So just what have I been up to? I’ve been dividing my time between a major initiative and product development. Much of my involvement revolves around Evidence Based Marketing – and it’s literally that deadly. It’s that level of sustainable competitive advantage. It’s like a Philosoraptor armed with an RPG, riding a shark. Yeaaaaaaaaaaah. The most interesting aspect has been the integration of measurement science with information architecture with development with creative with product development. There are continuous collisions between the desire for intuitive simplicity with utility with robust functionality with elegant design with data accuracy – all within budget and a desired launch date of yesterday. The best business models are those which you solve a problem for a[…]
Author: Christopher Berry
I’ll be in London next week for a whirlwind 46 hours, coming for eMetrics and staying for the company. I’m looking forward to talking to Lovett to carry on where we left off two weeks ago. I’ll be talking more about Villanueva and linking in Earned Media Value (EMV), as well as talking about the differentiation in the definition. I’d like to meet up with Andy Lepki who does the analytics over at The Guardian. There are a few tweeple on the list. If you’re at eMetrics London too, don’t be a stranger. I don’t know nearly enough of you. I took in the British Election coverage on BBC World – garnering scorn for how much of it took up[…]
John Lovett and Jeremiah Owyang has written (with others) a white paper on Social Marketing Analytics. I’ll be referencing the report throughout this posting, so go check it out. This response is divided into three parts. It starts with a ‘I see where you’re coming from’, then ‘a few questions and inquiries’ and then ‘a few caveats and ways I’d improve it’. First, I see where John is coming from. John states, clearly, that “The objectives and metrics defined….in this report are a starting point for the infrastructure of social media measurement.” (p. 6). The whole document then goes into a very transparent goal alignment strategy – where four business objectives are lined out based on a goal, then KPI’s[…]
I’m increasingly disturbed by the accuracy of Topic Bearing Word of Mouth (WOM) algorithms. A previous study, published in this space, expressed dissatisfaction with standard sentiment analysis. My mind has since turned to the difficulty in expressing massive amounts of WOM into simple metrics that are actionable and decomposable. So let’s just go beyond the realm of evidence based pre-optimization of marketing messages, and set the entire area of sentiment-bearing word polarity aside for awhile. It’s relevant and important. Just not the focus tonight. Let’s turn to topic bearing WOM. Imagine you could listen to the world, and assume that Burke’s reality is now…a reality. If you haven’t seen the video from my ‘about’ section – here it is again.[…]
For Syncapse, eMetrics Toronto was a success. This post is long, and divided into three parts: a summary, a response to Glinski, and then a few thoughts about the next eMetrics summit to come to Toronto. The first presentation was Theresa Locklear of the National Hockey League. She demonstrated just how far that team had come in just two years. She presented real data – how it’s really presented – across multiple parts of the organization. I applaud that degree of transparency and I applaud her in particular for bringing her entire team. And her analytics team is simply brilliant. They’re well inspired and well informed. Solid. I’ll start with the Quant/Qual mix panel on Wednesday night. There was no[…]
eMetrics is coming Toronto next week. There’s still time to register, and I have a discount code if you want to attend. Tweet me at @cjpberry and I’ll shoot it on over. This will be my third eMetrics in three years, and as such, I’ll offer a few predictions. The panel I’m moderating on Wednesday will go off swimmingly. There will be some controversy as the panelists tussle over what’s really important in the qual/quant mix. There will be enough sparks to ignite some lively debate that evening. The whole Syncapse Measurement Science team will be there in force that night and on Thursday. They’re going to see just how other people present their material and they’ll have quite a[…]
Social media data. Huge amount of volume. Huge amount of complexity and simplicity in structure. Time for a radical metaphor. It’s like the night sky. With the naked eye, you can see thousands individual dots of light. And, humans being human, if you look long and hard enough, you’ll see patterns and start associating events with those patterns. See below. I offer some evidence to back up that claim. Of course, those relationships are one possible interpretation. (And fine. I accept where they’re coming from). If I used something significantly more powerful, like the Hubble, and trained it at a fairly dark part of the sky – (and they did) – you’d see this: Right there – next to the[…]
Pat LaPointe wrote a pretty interesting article for MediaPost Publications. You can check it out here. My response is pretty much ‘Yes, And…’ I don’t understand why some people are making inductive inferences that online word of mouth is somehow reflective of offline word of mouth. (As a certain company appears to be making). I share his concern and skepticism. Let me unpack that. A whole generation of quantitative market researchers are supposed to understand that if you take a small, random sample of a population and expose them to a treatment, then you can make an inductive inference on how the entire population will react to that same treatment. The probability that the inductive inference is accurate is a[…]
Consider the impact of the mechanical clock and the curved lens on early analytics. The mechanical clock enabled consistent, scale, time. You won’t optimize what you won’t measure. And Europeans most certainly started optimizing time. They’ve been optimizing work per time unit, productivity, since the renaissance. Countries that didn’t have a method of measuring productivity simply didn’t optimize it. Worse, cultures that didn’t value the standardization of time simply didn’t value productivity. Why care about productivity when you have loads of population to toss at a project? It put whole swaths of the globe at a competitive disadvantage. The curved lens, aside from giving us astronomy and microbiology, enabled great strides in miniaturization and productivity. A skilled worker could work[…]
The Syncapse Measurement Science team put together an experiment on sentiment analysis, as applied to social media measurement. As promised: Link to the White Paper: syncapse-sentiment-analysis Link to the Data Set: The Geurilla Analytics Project _ Sentiment The paper will speak for itself. We can discuss it here and on Twitter.