So What? Marketing Analytics and Insights Live airs every Thursday at 1 pm EST. You can watch on Facebook Live or YouTube Live. Be sure to subscribe and follow so you never miss an episode! In this week’s episode of So What? we focus on what Natural Language Processing is, why you should care, and how to use […]
Read More… from So What? Introduction to Natural Language Processing
In this week’s In-Ear Insights, Katie and Chris talk about AI applications and distractions. How important is it that you know the technology? What level of depth is necessary for marketers to make marketing technology work for them? Tune in to find out! [podcastsponsor] Watch the video here: Can’t see anything? Watch it on YouTube […]
Read More… from {PODCAST} In-Ear Insights: AI Applications and Distractions in Marketing
In this week’s In-Ear Insights, Katie and Chris talk about the newest advances in natural language generation and walk through an example of what’s available now for creating content with the assistance of AI. Watch the demonstration, listen to the implications for marketers, and start formulating your AI-based content marketing strategy. Tune in to find […]
In this episode of In-Ear Insights, Katie and Chris dig into the announcements around Google’s newly announced AI model for advanced search, Google MUM, or the multitask unified model. Learn what Google MUM is, why it should matter to content producers, and how to think about adapting your content strategy to deal with what could […]
Read More… from {PODCAST} In-Ear Insights: Google MUM, SEO, and Content Strategy
You’re busy. We get it. We’ve compiled some of the top-clicked and shared articles that you don’t want to miss. Here is a quick review of the top news in marketing analytics, data science, and leadership you should be reading. Application Migration and Modernization with IBM WebSphere Hybrid Edition via @IBMTraining We are pleased to […]
Read More… from Marketing Analytics, Data Science and Leadership – May 17, 2021 Week In Review
In this episode of In-Ear Insights, Katie and Chris tackled the thorny ethics of what you put in your AI models, based on leaked memos from Tiktok allegedly discriminating against protected classes. How do we know when an AI model is behaving badly by accident and by design? What are the steps we should take […]
Read More… from {PODCAST} In-Ear Insights: Ethics, Explainability, AI, and Tiktok
In this week’s In-Ear Insights, Katie and Chris discuss shiny object syndrome, blind spots in your marketing technology (especially around AI and machine learning) and how arrogance can lead to substantial technical problems in your tech stack and company culture. How can you avoid pitfalls and blind spots? How do you manage AI and machine […]
Read More… from {PODCAST} In-Ear Insights: Shiny Object Syndrome and Tech Arrogance
In this episode of In-Ear Insights, Chris and special guest John Wall discuss the state of consumer recommendation engines. Why are recommendations so narrow and ineffective many times? What could we do to improve them beyond what we get now? Listen in as we discuss limitations of computational power, algorithm choice, and more. [podcastsponsor] Watch […]
Read More… from {PODCAST} In-Ear Insights: Why Consumer Recommendation Engines Fail
In this week’s In-Ear Insights, Katie and Chris discuss what happens when algorithm choices go wrong. What happens when junior or naive AI engineers or data scientists make bad choices for algorithms. Using an example from a writing analysis website, we discuss what went wrong, what an appropriate choice should have been, and why it’s […]
Read More… from {PODCAST} In-Ear Insights: When Algorithm Choices Go Wrong
In this episode of In-Ear Insights, Katie and Chris tackle the sorry state of digital advertising, and advertising in general. Why is advertising so terrible? Are companies and marketers focused on the wrong metrics? What are we doing with the data we collect, and could we be doing something different and better with it? Find […]
Read More… from {PODCAST} In-Ear Insights: The Sorry State of Advertising
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