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Artificial Intelligence In Marketing: Use-Cases, Readiness, Skill Sets, Challenges And Ethics| 58

Artificial Intelligence In Marketing: Use-Cases, Readiness, Skill Sets, Challenges And Ethics| 58

Released Tuesday, 1st October 2019
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Artificial Intelligence In Marketing: Use-Cases, Readiness, Skill Sets, Challenges And Ethics| 58

Artificial Intelligence In Marketing: Use-Cases, Readiness, Skill Sets, Challenges And Ethics| 58

Artificial Intelligence In Marketing: Use-Cases, Readiness, Skill Sets, Challenges And Ethics| 58

Artificial Intelligence In Marketing: Use-Cases, Readiness, Skill Sets, Challenges And Ethics| 58

Tuesday, 1st October 2019
Good episode? Give it some love!
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Today we are talking about Artificial Intelligence (AI) and Machine Learning (ML) in marketing with Loren McDonald, who is Program Director, Marketing Research at Acoustic, and a well-regarded figure in the AI in Marketing space, having been the marketing evangelist for IBM’s Watson platform for over a decade.We start with clarifying the various terms related to AI in marketing – from predictive analytics to ML to AI and RPA and everything in between, how can marketers not be confused about what this really means to them? And how much do marketers really need to know about AI, technically, in order to make the right marketing technology purchase decisions? Loren suggests a level of conversational competency- knowing enough to ask the right questions about how it’s going to solve your specific problems is central to that approach. What are some of the most common misperceptions about AI? Most importantly, it’s not a magic black box – a lot of work must go into AI-readiness. What are some of the challenges with leveraging AI and ML for B2B use-cases? Of course, the volume of data points is lesser because there are fewer customers, so does that automatically translate into the AI no having enough to work with for pattern recognition? Lorens suggestion is to design marketing messages in a way that encourages ‘data interactions’ - design not just to drive clicks but design in a way that the system can learn as much as possible from simple, day-to-day customer actions and interactions on site and elsewhere. The real B2B challenge when it comes to trusting the data is also salespeople collecting and recording subjective data – since B2B is all about the relationships and networks versus a straight line buying decision, its imperative for B2B AI to be adept at understanding nuance, relationships and the networks that govern the buying decision.Finally, we talk about why consumer companies like McDonald's are investing so heavily into AI-powered technology – where is it going to fit into the overall CX? Are they motivated by owning the customer journey or by the need to automate human tasks at the order taking level? And what are the ethical issues involved with ML and AI-powered marketing?All this and more with Loren McDonald, Anand Thaker, and Loren McDonald, this week on The Talking Stack! If you enjoy it, take a moment to like us on Soundcloud or leave a review on iTunes! It will help keep the show going!
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