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Articles by Jim Sterne
Guest Essay: AI gives SB County Behavioral Wellness Department its Fridays back
Most enterprise AI rollouts begin with a pilot, a dozen volunteers, six months of evaluation, and a report recommending further evaluation. Ryan Weyman, Branch Chief of Information Technology at Santa Barbara County’s Behavioral Wellness Department skipped that part.
Guest commentary: How to master AI without losing the human touch
By Jim Sterne The hardest part of adopting generative AI is identifying the use cases. That’s why most people are still stuck on “help me write this email.” Anthony Hamilton is well past that. He filled out a Better Business Bureau survey about AI use and his answers were interesting enough that I asked for a call. Hamilton co-founded THE Water Heater Company in Camarillo in 2019.
AI-Driven B2B Marketing: Transforming Client Engagement Through Advanced Automation Techniques
By 2025, AI-driven businesses will account for 80% of all B2B sales interactions. This statistic underscores the transformative potential of AI and Automation in B2B Marketing.AI and automation are not just trends; they are becoming indispensable in B2B strategies. These technologies allow businesses to operate with greater efficiency, gain deeper insights into customer behavior, and deliver highly personalized experiences at scale.
GenAI Can Help Companies Do More with Customer Feedback
Many companies are experimenting with generative artificial intelligence (GenAI) now, both for internal employee productivity objectives as well as customer interaction, but only a few have production deployments. Difficulties with upskilling workers, changing processes, and integrating technology persist, and many companies are caught in a perpetual experimentation loop.
What is the Cost of a Dashboard?
One note from the first day of the Marketing Analytics Summit and this was just one workshop... What is the Cost of a Dashboard? "Hey, can your team whip up a quick dashboard that shows engagement by email segment for mobile vs. desktop?" "Sure. When do you need it?" "Yesterday would be good." "OK, let me ask about how you're going to use this dashboard. What business decisions will you be making?" "Well, you know...
When Privacy and Business Collide
Author Jim Sterne Date published January 17, 2013 Categories Last May, I suggested that if only marketers would embrace “incremental opt-in,” it would usher in the end of the privacy problem. Conceptually, this was a good idea. But the world keeps turning and things continue to get more complicated. The issues are more interconnected in global reach and broader in philosophic morality.
How to Get Started with Machine Learning and AI for Marketing
Artificial Intelligence is powerful and will open doors we don’t even know exist at the moment. But there are some steps you can take today to ensure that you are making the most of this new capability and are not left behind. As this is such a nascent area, it serves to begin with a brief description of Artificial Intelligence and Machine Learning. My assumption is that you have read a dozen different definitions and should be curious about which applies to this particular essay.
Where is Your Organization on the Marketing Data Literacy Spectrum?
From the Data Deniers to the Data Forward, your organization is on this chart. The marketing race will go to the most data-enriched organizations. Time for a look in the mirror. There are some who can read well enough to navigate a cookbook. Some can write a lengthy treatise on a complex subject. Some can pen an eloquent illumination of comparison between Shakespeare, Marlowe and Milton. They are all literate, but to varying degrees.
Jim Sterne’s Book Review of “Predictive Analytics” by Eric Siegel " Machine Learning Times
5 years ago Jim Sterne’s Book Review of “Predictive Analytics” by Eric Siegel Book review originally published in the journal Applied Marketing Analytics Eric Siegel’s book, ‘Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die’ gets its subtitle from the many ways statistical prognostication has been used. The life insurance industry was founded on and continues to grow by predicting when you are likely to shuffle off this mortal coil.
Editorial: How should an Enterprise Risk Management department be organised? And what should it do?
Click the button below to download the full text of the article. Introduction: Since the financial crisis, financial institutions have focused much more heavily on capital adequacy and therefore on measuring all risks across the enterprise in a coherent and consistent manner. Over that same period, the risk profile of financial institutions has continued to increase in interdependent complexity.
Today's 5 Top Analytical Problems
A few weeks ago, in the middle of February, I reviewed some analytics dilemmas from 2005 in a column entitled “Analytics Problems Won’t Die.” I laughed at some, shrugged off some, and commented on the really nasty ones in light of current events. It’s time to revisit that list in light of the even more current state of affairs. What makes this week more current than five weeks ago?
How to Get Started with Machine Learning and AI for Marketing
Artificial Intelligence is powerful and will open doors we don’t even know exist at the moment. But there are some steps you can take today to ensure that you are making the most of this new capability and are not left behind. As this is such a nascent area, it serves to begin with a brief description of Artificial Intelligence and Machine Learning. My assumption is that you have read a dozen different definitions and should be curious about which applies to this particular essay.
How to Get Started with Machine Learning and AI for Marketing
Artificial Intelligence is powerful and will open doors we don’t even know exist at the moment. But there are some steps you can take today to ensure that you are making the most of this new capability and are not left behind. As this is such a nascent area, it serves to begin with a brief description of Artificial Intelligence and Machine Learning. My assumption is that you have read a dozen different definitions and should be curious about which applies to this particular essay.
The Devil's Data Dictionary
When coined the description of Big Data as ‘That which doesn’t fit in an Excel spreadsheet’, I realized it was well past time for the datarati to have some fun poked at us. There is no better example for what I had in mind than Ambrose Bierce’s Devil’s Dictionary (1906); an absolute gem that includes such treats as these: Bore, n. A person who talks when you wish him to listen. Love, n. A temporary insanity curable by marriage. Politeness , n. The most acceptable hypocrisy. Self-evident, adj.
Good and Bad vs. Right and Wrong
Artificial intelligence is not just the stuff of science-fiction movies anymore, but what problems does it present for marketers? After 40 years in marketing, I have learned that I am not a representative of whatever market I am trying to reach. My very best guess is only as good as the next guy's, and it is still only a guess. With the advent of digital analytics, I can now switch my terminology to "experiment" and "hypothesis" and suddenly, I'm a modern marketing marvel. But why not go further?
Data Variety - The Spice of Life
Marketers are on the brink of a deluge of data sources that could prove to be extremely useful in future digital marketing strategies. Would you freely give your biometric data to a vendor in response to an online advertisement? I would. But first, a word about big data. I'm all for volume and velocity. In fact, velocity gives us a whole new way to think about data: time series. But for my money, variety is the spice of life in big data that can unlock more doors than ever.
Data Visualization, Big Data, and the Quest for Better Decisions - a Synopsis
You’re time starved, right? So, in my never-ending effort to help you with an overflow of TL;DR things you were supposed to read, here’s my synopsis of a synopsis of a book by Phil Simon. Simon is an author, advisor, speaker, and thought leader. It says so right on his LinkedIn page. But before you judge him harshly, please consider the valuable service he provides. His job is making sense of things you don’t have time to study, research or assimilate. Synopsis of a synopsis? That’s right.
So, What Do You Do for a Living?
Author Jim Sterne Date published February 13, 2014 Categories When I’m out on the road and too tired to open even one more email, I love to look at examples of that great meme: “What my clients think I do, what my boss thinks I do, what I think I do, what I really do.” They’re funny. And they pretty much sum things up. When asked, “What do you do?” about 10 years ago, those of us who called ourselves Web analysts would mumble something about measuring the success of a website.
The Modern Data Analyst
You have a tough job and there are a lot of moving parts. That means there’s a lot to know and so, in your honor, please enjoy this little ditty as a token of appreciation. With apologies to Gilbert and Sullivan. The old-fashioned (1993) data analyst was called a Web Analyst and got that way by sifting through a brand new type of data: web server log files.
A New Marketing Metric: Personally Provided Information
As more and more data becomes available to anybody with a disk drive, the world is becoming a more and more privacy-conscious place. At the same time, the role of marketer has shifted dramatically from slogan-writer, jingle-writer and color-picker to digital analyst. The growing sophistication of the work is outstripping management’s ability to determine whether the marketing department is doing a good job or not. “How are things going?
Is It Wrong to Love Analytics This Much?
The new Digital Analytics Association website includes an Open Forum for members. In an effort to help get the conversation started, I asked what people love about their job and about the industry in general. Christopher Berry, chief science officer at Authintic and co-chair of the DAA Research Committee, rigorously enumerated his top three reasons: 1. The Solution Set 2. The Problem Set 3.
Getting People to Buy Less
Spend a few minutes Googling about online clothing sales and you’ll discover a general consensus that something like 40 percent of fashion items bought online are returned. Fully 30 percent of returns are caused by first-time, dissatisfied customers. This may simply be the cost of doing business. But what if you use the analytics generally employed to get people to buy more, to get people to buy less instead?
What to Measure? Start at the Top
You can measure every online thing these days. But should you? Big data says yes: collect it all and decide what questions you wish to ask later. This bottom-up approach is fine if you have the technology and the resources. It’s great for discovery and correlation hunting. But what it you just want your business to improve? Then you should start at the top. Metrics Priorities Begin With Philosophy Philosophically, the most important thing an organization can do is make customers happy.
Digging for Data Diamonds
Rod Bryan has worked for Teradata, DoubleClick, PwC, IBM Global Services, and is currently a partner with Deloitte Australia. He is also one of those public speakers who commands all of the attention in the room. He is knowledgeable, excitable, forceful, passionate, and animated, and delivered an analogy at the eMetrics Summit in Sydney that works well on so many levels, we had to lean forward to catch it all. Analogies are great – the human mind soaks them up like a dry sponge in a spring rain.
No More Actionable Analytics, Please!
After only five years, I got the Web Analytics Association to change its name to the Digital Analytics Association. I do not presume to hog all the credit, but I join in the victory lap for all of us scoring one for our side. Next up? I raise my lance, mount my valiant steed, and prepare to tilt at another term of art. Perhaps, just perhaps, I can rid the world of “actionable analytics.” What’s my beef? Misappropriation.
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