Competitive Intelligence. Why?

Why?: There is a revenue opportunity using competitive intelligence!

I think it’s naive to believe that you control your own web setting. You might control your website, but numerous factors way beyond site optimization have impact on your Revenue! – and more often than not, a revenue impact is due to competitor actions. It’s time to recognize that your own silo of data is only half the picture. You are dangerously putting your revenue at risk if all your decisions are based on inward looking data, as in e.g. clickstream data - you have to count in the overall industry setting.

The good thing however; is that there is everything from FREE competitive intelligence tools to high end tools, such as:

• www.alexa.com (-)
• www.compete.com (-)
• www.ranking.com (-)
• www.chart.dk (- local Danish CI portal, I am quite sure you could find one in each country)
• www.hitwise.com ($)
• www.comscore.com ($)

But it should not be discounted that the Search Engines provide some very valuable competitive insights as well (for free).

www.adwords.google.com
www.adcenter.microsoft.com

Let me try to illustrate, by using an example, what I am talking about when I say that there is valuable actions to take, analyzing competitive intelligence. As a very basic example using the infamous Alexa – the competitive intelligence feature: “related links” – which in reality is upstream analysis and downstream analysis (of course not on a level as we know it from enterprise tools like e.g. HitWise). Forgetting for a moment that this data might be flawed – it’s super interesting to see that Clicktracks (a IndexTools Web Analytics vendor competitor) have visitors visit the following links before and after they visit ClickTracks.com

Sample Alexa “Related Links” for clicktracks.com:

• www.webtrends.com (Log Analysis vendor)
• www.sitelogz.com (Log Analysis vendor)
• www.newmanservices.com/logjam (Log Analysis vendor)
• www.urchin.com (Log Analysis vendor)

Where this initial finding, that visitors to the ClickTracks website are searching the web for "log analysis software", can be further confirmed by using the “Google AdWords - Related Keywords” competitive intelligence feature.

Google Related Keywords for clicktracks.com:

• log file
• log
• logs

CI CONCLUSION:
And based upon the above, one could (or at least for sake of this blog post) conclude that the visitors have a focus, or at least stronger focus than my initial stance, on log analysis software, when visiting clicktracks.com. And with that in mind we could conclude that they (hi John) have more revenue coming from software licensees than from ASP subscriptions.

CI ACTION:
I should remove ClickTracks from my immediate top level competitor list – as I do not provide a log analysis software package (or have any plans of doing so). I should investigate whether there really is two very differently customer segments - by looking at competitive intelligence for a pure on-demand (ASP) vendor as well.

I would like to dig even deeper into the competitive intelligence subject later, but I hope the above gave you an indication on WHY I think CI is important - You can read some in depth post about the subject as well from both Avinash’s and Marshall’s blogs.

Comments from Search Engine Strategies - Munich 2007

I just returned from SES in Munich; and from an Exhibitor point of view – it was not that bad! :-)

I was sitting in on Rand Fishkin’s presentation yesterday and beyond the usual fantastic show, he gave one memorable quote about how you could “easily” manage your online reputation - agreeing that SERP results is a major part in that.

TIP: Use Social Network Profile pages to control your online reputation.

Checking for “Dennis R. Mortensen” – you will find:

• LinkedIN (Profile Page)
• SEOmoz (Profile Page)
• Ecademy (Profile Page)
• Blogger (Profile Page)
• eMarketing (Profile Page)

Discounting my own blog and a Webmasterworld comment – there is nothing but profile pages on the first page of the SERP. Amazing; perhaps I should sign up for a couple other social networks and get “control” over the last couple of results and own the first page :-) – A super tip Rand. Thanks. As always Rand was pouring out his love for Action Tracking Action Tracking (a.k.a. Conversion Tracking) – and I absolutely think he is true. That it simply the first thing you have to get in control of, in any online venture! - find Rand’s post about SES Munich here: ses-munich-linkbait-truffles-more-insomnia.

Friends and Contacts from the show:
It was a pleasure to meet up with: Steve Johnston at lunch - still pitching his brilliant business card with NO information, but his name – you guessed it, he is in SEO. Sara Andersson (we need more blond good looking Swedish girls in the SEM industry – and what was up with the moderator at your session?? :-). And I would like to Welcome Timo Aden to the blogosphere – and that said from a newbie like me – by the way, will you be at Emetrics Germany?. Markus Reif, Patrick Ludolph, Andreas Vogt, Mark Kofahl. Udayan, I do hope I will be able to meet up with you at New York SES – do let me know when you are there. Sebastien Doyen – PLEASE, with sugar on top; I need those 10 minutes to pitch to your team that Omniture is but the same as IndexTools, just in a green interface. I of course forgot to thanks Matthew Finlay for a great German show, but it was indeed from a exhibitor point of view worth going there, I of course have the same high expectations to Emetrics now (as Matthew runs as well). Oliver and Felix and the nice people from Webtrends – I still think we are a cooler tool.. ha ha. And it was of course great to meet up with Michael Buchheit from ISA again!

Roger over! :-)

Best Practice Comment: Title, Heading, File name and Document name. (Caption)

I think we all agree that creating a “Caption” for a text (blog-post or other web copy) is much more than winging a quick title including a couple of keywords. I would like to conclude (not suggest) – that when creating a “Caption” you have to take the following upper level related elements into consideration – as they all derive from the same thought – but most certainly have different usage:

• Title Tag (Writing caption focussing on: SEO and Conversion)
• Heading Tag (Writing caption focussing on: Usability, SEO and Conversion)
• File Name and Folder (Writing caption focussing on: SEO, Conversion and Systems)
• Document Name (Writing caption focussing on: Analytics)

N.B. Please note than when I talk about “Caption” – there is no relation to the deprecated HTML tag of the same name – it was simply the best word I could find describing all of the above four elements (me being Danish and all)

The reasoning for doing this post is that most of the comments read so far (by me at least) – tend to focus on the HTML Title for SEO purposes only – leaving out the fact that there is an instantly related Analysis task at the same time – creating a "Document Name" for your Web Analytics Tool.

I will not go into details on how to write your Title Tag, Heading Tag or File Name (plenty of good posts out there about this) – but I would like to comment on why you should use the Document Name feature in your analytics tool and incorporate that into your procedures when creating Captions. Find a quick bulleted list of some of the basics you have to take intoconsideration:


Title Tag (Writing caption focussing on: SEO and Conversion)
Example: VisualRevenue.com - Web Analytics and Affiliate Marketing Blog

• The searchers intent
• Branding your traffic
• Incorporating your keyword phrases (shorter vs. longer phrases)
• Your use of dividers
• Click-through rates and thus conversion in mind
• Character limitation (about 65)
• Being consistent with the rest of your site’s titles
• Have your Heading in mind
• Have your file-name in mind
• ...

Heading (Writing caption focussing on: Usability, SEO and Conversion)
Example: Web Analytics and Affiliate Marketing Blog

• Click-through rates and thus conversion in mind
• Incorporating your keyword phrases (shorter vs. longer phrases)
• Make the phrasing of headings self-explanatory
• Scanability if heading is long
• Highlighting of important words
• Avoid exaggerated promotional words and phrases
• Have your Title in mind
• ...

File Name and Folder (Writing caption focussing on: SEO, Conversion and Systems)
Example: /blog/default.htm

• Click-through rates and thus conversion in mind
• Incorporating your keyword phrases (shorter vs. longer phrases)
• Have your Title in mind
• Be aware of Systems limitations on file name length
• Cases do matter (I recommend using ONLY lower case)
• Avoid parameters if possible
• ...

Document Name (Writing caption focussing on: Analytics)
Example: var DOCUMENTNAME='Blog Homepage'; (IndexTools Java-script example)

• Have your Title in mind
• As Title, Heading can change for SEO purposes – choose a broader permanent name for the document
• Be aware of Web Analytics tool limitations on Document Name in length and characters (including how much is shown in reporting)
• Decide for grouping (matching names are typically grouped) – this can also be pitfall and it is very hard to diagnose and cure later on, should you by mistake have named two pages the same
• Be consistent with the rest of your site’s analytics naming convention
• ...

Conclusion..... and Why all the fuss?

Most sites today, and specially in the affiliated marketing space, are SUPER aggressive on SEO and have implemented heavily Search Engine optimized titles and headings. The results of this is in most cases that you end up with useless and changing naming in your Web Analytics tools – I would even go as far as to say worthless per page data, as it is not grouped correctly due to changing titles. Therefore one must look at caption as a four point task – and not just a title task!

Looking at my own blog... hmmm – I can see it’s time to take my own medicine! :-) however; tomorrow there is a new day. :-)

Off to Search Engines Strategies in Munich (sitting at the Hotel with my Red Bull breakfast)

Discount Coupon: Search Engine Strategies, New York 2007

If you are thinking of attending SES NY in April, I am happy to say that you can get a 20% discount on the full conference or 1-day pass. Thanks to JoAnn and Elaine at IncisiveMedia... And do let me know if you are going.

Cheers..

Take a look at the coupon (click for a larger view)

Podcast: Web Analytics and Click Fraud - Dennis R. Mortensen interviewed by industry expert Eric Enge

Eric interviewed me a good week back on the subject Web Analytics and Click Fraud for a Podcast.

The summary of the podcast:

• Reports based analytics approaches vs. metrics based analytics approaches?
• The Report surfing sin
• The web analysts persons role in a successful analytics strategy
• Click fraud and comments on measurements
• Challenges facing the web analytics industry in 2007 and beyond

If you find that as intriguing as I do :-) here we go:

DOWNLOAD/PLAY: Dennis R. Mortensen Podcast (MP3)
File Size: 6.0 MB, Duration: 26.0 minutes

Find the following Cool Podcasts over at StoneTemple Consulting:

• Dennis R. Mortensen – Mar 9,2007
• John Marshall - Mar 8, 2007
• Jim Sterne - Feb 22, 2007
• Avinash Kaushik - Feb 9, 2007

..And what a fantastic group of people I am associated with here. If I am not mistaken, we will all meet up in a week’s time at Jim’s E-metrics summit.

N.B.
Eric blogged about it over at SearchEngineWatch.com as well, under the title: Click Fraud is between 2% and 4%! :-)

Cheers.

The Long Tail ... and how to calculate missing Revenue

Inspired by Avinash’s “long tail” post today I thought it would be appropriate to take it a step further and indicate how you as an affiliate with revenue generation based on content can calculate how much revenue you are leaving on the table - spotting a drooping tail. I know this is going to be a bit long haired, but stay with me for a second.

First lets draw our own graph (based on an anonymous dataset from the perfect IndexTools client).

Graph: "The number of visits per page" - the homepage got 16241 visits in the given period and was the most popular page




This is the traditional Long Tail graph, telling us that a few pages generates a lot of traffic, BUT the same amount of traffic is generated by a large pool of lesser visited pages. Without going into detail, I think we can agree that it is fair to assume (just by looking at it) that a standard long tail distribution as the above is inversely proportional and thus follows Zipf's law. With that said, let’s try to plot the same information into a double-logarithmic chart, to confirm that we indeed have a straight line.




I think it’s fair to say (from this perfect dataset) that we do indeed have a straight line and thus a distribution that follows Zipf’s law. However; let try to look at a less perfect dataset, another IndexTools client, who will not know how much revenue they are leaving on the table, if they are using traditional long tail linear graphs visualizations. I will have Sales call them up tommorow ... :-)

Graph: "The number of visits per page" - the homepage got 319270 visits in the given period and was the most popular page



And by looking at it (using a linear graph) – everything looks "normal" and I could assume that this is the traditional long tail distribution. But using a double-logarithmic chart, we all of a sudden see that there is a drooping tail.





And if we keep the assumption that the long tail should be inversely proportional and as indicated follow Zipf's law – we are missing something here. And what we are missing is more CONTENT! – this client simply do not have enough content to support the long tail.

We could therefore say that additional content would increase Revenue. With the above as an example, the perfect distribution would roughly add an additional 1.7M visits per week, it would also mean that they had to move from 3600 something content pages to more than 300.000+ content pages.

For the fun of it, let’s assume (based on my latest Google AdSense experience) that you have an average ECPM on $2 and that each visit resulted in 5 page views. That’s a $17000 per week revenue increase!! – whether this offset the cost of creating 300.000+ pages is another debate.

But we should have in mind that this approach is not just for Content Pages – it might as well be for keywords (as Avinash used in his post), referring URLs and other metrics generating the typical long tail distribution.

Conclusion:
There is a Revenue opportunity in the dropping tail that most content sites miss out on – because they do not have optimal reporting on their data.

NB:
If you are an IndexTools client and this does not make sense – Add a comment (including your account name) – and I, ..probably outsourced to someone else. :-) will show you how to do the right exports and Excel setup’s to see if YOU are missing out and whether you have a drooping tale opportunity.

.

Q. Name an example of when analytics can increase an affiliates revenue

I was recently asked whether I wanted to answer a set of questions in line with the topic of my blog – which I am of course delighted to do. The first question goes like this:

Q. Ingrid:
“Kindly give us an example of when analytics could increase an affiliates revenue drastically – indicating why analytics was important and how it was used”

A. Dennis:
No problem Ingrid. First, let me point out that I think there is multiple Analytics Strategies that an Affiliate (on any level) can use to increase revenue, but to answer your question on a very actionable level, I will use one of my favourite affiliate metrics as an example; The “Conversion Participation Metric”. (I talked a bit about conversion funnels on my blog last month, and this is what I described as a “Non-Linear Path towards conversion”).
Most affiliates (or Publisher as some call it) write valuable content that are aligned with their keyword strategy and use these pages as part of their SEO (Search Engine Optimization) strategy. However; ranking well and driving in organic traffic on a specific set of keywords, based on a well optimized content page, is not the same as concluding that this is the page that contributes the most towards conversion.

Conversion of course being a bit tricky when you are an affiliate (I briefly touched the subject in my outline of conversion tracking for affiliates post). Complicated because you typically do not convert the visitor on your own site, this is done on the retailers site. But let’s just conclude for the sake of the example that conversion is a “On Click conversion” (clicking the retailers banner). As an example, let’s imagine an affiliate website with the following pages:

• CarPage01.html
• CarPage02.html
• CarPage03.html
• CarPage04.html
• ...
• CarPage99.html

Best performing affiliate programs for this imaginary website is:

• TradeDoubler’s “AVIS Car Rental”
• TradeDoubler’s “Hertz Car Rental”

The content pages all drive relevant incoming traffic for wanted keywords, BUT given the question on how to optimize your content to increase “Car Rental” conversion (clicks on banners) – we simply do not know which of our pages contributes the most towards this conversion. So we would not be able to conclude where to optimize. This is where the Web Analytics Conversion Participation Metrics comes in handy. Running a report on the pages that contributed the most towards the “Car Rental” conversions, we would be able to find out that it is in fact e.g. CarPage37.html and 5 other pages that contributes the most when talking about these conversions (Remember we might even find pages here that do NOT have the AVIS or Hertz banners). This conclusion gives us a clear actionable insight of where to optimize for even better conversions in the future, it might even enlighten us on what behaviour drives “Car Rental” conversion.

I hope this straight forward example gives you and your readers an indication of how powerful analytics can be. :-)

Go see the original post here: http://www.rabbitblog.hu/2007/03/13/webanalitika-novekvo-bevetel (Hungarian)

Web Analytics Wednesday Stockholm

Lars Johansson put together a super Web Analytics Wednesday event last night! The main events of the evening, beyond some really pleasant networking, was two presentations by Practitioners and the Vendor Panel:

  

• Practitioner Case Study: Jannike Tillå, Aftonbladet (reporting KPI’s on a hourly basis – I am impressed)
• Practitioner Case Study: Massimo Pascotto, Scandinavian Airlines
• Vendor panel, moderated by Lars Johansson & Mattias Malmnäs

I (IndexTools) participated in the Vendor Panel together with Google , Omniture , Webtrends , and WebSideStory and one of the surprising questions and debates was about accuracy in Web Analytics tools. Surprising, because this is a debate that was somehow closed over the last few years. All vendors on the Panel use pretty much the same data collection methodology - and yes, WebTrends' patent-pending first-party cookie solution is no different ;-). Brian from Google (as part of the audience this evening) – added a few truths about why we just have to accept that there is no such thing as 100% accuracy. This included the fact that:

• A) Not all visitors accepts 3rd party cookies
• B) Not all visitors accepts 1st party cookies
• C) Some visitors use both their “WORK” computer and their “HOME” computer and are "counted" as two.
• D) ...

If you want to do dig a bit deeper into this subject; go read Avinash’s super post about Data Quality Sucks, Let’s Just Get Over It – and the one advice you should take from that post is, if you ask me:

- Assume a level of comfort with your data

And of course – it’s always nice to meet up with Brian, Sara, Matthew, Ian (Thank you for the WebTrends powered “Belgisch bier” .. and of course the opportunity to say hi to the smart people from Pricerunner.com.

Is Google Analytics really as good as other tools?

This is the question Michael Helbling ask over at his excellent Web Analytics Blog – and not a bad question at all. But before voicing my opinion, let’s try to have a look at the fairly straight forward reports Michael ask for:

• Keywords Report
• Search Engine Report

(the pictures are the ones from Michaels post)

At first sight, two standard reports! But when he try to do a bit of analysis:

“Let’s say that I am trying to optimize my site for the phrases, “wowza”, “yowza”, and “gyoza”. Wouldn’t it be useful to be able to track the number of referrals I got from Google and Yahoo over time without having to expand and collapse multiple boxes within the report?”

He’s stumbles into the following problems:

• “You can’t see a report that displays all the search engines and their underlying search phrases simultaneously and vice versa”
• “In addition the export function only grabs what is on the screen, so there is no correlation of those two data points in any exported report”

And this is where the power of more flexible tools appear, the ability to change report layout and metrics on the fly. So given the upper business requirement, my first step would be to open a “custom report wizard” – and drag & drop the groups and metrics needed to answer this. (to spice up the report example, I replaced Michaels conversion metrics (called Goals in Google) with a Revenue metric, but any metrics could of course be presented here.


The report result is as follows. (N.B. I have replaced the keywords, as the revenue is from one of our hospitality industry clients)


Where I have the sought after oppertunity to expand the tree and compare engines - "side by side". Like this:

And one could re-arrange the metrics and put Keywords on top as well, for a different view. Giving the Web Analyst the freedom to investigate, turning metrics upside down anyway they want.

And this is of course something that is doable in any of the “Big Four” analytics packages that Michael mentions; this including a few contenders... as us :-)

So: “Is Google Analytics really as good as other tools?” - The answer is No. Not because of the above of course, but the tool has technical limits in regards to customization that most enterprise clients not want, but need to carry out their analysis. However; my question would not so much be, whether it is as good, but whether the tool of choice solved the problem at hand – and for a lot of people, Google Analytics does and for that reason I think it is a splendid tool that I can only highly recommend. And with Avinash beginning to advocate Google Analytics as a consultant, I might as well just surrender now.. :-)

.. I am as we speak on my way from Arlanda Airport to Stockholm – where I tomorrow will meet up with Brian (Head of Google Analytics EU) at the Web Analytics Wednesday event. So plenty of time to debate the above on the Vendor Panel. More about that event later.

Local Online Media blog – Dennis R. Mortensen featured as Web Analytics Expert

I was graciously introduced over at - Ihász Ingrid’s blog – as the Web Analytics Expert or as the post says in Hungarian – “Web analitika expert a Rabbitblogon” - and THAT is something worth posting about.. ha ha.

But seriously, I will be answering a set of question in line with the topic of my blog: Web Analytics and Affiliate Marketing. The first question goes like this:

Q. Ingrid:
“Kindly give us an example of when analytics could increase an affiliates revenue drastically – indicating why analytics was important and how it was used”

Drastically is of course a strong word, however; you will see my response over at her blog one of these days. I will post the English version here as well, for those of you (including ME) who do not speak Hungarian.

Conversion Tracking (outline)

I talked about conversion funnel analysis in one of my first posts and I do profoundly believe that increasing your website conversions is the most effective way to increase Revenue. However; this is easier said than done if you are in affiliate marketing, as most of the conversions you are working with happens on the retailers site.

But first we have to define what types of conversion tracking we can do and I tend to look at the following three when talking about the affiliate marketing conversion challenge:

1. On Page conversion tracking
2. On Click conversion tracking
3. On Redirect conversion tracking

Please observe that these are not different metrics (kpi's) but different methodologies. With that said and even though they are pretty self explanatory - let me try to give three quick examples:

On Page conversion
This the traditional “thank you”-page conversion tracking.
And this typically being a page at the very end of a funnel.


On Click conversion
This is the typical affiliate “exit link” banner or text – a link which links to the affiliate network redirect page (the affiliate tracking code). The conversion tracking have to be deployed as a HTML on-click for the affiliate to be able to track this as a conversion (click to retailer) – I will talk about consolidating revenue later on.


On Redirect conversion
Most affiliates (due to many reasons, that I will debate later) use a redirect script/page to redirect their exit link traffic through. You typically see this as a e.g. click.php link on a banner with added variables such e.g. click.php?retailer=2&campaign=1.


...But much much more about this - I have decided to do a specific post (beyond this basic outline) about all three conversion types as this is the foundation for everything else we want to do in regards to revenue tracking! and hey, I got to get this posted... it’s my mom’s birthday today and that magic call have to happen soon :-)


N.B. Here goes a pool of links about conversions at blogs I read and recommend:

Excellent Analytics Tip#5: Conversion Rate Basics & Best Practices
Buyer versus order conversion rates
Anatomy of a Conversion (/actually a funny story at the same time)
Increase Conversion Rates with Copy Testing
The (un)Real Conversion Rate topic discussion
..

Search Engine Strategies London 2007 (+Bonus Interview)

I recently returned from Search Engine Strategies (SES) in London. And I think most people would agree that an event / forum like this is successful if you return with ONE advice/input on how to optimize and improve your business. I of course, as an exhibitor, was there for the leads! :-)

Two of our really smart partners demib.com and SEOmoz.org were both part of the advanced track panel: “Organic Listings Forum” – where the following simple but powerful advice where presented and debated:

SEO Advice: “If one are to start a new web project – do NOT register a new domain, instead Google your industry keywords and start looking from 'page 5' for old mismanaged domains. Acquiring such a domain will give you a very valuable head start in your SEO efforts."


NB:
I had the pleasure of being able to add my comments on the Analytics industry in general - at the last London SES. So here goes a 5 min Interview With Dennis R. Mortensen (me!)

Using visitor based segmentation – where do you part?

“Real visitor based segmentation” – which only a handful of the Analytics Vendors provide at the moment – raise beyond the technology some exciting Marketer / Analyst questions as well.

It is a common understanding that segmentation is fundamental in conducting in depth analysis of web analytics data in today’s online marketing industry (and this definitely includes those who have revenue income based on affiliation – where conversion on high value items is NOT done in the same visit session). Leveraging segmentation allows one to answer ever more complex questions that originally stem from basic reporting.

In more report focused tools (e.g. Google Analytics), visit segmentation might require defining all aspects of the report result in advance or it would require the reprocessing of data to create the desired segments.

Truly flexible tools allows exploration of the data by defining and evaluating segments in Real-Time. Keeping this in mind moving forward, I have been quite interested in keeping this vision about being able to provide results in Real-Time no matter what the analyst question is. So moving on forward from here and into “Real visitor based segmentation” I see two roads one can take - but before describing these I would like to make sure we don’t muddle up the visitor segment concept with basic “fake” visitor segmentation, providing aggregated metrics, such as lifetime customer value etc. We are talking about system wide “Real visitor based segmentation”!

Given the segmentation example:

• Visitors from New York
• Who looked at the “IPOD” page
• But did not buy an IPOD product

And the Visitor behaviour:

• The Visitor visited the site and looked at the “IPOD” page February 15th 2006
• The Visitor bought the IPOD product on April 15th 2006

Applying the above visitor segment today (March 14th 2007) on a report (dataset) for Q1 2006 what is the result?

• A) The visitor is NOT included as he did NOT buy it in Q1 (Thus the segment is fixed and the results are always the same)
• B) the visitor IS included as he did eventually buy it (Thus the segment is floating and the result can vary)

In summary, would one want to, from an e.g. forward looking sales perspective, to choose solution B – the attitude of: he did eventually buy it and I do not want to market it to him again. OR would one want to, from an e.g. backward looking marketing perspective, to choose solution A – the attitude of direct ROI and the fact that I spent a fixed amount of money and had a fixed measurable Q1 result from it.

I have had exciting dialogues with friends, clients, prospects and colleagues about this over the lasts months and there are different opinions.

• A) Fixed visitor segments (the direct ROI attitude)
• B) Floating visitor segments (the forward looking sales attitude)

What do you think?

Interview of IndexTools' Dennis R. Mortensen

I was recently interviewed by Eric Enge - Eric is the President of Stone Temple Consulting and writes for Search Engine Watch. We talked about a lot of stuff, amongst others:

• Metrics based approaches versus report based approaches
• Key challenges facing the analytics industry in 2007 and beyond
• key questions businesses should be asking, when they are deciding upon analytics solutions

The interview is long and I recommend, should you find the time to read it one day, that you print and bring it on your tram ride as I did :-)

Link: http://www.stonetemple.com/articles/interview-dennis-mortensen.shtml

He have done a set of interviews with some really cool guys (and yes - you can discount me.. ha ha) – which till date counts:

• John Marshall - Feb. 28, 2007
• Avinash Kaushik - Feb. 25, 2007 (Avinash's analytics blog)
• Mark Lucovsky - Feb. 18, 2007
• Eric Peterson - Feb. 11, 2007 (Eric's analytics blog)
• Jim Sterne - Jan. 17, 2007
• IndexTool's Dennis Mortensen - Jan. 8, 2007 (my analytics blog)
• Google's Brett Crosby - Jan. 3, 2007 (google's analytics blog)
• Yahoo's Tim Mayer - Dec. 4, 2006
• Eurekster's Grant Ryan - Nov. 11, 2006
• Google's Shashi Seth - Oct. 24, 2006

I will be doing a PodCast with Eric one of these days and will post the result / link here as well.