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42. Emotions, motivators and drivers: what matters most in marketing

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Manage episode 403362561 series 3361976
Contenu fourni par Dom Hawes. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Dom Hawes ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Today's show is a little different. It's not your standard interview style discussion, because today's guest is not our standard guest. He is an Emmy Award winner, an entrepreneur, inventor, and researcher. He's a master of advertising and marketing effectiveness. No-one has worked harder or been more effective at understanding the relationship between marketing effectiveness, emotions, motivations and drivers. And... he built it into a machine learning model.

So, what we're bringing you today is a first hand account from a pioneer in machine learning of how he built his AI, Bill Harvey. What do I mean by pioneer?

Well, Amazon got there in 1998 or 99, but today's guest built a machine learning recommendation engine that was embedded in cable tv boxes in 1997. Not too shabby, eh?

This year, McKinsey tells us that AI is at the top of CEO's agendas. As a CMO, you are probably all over gen AI and tools driven by machine learning too. That's why we thought you might want to hear this.

About Bill Harvey

Emmy award winner, innovator & inventor with 35+ years as thought leader in media research & key solution-provider to Fortune 500 brands.

Breakthrough inventions include:

  • The ADI/DMA
  • Addressable commercials
  • Passive Peoplemeters
  • Planning/Purchasing media based on single-source Big Data matching (4 U.S. patents)

Bill is the original discoverer of DriverTags™ the first proven scientific development of psychological attribute metatags for content (programs, movies, ads, etc.). RMT’s DriverTags™ have the highest predictivity of Nielsen ratings, series cancellations and renewals, and individual viewer likelihood of conversion to specific programs. Most recent work being presented at ARF shows an ability to lift ROI for brands by over +35%.

Links 

Full show notes: Unicorny.co.uk

LinkedIn: Bill Harvey | Dom Hawes

Website: Bill Harvey Consulting

Sponsor: Selbey Anderson 

Episode outline

  • Introduction to Bill Harvey
  • Importance of AI in Marketing
  • The Role of Emotion and Context in Advertising
  • The Start of Bill Harvey's Career
  • The Development of DriverTags™
  • AI-powered show recommendations
  • Effectiveness of DriverTags™
  • Digital Advertising and Somacio
  • Validation of Motivational Types
  • Introduction to Canadian Market and Vividata Partnership
  • Collaboration with AI Companies
  • Addressable TV and Programmatic Advertising
  • Application in B2B Marketing
  • Impact of DriverTags™ in Advertising

This podcast uses the following third-party services for analysis:
OP3 - https://op3.dev/privacy
Podder - https://www.podderapp.com/privacy-policy
Chartable - https://chartable.com/privacy
  continue reading

90 episodes

Artwork
iconPartager
 
Manage episode 403362561 series 3361976
Contenu fourni par Dom Hawes. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Dom Hawes ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Today's show is a little different. It's not your standard interview style discussion, because today's guest is not our standard guest. He is an Emmy Award winner, an entrepreneur, inventor, and researcher. He's a master of advertising and marketing effectiveness. No-one has worked harder or been more effective at understanding the relationship between marketing effectiveness, emotions, motivations and drivers. And... he built it into a machine learning model.

So, what we're bringing you today is a first hand account from a pioneer in machine learning of how he built his AI, Bill Harvey. What do I mean by pioneer?

Well, Amazon got there in 1998 or 99, but today's guest built a machine learning recommendation engine that was embedded in cable tv boxes in 1997. Not too shabby, eh?

This year, McKinsey tells us that AI is at the top of CEO's agendas. As a CMO, you are probably all over gen AI and tools driven by machine learning too. That's why we thought you might want to hear this.

About Bill Harvey

Emmy award winner, innovator & inventor with 35+ years as thought leader in media research & key solution-provider to Fortune 500 brands.

Breakthrough inventions include:

  • The ADI/DMA
  • Addressable commercials
  • Passive Peoplemeters
  • Planning/Purchasing media based on single-source Big Data matching (4 U.S. patents)

Bill is the original discoverer of DriverTags™ the first proven scientific development of psychological attribute metatags for content (programs, movies, ads, etc.). RMT’s DriverTags™ have the highest predictivity of Nielsen ratings, series cancellations and renewals, and individual viewer likelihood of conversion to specific programs. Most recent work being presented at ARF shows an ability to lift ROI for brands by over +35%.

Links 

Full show notes: Unicorny.co.uk

LinkedIn: Bill Harvey | Dom Hawes

Website: Bill Harvey Consulting

Sponsor: Selbey Anderson 

Episode outline

  • Introduction to Bill Harvey
  • Importance of AI in Marketing
  • The Role of Emotion and Context in Advertising
  • The Start of Bill Harvey's Career
  • The Development of DriverTags™
  • AI-powered show recommendations
  • Effectiveness of DriverTags™
  • Digital Advertising and Somacio
  • Validation of Motivational Types
  • Introduction to Canadian Market and Vividata Partnership
  • Collaboration with AI Companies
  • Addressable TV and Programmatic Advertising
  • Application in B2B Marketing
  • Impact of DriverTags™ in Advertising

This podcast uses the following third-party services for analysis:
OP3 - https://op3.dev/privacy
Podder - https://www.podderapp.com/privacy-policy
Chartable - https://chartable.com/privacy
  continue reading

90 episodes

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