There’s a reason why a few creative people wanted to build entire websites in Flash during the pre-Ajax/Jquery era: they wanted a seamless user experience, without that pageload. It might only take a fraction of a second for a page to load on most sites, but that interruption in the experience has been identified as unnecessary. Inelegant. More can be experienced these days without a pageload. And it’s through the pageload that most web analytics tools capture data. The writing was on the wall for a long time – perhaps since the begining, starting with real player content, quicktime, and then the onset of flash video. As experiences become more distributed, the pageview paradigm decays that much more. The denial[…]
Month: May 2009
John Lovett over at Analytics Evolution talks about the growth of our analytics industry. It’s worth a read. It’s one of the most succinct postings I’ve seen on all our ills. The inflated expectations, the skill gaps, the talent gaps…it’s great stuff – and that’s not just because we happen to agree on so much. There’s a market maturity issue with Google Analytics. GA is great at telling people ‘what’ is going on. In effect, that’s what 90% of web analyst did between 1995 and 2007 – fight with in an effort to determine ‘what’ is going on. The journey ended at the dashboard. Since most people assume that since they have Google Analytics on their blog, and they can[…]
It’s a pretty cryptic tweet, yes. A paper was published in the Journal Marketing Science that just came to my attention. A review will be forthcoming on the Web Analytics Association website. I’ll publish the link once I write it. The article in question is very theoretical and mathematical, but it leverages an area of mathematics that has yet to be applied, practically, to web analytics. What’s most exciting is that the physical technology to make it happen exists. The case study that it works is there. The one sentence summary is: “There’s a way to radically increase the tempo of optimization while drastically lowering both the monetary and personhour cost”. Now the bad news: The social technology is another[…]
Begin with five statements: 1. The set of business questions that could be asked is infinite. 2. The subset of business questions that could be answered by our current toolset set is very large, but ultimately finite. 3. The subset of business questions that, when answered, could be valuable, is a smaller, finite set. 4. This subset is volatile. 5. The current analytical paradigm is ill equipped to grapple with statements 1 through 4. Unpack these statements: 1. The set of business questions that could be asked is infinite. Consider every single combination of characters and numbers that can be packed into quotation marks, ended with a question mark. Consider writing all of these down. You’d end up with millions[…]
In my previous post, I argued that Web Analytics was not easy because of complexity, much of it caused by people. Things can get lost in translation when translating data into actionable insight and actionable insight into action. Let’s turn to the solution, something that Jacques Warren, fellow tweeter (and #wa guru), has termed “Organizational Engineering”. What follows is a laundry list of the elements, considerations, and biases that should feed a successful web analytics organizational design pattern. 1. It all starts with a great web analyst, a few things a great web analyst does or understands: a) Takes the site map, goes through the site, and understands it. b) If no site map exists (which is common), then that[…]
If Web Analytics is so easy, why then is it so hard to get something done with them? Start with physical technology – the machines and software: 1) The accuracy of the data is in question (See the case of Peterson v. Unique Visitors / Cookies) 2) Web Analytics tools are incapable of automating actionable insight 3) Web Analytics tools report hindsight. They typically do not forecast or perform what-if analyses 4) Some Web Analytics tools require very careful calibration to report anything of value Solve the above 4 issues with social technology – the rules, processes, culture, norms, hierarchies and networks that people, tribes, communities, departments, companies and associations have developed over centuries: 1) The accuracy of web analytics[…]
Assume we had all the data we needed. Assume that all the systems were talking together. Assume that insights could be executed flawlessly. Assume that an analyst wasn’t weighed down by reporting. Assume we’ve reached the gates of paradise. Would most analysts know what to do with it? To be sure, we tend to build these systems with some idea of the business questions we want answered. These include: “Who are my most profitable customers?”“What are my most profitable customers like?”“Where can I find new customers like them, cheaply?”“Who are my least profitable customers?”“What are my least profitable customers like?”“How can I avoid attracting those customers, cheaply?” In reality, the set of business questions might be far less powerful. Or[…]