The rumours about my demise are grossly exaggerated. No, wait, there are no such claims. But maybe there should be? This blog has been painfully dead compared to previous years.

At one point this blog was one of the voices of the industry, now others have surpassed it. This blog was born roughly at the same time as Avinash’s blog. Needless to say his blog has been a resounding success, and maintains its focus to date. Mine has room for improvement!

I would like to apologize to you, dear reader, for the low activity rate on this blog. I still enjoy going back to it though.

This blog is somewhat of a museum of web analytics. You’ll find web analytics memorabilia, old web analytics vendor comparisons (find interviews, screenshots, facts, and comparisons of tools that no longer exist as well as ones that are still going strong—I challenge you to search for any tool on this blog), the first eight Web Analytics Wednesdays in Stockholm (2006-2007), information about web analytics around the world (Australia, China, Korea, Thailand, Singapore, India, Brazil, Japan, etc.), countless of interviews with the CEOs and rock stars of our industry (including Avinash Kaushik, Eric T. Peterson, Dennis Mortensen, Bob Page, Jim Novo, Jim Sterne, and Seth Godin), old predictions (including my own crazy predictions and dubious observations), early mobile analytics, and more.

Other posts have ranged from free KPI development for a specific website to more hardcore GA API stuff to vendor research to broader concepts to comparing you to monkeys and my mom, and a lot more.

I’m particularly fond of some of the podcasts that I’ve made, like Web Analytics in Europe 2007 (widely appreciated), and the Roundtable Podcast on Testing.

If tools like Offermatica, Visual Sciences, ClickTracks, ClientStep, Optimost, and Widemile sound familiar to you, then you’ve probably been around the block for some time as well.

Over the years I’ve been instrumental in the release of a free Google Analytics addin for Excel, and the free code for a GA app for iPhone.

I’ve worked for Satama, started Digital Days Stockholm, and helped organize Internet Marketing Conference in Stockholm, Vancouver, and New York.

I’ve written articles about web analytics for several large Swedish publications as well as for the American Website Magazine (10 Terrific Testing Tips and Evaluate Editorial Impact Using Google Analytics), and been interviewed on WebmasterRadio.FM.

I’ve also spoken at numerous conferences, and helped make the program for eMetrics Stockholm 2010 and 2011. I took Web Analytics Wednesday and Web Analytics Association to Sweden.

What I’m most happy about though is taking the step I did last year. I had been thinking about what to focus on, how great team members are found, and how to build something where I can give something back. Well, in 2010 I was instrumental in founding two new web analytics companies: inUse Insights and Ampliofy. The former is a web analytics services company, and the latter is a product company working on four products based on Google Analytics. Being based in Sweden seemed like a good idea.

I’ve always wanted to build a company the way it should be built. It should consist of skilled, fun, helpful, and innovative people. If you think you can do things better, give it a shot. If you never try to do it, don’t comment on what others do. My goal is not only to grow the business, but to do so with generous employee benefits, and the ability to contribute to the community (both to the web analytics community and to greater good).

Ampliofy’s (the name is a combination of the Latin word amplio and the English word amplify) products will add data to Google Analytics, and show data in new ways. We have also developed a better, more advanced, professional version of Excellent Analytics. It has been coded from scratch to be more efficient. Keep an eye out for it! The open source version will still exist, but the pro version will add more power to businesses and organizations.

inUse Insights has been profitable from day one, we’ve recruited several people, and we have given away hours of work to charities.

If you e-mail me I always try my best to take my time to respond. I have never said no to meeting students interested in web analytics, I’ve found many people work (not only for my own company), and I’ve given plenty of free support for Excellent Analytics. Don’t hesitate to ask anything. I’m very busy, but I try my best to help. Just don’t take advantage of it by trying to get free consulting for your business.

See, I’m not dead. I’m just very busy! Once again, my sincere apologies for this blog being so dead. I hope to find time to change that!

Though I have that book I’ve promised to write too..

In the meanwhile, check out the Swedish blogs I’m a frequent contributor to:
Webbanalys.nu
inUse Insights’s blog

Do you agree that people are more important than tools? Do you think that actions are more important than reports? If you do, have a look at The Analytics Manifesto.

It’s an initiative by me and Christoffer Luthman. The Analytics Manifesto was developed to unite all stakeholders in web analytics about some core principles.

• People over Tools
• Change over Condition
• Actions over Reports
• Tests over Assumptions

Have a look at the manifesto, see if you agree, and like it on Facebook if you do. Go to the page, read the manifesto, scroll down to the bottom, and “sign” if you agree.


Many editors feel that once content has been created and uploaded, their job is done. Wrong! The next step is to analyze how well that content is doing its job. Using a web analytics tool, you can measure its effectiveness. It is possible to measure how well the content is performing even for purely informational websites, including intranets, that are not supported by ad or product sales.

If you don’t measure, you can’t analyze. If you don’t analyze, you can’t improve. Get Google Analytics if you’re not already using a tool. It’s free, so there is no excuse not to use it. And, yes, it works for intranets, too.

One of the first things you need to do—a step that is easy to miss—is to make sure you filter out writers and editors from your stats. Otherwise you’ll get inaccurate data.

You are not allowed to store personally identifiable information (such as social security numbers or names) in Google Analytics. You may, however, store data that can group visitors together in different clusters. For intranets that may be things as divisions and departments. For websites it could be consumers and businesses. By using custom variables to group visitors together, you’ll be able to analyze how different groups of visitors behave.

Keep in mind that file downloads are not automatically tracked by Google Analytics. If you want to track, say, PDFS, you need to trigger a virtual page view when a visitor is clicking on links to them.

Six measurements to maximize the impact of your content
Here are a few key performance indicators (KPIs) you can track to see how well your information is performing. There are many different things that can be measured—which KPIs are best to track varies from company to company, site to site. If you feel uncertain, talk to a web analytics consultant.

Too many pages and don’t know where to start? Prioritize which pages to optimize by looking at such things as bounce rate, read rate, $-index (monetary or goal value contribution) and satisfaction. Also check page view volume (tells you something about impact) and number of entrances (tells you how relevant the bounce rate is). Some of those metrics require additional configuration and JavaScript code on your website.

1. Readings per writer and writer impact
Find out how many times articles by a particular writer are being read, the number of conversions that happened during visits where the writer’s content was read, how long those visits lasted (best measured in intervals, use the Length of Visit report under Visitor Loyalty), and more. This is done by segmenting and creating custom reports based on a custom variable, as described below.

How to measure it: You need to edit the tracking script on your website that is used by Google Analytics. Trigger a page-level custom variable after a certain number of seconds on a page. Base the timer on a reasonable amount of time it takes to read an article. Add the name of the writer to a custom variable and the URL + “(read)” in _trackPageview(). This will result in the writer’s name being tied to the page and the page being marked as read. In “Top Content” you’ll have two entries for article1 looking like this: “/article1/index.php” and “/article1/index.php (read)”. You can filter the Top Content report by “(read)” to see how many times different articles have been read. If you only want to look at articles by a specific writer, use an advanced segment based on the custom variable containing the writer’s name.

Keep in mind that triggering an extra page view, as will be done above, will affect other metrics such as number of page views, page views/visit and bounce rate.

2. Page impact
If you have configured goals, you can find out how frequently visits, during which a certain page was viewed, led to goal completions and what the total goal value was for those visits. How well have those visits performed compared to other visits?

How to measure it: Create an advanced segment including only visits during which a specific page, or a certain group of pages, has been viewed.

3. Satisfaction
Measuring visitor satisfaction per writer and page adds an important extra dimension to your analysis. Imagine if you could find out how satisfied readers of specific writers are? Well, you can!

How to measure it: There are two ways. You can incorporate the possibility to give a rating for an individual page, or you can trigger a survey after the user has done certain actions, spent a certain amount of time on the site, or left the site. The key is to store the grade in Google Analytics. By combining behavioral and attitudinal data in Google Analytics, you’ll be able to see how frequently certain pages, or writers, have been involved in high and low satisfaction visits. Survey data can be stored as custom variables or virtual page views depending on what works best for you.

4. Time spent writing vs. reading
This measurement can tell you if there are pages that readers spend less time reading than the writers and editors spend creating. It is particularly valuable for intranets or websites with low traffic. If you spend a lot of time on an article and few people read it you’ve either failed at marketing the article or it’s simply not appealing to readers. Besides learning what content works best, this KPI will let you know how well writers are spending their time.

How to measure it: This requires a CMS hack.

Caveat: It will paint the true picture only if all writing is done directly in the CMS.

5. Unread pages
Pages need to generate at least one page view to be included in Google Analytics. Pages with no views won’t be listed. If you do not track unread pages, you won’t be able to accurately measure the average amount of page views per article or the average amount of readings per article. Both of those metrics are valuable to look at to evaluate content.

How to measure it: To find out which pages did not generate a single page view or reading, you need to match a list of pages from your CMS with page view data from Google Analytics. I recommend using Excellent Analytics, a free plug-in for Microsoft Excel, when combining data from Google Analytics with data from other systems. You can download it for free from: http://excellentanalytics.com/.

6. Cost per reading
Some organizations have goals stating that writers need to produce a certain amount of articles per week. I believe that it is more important to measure the impact of a writer’s articles.

How to measure it: Cost per reading = writer cost/number of times the writer’s articles have been read.

Better articles should generate more readings. Writers should strive to achieve a low cost per reading and a high satisfaction score.

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Note: I originally wrote this article for Website Magazine in March. As a favor to them they got to use it exclusively until now.