Francisco next week AND you’re on Twitter (if you’re not - why not?) then use #emetrics whenever you tweet about the event and you can keep track of it (live even) at twemes.com/emetrics or grab the RSS feed for your reader, whatever you want.

We can share ideas/thoughts/opinions of the event that way (the discussion can get pretty lively) and those not fortunate enough to be at Emetrics can read about what’s going on…

June Dershewitz saw my Tweet and has on-boarded the idea.

Also joining in so far are:

• Bob Page
• Jim Sterne (!)
• Julien Coquet
• René Dechamps

So what about it? Will you play the Tweme game too? Leave a comment or tweet me with your thoughts!

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Essentially, one group - to a varying degree - are challenging Twitter’s utility to the marketing organization and others are defending said usefulness.

Jim Novo seems to be the most vocal of the former group and while his points are well taken I think that his POV is somewhat skewed. To wit:

Thanks for responding. I’m not saying Word of Mouth isn’t important, we get a ton of it for the Lab Store, and it’s everywhere - Twitter, YouTube, Facebook, all of it. And, I’m happy to say, it’s very positive, because we take really good care of our customers, and they don’t hesitate one moment to contact Service if they have any issues.

Jim goes on to say,

So I guess my question is this: why in the world would a company create a relationship where customers “seek support or “service” from peers, whom they trust, rather than from the company”?

That’s insane, in my mind.

And

We love all the social commentary about the Lab Store but we don’t “do anything” about it, because it just is what it is, it’s a result of smart Marketing and great Service. This kind of chatter has (hopefully) always gone on about great companies. The only difference now is there exists a public, crunchable record of it.

In a perfect world, yes the customer service logs are going to have all the information you need and you can act on them instantaneously. The thing that gets me about Jim’s comments is that his company apparently enjoys the enviable position of being loved by most, if not all, its customers. Apparently, he can afford not to be involved in this channel - instead he can sit back and enjoy it. So why, indeed, track what’s going on out there and use it to your advantage? Why engage at all?

Beyond Jim’s colored perception (and kudos to Jim for having that luxury) most companies aren’t in the same position with their customers and I’m sure that most companies don’t go out and try to create a negative relationship with their customers. None the less, customer distrust is out there and while the customer is on the phone with Customer Service, they are also spreading the word … and increasingly doing it on Twitter, at least that’s where the influencers seem to be. Gone are the days when one disabused customer is telling 20 friends about her bad experience, now she’s sharing it with thousands or millions of people at a highly accelerated pace.

Remember "Dell Hell"? These kind of customer service nightmares are now playing out on Twitter and savvy companies are there trying to listen, engage and remedy. Two incidents recently with @davewiner and @techcrunch (Michael Arrington) stand as evidence and @comcastcares certainly seems to be having a mostly positive impact on perception as well as customer satisfaction.

I’m not sure that Twitter is usable as a quantitative tool yet but certainly the qualitative impact (positive or negative) shouldn’t be ignored. Arrington mentions Tweetscan as an easy way to keep track of buzz …

So, Jim, to summarize

• You may have a very rare or even unique POV based on your reputation among your customers
• Influentials are on Twitter and are tweeting their experience with your customer service team as it happens, so which do you pick - the call logs or twitter?
• Twitter is relatively opaque to J-I-T quantitative analysis but the qualitative impact of what is happening there shouldn’t be ignored
• In light of the examples above (just how many people listen to what Arrington says?) companies can’t afford to ignore Twitter or other social media channels, don’t believe me? Ask @jowyang (Jeremiah Owyang, Sr. Analyst - Social Computing at Forrester Research)

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Obviously these behemoths see value in web analytics but not enough to make it a stand alone business. Instead, it increasingly appears that these ad networks think that it’s important to offer analytics as part of the ad suite in that it either draws in business, makes switching to them easier or makes it harder for advertisers to leave - if your spend AND your analytics are tied up in one ad network it will be harder to make the switch to another.

I’d love to see the folks at Jupiter or Forrester weigh in on this but it seems to me that consolidation is making the web analytics market weak and open to extinction as a stand alone. Either the current trend will continue and web analytics will be subsumed by the advertising market or the BI players will resurge and take over the remaining pieces of the WA providers.

On second thought, it will be both. Ad Networks will offer free, entry to mid-level analytics capability across the spectrum of the market (Individuals –> SMB –> Enterprise) while the BI players will integrate the remaining "Enterprise" level web analytics services into their suites in order to offer comprehensive channel analytics and advanced segmentation and data mining capabilities. Watch out folks, there are sharks in the water.

IMHO

Photo Credit: B. Stabler via a creative commons license

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According to my email, I signed up on March 30, 2008 - 14 days ago. At the time, I was unable to configure a site because although I could register for the service, setting up a site required an invitation - which I didn’t have and there were no instructions for getting one. The next day, the invitation was made ‘optional’ so I was able to add this site. However, adding the site just sent me into a queue and I received the message that I would hear back regarding site approval within 7 days - this was 13 days ago.

Two or three days ago (don’t remember which since it was a form on woopra.com and I didn’t receive even an automated recognition of the submission) I sent a support request via the woopra website asking for a status on the site approval. Nope, haven’t heard a word.

I was just cruising the forums over at woopra and there’s a whole topic dedicated to the approval timeline. According to CEO John Pozadzides, Woopra is too busy with other things like a site redesign, bug fixes and infrastructure scaling to take care of approvals - or customer service apparently.

I’m a web analyst and I like to evaluate web analytics packages when I can, I’ve had as many as six running on this site concurrently (don’t try that at home - it’s like going down the rabbit hole not to mention the impact to load times) seeing how things work and blogging about them from time to time.

Of course, with Woopra so far behind the customer service curve I’m just peeved enough to write a review with the information I have at hand.

Woopra had set my expectation for one week, in one week after sign up I was to know the status of my approval. Seven days came and went and there has been no communication. No resetting of my expectations no “Woops! We’re sorry” - not a peep.

So, it would seem that the folks at Woopra weren’t prepared for their launch and are managing poorly. Instead of focusing - at least a little - on managing mine, and others’ expectations as well as other aspects of customer service they are busy launching a redesign a couple of weeks after their launch.

How would I rate Woopra so far?

• Technology: UNK
• Core Reporting: UNK
• Segmentation: UNK
• Campaign Analysis: UNK
• Intra-Page Event Analysis: UNK
• ECommerce Analysis: UNK
• Multimedia Analysis: UNK
• Data Visualization & Exploration: UNK
• Customer Service: Non Existent

I also checked their official blog and there’s no discussion of the approval process or problems nor is it discussed in the FAQ so it would seem that the only place to talk about it is in the forum since support requests seem to be in an endless queue.

I found one of the co-founders on Twitter and there’s no discussion there about how the flood of sign-ups has derailed their customer service. I wonder what @jowyang would say about their apparent lack of social media strategy and management?

I guess my point is this: Even if you (or Woopra) think of yourselves as a technology company, at the end of the day people use the technology and you need to spend at least the same amount of time on us, your customers (or potential customers), as you do on your technology and service and I’m not feeling that at the moment.

Anyone in on the private beta beforehand that would like to tell us about the service?

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Beyond the cuteness of the little wiener dog chasing the ball, check out the awesome action on the tennis-ball-throwing robot. It knows when a ball is in place, draws the shot and fires. The dog ain’t bad either. He knows how to get the ball in ‘just so’ and will even take it out if it’s not right (notice that the robot resets as soon as the ball is removed). Maybe it’s just me cuz I have dogs, but this little robot solves its challenge beautifully.

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o, it’s no secret that I’m a number and visualization geek. I mean you have been here before right?

Well, I also happen to have a 1st (British!) Edition translation of Homer’s Odyssey by T.E. Shaw . It’s just the most prized of the 4 or so translations I have (not to mention the Odyssey in its original ancient Greek). So, I’m a history geek too (Shhh, don’t tell anyone).

To my delight, I found this combination of visualization and Greek mythology. It’s the genaeology of the Greek Gods in an interactive Network Diagram. Ok, I think it’s a network diagram, but the folks at Spicynodes say it’s a "sophisticated radial mapping technology" - which doesn’t seem to match what I know so maybe it’s a hybrid of some kind or I’m just ignorant.

Here’s a screen grab of the starting point…

 It’s definitely fun to explore the Gods’ family tree. There are some quibbles that I could raise - more like constructive criticisms.

I wish that the descriptions at the bottom of the map were highlighted a little more - even if only briefly. I’m not a fan of the navigation wheel that appears on the central node when you roll over it so I’d rather have the bottom navigation be a little more visually important.

Even though it probably has little data value, it’d be a lot more fun if, when you searched for a God (or Goddess), the visualization ‘zoomed’ through the tree to your selection a la Google Earth. Frankly with a little thought into the speed of the zoom and some appropriate pausing, you could probably do a fairly decent job of showing a God’s direct line of descent.

Ok, on the mythology side … Greek mythology is complex and most Gods have at least one genesis story…it’s hard to show that in the visualization so the authors rightly include tidbits of that complexity in the descriptions. BUT, it bothers me that for Aphrodite they list Ouranos (The Sky) as her father. This is technically true as she sprang from the sea foam created when the -uh- remains of his castration were cast out over the sea, but ummm, Zeus did the work so shouldn’t he get at least half credit? (Nitpicky - I know, I know).

I also think that it would be great if the Web Exhibit folks would provide links to additional reading/details on each God/Goddess and ancient Greece in general for folks who stumble upon this (literally) and want to learn more. Hey, I started out on Bulfinch’s Mythology waaaaay back in the day.

What do you think? Is this a good visualization? A good use of visualization tools? What do you love or hate about it? What would you change?

Both images (the screenshot and the Temple of Zeus) are used with permission under creative commons licenses:

Attribution-Noncommercial-No Derivative Works 3.0 Unported - Web Exhibit

Attribution-Noncommercial 2.0 Generic - Feuillu

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I am inviting Jeff to write his own discourse on how to create sparklines with the Google API, so Jeff, please email me (my email is at the bottom of the right-hand nav) with your description of how to create the sparklines.

First, let’s cover some basics of the API.

The API is pretty simple, it’s just a URL with a bunch of query parameters attached to define the chart and its elements. It can also be a bit annoying when you’re encoding the data sets and their associated information. My guess would be that to really get the power out of the API you would want some sort of programmatic interface to it as building the chart request ‘by hand’ can be laborious.

So, components that are used in these examples:

• Base API URL: http://chart.apis.google.com/chart?
• Required Elements
  • Chart Type Parameter: cht - Allowable Chart Types
  • Chart Size: chs - Chart Size in pixels [w]x[h] (chs=250×250)
  • Chart Data: chd - Chart data encoding methods (simple, text, extended)
• Optional Elements Used
• Chart Title: chtt - Text Title for the Chart
  • Chart Title Text Size: chts - Title font size and color
  • Bar Chart Height: chbh - Bar width
  • Chart Colors: chco - data series colors
  • Chart Background Fill: chf - Chart fill options

For me, let’s start with the Bullet Chart. The stumbling blocks here are that

1. The Google Chart API does not support combination charts, or at least not a bar chart / scatter plot combo, which is how I create Bullet Charts in Excel.
2. The API does not seem to support single data point properties. In other words, I can set the color and width properties for the stack (e.g. series) but not for data points in the stack.

If you remember the Excel example of the Bullet chart, you will recall that we have 3 data series (top, middle, bottom) each with 4 data points to create the basic visualization of the Bullet chart. We then combine into that chart a scatter plot to create the target line. Well this API doesn’t support coloring for a single data point (which is required in the Excel solution) so what does Google offer as a replacement? Well, with the background fill, we can go a linear stripe that will take up some percentage of the chart space - ok, I think I can work with that:

But first things first. Let’s define the chart type:

http://chart.apis.google.com/chart?cht=bhs

• cht=bhs tells Google that we are working with a horizontal bar chart

Next, let’s set the chart size

http://chart.apis.google.com/chart?cht=bhs&chs=250×40

• Remember, chs wants [width]x[height] in pixels and it’s required

While we’re at it, lets go ahead and set the bar width (or height if you prefer)

http://chart.apis.google.com/chart?cht=bhs&chs=250×40&chbh=10,25

• chbh lets us define that bar width and optionally the spacing between bars. In this example the gap is set to 25 to make sure that the chart fill area shows up around the bar itself.

Ok, for the last of the easy bits, let’s go ahead and set the Chart title

http://chart.apis.google.com/chart?cht=bhs&chs=250×40&chbh=10,25&chtt=Homepage+Retention+Rate:+90%

• Note the plus (+) symbols in the Chart Title text, this tells the API to use a blank space when creating the title

On to the data. As noted above, there are 3 options for encoding data - simple, text, and extended. I haven’t really figured out why you would use simple because it’s basically a substitution scheme that feels more annoying than anything. However, in this example we are using text encoding because it allows us to use regular numbers with up to 1/10th precision.

http://chart.apis.google.com/chart?cht=bhs&chs=250×40&chbh=10,25&chtt=Homepage+Retention+Rate:+90%&chd=t:90.0

• when adding the chart data, you must first tell chd how you are encoding the data (chd=t) and then supply the data itself (:90.0)

The above gives us a basic bar chart:

Now we need to add the elements that will make this look like a Bullet chart and we’re going to get it all done with chart fill!

http://chart.apis.google.com/chart?cht=bhs&chs=250×40&chbh=10,25&chtt=Homepage+Retention+Rate:+90%&chd=t:90.0&chf=c,ls,0,000000,0.50,cccccc,0.25,000000,0.005,efefef,0.245

chf (chart fill) takes the following arguments:

• fill area: background (bg) or chart area (c), in the Bullet chart, we use the chart fill method
• fill type: solid (s), linear gradient (lg), and linear stripes (ls)
• angle: angle of the stripe between 0 (horizontal) and 90 (vertical)
• stripe color and width pairs: color hex value and length expressed as a percentage

If you look at the URL snippet above in bold, you will see that we have defined

• the background element as "chart fill" (c)
• the fill type as "linear stripe" (ls)
• the "angle" as zero
• The first section is black and extends to 25% of the length
• The second fill section is the same as the first
• the third section is also 25% but is a dark gray
• the fourth section, only 1/2 of 1 percent in width is black - It’s a trick, this is the target line!
• The last section is 24 & 1/2 percent of the length and is a very light gray

That’s it, now we have a functioning bullet chart

I sure wish that I could remove the axes lines, and add data labels to the bar and target line, but oh well.

Ok, I need to take a break as this is quite a long post. In part 2, we will walk through the pie chart solution (which is not that great),

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"Reporting Is Evil"

You might as well say Seeing is evil.

Seeing, after all, is just your eyes reporting received electromagnetic stimuli to your brain.

I can understand the sentiment behind it - I really can. It comes from a frustration with organizations and people who think web analytics is nothing more than regurgitation of data. A frustration with people and organizations that don’t "get it" and can’t "grok it". The frustration comes from web analysts within those organizations (I’ve felt it, believe me), from consultants trying to help companies get to the next level and vendors trying to sell their wares.

The problem is that reporting is NOT evil. It is vital to the web analytics process.

Analysis, web analysis, is a process - or at least it should be.

Analyses, like any process, have outcomes. The outcomes might be changes to the website, changes to advertising creative, changes in SEM strategies, changes to the web analytics implementation itself and many more that I’m not thinking of at the moment. One of the over-arching deliverables of a process is communicating its results. If the results of the web analytics process are not communicated, then no outcomes are possible. How can recommended changes to the website be made if they aren’t communicated and substantiated with an analysis of the data?

Yep, that’s my way of saying that reporting is an expected outcome of the analytic process. A process that doesn’t communicate its results is a failed process. Thus, if we excise reporting from web analytics because it is evil, we are left with a process that can give us no insight because there is no way to extract information from it. What is the point of going through the process at that point? We might as well use ‘Pin the Tail on the Donkey’ in all its blindfolded glory to make a decisions.

There are many definitions of reporting, but in this context I think that there are two that are most important:

1. Reporting is a required outcome of the analytics process
2. Reporting is a communication tool

The frustration that leads people, Eric included, into thinking and saying that reporting is evil derives from organizations treating reporting as the whole analytics process.

So, if you are spending time, money and resources on web analytics and all you are doing is reporting the data, then you probably feel like you’re not getting nearly enough value out of your investment.

Heck, without reporting there is no feedback loop in analytics and then your just running one blind test after another - throwing spaghetti at the wall as it were - until something sticks.

Reporting without analysis is just a regurgitation of facts. Analysis without reporting is impossible because then there is no mechanism for creating the feedback loop within the process.

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photo credit: bigeoino, creative commons license

Hey, I’ll be at XChange next week, leading a huddle on developing reports. The focus will be Excel because

• it’s what I’m most familiar with
• all things considered, it’s pretty easy to use - even for a n00b
• it’s widely deployed in most organizations so it doesn’t require an IT project to deploy and most business users are familiar with it

The huddle will hopefully be a discussion of best practices for developing sustainable web analytics reports - I really don’t want to talk at people for 2 hours, I want opinions, experiences, tips and tricks and discussions that will make us all better at report development. As the huddle leader I will come armed with questions and opinions that will serve to facilitate the discussion. It will be my job to get the huddle going, keep it on task and make sure we have a positive environment for discussion. It will be your job to bring your brains and experience. If we do our job well we should be able to come up with some substantive wisdom that everyone can use - not just us.

Interested? Today is your last day to get your huddle preferences into the folks at SEMPhonic.

Other huddles that I am interested in? (I know I won’t be able to attend them all - alas)

• Understanding Consumer Attitudes on the Web by Joseph Carrabis
• Deploying measurement systems across the globally distributed enterprise by Judah Phillips
• Advanced Visitor Segmentation by Matt Belkin
• Customer and Web Behavioral Integration by Matt Jacobs
• Measuring Return on Engagement by Terry Cohen
• Optimizing Main and Secondary Navigation by my colleague Olivier Sylvestre
• Persuasion Architecture & Functionalism by John Q (FutureNow!) and Gary Angel (SEMPhonic)
• And, of course, I am looking forward to Eric’s Keynote.

The full agenda is here.

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