Currently set to No Index

Understanding Data Is a Science, but Not All Marketers Have the Right Formula

For people, knowledge is power. For businesses, data is knowledge. With nearly everyone and everything connected to an IP address, information is continuously collected and stored on a massive scale. Raw consumer data is a hot commodity that often goes untapped for brand marketing and advertising campaigns, especially when it comes down to understanding the impact and results.

Read Full Story

Attention Marketers: U.S. Women Are Eager to Hear From You

Think about everything you have to get done today. If you’re a woman, chances are pretty high that you’ll have to work a little harder than men will to get it all done. In fact, you might even need to do it better just to measure up. Yet despite the countless responsibilities and challenges that women have in a given week, they’re voracious consumers of media.

Read Full Story

Real-Time Customer Experience Is Happening, with or Without You

Today’s customers expect nearly everything at the speed of now, and that includes how their brands interact with them. To keep pace with this increasingly sophisticated customer for whom time is always of the essence, brands must endeavor to deliver a customer experience (CX) in real-time or as close to real-time as possible.

Read Full Story

Accelerating progress in dialogue

In machine learning, assessment isn’t everything: it’s the only thing. That’s the lesson from Imagenet (a labeled data set) and the Arcade Learning Environment (a simulation environment). A simulator is the partial feedback analog of a labeled data set: something that lets any researcher assess the value of any policy.

Read Full Story

Technical SEO Clickability Checklist

While click-through rate (CTR) has everything to do with searcher behavior, there are things you can do to improve your clickability on the SERPs. While meta descriptions and page titles with keywords do impact CTR, we’re going to focus on the technical elements because that’s why you’re here.

Read Full Story

On Marginal Likelihood and Cross-Validation

Here’s a paper someone has pointed me to, along the lines of “everything that works, works because it’s Bayesian”:Edwin Fong, Chris Holmes (2019) On the marginal likelihood and cross-validationI found this paper to be lacking on the accessibility front, mostly owing to the fact that it is a mixture of two somewhat related but separate things:(A) a simple-in-hindsight and c

Read Full Story

Zombie semantics spread in the hope of keeping most on the same low road you are comfortable with now: Delaying the hardship of learning better methodology.

Now, everything is connected, but this is not primarily about persistent research misconceptions such as statistical significance.
Instead it is about (inherently) interpretable ML versus (misleading with some nonzero frequency) explanatory ML that I previously blogged on just over a year ago.

Read Full Story