Adobe is more than Flash. Heck, before Adobe acquired Macromedia it wasn’t anything approaching Flash.

Don’t get me wrong, Flash is important. How much of online video is distributed via Flash? A significant majority I imagine. Flash is also used for interactive web pages and light gaming. Oh, it’s also developing into a desktop connected-application platform via Flex.

Integrating Omniture (or any other measurement technology) into Flash or Flex, what’s the difference? There largely isn’t one. And Flex desktop apps are proliferating. How valuable will it be for those developers/companies to have a solved, stable integration of analytics into those apps? And of course, since Flash serves SO MUCH of the video content online, how will Adobe’s acquisition apply pressure to the standards that are used to measure video?

Adobe has not one, but two development and publishing platforms (Dreamweaver (ok, who still uses Dreamweaver?) and Cold Fusion)

What if some of the components of Insight and/or Test & Target are integrated directly into Cold Fusion?

What about Shockwave/Director for rich gaming experiences?

In-game analytics don’t really exist, not on a large scale anyway. What if Adobe-ture can solve that?

And of course the standards: Photoshop, Illustrator, Acrobat.

Holy Crap! Adobe has an end-to-end services & platform suite for developing connected applications, web-sites etc.

With the addition of Omniture to the fold, Adobe can now add adjunct services to their platform.

• Basic Measurement (Site Catalyst), customized for specific environments
• Data Integration & Data Mining (via Discover, Insight, etc)
• Testing & Targeting via –wait for it- Test & Target

And don’t take “adjunct” the wrong way, we all know that the worst kept secret of online is better analysis and synthesis right? The data and the insight they drive are as important as the products/sites/apps that drive the data.

Once you step past the WTF moment, you start to realize that this may be less of an eBay-Skype thing and might just be more of a Google-Applied Semantics kind of thing. It will take careful execution of a well-thought out integration plan but it could be a very interesting play.

What if Adobe dusts off HBX (or offers a trimmed down version of Site Catalyst) for free to publishers (especially video publishers) in return for aggregated and anonymous video usage data? What if they push something like that through partners like BrightCove that provide video players to publishers?

Again, once you move past the shock and think about a bit, this acquisition might just make more sense than you thought, or at least the possible reasons for it begin to emerge.

What do you think? Why did Adobe do this? Why did Josh et. al. agree to it? Are the reasons above worthwhile? Are there other more important factors? Please leave a comment and let me know!

One last random thought, does this help Adobe in positioning against HTML 5? My understanding is limited but it seems to me that the HTML 5 standard is, in some ways, a direct shot at Flash.

BTW, Gary Angel over at SEMPhonic has a very thoughtful post on this deal

Photo Credit: Graeme Lloyd, University of Bristol

This image, a so-called “super-tree”, shows the relationship of 440 of the 600 known species in the Dinosaur family. It was created as part of a study with the goal of determining the various rates of diversification within the tree. You can read a nice summary of the research at Science Daily. But seriously all the chatter about Social Graphs that use a similarly formatted chart and I have to wonder, who has one as cool as this?
 

One of their first offerings – beyond consulting – is a little service to help you integrate online analytics data into your CRM system. Wait … what? WebToCRM does just what it says – helps you get your web analytics data into your CRM system for a more comprehensive view of your marketing efforts.

It’s interesting (to me) that they should launch WebToCRM so closely on the heels of eMetrics because while I was there I went to dinner with Eric T. Peterson, Judah Phillips and June Dershewitz. At dinner, we discussed (among other things) where web analytics is going. Eric declaimed that the next battlefront in our market is open systems vs. closed systems. Open systems let data come in and go out. Closed systems, on the other hand, are like roach motels – data might get in, but it will never get out!

Essentially what Tealium is doing with WebToCRM is eliminating the need to wait for the platforms (web analytics and CRM) to offer easy, true pass-through of data. WebToCRM is configured for several popular web analytics applications and two CRM platforms with options for ‘other’. As the service grows, I imagine that the preprogrammed options will grow too.

With the free version, you can pass a campaign ID and up to three (3) campaign attributes from your analytics system to your CRM platform.

So how does it work? After going through the WebToCRM configuration process you will receive a JavaScript, in email, that can be deployed across your site in one of your global includes (header, footer, etc). This JavaScript is programmed to "listen" for activated campaign ID and campaign attributes variables encoded on the destination URL. When a potential lead enters your site via a campaign that is properly encoded WebToCRM grabs that data and stores it in a cookie so that when the lead gets to your sign-up form, the campaign information can be passed to the CRM app.

Pretty slick right?

So now you can use online campaign data to inform offline marketing processes. For instance, you can get a ‘whole view’ of the campaign from online acquisition to offline conversion. It becomes a relatively simple matter to judge which online-to-offline track offers the best conversion rate. Or to see that some online campaigns that convert-to-lead really well don’t fulfill the backend promise of conversion.

WebToCRM Vital Info

• Cost: Free!
• Preconfigured Web Analytics Applications:
  • HBX
  • Site Catalyst
  • Google Analytics
  • WebTrends
  • IndexTools
  • Core Metrics
• Preconfigured CRM Applications:
  • SugarCRM
  • SalesForce
• Campaign Variables Tracked: 4 (campaign ID + 3 attributes)
• Implementation: Global JavaScript File
• More Information: User Guide
• Learn More: WebToCRM Information Page
• Get Started: Sign Up Page
• Offered By: Tealium, Inc.

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

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?

"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.

 "I’ll have to check with my manager"

"What will it take to get you to take this baby home with you today?"

<endless waiting designed to make you willing to do anything to leave>

<forms, upon forms, upon forms>

Any of this sounding familiar yet? Why am I bringing this up and making you sweat, cringe and shiver all at the same time?

-glad you asked-

Over on the Lunametrics Blog, Robbin Steif has published part four of her interview with Avinash Kaushik about his book "Web Analytics: An Hour A Day" and at one point she asks

Why do you care so much about the customer experience and discount conversion rate so much? (We can say, p. 340, but you address this elsewhere too) The way that I look at it, there are either other conversions (like applying for a job, or getting help on the website), and the analyst is just forgetting to include those conversions. Or, it’s important that the customer have a good experience so that when he is ready to buy, he will (and it is a long term problem, but it is still about conversion rate.) Or, he will tell other people or write about what a good experience he had, and *they* will come and convert, eventually. So it is still a conversion rate problem. Ultimately, it is always about conversion rate. (Go ahead. Tell me that I’m wrong.)

Avinash goes into a long and informative response detailing why focusing on just conversion rate is a bad idea. For me, it boils down to ‘visitors at your site have all kinds of tasks in mind – other than buying – so optimizing for just one task neglects (or worse) the other visitors.’

However, it got me thinking … well that’s unfair … I had a little flash of an idea and here it is:

"I’ll bet Car Dealerships are massively over optimized for ‘Conversion’"

So, even if you are there to buy, it can be (and often is) a massively uncomfortable experience. If, instead of optimizing for conversion, you optimize the user/consumer experience in effect what you are doing is creating a comfortable and reassuring environment where your visitors can feel confident in doing whatever it is they came there to do.

You don’t want to be the car dealership of the online world do you?

Does anyone have a story about how optimizing for the user (versus a metric like conversion rate) had unanticipated positive results? Please share your story in the comments here.

Hey, I’m equal opportunity – if you have a UX horror story share it here too…

Web Analytics Guru and all-around nice guy, Eric T. Peterson, is doing a webcast – exclusively for Web Analytics Association Members. The webcast is entitled "Web Analytics Is Easy!", can’t wait to find out what that means but more importantly, there will be an extended question and answer session at the end of the webcast! Ever wish that you could have a sit-down with a luminary like Eric to find out what’s what? Well, the cost of membership to the WAA is probably cheaper than getting Eric on a consulting gig or traveling to an Emetrics summit so it might be easier to get your management to defray the cost on your membership than getting the OK for Emetrics. Hey, you do what you can right?

The webcast is next Wednesday, August 29th (yip just nine days away) so hop to it!

Disclaimer: I am a Director on the WAA Board

If you don’t understand the context of your web data then all you can do is report the data – you can’t interpret it correctly.

If we think of web analytics as this overly-simplified equation: people(motivations) + website =  actions(data), as analysts, we are trying to solve for people(motivations).

So if you’re the analyst, you’ve got the data and I am sure you are crazy-familiar with it, but that’s only half of it. Knowing your website(s) – how it operates, what changes are made and when, how changes are made – is the other half. If you don’t understand your website and how it works, how can you properly interpret the data to understand how your audience is reacting to your site? How can you proactively recommend changes or tests on the site if you don’t understand how it works?

photo credit: threed – some rights reserved.

You Can’t

So, if you can, do a tour in web production  – this will give the best chance of understanding the website context.

If you don’t understand the website context, your analysis (if you’re trying to do it) is just a W.A.G.

Is this a Google challange or just being caught up in the current acquisition frenzy?

Auto delete? Since when is this a special feature that only Google can bring to market? All cookies have an expiration date – last time I checked. It’s just that often, they are set with an expiration date so far in the future as to be effectively perpetual. 

The article quotes Peter Fleischer, Google’s global privacy council, as saying (in a statement)

"listening to feedback from our users and from privacy advocates, we’ve concluded that it would be a good thing for privacy to significantly shorten the lifetime of our cookies."

Oh, and there’s this interesting bit from the article, "They will be deleted unless the user returns to a Google site within the two-year period, prompting a re-setting of the file’s lifespan."

Interesting, it’s not a fixed two years, it’s relative to your last visit to Google so every time you visit Google the cookies expiration date will be reset to a new date. When was the last time you went 2 years without visiting a website that you found extremely useful (as most people would say about Google)?

I actually like the idea, from a certain point of view, users who have not visited the site in some amount of time (2 years in this case) could be deemed to have abandoned the site (in a much more considered way than we in web analytics tend to look at it) and therefore Google doesn’t need to keep track of that user’s preferences anymore.

The thing that I find weird is that the BBC – via the title of the article – seems to think that Google is doing something that no one else could or might do.

I wonder what the implications to web analytics would be if the providers implemented a similar function? Would it wreak havoc on the data? Probably not unless the cookie expiration date was set absurdly low (less than 4 weeks or so). What about a new metric – "Lost Visitors" or "Qualified Abandons"?

The basic question is (paraphrasing here) "Are bounces and bounce rates for a blog home page of the same importance as they are for ‘regular’ sites?"

I have a long and poorly written response to the question on Jeremiah’s blog, but I thought I would respond here as well – hopefully a little more cogently (though no less lengthy) – to Beth Kanter’s question.

Let’s start with a definition of bounce rate just so we can all be on the same page .

Bounce Rate (for a web page) = (Single Access Visits / Visits where the web page is the entry point to the site)*100.

Single Access Visit: Any Visit where there was only 1 web page viewed

Visit: A collection of activity on a site from a single browser where there is no period of inactivity greater than 30 minutes

Entry: Where (which web page) the visit started (a visit-start or visit-entry)

For instance, in May 2007 here on this blog at my home page:

Visits with the Home Page as the Entry: 127

Single Access Visits: 110

Bounce Rate: (110/127) *100 = 86.6% (OUCH)

That means that nearly 87% of the visits that started on my blog home page ended  on that page without any other pages being looked at.

But is that really bad on a blog? Well, what are some of the proposed reason why high bounce rates are acceptable on a blog as opposed to another kind of site?

1. A blog home page (or category page) contains a lot of content in it. For instance, WordPress defaults to showing something like the 10 most recent posts on the home page so it isn’t necessary for visitors, especially loyal or repeat visitors who are just interested in my latest post to click beyond the homepage (of course, they don’t have to come to the site at all because they are probably subscribed to my feed).
2. Blogs tend to link outside of themselves (link love) where regular sites try to avoid it so on your blog, you are actually telling people to leave and read something else and those visits aren’t actually a bounce.
3. Traditionally KPIs aren’t important on a blog because they don’t measure ‘attention’ or ‘engagement’ very well. Time Spent on Page is a much more effective measure of your blog homepage’s effectiveness than Bounce Rate.

I haven’t done the segmentation yet, but looking at raw click counts I can see that there were 58 clicks from the blog home page to external resources so let’s assume that each click is equal to one visit and that those clicks/visits don’t count against the bounce rate since I directed my visitors to them. That reduces my single access count to 52 for a bounce rate of 40% – that’s still pretty darn high.

Average Time Spent on this blog’s home page in May was 3 minutes 25 seconds. Not too bad I guess. The problem is that this metric typically (and specifically in my case) excludes visits where the home page was the exit page (including single accesses) so this time spent is just for visitors who went deeper than the home page. I don’t know, and chances are you won’t know either (depending on the analytics tool you use) how much time single access visitors (e.g. ‘bouncers’) spend on that page.

I was going to put together some segments to further illustrate my discussion of point number one, but I’m feeling lazy so just let me highlight some thoughts and tactics.

Even on a blog, the home page is probably the most trafficked page you have, unless you get DIGGED or Slashdotted or something like that. The blog home page (and category pages) are also probably the most search friendly ones you have so new visitors are highly likely to enter your site there than anywhere else. So, when thinking about whether or not Bounce Rate is an important measure for your blog, start by segmenting new vs. returning visitors (yes, even though a reported new visitor might not actually be one) and see how the bounce rate compares for new vs. returning vs. all – is the new visitor bounce rate higher than one or both of the others? Then you have an engagement problem – new visitors are not tuning into your content – the home page has no scent.

Segment out your visitors that were referred to your site by search, what is their home page bounce rate? They were looking for something specific and they thought your blog might have it. If search visitors have a high degree of bounce, there’s a problem. User’s who bounce, especially new ones are not engaging in your discussion.

So, even after I excluded the visits that were taking an action I asked them to (subscribing to a feed or clicking on a link outside my blog) my home page bounce rate is still 40%. Forty Percent (4 out of 10) of visits to my blog home page never look any deeper, they never engage in my conversation! That’s a lot of people who are missing out on a great discussion (IMHO)

So, does bounce rate matter for a blog? Is a blog so special that it can ignore this standard web analytics KPI?

Absolutely NOT. Visitors that bounce off my home page, especially new visitors and search visitors are not engaging with my content even though they came to the site in the first place – which means that they thought they were going to find what they were looking for but didn’t…

The one complexity I see here is the home page content. Depending on how frequently you write new posts, the bounce rate can be highly and quickly divergent (really good on some days and really bad on others) so you will want to tie the bounce rate back to the content that was available on the home page during any given period – a lower bounce rate in period 1 compared to period 2 may indicate that the content from period 1 was ‘better’ and you can learn from it.

You can download it here, the installation for WordPress is relatively simple, installs just like any other plugin. The OWA group also has a wiki, though documentation seems a bit light so far.

I don’t have much of an opinion yet except these two things:

1. Installation (at least on WP) is a snap
2. The Geolocation feature seems to be broken

On the note of the Geolocation, I entered my Google Maps API key but I get errors when trying to view the geolocation reports and the download to Google Earth feature also appears to not work…I’ve posted a couple of questions to the OWA discussion group but haven’t heard back yet.

If anyone has experienced this, or has any idea about what to do to fix it, I’d love to hear from you.

Also, if anyone else out there is running OWA I’d like to hear about your experiences with it.

Update: Google Analytics Team, please don’t do this anymore. I just turned on the ‘compare to past’ feature and noticed that you are doubling up series on the sparklines. This is a big no-no as far as I am concerned because the sparkline with mutliple series on it just ends up looking like a squiggle. The data from the second series actually becomes chart junk!

If your a visual analysis wonk like me you probably couldn’t help but be excited with the new version of Google Analytics and the introduction of Sparklines. To me, it comes across as a major endorsement of sparklines as a business tool.

But, for this implementation to be a useful endorsement of sparklines, they have to show value as a tool and I don’t think the GA implementation is quite there – yet. Remember the new version of GA is in Beta so the team has lots of opportunity to improve.

From the Visitor Summary Report…

In this case, the shaded area is not useful, it’s distracting. The reason for this is relatively simple – it’s shading the area under the curve (plotted line) in the case of a sparkline, the shaded area should code more or different information. I’d really like so see this shaded area represent some UCL and LCL data, for instance the standard deviation (plus or minus) from the mean of all values.

The value currently associated with the sparklines are the total or total average for the period represented when they should be the current (or most recent) value.

I’d like to see some data markers on the chart – current value, high water mark and low water mark. Of course, the markers should be color coded to their value on the right. So, for instance the most current data point marker could be red and the current value would also be in red. The high and low water marks would be different colors and their associated text would be those colors to tie them together.

If that’s as clear as mud, here’s a quick example:

Notice that my example is a bit longer, this is because Tufte recommends shooting for a 45 degree angle on the line slopes (it eases understanding)

1. The gray area represents the ‘normal’ distribution of visitors – the "biorhythm" as Avinash would say and it is the mean +/- 1 Standard Deviation
2. Both the oldest point (starting point) and newest point (end point) are marked in red
3. The watermarks (high and low) are marked in green
4. For each of the data points that are marked (except for the starting point) an associated value is presented to the right and is color coded so that associations between the chart and the values are easily made

Finally, I’d like to see the sparklines be more contextual to the report or dashboard that they are in. For instance, I’m not quite sure why total page views is reported in the Visitor report. Also, is that average page views per visit or page views per visitor? I’d rather see average visits per visitor and average usage days per visitor (daily visitors divided by absolute unique visitors) than some of these other metrics.

What do you think of the Google Analytics sparklines?

I’d really love to start off by talking about the addition of sparklines, but I just can’t because I am too distracted by the big trend chart.

Here’s what that looks like:

Let’s take a quick moment to compare that to a Google Finance chart:

Notice that they are both ‘web 2.0-ey’ and ‘ajaxey’. However, the GA chart seems to have gone a little over the top with the very thick trend line and large diameter data point markers.

It’s worth noting that the Google Finance chart offers multiple ways to traverse (interact) with this data. I can both traverse and zoom (or unzoom) the chart at the bottom as well as zoom the chart from the top-left text links. In the GA chart my only option for interacting with the data is through the pull down menus at the top right (one for date(s) and one for dimension which are kind of kludgey if you ask me – they don’t respond -hhmmm- smoothly and they rearrange the page whereas the controls in the GF charts don’t require the page to be reordered and react both quickly and smoothly.

None of these are my biggest criticism, the simple fact is that the GA chart with the heavy line and large radius markers makes me feel like it’s a kid’s chart, that is a chart designed for a kid.

I find it very odd that the GA Dashboard chart is liquid – that is it stretches to fit the browser width. This changes the horizontal scale of the chart and can either obscure important trend details or create artifacts in the visualization – a fixed width chart that is appropriately scaled would be better.

Maybe it’s just me but I actually feel patronized by the Google Analytics chart like I’m so clueless that I wouldn’t notice the trends or the data points if they weren’t pessimistically obvious. I *think* that I actually like the roll-over data labels because it puts the detailed data into the chart as opposed to how the GF chart updates the information way up in the right hand corner is you hover over the map. But, again the heavy black border just screams ‘MAKE SURE YOU LOOK AT ME AND IF YOU DON’T THEN YOU DON’T KNOW WHAT’S GOING ON HERE!’.

It’s not that I’m totally in love with the GF charts, as noted above I’d really like to see the detail data down next to the chart in a data label and while I theoretically like the idea of marking key news events on the chart, the implementation can get quite messy and distracting. Unfortunately I don’t have a good solution in mind yet but I’d really like to see it cleaned up.

For the GA chart, I’d recommend:

1. Don’t talk down to the user, move towards a more elegant presentation like that of Google Finance
2. Build in interactive controls like the ones used in GF
3. Make the chart fixed-width, in this case liquidity is bad
4. Potentially allow for multiple dimensions to be charted (within reason)

Ok, that’s enough about the dashboard chart, sparklines will have to wait for another day.

By the way, overall I like the redesign of GA – for me it is generally more intuitive to navigate and use.

I’d love to hear what you think…

This will be my second year at Emetrics, but unfortunately I am not speaking this time (or perhaps fortunately for those who remember my session from last year).

But I have to wonder…
Is Eric opening a content mall for web analytics?

But it got me to thinking about Gary Angel’s recent post entitled "Web Analytics Toolkit and Internal Search". Commenting on a Commerce360 blog entry that laments the lack of presentation on how to do the analysis part of web analytics, Gary says,

"So true. And the comment doesn’t just apply to Conferences. It applies to the vast majority of all our blogging as well. In fact, I find that even when most of us are talking how-to analytics that the discussion might be about some charting technique, data visualization or data manipulation. That’s all well and good, but it takes for granted that you know how to actually use that technique to approach an analysis."

Why do these two things go together in my head (besides the random association that happens more than I’d care to admit)?

Well, in the play (spoiler alert for anyone who hasn’t read or seen it), a jury is presented with a set of facts that they must use to determine the guilt or non-guilt of the accused. Each of the panelists, for reasons of their own has arrived at a decision – at least they think so. Eleven them, for a variety of reasons including the most trivial (baseball tickets) to reasoned logic, have decided, at the beginning of the play that the accused is guilty. But there is a lone standout – who is preventing the other eleven from returning to their ‘normal’ lives.

This dissenter (played by Thomas) proceeds to take the other members of the jury through the case, point-by-point, and evidence-by-evidence and questions each one. He pokes holes in everything that was presented by the prosecution and even tears down the public defender. By the end, he has convinced the other eleven that there exists reasonable doubt that the defendant is guilty and it’s twelve votes for not-guilty.

What did he do and what does this have to do with the analysis part of web analytics?

He observed, and prodded, and poked each datum, he ran scenarios in his mind, he found inconsistencies in the logic (as presented during the trial) and the facts. In a word, he analyzed.

It’s interesting to note that eleven jury members all started out with the same decision (guilty) but for a variety of reasons – they didn’t all get to that decision in the same way.

So, why don’t we blog about or teach analysis? Because it’s hard (where have I heard that before). My way of doing analysis is probably different from just about everybody else’s.

My basic approach is to look for patterns and violations of pattern. When I find a pattern or a violation of a preexisting pattern, I have something tangible, something that I can try to explain. My patterns are built out of a lot of things: my familiarity with the data, my familiarity with the website, my familiarity with the market, my familiarity with the data collection tools, my accumulated experience and on and on.

It’s also a function of my training, I studied as an anthropologist in school and my early career was spent doing technical support. Technical Support is essentially analysis of a system in order to identify a root cause and eliminate that cause so that the system can work correctly. That training BTW, provides my primary framework for analysis (at least I think so).

I don’t think the above is particularly teachable – you can read the words above, and believe that’s how I do it, but how much does that help you in learning to do analysis?

One last thought…

Let’s also take a look at the definition of analysis.

According to Dictionary.com, analysis is "the separating of any material or abstract entity into its constituent elements (opposed to synthesis)." Isn’t that interesting? There are of course many more definitions, but this is the first one. It seems to me that analysis in this context is breaking down behavior into it’s constituent pieces – hmmm isn’t that we do in the data collection phase?

Here’s the definition of synthesis: "the combining of the constituent elements of separate material or abstract entities into a single or unified entity (opposed to analysis)." Ok, so they language is fairly opaque, but what it says to me is taking a bunch of discrete elements and putting them together in an understandable and informative way.

…I think I’ll go ask my boss if I can be a web synthesist instead of analyst

Eric is particularly interested in getting responses from folks, like me, who work on consulting teams for web analytics vendors.

I’ve taken the survey and it’s very short and to the point – it won’t take up much of your time.

As an added incentive, Eric will be sending out a copy of the completed results to those who participate and a discount on a couple of his books (if you don’t have them already).

Of course, your survey responses are completely anonymous and Eric is doing this survey independently of his employer.

Take the Web Analytics Demystified Survey

I don’t need the preamble, take me straight to the survey