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Unlocking AI’s Potential: A Guide for Success in the Experience Age

Artificial Intelligence (AI) has taken off in 2023. From generative AI to automation, there are ways AI can be implemented to help almost every industry—including marketing. On November 2nd, we were joined by Katie King to discuss the potential of AI in marketing and how it can impact the customer experience.

Voted a top 10 AI Influencer by AI Time Journal, Katie King has a 30-year career in consulting and marketing and has published two books. So, when we say she wrote the book on AI marketing, we mean…literally. She currently serves as the CEO of AI in Business, a future-focused consultancy dedicated to helping organizations gain a competitive edge in the age of AI, and Zoodikers, a content marketing, business strategy, and thought leadership agency built for the digital age.

It’s safe to say that when it comes to AI, Katie knows her stuff. So, let’s get into what she covered in her recent webinar with Iterable.

Want to watch the webinar? It’s available on-demand right now.

Defining AI

To kick things off, Katie went back to basics and defined what AI really means. Because 87% of global organizations believe that AI technologies will give them a competitive edge, it’s important to understand exactly what AI is in the context of business.

According to Katie, “AI is the capability of a machine to imitate intelligent human behavior.” This is the broad, all-encompassing definition of AI. There are subsets of AI, however, that connect more to how we understand AI today. Machine learning (ML), for example, is “a current application or subset of AI, using pattern recognition and algorithms to enable machines to accelerate learning through experience.”

Three profile views of heads, brains visible. From left to right the heads get larger and go from narrow AI to super AI.

Katie shared this graphic that defines narrow, general, and super AI.

Katie also broke down what AI is and what AI is not—a helpful distinction to help users overcome some initial hesitation to adapt the use of AI technology.

What AI is:

  • A specialized technology capable of amazing things
  • Better and more efficient at certain tasks than humans are, like data collection and analysis
  • A tool and ally

What AI is not:

  • An all-knowing, all-capable, superintelligent technology
  • A total replacement for human intelligence, creativity, and skill
  • A threat to every job and human worker

The Different Forms of AI

Of course, AI can look different depending on how you intend to use the tool’s capabilities. So, Katie then covered the different forms of AI.

Interactive AI

Interactive AI refers to developing AI systems that can engage in human-like conversations and respond dynamically to user inputs.

Common Examples: Chatbots, Smart Personal Assistants
Real World Use Cases: Amazon’s Echo devices, Apple’s Siri

Visual AI

Visual AI is an aspect of computer science that teaches machines to make sense of images and visual data the same way people do.

Common Examples: Computer Vision, Augmented Reality, Facial Recognition
Real World Use Case: Some insurers use Visual AI to assess the damage from vehicular accidents to draft a claim

Functional AI

Functional AI also scans huge amounts of data and searches for patterns and dependencies in it. However, instead of giving recommendations, functional AI takes actions.

Common Examples: IoT Solutions, Robots, Iterable’s Send Time Optimization (STO)
Real World Use Case: An IoT sensor on a manufacturing line notices a malfunction, and sends a command for the machine to shut down before further damage is incurred

Analytic AI

Powered with machine learning, analytic AI scans tons of data for dependencies and patterns to ultimately produce recommendations or provide a business with insights.

Common Examples: Sentiment Analysis, Risk Assessment, Market Insights, Iterable’s Brand Affinity
Real World Use Case: Various retailers use analytic AI to forecast demand and make smarter inventory recommendations

Generative AI

Generative AI is the process of AI algorithms generating or creating an output, such as text, photo, video, code, data, and 3D renderings, from data they are trained on.

The purpose of generative AI is to create content, as opposed to other forms of AI, which might be used for other purposes, such as analyzing data or helping to control a self-driving car.

Common Examples: ChatGPT, Bard, DALL-E, Iterable’s Copy Assist
Real World Use Case: A marketing team could use generative AI to craft copy for websites, social media, emails, etc.

You might be thinking, “All of these different types of AI are great, but how do they relate to marketing?” We’ve got you covered.

AI in Marketing

There are a variety of ways AI can be used in marketing that help both the marketing practitioner and the customer on the other end.

Crafting Experiences

Marketers can use AI to bridge the gap between online and in-person experiences, differentiate, and build loyalty.

Real World Use Cases: AI-powered tailored emails based a website or store visit, loyalty programs, ‘Smart Mirrors’ in fitting rooms

Smarter Targeting

Marketers can use AI to better understand their customers, build more detailed personas, and segment their audiences more effectively.

Real World Use Cases: Audience insight platforms, CRM, lead generation and scoring

Personalization at Scale

Marketers can use AI to better understand their customers, build more detailed personas, and segment their audiences more effectively.

Real World Use Cases: Audience insight platforms, CRM, lead generation and scoring

Campaign Generation

Marketers can use AI to make sense of their data and translate it into customer-focused campaign ideas.

Real World Use Cases: Creative campaigns for brands such as Coca-Cola, Lexus, Heinz, Stradivarius, and Kit-Kat

Content Creation

Marketers can use AI to craft engaging copy for all of their channels and modify it for different audiences, geographies, languages, etc.

Real World Use Cases: Social media copy, website content, AI-generated artwork, video closed captioning, etc.

Automated Engagement

Marketers can use AI to automatically engage their customers with messaging to keep the pipeline warm throughout their entire journey.

Real World Use Cases: Push messaging, abandoned cart reminders, etc.

Reputation Management

Marketers and comms pros can use AI to keep tabs on customers’ perceptions and attitudes, success of their campaigns, and discussions of their brand across platforms.

Real World Use Cases: Social listening tools, sentiment analysis platforms

Check Out the Full Webinar

Looking for even more AI info? In addition to covering all of the above information in her webinar, Katie also explores some real life applications. These include examples from Barbie, Delta, Jaguar, and more. Plus Katie covers macro issues and AI regulations and also covers top AI vendors, including reviewing Iterable’s AI Suite.

Don’t miss out, stream the full webinar now.

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