I’ve had a fairly rough 9 days with a very troublesome model. My original hypotheses are rejected. A piece of the world doesn’t really work the way that I expected. The great news is that I’m forced to look beyond the clean dataset and write new hypotheses. Even failures can be great. However, it doesn’t make for good commercial reading. Instead of having that nice, clean, nugget: Brands that did x realized y. There’s a much messier message: Neither a, b, c, d, e, f, g, h, i , j, k, l, m, n, nor p had a significant impact on y. That messier message works among marketing scientists. Usually a sound of surprise. Then acceptance when they see the[…]
Yesterday I participated in my first TTMM event, and spoke on ROI. Like any first contact situation, you know they have their points of view, value systems, and language. And the least you can do is have knowledge of why you think the way you do, and why. I told the story about how different versions of ROI is rooted well before anybody in the room had been born. And it’s such a contentious issue because it goes directly to one’s being. ROI is the reflection of your own worth to an organization, and naturally, as such, it’s going to be contended. The approach taken in the Syncapse Value of a Fan study was selected for a very specific reason[…]
What kind of Return can you expect from Social Media? The legitimacy of the answer has a lot to do with your mental model of the world. When I talked first in this space about it in January, I made the distinction between how Direct people and Brand people would answer the question. It turns out that the difference predates the invention of Radio and TV as mass mediums. There was a difference between Claude C. Hopkins approached it, and how Earnest Calkins approached it, as far back as 1890. Hopkins argued for the hard sell and scientific advertising. Hopkins view of time was narrow, short-term, and of instant reaction. Calkins argued for the soft sell and branding. Calkins view[…]
I started tweeting right around when I started blogging on analytics – between May 8 and May 18, 2008. It kicked off professional public speaking, intensified my contributions to the WAA, and pushed me even more into a weak tie among diverse communities. I knew most of my followers by name, and met with most of them monthly. It was just a coincidence that 95% of them were in analytics. Even though I was living between Toronto, Calgary, Chicago, Vancouver and New York, Twitter was a localized, central hub. I was in 5 places at once. Twitter was a place where conversations happened out loud, in public, and other people who were interested in what we were interested in could[…]
There’s a DRY principle in programming, and one that is pervasive in RAILS-land: Don’t Repeat Yourself. The same should go for everybody. From commenting, blogging, to writing books. Repeating somebody’s work in its entirety is pretty unnecessary when a citation would do. What you build off others, how you do intellectual parkour and create something new out of many things old, is what’s valuable. You advance everybody that much further and faster by doing so. And a gap in the literature doesn’t always need to be filled. There might be a very good reason for such a gap. It’s finally time for me to make an original contribution because I have something original to say. There’s a gap that needs[…]
I’ve been heads down with the team for awhile pounding out a study examining the value of a Facebook Fan. The results of that study were presented at Internet Week on Friday morning and can be downloaded here. I have hopes. I hope it throws some wind into the sails of people who are doing good social media marketing strategy. Absolution is frequently sought in simple numbers. The importance of activation strategy should be very clear in the charts and text of the paper. The second is for the lack of misquotes. It would be really nice if it wasn’t misquoted. The third is that I hope you’ll find it useful. In sum, take a look, and feed on back.
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[…]
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.[…]
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[…]
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.