On the Need to Reorganize Approach
Maturity Models for Web Analytics have been a continual topic of discussion among web analytics evangelist. Stephane Hamel, one of my WABITs on Twitter, has put considerable thought in developing the Online Analytics Maturity Model, while others such as Jim Stearn, founder of WAA, have recognized that the actual path to maturity is strung with speed bumps. I have taken my crack at one in “Tracking Multi-channel Behavior in 5 Difficult Steps”, where the steps are iterated again and again to achieve more refined, more inclusive, more difficult objectives set by an enterprise. However, when in the trenches putting the processes, organization and communications in place to get to the next landing on the stair case to maturity, it can be difficult to recognize when one has “landed” and not readily accepted that this means starting all over again to reach the next level. That is why, on an emotional level, the steps are difficult.
Posted in Uncategorized, Web Analytics, Methodology
Tagged Omniture, Google Analytics, maturity model, Web 2.0, IT, web analytic capabilies, Webtrends, Methodology, Center of Excellence, Solution Designer, Implementation Lead, Business Architecture, RIA, COE, aspect oriented programming, AOP, observable application development, agile development, sprints
Beware How You Count Events!
I am aware that a large segment of the HIPPO community advocate visit based metrics, but honestly, one can get into trouble – big trouble – if one blindly adheres to “Visits are what count.” and apply visits like ketchup to every metric entree. In web analytics there are three basic tempos – page views, visits, and visitors (actions over multiple visits). Page views represent the raw vibrance of your web site – lots of visitor actions that are difficult at times to summarize and trend. So to gloss over the visitor churn and their propensity to reload or revisit pages, we often apply visits to metrics to put a wet blanket, metaphorically speaking, over the fire that raging in the page view traffic.
Posted in Measures & Metrics, Web Analytics
Tagged HIPPO, KPI, measures, metrics, Omniture SiteCatalyst, serialization, site optimization, success events, Visitors, Visits, Voice of Customer
Building Reports that Cover All Behavior
In my line of work consulting with various customers I have been able to see common threads in how different companies approach web analytics and apply it to their business. One puzzling aspect that becomes immediately obvious to see but takes longer to understand is how many reports seem to cover only a small portion of web behavior with most visitors and visits pushed into the general category of ‘None’. None meaning that visitor does not belong to any of the categories for the dimension being reported.
A Puzzling Predicament
What is puzzling is: How do such reports provide useful information on visitor behavior? The next question that comes to mind is who are those people that belong to ‘None’ or for the person that implements the report: Did I set up the metric correctly? In brief, How many of that are None should be Something? This has lead me to the concept of “None is not an Option” reporting, meaning None is not a category of behavior but an indication of analytic failure or incompleteness.
Posted in Methodology, Web Analytics
Tagged actionable insights, actionable reports, axioms, best practices, business funnels, Channel Management, classification, conversion variables, correlation, eVars, Google Analytics, Omniture Discover, Omniture SAINT, Omniture SiteCatalyst, Plug-ins, Segments, sprops, success events, tag plans, visitor segments, web analytic capabilies, Web Analytics
An Oxymoron Worth Making?
More recently Oracle CEO Larry Ellison announced Oracle’s entry into the cloud-computing arena with Exalogic Elastic Cloud, that has been dubbed “Cloud in a Box”[i]. Ironically the Cloud is supposed to eliminate the Box[ii], so technically this is an oxymoron following current definitions and trends in Cloud Computing[iii]. For example, elastic is interrupted as being able to scale computing resources to demand by incorporating more virtualized servers in the cloud and hence only pay for resources consumed. A box on the other hand is a set configuration of resources that must be purchased (as a box) and remains idle as a box until peak demand utilizes its entire potential. So how can Oracle claim to have a cloud in a box? Continue reading
Has the Brain’s Plan Been Foiled?
OK – So its not quite breaking news. It took awhile to recover from the shock. For the moment just play along.
Google announced recently that they are suspending further development of Google Wave[i].
Actors without the Lisp.
Just launched on Project Hosting at Google the loafwithjam project. LOAF stands for Live Object Application Framework and supports the Actor Model of Concurrency introduced in my last post. I have upload the documentation for codes that are similar to what have been in operation for web analytics collection and processing successfully for many years. The intent is to initiate a Live Object in a context server when a visitor first arrives at a site and process the events of that visitor in real time. Hence the name: Live Objects. Continue reading
That has been around a very long time.
We have seen in a previous post[i] how Map Reduce is analogous to how business and product managers plan and implement projects with Gantt Charts allowing a number of tasks to proceed independently in parallel and integrating their products at the end. A question from those outside of computer science might be: why has it taken this long to figure this out? In fact, if computers are so fast and capable, why don’t they figure the quickest, most parallel way of executing multiple tasks all by themselves?
Google: Pinky and the Brain
World Domination Plan 137:
Phase 3: Distract before Conquering
While everyone is building out their Hadoop farms[i] and adopting Map Reduce to establish elastic computing[ii], Google is busy building (and patenting) some strange new technologies with names from a Dick Tracy line up – Gears, Big Table and Chubby Locks. Also it is busily building the biggest mash up heretofore envisioned called Google Wave allowing individuals across the web to message and collaborate in real time … at a keystroke level[iii]!
I Can See Your Eyes Rolling
From my blog analytics, I can actually see the eyes rolling as my audience quickly skirts my Cloud Computing posts to go to the old stuff (back when I was funny). In some ways I understand the ambivalence. I perhaps like you are not overtaken by awe with virtualization and utility computing that defines cloud computing today. I would call this more cloud hosting than computing. My urge is to go beyond this in an attempt to grasp the computing part of the cloud. Understand what new capabilities may be facilitated and computations performed. So why should you care?
Posted in Technology, Web Analytics
Tagged Cloud Computing, Cloud Hosting, Glen Beck, Google Analytics, Google Wave, Hadoop, Interwoven, IT, Justin Bieber, Larry Ellison, Map Reduce, Mark Hurd, Marshall McLuhan, Massive Distributed Computing, Tealeaf, Teradata, Web 2.0, Web 3.0, Web Analytics, Web Analytics as a Service
It’s Effects Beyond IT
Cloud computing is a concept best understood within the context of IT[i]. Its primary effect on business is the potential significant saving in capital expenditures (CAPEX) and potentially maintenance (OPEX)[ii] of IT’s hosting assets. This is due to leveraging the scale of large server farms, and the recent ability to allocate slices of CPU, memory and storage on demand within these farms[iii]. This is sometimes referred to as elastic computing or utility computing. Elastic in the sense that additional resources can be allocated to meet periods of peak demand[iv] and utility in that one pays only for resources used[v]. So this would be a boon for startups and for new ventures within established companies to launch new products and services with significantly reduced startup expenditures and time to market[vi]. Continue reading