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A year ago Forrester Research Inc. published The Forrester Wave(tm): Web Analytics, Q3 2007 report which included a bubble chart depicting the Web Analytics vendor’s landscape.

The vertical axis represents the vendors Current Offering.  In a scale value of 0 (weak) to 5 (strong) accounting for the following factors:

• Data handling: How well does the vendor handle data?
• Reliability: How reliable is the vendor’s hosted/ASP platform?
• Metrics, dimensions and correlations: How robust is the product’s set of metrics, dimensions and correlations?
• Reporting and analysis: How robust is the platform’s support for reporting and analysis?
• Integration: How well does the product integrate with the client’s technology ecosystem?
• Usability : How well does the product conform to software usability best practices?
• Service and support: How robust are the vendor’s service and support offering?

 
The horizontal axis represents the vendors Strategy in a scale value of 0 (weak) to 5 (strong) accounting the following factors:

• Product direction: How strong is the vendor’s product strategy?
• Commitment: How many employees does the vendor have dedicated to this product?
• Reference client strength: How strongly do reference clients endorse this vendor?

The size of the bubles represents the vendors Market Presence in a scale value of 0 (weak) to 5 (strong) accounting the following factors: 

• Installed base: How large is the vendor’s installed base of customers for this product?
• Industry presence: Does the vendor have a significant presence (15 or more enterprise-class clients in the following industries? (Banking & Financial services, Leisure & Travel, Entertainment, Retail and Publishers)
• International presence: How suitable is the vendor’s product for use worldwide?
  

I hope their 2008 Q3 report comes out soon! While I waited for it, inspired on James Surowiecki’s The Wisdom of Crowds, I set-up the following Experiment.

Why not pick up the brains of Web Analytics Demystified Forum members to build the same chart and afterwards compare it with Forrester’s Reserch updated report.

The experiment is over. See the results here.

It’s really simple

Could you value these 3 dimensions (Current Offering, Strategy and Market Presence) for the following vendors Omniture/HBX, Coremetrics, Webtrends, Google Analytics and Yahoo Analytics?

Answer based on your experience as a Web Analyst and WA market knowledge. Take the survey now

Jaume Clotet sends me this meme asking me about:

Most relevant happenings related to emarketing during 2008 (in Spain).

1. The world (including Spain) followed Beijing Olympic Games online (on desktop and mobile devices).
2. Spanish Facebook users grow almost 600% during 2008, reaching 2,3 million users.
3. We had a lot of Web Analytics buzz, a successful WA Practitioner event paved the way.
4. Mobuzz-GATE and its lessons on online reputation management.
5. The fact that online marketing has been spotted as a key element to overcome the current economic mischief.

My wishes for 2008

1. That we, online marketing professionals, show our true colors through the economic crisis helping organizations out of it.
2. More focus on ROI analysis, beyond broad traffic and conversion figures.
3. Embracing of a worldwide certification for Web Analytics professionals.
4. Spanish Internet start-ups innovating more on  business model (hopefully successful too).
5. Everybody thinking about WASABI and the value it provides to organizations.

Finally since I don’t want to kill this meme… Varis and Albert what do you think?

I bet you have heard about Marketing Mix 4Ps (Product, Price, Place & Promotion) or Entrepreneurship Funding 3 Fs (Family, Fools & Friends).

I thought it was about time Web Analytics got a marketing-like-named framework (so far we had Trinity). Here is something lighter you can use to explain your job, pitch a prospect and also as an initial analysis strategy.

Web Analytics’ 5Cs are, Campaigns, Content, Customers, Conversion and Competition.

Campaigns (/Traffic Sources)

• Which traffic sources are driving the most traffic to your site?
• Which traffic sources are driving quality traffic to your site?
• Which traffic sources are efficient (cost-revenue wise, ROI analysis)?
• What does a traffic source can tell me about that visit

Content (/Product Offer)

• Which contents are more popular?
• Which contents/products generate more revenue?
• Which contents are entry points to your site?
• Which of those contents have high bounce rates?
• Which content are driving organic traffic (through what keywords)?
• Which contents have high exit rates (any of those is part of a funnel, form or conversion process)?
• What features are working (insite search, tag clouds, dynamic content blocks)?

Customers (/Visitors)

• What is your rate of returning visitors?
• What % of your visits sees more than n page views per visit?
• What % of your visits stays more than t seconds per visit?
• How does the recency histogram fluctuate over time?
• What is the geographic origin of your visits?
• Can you segment them based on metadata available at login or based on behavior on your website (survey, forms and keywords)?

Conversion

• What traffic sources have higher conversion rates?
• Which contents have a higher impact on conversion (Google Analytics Money Index)?
• How does a conversion funnel perform?
• Are there any products with a better conversion rate? Is this general or specific for traffic sources, visitor segments or content paths?
• Can you identify visit segments with high conversion rates (low hanging fruit)?

Competition

• What is your competition doing (SEO, Adwords, Ads, offline)?
• What is your competition offering?
• What share of traffic is your competition getting (Hitwise, Compete, Google Trends)?
• Is your competition HOT (Buzz monitoring)?

This post is just a reference and I’m probably missing several ideas that could be added to this framework. If you have any they are welcome.

Have you ever wondered what the last column of your Top Contet reports showing $ Index stands for?

Well, this is a very short explanation!

If you have monetized your traffic within Google Analytics (either by assigning a value to a goal or by tracking ecommerce transactions with a value) you will see a $ index value that is calculated like this:

For each content:

Sum up the revenue that was generated after visiting that particular content and divide it by the total visits in which that content was viewed at least once.

So imagine yesterday you had only 2 visits that viewed the following content:

• Visit 1:   page 1 > page 2 > goal page > page 3
• Visit 2:    page 2 > page 3
  

Goal page has been assigned a value of $ 2. What is the $ index for each page (for yesterday)?

• $ index page  1 = $2 ($2 divided by 1)
• $ index page 2 = $1 ($2 divided by 2)
  
• $ index page 3 = $0 ($0 divided by 2)
  

As you can see the money index (especially for contents with a lot of unique views) can be understand as the expected revenue of a visit that sees that content. If we are able to increase traffic to these high $ index contents without dropping the figure will be increasing our overall site revenue.

Good treasure hunt!

Yesterday I attended the last Conversion Thursday of 2008 in Barcelona. I haven’t been to one since the very first, at least in Barcelona. I was surprised by the amount of people, more than 70, especially when I was told yesterday’s gathering had not been the most crowed of all. Good for Pere and Jordi!

The agenda included 3 things:

1) Free welcome drink!

2) Experts panel to discuss what to expect and look for in your Web Analytics tool during 2009

3) Networking and mingling

In 45 minutes Enrique Quintero, Victor Pascual, Pablo Román, José Panzano and Niklas Schappkohl answered Pere’s questions from the point of provider, university, consultancy and customer (not everybody in the panel had an exact match to one of this roles). 

I heard them talk about web analytics, visualizations, statitical significance, data predictors, smart tools, adaptive tools, automatization and actionability and I kept coming back to an acronym that I have thought of a couple months ago, WASABI (Web Analytics, Statistical Analysis & Business Intelligence).

I have been working for more that 3 years in Web Analytics and I really wish I could get involved in more WASABI projects. It seems that 2009 will be the year to do so and I’m very happy.

So happy I made a t-shirt (And you can get yours here).