Artificial Intelligence (AI) has become integral to modern marketing strategies. It is a field of computer science that aims to create systems capable of performing tasks usually requiring human intelligence. These tasks include learning, reasoning, problem-solving, perception, and language understanding. In marketing, AI can analyze consumer behavior, predict trends, automate tasks, and improve customer experiences. AI

Machine Learning (ML) is a subset of Artificial Intelligence (AI) that allows systems to learn and improve from experience without being explicitly programmed. In marketing, Machine Learning can be a game-changer, offering unprecedented opportunities for businesses to understand their customers, predict trends, and make data-driven decisions. This article will delve into the intricacies of Machine Learning

Deep Learning, a subset of Artificial Intelligence (AI), is revolutionizing the marketing landscape. By leveraging complex algorithms and neural networks, deep Learning enables marketers to analyze vast amounts of data, extract meaningful insights, and make informed decisions. This article delves into the intricacies of deep Learning, its applications in marketing, and its potential implications for

Named Entity Recognition (NER) is a subfield of artificial intelligence (AI) that focuses on identifying and classifying named entities in text. Named entities can be anything from people’s names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc. In marketing, NER can analyze customer feedback, social media posts, and unstructured data to extract

Artificial Intelligence (AI) has revolutionized various sectors, and marketing is no exception. One of the most significant aspects of AI in marketing is using neural networks. This glossary article aims to provide an in-depth understanding of neural networks and their application in marketing. Neural networks, a subset of machine learning, are designed to mimic the

Generative AI, a subfield of artificial intelligence, has gained significant attention in recent years for its potential to revolutionize various industries, including marketing. This technology leverages machine learning algorithms to generate content, such as text, images, or music, that is new, unique, and often indistinguishable from content created by humans. In marketing, generative AI can

Generative Adversarial Networks (GANs) are a class of artificial intelligence algorithms used in unsupervised machine learning.  GANs are systems consisting of two parts, namely a Generator and a Discriminator, which are in a constant game of cat and mouse. The Generator creates new data instances while the Discriminator evaluates them for authenticity, i.e., whether each

Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that focuses on the interaction between computers and humans through language. It enables machines to understand, interpret, and generate human language in a valuable and meaningful way. In marketing, NLP AI can be a game-changer, offering many opportunities to enhance customer experience, improve targeting,

Augmented Reality (AR) is a technology that overlays digital information in the real world, enhancing the user’s perception and interaction with their environment. This technology has found a significant place in various industries, including marketing. With Artificial Intelligence (AI) integration, AR has been revolutionized, offering marketers new ways to engage with their audience, personalize content,