A Marketer’s Guide to Artificial Intelligence

Registration and Hot Breakfast

We’ll kick off the day with a nice breakfast so you’ll have energy for the day. You’ll also be provided with lunch and breaks throughout the day.

Artificial Intelligence Defined

• Science fiction vs. fact
• Voice recognition
• Natural language processing
• Computer vision
• Augmented reality
• Robotics
• Machine learning

Separating the Hype from the Possibilities

• Why now?
• General vs. narrow ai: when to roll your eyes/when to keep them wide open
• The myth of the AI-pocalypse
• Robots will not eat your job
• Scary pronouncements and the reasoning behind them
  • Lack of explainability
  • Bias in the data
  • Bad actors

Intro to Marketing Analytics

• Analytics: A prerequisite to AI and ML
• What makes a great analyst?

EXERCISE: Marketing data literacy spectrum – Where is your organization today?

Machine Learning Explained - How ML is Different

• From programming to statistics to machine learning
• Examples of ML explained
  • Decision trees become a random forrest
  • Support vector machines
  • Neural networks become deep learning

What ML is Good AT: Functional Proficiency

• Counting
• Segmenting/clustering
• Pattern matching
• Anomaly detection

What AI is Good FOR: Marketing

Where Machines Fail

• Statistics and logic are not reason and common sense

Hot Breakfast

Breakfast will be waiting for you when you arrive for day two. Lunch and breaks will be provided throughout the day.

The New Importance of Data

• Need for large amounts of data
• Need for clean data
• Need to understand data streams

On-boarding AI - How to bring AI and ML into Your Organization

• Goal Identification
• Task prioritization
• Choosing useful data sets
• Working with data scientists
• Buy vs. build
• Change management and expectation setting

EXERCISE: The AI maturity model – Where do you stand?

Keeping Your Job - Uniquely Human Skills & Strengths

• Perfecting the smell test
• The power of experience
• The need for creativity
• The power of collaboration
• Soft skills become paramount

EXERCISE – Identifying the best place to start

• What is your top, corporate goal?
• Which is your most agile marketing task/ function/ team?
• Who in your company is most likely to support experimentation?
• Who in your org has budgetary discretion?
• Where/from whom do they get their input?
• Which repetitive tasks are best for pilot projects?
• What is your next step?

A Look Over the Horizon - The Weird Future Right Around the Corner

• Training an ecosystem of bots
• Systems that negotiate with systems
• Brand building becomes even more crucial

Open Discussion/Wrap-up