As artificial intelligence continues to be at the forefront of our day-to-day professional lives, it’s important we’re all on the same page when it comes to the AI terms being used.
In this post, we cut through the confusion, clarifying essential AI terms we, as marketers, should start to familiarize ourselves with. Whether you’re new to AI or just need a quick refresher, these AI terms will provide you with a clearer understanding of key concepts, especially as they relate to using AI in your marketing campaigns.
The Go-To AI Glossary
AI (Artificial Intelligence): Gartner defines artificial intelligence, or AI, as “applying advanced analysis and logic-based techniques, including machine learning (ML), to interpret events, support and automate decisions, and take actions.”
AI Marketing: AI marketing is the use of AI concepts and models to execute marketing strategies and campaigns that achieve business goals. When properly integrated, AI marketing can sort through massive volumes of data and quickly analyze patterns, making it easier to target audiences more precisely.
For more AI marketing best practices, peruse these Iterable resources:
- The 5 Ws of AI Marketing
- 20+ AI Marketing Stats You Wish You Knew Sooner
- Great Examples of AI in Marketing…and Some Not So Great
AI Prompt: An AI prompt, according to TechTarget, is “a mode of interaction between a human and a large language model (LLM) that lets the model generate the intended output. This interaction can be in the form of a question, text, code snippets, or examples.”
To build better AI prompts for marketing campaigns, check out our list of five top tips.
Brand AffinityTM: In Iterable’s AI Suite, Brand Affinity generates sentiment labels for each user that reflect their level of engagement. These labels can be used in segmentation, campaigns, journeys, data feeds, and Catalog collections to send personalized, relevant messages to customers.
Learn the science behind Brand Affinity in this explainer.
Channel Optimization: Using Iterable AI, Channel Optimization sends messages to each user on the channel that they are most likely to engage with. Currently, Channel Optimization supports email, SMS, and push notifications, and data is analyzed on a weekly basis to account for changes in channel preference.
For the factors to consider before using Channel Optimization, review this Iterable support article.
ChatGPT: Developed by OpenAI, ChatGPT is an AI-powered large language model (LLM) capable of generating human-like text based on context and past conversations. ChatGPT uses what it has learned to “predict the next most likely word that might appear in response to a user request […] similar to auto-complete capabilities on search engines, smartphones, and email programs.”
Copy Assist: In Iterable, Copy Assist enhances and expedites the process of writing campaign copy. During the creation of a campaign or template, Copy Assist generates alternative suggestions for email subject lines and preheaders, SMS messages, and push notifications.
This Copy Assist support article details how to use the AI-powered feature in the Iterable platform.
Explainable AI: Explainable AI involves transparent systems with clear, understandable processes. Unlike the opaque, black box of certain AI solutions, Explainable AI provides a more “glass box” experience that shares deeper insights into the data that powers predictions.
Iterable’s AI Suite integrates Explainable AI within Brand Affinity and Predictive Goals to gauge customer sentiment and gain insights into what drives your predictive goals. Learn more about our approach to Explainable AI.
Generative AI (GenAI): McKinsey defines generative artificial intelligence, or GenAI, as “algorithms (such as ChatGPT) that can be used to create new content, including audio, code, images, text, simulations, and videos.” GenAI has become popularized among marketing professionals as a tool to assist with copywriting and content creation.
Large Language Model (LLM): A large language model (LLM) is defined by Gartner as “a specialized type of AI that has been trained on vast amounts of text to understand existing content and generate original content.”
Machine Learning (ML): According to McKinsey, machine learning (ML), is defined as “a form of artificial intelligence based on algorithms that are trained on data. These algorithms can detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction.”
Natural Language Processing (NLP): Britannica defines natural language processing (NLP) as “the use of operations, systems, and technologies that allow computers to process and respond to written and spoken language in a way that mirrors human ability.”
Predictive Goals: Within Iterable’s AI Suite, Predictive Goals identifies which customers are most likely to convert on a marketer’s goals in the future, so they can create experiences that match their interests and promote desired business outcomes.
To bridge the gap between insights and actions, check out this Predictive Goals support article.
Prompt Engineering: Prompt engineering, according to Techopedia, is “a technique used in AI to optimize and fine-tune language models for particular tasks and desired outputs. Also known as prompt design, it refers to the process of carefully constructing prompts or inputs for AI models to enhance their performance on specific tasks.”
Seed Copy: In the context of AI, seed copy refers to initial messaging to include with an AI prompt to provide examples and needed context to generate content or train an AI model. For generative AI, the seed copy acts as a foundation from which the AI can mirror the style, tone, or structure based on its programming and training.
This blog post includes examples of seed copy to build better AI prompts for marketing campaigns.
Send Time Optimization: Send Time Optimization (STO) is an Iterable AI feature that helps send email and push notifications when contacts are most likely to engage with them. For each campaign recipient, STO analyzes historical engagement behavior and selects an optimal, per-person send time.
For the finer details of STO, review the notes listed in this Iterable support article.
If Merriam-Webster Was Powered By AI
As AI continues to evolve, its terminology will grow and become more complex. Staying informed and familiar with these key AI terms not only aids in understanding the current landscape but also prepares your brand for the advancements that will shape the future of your AI-driven campaigns. Now that you’re caught up on the lingo, you can use AI to make marketing magic.
Interested in trying out Iterable’s AI Suite for yourself? Reach out and schedule a custom demo today.
