Jim Novo has really stirred up the hornet’s nest now. His post on “Analyze, Not Justify“, is a great read. Down in the comments Jim links to another post “Fear of Analytics“. It’s another good read. It all goes to the culture of analytics. There are people who are fail tolerant and people who are fail avoiding. I don’t see how people can survive without a healthy balance of failure and success. Repeated success is required for confidence building and repeated failure is required for learning. Like everything, there’s a downside too. Repeated success can lead to arrogance. Repeated failure doesn’t guarantee that somebody will learn, either. The fail avoiding behavior, if it persists too long, results in stagnation and,[…]
Author: Christopher Berry
Recently I wrote a review on Website Morphing for the Web Analytics Associations’ Research Committee. You can go ahead and take a look at it if you want. I’ll wait. Website Morphing represents a coherent method for automating incremental optimization. It’s not perfect. Morphing will require a heavy amount of human creative and analytical inputs. It’s the social technology that’s one of the big problems with Morphing, not the physical technology under the engine. People with diverse skill sets often have a hard time working together. It’s hard to communicate complex concepts with people who don’t share your vocabulary. Sometimes it’s like being an English Speaker in Germany, an increase in volume doesn’t equal an increase in comprehension. Those skills[…]
I’m presenting “Practical Social Analytics” at NetChange (Twitter search: #netchange ) tomorrow. The challenge of the session will be for charities to figure out how to practically measure the effectiveness of their social objectives, using social media. It’s going to be a great. I’m looking forward to meeting people who are new to me (just because I haven’t met them yet doesn’t make them ‘new’), and hopefully – preferably, building some bridges. There’s some trolling going on. I have been spending a disproportionate amount of time figuring out social media measurement over the past quarter – and an even more amount of time over the past three years on goal alignment strategies: so I come with a point a view[…]
First and foremost: Sentiment Analysis, Anyone? is the continuation of an ongoing push to bypass all the pain and suffering ahead of us on the social analytics front and move straight onto the good stuff. I want to avoid a lost decade scenario, and just bypass the trough in the Gartner Hype Cycle. It’s a lot to ask for, I know, but please – could we just make the decision this time to jump to the good stuff? It’s worth a read and it lays out a very specific challenge. Next is this theme of the “Power of Weak Ties”. There’s an early paper (1954 I think) on Word of Mouth marketing which proves a strong tie between two individuals[…]
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[…]
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[…]