tag:blogger.com,1999:blog-348588022025-11-27T13:48:37.759-07:00Thoughts, ideas and questions about using content to help people choose.anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.comBlogger588125tag:blogger.com,1999:blog-34858802.post-4279236451950396142015-04-29T09:54:00.000-06:002015-04-29T09:54:52.184-06:00

Where should marketing focus now? If at least one desk on your team doesn't look like this, you're missing out. Source. Given that 'digital is dead' - as in everything is now digital - we should be focusing the experimental portion of our budget should now be working on the interaction and experience itself. This can come in the form of either the Internet of Things where pretty much

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-1464383724100711602015-03-21T09:23:00.000-06:002015-03-21T09:55:37.815-06:00

What did we learn from predicting song popularity? A recent data science competition focused on whether one could predict the success of a Taylor Swift song from less than half a second of audio.  One sample sounded like: The objective was to predict whether that clip (and some 20k others) came from a popular song, or not.  As mentioned in a previous post this is a case where

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-82282869859424027862015-03-21T09:00:00.000-06:002015-03-21T09:00:29.063-06:00

What advantage do marketers have over machines? There are lots of cool examples in the use of math, models and machines to predict, classify and recommend.  Some can be found on econsultany's site. Within the domain of marketing analytics there is the application of machine learning whereby we are simply trying to discern cues about our business from the data.  It works, we can predict

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-7681784144083219422015-03-10T14:15:00.000-06:002015-03-10T14:15:01.177-06:00

What products do my pictures suggest? This is a continuation of an idea that arose from a conversation in a bar around the question: "How does content work?" Recommendation engines typically work with data from one site. We've all seen examples of "people also bought..." on web sites. But an interesting idea would be to link my curated content (Instagram, Pinterest, or Houzz) to the shopping

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-58569674776066448502015-03-09T07:53:00.000-06:002015-03-09T07:53:07.224-06:00

How should we measure our efforts? There is nothing new about the idea of measuring marketing. What is changing however is out ability to do so. Yet, we're not there yet. Metrology, or the science of measurement, requires three things: An internationally accepted unit of measure. How to realize those units in practice, i.e just what is a meter? Chains of traceability between a measurement

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-70095321880326900652015-02-24T12:11:00.000-07:002015-02-24T12:12:18.442-07:00

What's changing in marketing? I stumbled upon a piece in McKinsey's insights section entitled "The Changing Face of Marketing". The author outlines six factors impacting marketing. Customer - "the end users of almost every company’s products are shifting in makeup, location, and number at an ever-increasing rate." Insights - "If knowledge about future customers is essential, and if the

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-27074411303885425582015-02-17T12:21:00.000-07:002015-02-17T12:21:07.384-07:00

What do Taylor Swift's videos have to tell us about marketing? There's a machine learning competition running here in Salt Lake City that deals with predicting the popularity of Taylor Swift videos from snippets of music. And by snippets I mean 1/10th of a second of a song. The goal is to classify whether a song is a 'success' or 'not' (if you can take 30m views as not being successful and 300m

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-23413456905402959012015-02-10T06:05:00.001-07:002015-02-10T06:05:25.096-07:00

How does rainfall relate to sales? The weather service now measure things with such precision that we can determine flat (rain) vs. elongated (ice) droplets, etc. A new project on data science competition site Kaggle focuses on predicting how much rain actually hits the ground from a series observations on the way down. The objective of the contest is to estimate the likely outcomes from an

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-21395499575094734762015-02-05T16:28:00.000-07:002015-02-05T16:28:15.361-07:00

Does auto-classification of images work? There is a trend toward "Analtyics-as-a-Service" where companies can leverage specialized functions on demand. There are predictive modeling options like IBM's Watson and MonkeyLearn for text modeling. There are even image recognition options emerging that offer auto-classification. And as part of a personal interest on figuring out how content works I'm

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-34497630493331604922015-01-29T12:13:00.000-07:002015-01-29T12:13:34.534-07:00

How will agile development affect your calendar? In the second and third installments of "what Agile means to the rest of us" posted originally on LinkedIn Tom and I discuss new behaviors you should expect to notice when working with an Agile team. A new set of questions will emerge and they focus on the business value that a project delivers. The discussion is all about outcomes, not how

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-64012667881354932192015-01-29T11:49:00.000-07:002015-01-29T11:49:43.907-07:00

What does football tell us about how to measure campaigns? A recent installment of Think with Google had a topical piece on football.  In it is the following chart showing the trends in "American Football" broken out by the terms that the search contained: What, Who, When, Where, and Why. The annual spike is the playoff season. American Football Searches: What, Who, When, Where and Why

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-85387281428884140392015-01-27T10:46:00.000-07:002015-01-27T10:46:05.130-07:00

What does it mean to be agile? A friend of mine who has a lot of experience delivering software products based on Agile Development recently asked me about the training course he's developed. I thought it was a perfect setting to explain what the implications of Agile are to the rest of the organization.  If IT is doing things totally different, then we probably should be changing our

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-91871585911347386312015-01-26T11:21:00.000-07:002015-01-26T11:21:52.066-07:00

How should we approach developing insights? The typical path to insights is lined with roadblocks of making sure the anticipated results are scaleable, generalizable and solid enough to base a business on. We typically don't go looking until we're sure that what we find is usable and workable. To be honest, we're handcuffing ourselves; maybe there is another path. In The Marshmallow Challenge

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-59227108758722453262015-01-25T06:03:00.000-07:002015-01-25T06:03:08.121-07:00

How do consumers end up where they do? We try to understand the path-to-purchase by stitching together data from various touch points and appending them to an artificial identifier meant to represent a consumer. I'm not sure if it is a love relationship or a hate relationship with technology, but marketers use a variety of data-related tools to connect with consumers and figure out how they

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-1799156703817345512015-01-21T15:13:00.001-07:002015-01-21T15:13:17.400-07:00

What happens when it all comes together? Some times you just smile. http://www.boxedwaterisbetter.com/

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-10090149671087796542015-01-21T09:14:00.001-07:002015-01-21T09:14:42.347-07:00

Why don't the best and brightest work here? This story is based on conversations around a panel discussion at the Utah State of Data, an event discussing the impact of data on education, finance, employment, government, and technology. While localized to Salt Lake City there are some general ideas about positioning and differentiation of a specific market. Salt Lake City's biggest

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-63083151285159655052014-11-03T17:27:00.000-07:002014-11-03T17:27:36.692-07:00

What do we often forget to mention? I missed an important birthday last month; the banner ad turned 40.  We're certainly not going to see the 40% CTR that this ATT ad achieved back then.  In fact we're not likely to see much above a single digit or even decimal place. At the time I don't think anyone had an idea what the click thru rate would be, but in today's data-driven world we

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-26130670081889373042014-10-20T11:03:00.000-06:002014-10-20T11:03:13.820-06:00

How do we come to understand things? In the era of "big data" this and "big data" that, we have a problem. Our minds are wired for language not data. Rarely do we have direct intuition about data, what it means, and what we ought to do with it.  We need to invent the Rosetta Stone that bridges the hieroglyphics of machine learning with the ancient language of marketing. Consider the

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-74743256847190536302014-10-15T06:31:00.000-06:002014-10-15T06:31:39.944-06:00

How does differentiation apply in a digital world? This post was inspired after reading "Digital Brand Differentiation - 3 Frameworks to Follow and asking the question above. Differentiation is required when we are faced with the chore of choosing.  It works because it provides a focused benefit that we can internalize and compartmentalize as "that does this".  So when we have "

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-40933062863619359052014-10-14T16:00:00.000-06:002014-10-14T16:00:09.090-06:00

How do we decide WHICH Big Data is right? The stories about Big Data talk about it as if it is one thing; it isn't. Big Data actually encompasses several different universes based to some extent on the fact that there are different underlying technology that can be deployed. And since technology is versatile but not omnipotent it makes some sense to first try to articulate what one is trying to

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-1518752962765400592014-09-25T15:03:00.000-06:002014-09-25T15:03:21.092-06:00

How do we go about finding insights? Let's start with what we mean by 'insights' -- here's my working definition in the context of marketing: the identification of a previously unknown connection between marketing activities and consumer behavior that changes how we align our solutions we human needs. Or, simply the finding of something "I didn't know I needed to know." The typical story line

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-43968833749524748252014-09-24T16:31:00.000-06:002014-09-24T16:31:00.580-06:00

How can we leverage the fact that we're creatures of habit? We often talk and read about benchmarks by tactic.  For instance 'email open rate' is tracked because it is the gate keeper to engagement and involvement.   As an example Silverpop reported the median open rate in APAC in 2012 as 27.2%. I chose a two-year old number from 5,000 miles away in order to focus on the fact that

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-39634294836988053842014-09-23T16:35:00.000-06:002014-09-23T16:35:33.577-06:00

Why do people share? And with whom? A recent post on LinkedIn about the phenomenon of sharing made the point:  we all ask for a share, but virtually no one offers a reason as to why we should bother.   Making it clear what we're offering and what action we want should be basic marketing. But what should our expectations be about sharing? The following is some of what Google

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-65575719225516696022014-09-22T15:02:00.000-06:002014-09-22T15:02:32.347-06:00

Are there {un}intended consequences of being data-driven? As analytics moves closer to what Bill Franks of Teradata recently described in a post on operational analtyics there are organizational changes looming on the horizon.   A couple of things come to mind: Predicting the Future Creates the Future: If analytic output is implemented by the business then the creators need to

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0tag:blogger.com,1999:blog-34858802.post-55996940696555158662014-09-19T08:09:00.000-06:002014-09-19T08:09:12.114-06:00

Why do we test? Very often the discussion about testing is framed in the measurement side of things.  "To improve ROI" is a fairly typical the answer to the question above.  Yet, from an analytic or data science perspective that actually misses the point. The reason we test is to gain knowledge. To be sure testing green buttons vs. red buttons should be framed in terms of conversion

anthonyhttp://www.blogger.com/profile/03842473877753081166noreply@blogger.com0