Artificial Intelligence: Terms Marketers Need to Know

08/02/2017 3 min read Written by Roman Kniahynyckyj

Artificial Intelligence (AI) continues to make its way into the world, influencing popular culture (think Steven Spielberg’s “A.I.”, or Disney’s “Big Hero 6”) and becoming a disruptor is a variety of industries. From customer service chatbots to extremely sophisticated autopilot driving machines, artificial intelligence is undoubtedly making an impact on everything around us. And marketers have the opportunity to make AI work for them.

To understand how AI impacts our marketing world, we need to know the language of AI and have a basic understanding of how it works. Some important terms to become familiar with:


An algorithm is a formula representing the relationship between certain variables. Think of algorithms as a simple set of instructions with a finite end designed to produce an output. An every day example of an algorithm is a recipe. You have a set amount of inputs (ingredients) designed to produce a repeatable output - apple pie, for example. Machine learning programs in AI use algorithms to make predictions, and in the case of marketing, suggestions are based on algorithms that hope to target the user’s specific preferences (if website visitor 'A' visits pages for kid's short sleeve shirts an algorithm will email them coupons for kid's short sleeve shirts).

Artificial Intelligence

Chatbots (or “Bots”)

A chatbot is a program that runs within websites and apps that interacts directly with users to help them with simple tasks. A “conversation” happens between the user and the computer program. These are often currently used for customer support, but the applications for chat bots are growing.


Any group of people or things that share a common characteristic. Data is combed through by AI to uncover patterns and connections that humans might not readily see. Clusters can be used to identify target segments or audiences, creating marketing opportunities through commonalities.

Cognitive Science

The broader form of study that includes AI in addition to philosophy, linguistics, psychology, neuroscience, and anthropology. All of these combine together to learn how the mind functions and, when applied to AI, how machines can simulate human thought and action.

Machine Learning

With limited need for programming, machines can teach themselves. Combing through massive amounts of data allows AI to identify patterns and groupings. This could be used to determine target audiences, decide on optimal times to send emails, or segment out groupings for deeper engagement.

Deep Learning

In this advanced version of machine learning, computers actually teach themselves with minimal programming by humans. Marketers can use deep learning to identify data and make predictions related to how consumers might behave.

Image Recognition (or “Computer Vision”)

One of the more complicated processes for machine learning, computers can be programmed to understand what is happening in an image. AI searches for patterns within images to quickly identify nuances that humans may not see.

Natural Language Processing (NLP)

This technology allows machines to determine what humans are saying, whether in text or by voice. More sophisticated programs can decipher speech in various languages, understanding not only the actual vocabulary, but also pulling out context and more hidden meanings. Sarcasm and subtlety are still difficult for AI, but advanced technology is working on it.

Neural Networks

Structured to be similar to the human brain, this AI model incorporates natural language processing and deep learning to identify faces in photos and analyze handwriting.

Semantic Analysis

A more sophisticated form of Natural Language Processing, this concept is focused on the process of stringing words together as well as the way that language is understood through cultural context. This could function as a help to create eBooks and blog posts, with the potential to replace human writers or content marketers (!). Wait, what? 

Supervised Learning

This form of machine learning does not function independently, but requires human input. Data is presented into the machine and the process is supervised by a person while the computer works toward a specific outcome.

Unsupervised Learning

Requiring little or no human involvement, this type of learning allows the machine to draw conclusions on its own from patterns that it finds.

Many of these terms are related and overlapping. It's important to be familiar with them to understand how these technologies can affect your marketing mix. A great resource for AI in the marketing realm is Paul Roetzer's Marketing Artificial Intelligence Institute (MAII) - unbeatable content for learning and seeing real world examples of AI in action.


By: Roman Kniahynyckyj

Roman has been helping clients develop and implement revenue enhancing inbound marketing strategies since 2009. Prior to becoming an inbound marketer, Roman was a management consultant with Ernst & Young, Booz Allen Hamilton, BearingPoint, and KPMG. Roman's relentless focus on client satisfaction and client results has garnered accolades from many clients and teams.

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