AI Terminologies for Marketers

Artificial intelligence, more commonly known as AI, is continuing to make a big impact in popular culture as well as numerous industries. Examples includes chatbots that acts as customer service representatives, personalized recommendations for customers based on past buying history, and automated driving machines. To say that AI is impacting the world at large is quite an understatement. However, marketing has been slow to adapt to AI and realize its many benefits.

When you first start using AI, it might seem like you’re speaking a different language. In a sense, you are. That’s why it’s important to master its terminology as well as its basic functions. Below are terms and definitions that everyone working with AI should take the time to master.

Algorithm

The term algorithm describes a formula that represents a relationship that exists between two or more variables. It’s helpful to think of algorithms as a list of instructions that include a finite end with the purpose of producing an output. A recipe is an everyday example of a common algorithm. Its ingredients are the inputs that design a specific output such as an apple pie. With AI machine learning, a computer uses algorithms to make predictions.

In marketing, it creates buying suggestions based on a consumer’s past actions to spur him or her to buy the suggested item. For example, a website visitor will see an ad for a smartphone on other sites on the Internet if he or she spends time viewing this product online.

Chatbots/Bots

A bot, short for chatbot, is a computer program within a website or phone application that directly interacts with users to assist them with simple questions and tasks. Many companies currently use bots for customer support, although their use in other areas is also growing.

Cluster

A cluster is a group of people with common demographics or characteristics. AI goes through data to determine patterns and make connections that a human might easily miss. Marketers can use clusters to identify their target audience, thus creating new marketing opportunities through things the people have in common.

Cognitive Science

Cognitive science combines topics such as anthropology, linguistics, neuroscience, philosophy, and psychology with AI. This helps marketers understand how the human mind functions so they can program a machine to simulate the actions and thoughts of people.

Machine Learning

Machines can teach themselves with only minimal programming from humans. They can sift though huge amounts of data to pick out groupings and patterns of interest to marketers. They can then select target audiences and decide when to take certain actions based on the machine’s input.

Deep Learning

This is a more complex version of machine learning. It enables computers to teach themselves with little human programming. Marketers can use deep learning data to predict how consumers might respond to certain products and services.

Image Recognition/Computer Vision

AI makes it possible to program a computer so it can accurately analyze an image. It searches for image patterns to identify things that a person might miss.

Natural Language Processing (NLP)

NLP makes it possible for machines to understand spoken language, whether a person is speaking or using text. The most sophisticated NLP programs can interpret speech in a variety of languages. Even more impressive, it understands the actual spoken words as well as their context and possible hidden meanings.

Neural Networks

AI technologists have created neural networks to mimic the human brain. For example, it can analyze handwriting and identify people in pictures based on deep learning and natural language processing.

Semantic Analysis

Semantic analysis is a sophisticated form of NLP that focuses on how people string words together as well as how they understand language in its cultural context. This could be useful in creating blog posts and eBooks and has the potential to replace content marketers or human writers.

Supervised Learning

This type of machine learning requires human input to function. A person inputs data into the machine and then supervises the process as the computer forms one or more desired outcomes.

Unsupervised Learning

In contract, machines with unsupervised learning capability require minimal or no assistance from humans to come up with conclusions based on patterns it has uncovered.

As you can see, many of these terms overlap and have related meaning. You should become familiar enough with them to understand how any one of these technologies can affect your marketing efforts. We are happy to answer your questions at any time at Call Sumo and look forward to helping your company experience explosive growth with AI.