Artificial Intelligence and the Future of Health Care Marketing

By The SHSMD Team posted 14 days ago

As part of the Advanced Social Media & Digital Marketing in Health Care Live Virtual Conference hosted by SHSMD and Mayo Clinic, Paul Roetzer. founder and CEO of PR 20/20 | Marketing AI Institute, shared perspectives on artificial intelligence and what it can do for marketers.

Artificial intelligence (AI) is forecasted to have trillions of dollars in annual impact, yet most marketers still struggle to understand what AI is and how they can actually use it in their organizations, according to Roetzer.Artificial intelligence (AI) is forecasted to have trillions of dollars in annual impact, yet most marketers still struggle to understand what AI is and how they can actually use it in their organizations, according to Roetzer.

So what is AI? One definition, according to Demis Hassabis, co-founder and CEO of Deepmind, says it is the science of making machines smart. Machines are inherently “dumb.”.Computers and software have no inherent intelligence of their own. They don’t get smarter and don’t recommend things to you that they have learned. It is the programmers that make them “smart” by telling the software what to do. 

So, it would follow that marketing AI is the science of helping marketers make decisions.

But is this really possible? Can we teach machines to learn and become more human? 

To answer this, Roetzer says we need to realize that AI is an overarching umbrella term. “Machine learning is a form of AI and “deep learning” is a form of machine learning that makes machines think and learn like humans,” he points out. “We aren’t there yet but there are a lot of researchers working on this problem.” 

There are three kinds of applications and ways we are already using AI: language, vision and predictions.

  • Natural language processing.
  • Natural language generation.
  • Sentiment analysis.
  • Speaker identification.
  • Speech-to-text.
  • Text analysis.
  • Text extraction.
  • Text generation.
  • Text-to-speech.
  • Translation.
  • Voice generation.
  • Voice recognition.
  • Emotion detection.
  • Image analysis.
  • Image recognition.
  • Facial recognition.
  • Movement detection.
  • Video recognition.
  • Forecasting.
  • Pattern recognition.
  • Personalization.
  • Recommendation.

This all sounds great, but what practical use is this? You’re already using it if you use autocorrect, predictive text (the tools that predict the next word you’ll type), face recognition in photo apps or recommendations on Netflix or Amazon. 

All this means is that your life is AI-assisted, many times without you knowing it. That’s what’s going to be happening in marketing, notes Roetzer, who says AI can help marketers be more proactive in seeking out smarter marketing solutions and become more productive. Why should marketers use AI?

AI reduces cost. “Don’t worry, we’re not talking about laying people off,” explains Roetzer. “AI reduces costs by intelligently automating repetitive, data-driven tasks. This dramatically improve ROI and revenue by making better predictions.” 

Roetzer says there are two ways to get started using AI: problem-based and use case models.

Problem based model: Start with a known challenge you want to solve.
  1. Define the problem statement.
  2. Build and prioritize the issues list.
  3. Identify and prioritize the key drivers.
  4. Develop an initial hypothesis.
  5. Conduct discovery research.
  6. Validate issues and drivers.
  7. Analyze options and build a solutions matrix.
  8. Synthesize findings.
  9. Develop recommendations.
  10. Present the final report and plan.
Example of a problem: While an organization has more emails in its database than ever, opening rates, click rates and conversation rates are low and/or declining. There could be several reasons:
  • List fatigue.
  • Email design and content.
  • Duplicate contacts.
  • Lack of list segmentation.
  • Lack of personalization.
  • Highly manual processes.
  • Underutilized or missing tech.
  • Lack of reporting/ performance management.
AI tools can help fix all of these.

Use case model

If we could automate, how valuable would that be? 

How do you identify an AI use case? Ask:
  • Is it data driven?
  • Is it repetitive?
  • Is it making a prediction?
These are some use case areas to look at:
  • Advertising
  • Content marketing
  • Data analytics
  • Social media
  • Communications and public affairs
Closing thoughts: What remains uniquely human? 
  • Curiosity
  • Creativity
  • Strategy
  • Empathy
  • Emotion
  • Intuition
  • And, maybe most of all, imagination.

To access the full keynote presentation or other sessions from the conference, you can register here. There is no charge for registration. For more on social media and marketing, be sure to explore SHSMD’s Resource Library.