Where’s Dennis? – a comment about Web Analytics in Asia

posted by Dennis R. Mortensen
Tuesday, July 31, 2007
Bookmark: Where’s Dennis? – a comment about Web Analytics in Asia




I recently returned from a month in Singapore, where I had the opportunity to explore the Asian Web Analytics market (as far as Singapore represent the region, which of course is not a fair representative). This is no Forester or Gartner in depth market analysis; this is my own very subjective comment and view after:
  • Meeting with some almost 10 interactive agencies (SME and Enterprise level)
  • Meeting with our existing partners in Singapore
  • Meeting with a handful of direct clients
  • Presenting and demoing IndexTools
  • Attending the Online Marketing and Web Analytics conference and seminar hosted by GSQM at the Marketing Institute of Singapore. (Jim Sterne actually presented there, what a small world)
  • Meeting up with Jim Sterne at Raffles Hotel, sharing a handful of Singapore Sling’s (see that is great in depth market RESEARCH if you ask me..)
With ultrahigh Internet penetration (they have nationwide FREE Wi-Fi) – one would expect sophistication in their use of online marketing and this including sophisticated use of Web Analytics Tools. There was only very limited in depth knowledge of the powers of Web Analytics as a discipline and even more surprising, there were very little knowledge about web analytics tools – Only two tools were mentioned:
  • Google Analytics
  • Webtrends (mostly the LOG analyzer)
No mentioning of IndexTools, Omniture, Visual Sciences or any other Enterprise Web Analytics Vendor – this including Asia specific vendors like Digital Forest and CCMedia. Whenever debating use of the deployed Web analytics tools – it became clear that it was merely on a reporting level and not on a analysis level.

My instantaneous conclusion is that the web analytics market is not yet mature in Asia (Singapore). A big reason for this includes the fact that Online Marketing spend was below 1% last year, BUT there is no doubt that it will be there soon (1 to 2 years according to most of the agencies interviewed).. so perhaps it is time to move out there, because Singapore in general was absolutely fascinating and the people I spoke to at the agencies utterly friendly.

I would be very happy to get your input on the market and I am more than happy to bring it up at the next fantastic 6 podcast Lars? :-)

N.B.
Where’s Dennis? – I am actually in Chicago attending Ad:Tech, so if you are there, post a comment or throw me an email and we should meet up! :-)

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Top 10 Web Analytics Blogs – July 2007

posted by Dennis R. Mortensen
Friday, July 27, 2007
Bookmark: Top 10 Web Analytics Blogs – July 2007

I set of on my blog journey back at the end of February 2007 (exactly 4 months ago today) – and was really cheerful to see that after 2 months (mid April), that I made it onto the Avinash - Top 10 Web Analytics blogs (as a personal recommendation). The new new list is out and it goes like this; and you will notice that I am once again on his recommended list – Juuuhuu AGAIN, thank you very much Avinash!


Avinash’s Personal Web Analytics Blogs Recommendations:
  1. Coremark Analytics by Wendi Malley
  2. Web Analytics Demystified by Judah Phillips
  3. Visual Revenue by Dennis R. Mortensen


Overall Top Ranked Web Analytics Blogs:
  1. Occam’s Razor by Avinash Kaushik
  2. Google Analytics Blog by Jeff Gills
  3. Web Metrics Guru by Marshall Sponder
  4. Web Analytics World by Manoj Jasra
  5. WebAnalytics.be Blog by Aurélie Pols
  6. Analytics Talk by Justin Cutroni
  7. Unofficial Google Analytics Blog by Shawn Purtell
  8. Lies, Damned Lies… by Ian Thomas
  9. Increasing Your Website’s Conversion Rate by Robbin Steif
  10. The Commerce360 Blog by Craig Danuloff
BUT a more exciting notion, beyond nurturing my ego :-), is that Avinash introduced a new ranking system (which you should go and have a look at, as the regression analysis thought behind it, is super for other matters of analysis as well.





Where E4 are your FeedBurner subscribers and F4 is your Technorati ranking. I am at about 35 (using todays Feedburner and Technorati numbers) according to Avinash new proprietary ranking system – so watch out Craig! (who is at 44) :-)

N.B.
Is the data (in particular Technorati) used for the list flawed/polluted as suggested by Mr. Peterson – I am absolutely sure it is. However; it is still a fun list that encourage volunteers like myself to continue.

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What and how to measure Media and Content websites

posted by Dennis R. Mortensen
Thursday, July 26, 2007
Bookmark: What and how to measure Media and Content websites

By media and content websites, I am talking about pure online media properties like CNET as well as companies (e.g. traditional newspapers like New York Post) who must somehow, either be in the midst of an involuntary transitioning of readers, from offline content consumption (their paper) to online content consumption (their website) – or in the fortunate circumstance that they managed to set up a business model that compliments both channels at the same time. (I am of course talking about any other website where the product is content – thus your typical affiliate website!)

Studies by analysts in general and in particular Jupiter Research concludes that - we are seeing an increased hunger for personalization and thereby a disaggregation of the website - and at the same time the emergence of an online-only audience who at the same time demand participation (social media as we konow it today).

Which makes me conclude on a progressive path and journey most media and content website have to take:
  1. Media
  2. Online Media
  3. Online Social Media
This seems straightforward and as understandable as in taking the newspaper (Media) and reprocess the content on a website (Online Media) and then throw in a couple of “post a comment” widgets (Online Social Media). I do hope that we all agree that is takes a lot more than that! ...and that a lot more is at stake. As online social media continues its striking invasion into the overall media landscape and seize valuable mindshare, particularly from the younger demographic, the degree to which a traditional media company move towards the final goal of social integration of its audience is rapidly becoming a proxy for its ability to survive the future.

If we partly agree on the above I think we also agree that It is simply NOT enough to just randomly report on the effects of this transitioning – in vague hopes of moving towards this goal of social integration. One have to accept that however sexy Online Social Media or even just your Online Media (your basic content website) sound, there MUST be a set of measurable KPI’s across all three steps from above - and they should very much be aligned to your business objectives.


Content websites business objectives:
  • Increase Advertising Revenue
  • Increase Subscriptions
Having in mind that I am allowing for a broad interpretation of the term “subscription” – the above clearly defines the business objectives for most Media and Content websites. Assuming that you agree with me, we then have the opportunity to define a set of specific KPI’s and accompanying important metrics to drive those objectives forward:


Content websites advertising revenue KPI’s:

  • Advertising Revenue
  • Visits per week
  • Ad units per visit*
  • Ads served*
  • Ad CTR
* The “Ad units per visit” KPI is a replacement for the old "page views per visit" as a way of indicating the size of your Ad inventory and the “Ads served” KPI is the actual number of revenue generating banners or other media type served in those units.

Remember, that when talking about these 5 important KPI’s (and no business should really have more than 5 KPI’s on a management level) – we are not just talking about a set of basic reports on their performance in retrospective – we are talking about collecting data on a granular level so that we can both report AND more importantly do analysis on these – by segmenting, slicing and dicing them any way imaginable.


Content websites subscription KPI’s:
  • Subscribers
  • Anonymous visitors to subscriber conversion rate*
  • Cost per new subscriber (CPA)
  • Subscriber churn rate
  • Articles viewed per visit
* "Subscribers" is not necessarily the same as or equal to that of an off-line subscriber, this could be something as loose as a RSS subscriber to something as tangible as an online paying subscriber (who get’s access to premium content by login and password).


Content Websites KPI control elements:
  • KPI Targets
  • KPI Indexes
  • KPI Competitive Intelligence
I am sorry to add to the list of tasks, but one simply have to create a credible target for every single content websites KPI that we discussed above (credible as in utilizing competitive intelligence to set realistic goals) so that there is a clear driver within the organization on where it is going. At the same time while working towards those targets one need to create a sensible content website KPI index that can be used when doing analysis for the KPI in question (sensible as in taking into consideration how the KPI fluctuates due to season, campaigns and other factors). Finally utilizing competitive intelligence to spot market opportunities for optimization and general KPI improvement.

NOW - having clear business objectives, 10 well defined content website KPI’s and a set of KPI control elements in place - we get the opportunity to put all this to work, as in nobody should go to the extent of setting up a framework as the above without aggressively pursuing a performance improvement in ones business objectives. It's really not worth measuring something if you cannot or will-not take any action on it, and to be worth taking action on, it has to have some kind of measurable monetary value. There is no magic 5 points to optimize, but given the framework as described above one would have an unlimited number of opportunities to make more money! - find a couple of suggestion below:

But before starting to think about optimization (however basic) – you need to make sure that the Web Analytics tool that you have deployed can collect and not only report on the mentioned KPI’s – but more importantly: That you are given the technological opportunity to do analysis!


Content websites optimization opportunities:
(7 basic and to some extent obvious suggestions)

My first comment is that before trying to optimize anything for the better - some sort of potential monetary valuation should be put on the effort as in; are we looking to increase revenue EUR 10.000 per year or are we looking to increase revenue EUR 2.000.000 per year and with what certainty can this be determined.

As an example, let’s say that we have 15 Ad units served per visit and that we have an Ad unit CPM value of EUR 3 and that we have 1.000.000 visits per week (notice how all of these are KPI’s) – this leaves us with a weekly Advertising Revenue on = EUR 45.000 (1.000.000 visit * 15 Ad units per visit / 1000 (CPM) * 3 EUR). The optimization opportunity in question estimates that we can increase the number of Ad units served to 18 by adding a small additional unit AND that there will be a 0.30 EUR decrease in Ad unit CPM value due to this (notice that we utilize our KPI’s index here). Therefore a monetary opportunity on EUR 3600 per week or in perspective approximately an opportunity per year of an additional EUR 188.000 in revenue!

Here goes is my 7 basic and obvious suggestions (very specific and less strategic though) on what you should look into when optimizing a content website:

  1. Segment articles based on ad unit placement to create insight on what ad unit placement drive the biggest Ad CTR KPI without decreasing the Ad units per visit.
    Opportunity: Increase Advertising Revenue by optimized ad unit size and placement.

  2. Segmenting the Anonymous visitors to subscriber conversion rate KPI by campaign channels (in my world ALL incoming traffic should be part of a campaign, this including SEO activities) to find and focus on better performing channels and campaigns.
    Opportunity: To increase the Anonymous visitors to subscribers conversion and thus if visits are constant the number of new subscribers

  3. Reporting on the Subscriber churn rate KPI over a given period and drill through (on spikes) to articles (or specific HTML pages) - to determine and create insight of less compelling content. Although it is nearly impossible to determine why subscribers end their relation with you (as basic as stop coming to the Website) – it is still possible over time with repeatedly insight on the same fact to drive a conclusion on what type of content is badly chosen.
    Opportunity: Decrease the Subscriber churn rate KPI and thus increase the numbers of total subscribers.

  4. Setting up basic external campaign tracking on ALL channels from PPC to Email to affiliate networks and compare not only channels, but compare campaign to campaign across channels, sorting out high performers and low performers to Decrease the Cost per Subscriber (CPA) KPI.
    Opportunity: To decrease the average cost per new subscriber and thus an the opportunity to re-invest that into new external campaigns

  5. Utilizing the articles viewed per visit KPI together with the Visual Overlay tools from your Web Analytics package to define Homepage content blocks -- not unique articles -- (this works for content category front pages as well). These content blocks typically on e.g. a newspaper website being; “Main article”, 2 sets of “Sub articles” and a list of “Most popular articles” and so forth. Then determining a CTR (Click trough rate) baseline for each of these content blocks – Now having an Index on the expected click through on e.g. the main article on the homepage on, say, 14% - any underperforming articles (as compared to the index and thus below 14%) can be replaced.
    Opportunity: Increase the Articles viewed per visit by pulling underperforming articles away from prominent positions.

  6. Tracking ALL your Internal Promotions (essential campaign tracking for banners or links on your site promoting other sections on your site) and then segmenting your visitors by these Internal Promotions and looking at the Ad units per visit KPI – you will to begin with, find out which internal promotions actually drive more Ad units (potential revenue) and more importantly which internal promotion does not work and at worst drive DOWN Ad units per visit according to your index.
    Opportunity: Increased Ad inventory by better internal promotions.

  7. Try to increase the “quality” of your Ad units per visit KPI by using External Data Sources and relate your CRM user database to the Member-ID tracking done by your Web Analytics package (this will give a plethora of opportunities), but one obvious is generating a simple report by content group and thereby get insight into the demographics and sociographics for every specific content group, whether that be sports, politics or tech.
    Opportunity: Increase the Ad unit CPM value by demanding higher pricing for better targeting and at the same time expect higher Ad CTR
Even though these 7 basic suggestions (and both you and I could come up with 50 others) somehow seem simple – then I am confident that anybody running a content site would be far better off looking at and concentrating on the KPI’s framework described.

My overall conclusion in this post about media and content websites is that; one simply cannot be successful -- in the long run – as a media company moving towards embracing Online Social Media, if not one or more activities around enterprise optimization analysis is deployed. I hope that the above somehow indicated and inspired which direction to go in.

N.B.
I recently wrote a post about what and how to measure Online Social Media websites, this including 7 online social media optimization opportunities (which I suggest you take a look at – should you be on the path towards becoming an Online Social Media). You will see that the KPI’s in that post to some extent are a progression of the KPI’s for Media and Content websites. Which is of course only natural and expected.

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Web Analytics educational opportunities (...and prophetic blogs)

posted by Dennis R. Mortensen
Saturday, July 21, 2007
Bookmark: Web Analytics educational opportunities (...and prophetic blogs)

John Lovett from Aberdeen recently (July 2007) produced a review of the educational opportunities (Analytics University: Part I and Part II ) that companies, analytics practitioners and aspiring web analysts can take to further their knowledge of web analytics. He split this into four different avenues as of today:
  • Vendor Sponsored Programs
  • Analytics Consultants, Blogs and Guru Sessions
  • Community Forums & Industry Associations
  • Academic Programs
The Reports are (6 and 9 pages), free and well worth a read - the only thing I am missing here are the European vendors, whether that be IndexTools or Nedstat. I am sure Lars Johansson would agree with me here? :-)

John included the following comment under his, Have You Been Blogging Today - section : “A sampling of prophetic blogs and bloggers includes:
Each of these sites can provide hours of education and are likely to rock your notions of web analytics while maintaining the ability to teach you something you didn’t know.


This is of course flattering and I am happy to see that he noticed the blogs that matters to me as well - I ofcourse have an additional 1x on my list as well :-)

Other Links:
Aberdeen on Web Analytics Education – By Jim Novo

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What and how to measure Social Networking websites

posted by Dennis R. Mortensen
Sunday, July 15, 2007
Bookmark: What and how to measure Social Networking websites

By social networking websites, I am talking about the likes of Facebook, Myspace, Linkedin, Xing and StudiVZ (and of course any other web property who are engaged in Social Media activities – like any decent blog you know).

Social Networking is the prime headline for Web 2.0 and highly successful so far. This fact only leading towards an even greater responsibility in trying to measure ROI on ones social networking activities, especially as it is somehow agreed upon that only a limited number of players can win (having Metcalfe's law in mind). Remember how quickly Friendster somehow lost momentum, I bet you that they did not deploy detailed analysis, at the level required in this game, within their organisation! – if so, they would have spotted the decreased user engagement and its relating metrics in time.

First I would like to conclude that one have to accept that however sexy social networking is as a trade, there MUST be a set of measurable KPI’s that are strongly aligned to ones business objectives, like any other organisation that operates with the web being a channel of theirs. Hereby concluding that KPI’s are meant to be acted on and not just reported on. Most of the social networking sites that I have been working with somehow work to optimize the following two business objectives.


Social Networking business objectives:
  • Increase Advertising and/or premium member-ship Revenue
  • Increase User Engagement

Now that we have clear business objectives defined – and some that in my humble opinion are pretty much spot on in regards to the overall success of any social networking business. Assuming that you agree with me, we now have the opportunity to define a set of specific KPI’s and accompanying important metrics.


Social Networking advertising revenue KPI’s:
  • Advertising Revenue
  • Visits per week
  • Ad units per visit*
  • Ads served*
  • Ad CTR

* The “Ad units per visit” KPI is a replacement for the old "page views per visit" as a way of indicating the size of your Ad inventory and the “Ads served” KPI is the actual number of revenue generating banners or other media type served in those units.

Remember, that when talking about these 5 important KPI’s (and no business should really have more than 5 KPI’s on a management level) – we are not just talking about a set of basic reports on their performance in retrospective – we are talking about collecting data on a granular level so that we can both report AND more importantly do analysis on these – by segmenting, slicing and dicing them any way imaginable.

In the end for any Social Network to succeed and survive it’s users have to be engaged with the website - and that engagement actually turns into positive revenue as they spend more time, take more action and convert on a higher rate than non-engaged users. Concluding that we are looking at a win-win-win situation for the user, the social network and finally it’s advertiser. We of course have to agree on what “user engagement” is to begin with and inspired by Eric Peterson I would say:

Social Network User Engagement is an estimate of the degree and depth of visitor interaction on the website against a clearly defined set of measurable goals.” – and with that in mind we can define our KPI’s.


Social Networking user engagement KPI’s:
  • User Engagement*
  • Anonymous visitors to members conversion rate*
  • Active member length
  • Time since last login
  • Total time spent on site

* The “User Engagement” KPI is a custom session metric designed and calculated from a set of basic metrics such as for example; pages viewed, time spent on site, time since last login, comments or other content submitted, subscribed to a feed or alert and so on – the calculation of this KPI is highly dependent on the structure of the Social Network in question). The “Anonymous visitors to members conversion rate” is very much a growth KPI that is used until the Social Network reaches its final plateau.

I think it is of the utmost importance (as in any other media company) to understand what benefits the advertiser and how he get the best possible ROI. Social Networks have the opportunity to create value for the advertiser far beyond the click -- if the Ad creative and Ad content showed allow this -- so it is also important to track the actions taken beyond the click (and in general for the website). Such accompanying social network user engagement action metrics like:

- Forwarded advertiser content
- Endorsed advertiser content
- Rated advertiser content
- ..and other obvious types of engagement with an advertisers content

As you can see the secondary audience is as important as the immediate audience and somehow one should be able to illustrate that value to ones advertisers - as in being able to increase revenue based on the fact that the advertiser gets proven value increase by word of mouth with the secondary audience derived from the immediate audience.

I also find it important that one set up specific custom fields for tracking such accompanying social network user engagement metrics like:

- User profile completion level
- Premium member level

Both the accompanying set of metrics for advertiser and user engagement are super specific - so the above two small lists are only a couple appetizers. More importantly how do we “work” the KPI’s


Social Networking KPI control elements:
  • KPI Targets
  • KPI Indexes
  • KPI Competitive Intelligence

I am sorry to add to the list of tasks, but one simply have to create a credible target for every single social networking KPI that we discussed above (credible as in utilizing competitive intelligence to set realistic goals) so that there is a clear driver within the organization on where it is going. At the same time while working towards those targets one need to create a sensible social networking KPI index that can be used when doing analysis for the KPI in question (sensible as in taking into consideration how the KPI fluctuates due to season, campaigns and other factors). Finally utilizing competitive intelligence to spot market opportunities for optimization and general KPI improvement.

NOW - having clear business objectives, 10 well defined social network KPI’s and a set of KPI control elements in place - we get the opportunity to put all this to work, as in nobody should go to the extent of setting up a framework as the above without aggressively pursuing a performance improvement in ones business objectives. It's really not worth measuring something if you cannot or will-not take any action on it, and to be worth taking action on, it has to have some kind of measurable monetary value. There is no magic 7 points to optimize, but given the framework as described above one would have an unlimited number of opportunities to make more money! - find a couple of suggestion below:


Social Networking optimization opportunities:
(7 basic and to some extent obvious suggestions)


My first comment is that before trying to optimize anything for the better - some sort of potential monetary valuation should be put on the effort as in; are we looking to increase revenue EUR 10.000 per year or are we looking to increase revenue EUR 2.000.000 per year and with what certainty can this be determined.

As an example, let’s say that we have 15 Ad units served per visit and that we have an Ad unit CPM value of EUR 3 and that we have 1.000.000 visits per week (notice how all of these are KPI’s) – this leaves us with a weekly Advertising Revenue on = EUR 45.000 (1.000.000 visit * 15 Ad units per visit / 1000 (CPM) * 3 EUR). The optimization opportunity in question estimates that we can increase the number of Ad units served to 18 by adding a small additional unit AND that there will be a 0.30 EUR decrease in Ad unit CPM value due to this (notice that we utilize out KPI’s index here). Therefore an monetary opportunity on EUR 3600 per week or in perspective approximately an opportunity per year of an additional EUR 188.000 in revenue!

Here goes is my 7 basic and obvious suggestions (very specific and less strategic though) on what you should look into when optimizing a social network:

  1. Segment users based on their community activity (this could be anything from viewing pictures or videos to commenting and participating in forums, this is essentially all the defined actions in your web analytics package) - and list this according to the Ad CTR KPI and comparing the different segments to your Ad-CTR index. This giving you an opportunity to do better internal promotions (as basic as a link in the right place) for better converting content (that above your index) on poorer performing content pages.
    Opportunity: To increase the Ad CTR and thus the Ad unit CPM value.

  2. Segmenting the Anonymous visitors to members conversion rate KPI by campaign channels (in my world ALL incoming traffic should be part of a campaign, this including SEO activities) to find and focus on better performing channels and campaigns.
    Opportunity: To increase the Anonymous visitors to members conversion and thus if visits are constant the number of new members

  3. Perform single-page FORM Analysis (tracking every single FORM field) on the sign-up page and cross-reference this to the Anonymous visitors to members conversion rate KPI - getting to know which fields make Anonymous visitors abandon the sign-up form.
    Opportunity: To increase the Anonymous visitors to members conversion and thus if visits are constant the number of new members

  4. Create a custom report with the metric Time since last login KPI and a grouping by entry pages. Filter out all user who have visited the site the last 5 weeks so that you end up with a list of somehow disengaged users who returned to the site. The most successful entry page for disengaged user should be the one heavily used in e.g. Email Marketing. (A common page on this list is the “Your Friend x added you as a friend”).
    Opportunity: To decrease the Time since last login and thus increase the numbers of Visits per week and thereby increase Ads served and finally increase Advertising Revenue as a result. At the same time increasing Active member length.

  5. Run an out of the box standard Action Participation report and add the User Engagement KPI – creating an easy an instant understanding of what content triggers a passive visitor to become a active contributing user and member of the community. As of now you probably do not really know whether the highly engaged users connect to the community by watching user submitted videos, read gossip, chat with friends or what have you.
    Opportunity: To increase the User Engagement compared to our index and thus we typical see an increase in Visits per week and thereby an increase in Ads served and finally increased Advertising Revenue as a result.

  6. The Total time spent on site KPI is not only important because Nielsen//NetRatings has officially replaced "page views" with the "time spent" metric for their official ranking -- whether you agree with Nielsen or not -- it is still very important to know which content groups that users spend their time on - the most valuable resource they have. Create a report that shows Total time spent on site divided per content group and conclude the individual standing on these content groups weighed against your competitors using competitive intelligence. Not as a relative result, but as in looking at the fact that if a user is willing to spend 15 minutes watching user generated videos in general, this is the actual number to target). Optimizing content groups that deliver below industry standard time consumption.
    Opportunity: Increase Total time spent on site and thus an increase in Ads served and finally increased Advertising Revenue as a result.

  7. Try to increase the “quality” of your Ad units per visit KPI by using External Data Sources and relate your internal user database to the Member-ID tracking done by your Web Analytics package (this will give a plethora of opportunities), but one obvious is generating a simple report by content area and thereby get insight into the demographics and sociographics for every specific content area (network of people).
    Opportunity: Increase the Ad unit CPM value by demanding higher pricing for better targeting and at the same time expect higher Ad CTR

..and a bonus optimization comment/suggestion inspired Jim Novo on why using the “User Engagement” KPI on a management level can save your business (or Job). Let say you have a Social Network for students and the number of members and total number of actions in general is increasing (up and to the right), but the “User Engagement” KPI and the related “Time since last login” is decreasing in value more rapidly – then at some point the disengaged users overpowers the increase in members and the website starts to spiral downward in volume. One can predict this downward spiral will happen by monitoring these KPI’s (even as a basic management Alert in your Web Analytics tool) so one can try to take action before it's too late. Most people look at volume as a measure of popularity and growth and by the time volume starts dropping, it is already to some extent too late to save the website. The audience has already disengaged. The user engagement drops off before the traffic volume does, and that is why user engagement is predictive and directly addresses future value.


Even though these 7 basic suggestions + bonus comment (and both you and I could come up with 50 others) somehow seem simple – I am confident that anybody running a social network would be far better off looking at and concentrating on the KPI’s framework described.

My overall conclusion is that one cannot be successful -- in the long run -- running any social media activities if not one or more activities around enterprise optimization analysis is deployed - and I hope that the above somehow indicated and inspired which direction to go in.. sorry for the partly long post (essay) :-)

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Tracking RSS subscribers via the IMG tag - a quick Web Analytics HACK

posted by Dennis R. Mortensen
Thursday, July 5, 2007
Bookmark: Tracking RSS subscribers via the IMG tag - a quick Web Analytics HACK

The single most intriguing KPI running a blog is: “# RSS Subscribers” – and most of us, get our daily fix through FeedBurner or a similar service. BUT there is typically a disconnect between this essential blog KPI and the remaining KPI’s, which usually are tracked by ones preferred Analytics Tool such as IndexTools, WebTrends or Google Analytics.

A typical reporting on the # RSS Subscribers - KPI looks like this:


note: RSS subscribers trend from 21st June 2007 to 4th July 2007 from the feedburner VisualRevenue.com/blog report.

However; there is very little opportunity to do analysis on this KPI, given the environment where we get it from -- and the limited data that it can be paired with -- thus we end up looking at the reporting only. Therefore, it is important to move this KPI into ones standard web analytics tool and there is a quick and dirty Web Analytics HACK to do so :-)

1.
Set up an Action (Goal) for you to track the # RSS subscribers. This is how it is presented under your IndexTools action settings:
 



2.
Customize the noscript pixel part of your tracking code – so that the previous created custom action is recorded. The syntax is as follows in e.g. IndexTools:

http://stats.indextools.com/p.pl?a=100012771897&x=5

a = the project that you want the collected data to be stored in
x = the action you want to set

 
Here is where you can locate this IMG tag in the code. this is quite similar from tool to tool.
 


3.
In RSS 2.0 you would include the above URL as an image as part of your channel definition or in ATOM you would include the above URL as part of your atom:logo definition. If you like me, run a service like FeedBurner, there is no need to fiddle around with the above RSS or ATOM syntax, you simply specify a “Feed Image” for your FeedBurner Feed. This is where to paste the above URL in FeedBurner:



That is it! – you now have a “real-time” # RSS subscribers metric available in your Analytics tool.

NOW! the bigger question; Without even describing how to actually define and conclude on what a RSS subscriber is – I take for granted that the delivered subscriber number from FeedBurner is somehow a de-facto standard and trusted. That said; comparing the number of subscribers as delivered from FeedBurner with that collected through the IMG tag; we get the following result (for this blog):



Is this accurate data; NO! – does it matter; NO! :-) – what matters, as most of the industry have been preaching for years, is the trend – as long as you are doing analysis! It should be said that if you are generating revenue of your RSS subscribers you would need the most accurate top line number of course. Just by looking at the above FeedBurner vs. IMG tag comparison, one can see that the Trend is very similar. Yes! there is a factor 4 difference in the actual numbers, but why would we care about that in most of the analysis that we are doing?

By adding a linear trending on the dataset we will get and even better idea on whether we can use the IMG tag for any serious analysis.
 


This shows (or actually my RAW calculated trend line numbers) that the GROWTH percentage is 26% when looking at the IMG tag data and 15% when looking at the FeedBurner data. However; looking at the data, any linear trend line will be a tad off with the limited amount of data and this much fluctuation. I am actually quite confident that this will become even more accurate from a trending point of view, when I get more data, as a lot of the fluctuation can be sorted out by looking at it from an e.g. week basis.

So the conclusion is -- and this is based on a 14 day short data sample, and I might change my mind -- That I believe it is very reasonable to use this quick hack to start doing some RSS subscriber analysis! – As in e.g. where are my readers located?
 


Paris? - I am actually wiser now! :-) .... Bonjour, je m'appelle Dennis.

Another great article on the Subject (Webtrends example included) is:
Web Analytics and Feeds #1: Feedburner (by: Eric Butler)

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Book: Whatever You Think, Think the Opposite

posted by Dennis R. Mortensen
Monday, July 2, 2007
Bookmark: Book: Whatever You Think, Think the Opposite

Most of the reviews that I have read about: Whatever You Think, Think the Opposite by Paul Arden have been negative and therefore it is with even more pleasure that I highly recommend it. The “book” is quite small. It is also fairly short. But Paul’s statements are extremely strong and you know he is right as you go from page to page - agreeing to most of them!

– the book is essentially about being comfortable with making decisions and mostly bad decisions and learn how to live life with the fact that taking risk is the best security you will ever get. But as an Entrepreneur there are simply too many great nuggets for me to mention them all. However; there is one takeaway I would like to publish (my rephrased version) as I think we all might forget this from time to time working with Web Analytics or Affiliate Marketing:

For any analytical and detail oriented person starting out on a career in Web Analytics, try not thinking about magic tools and metrics or whatever – Think about Money. It’s honest!”

I think this statement alone justifies the 2 hours reading the book. Happy reading.. I am off to: “The Black Swan” by Nassim Taleb.

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