Simulated Annealing

Definition Simulated Annealing in AI marketing refers to a probabilistic technique used for finding an approximate solution to an optimization problem. This computational algorithm analogues the process of slow cooling of metals, enabling marketers to find the optimal or near-optimal solution when dealing with a large search space. It is primarily used to minimize or […]

Swarm Intelligence

Definition Swarm Intelligence in marketing refers to the use of Artificial Intelligence algorithms inspired by the collective behavior of decentralized, self-organized systems, such as insects or bird flocks, to optimize marketing strategies. It utilizes autonomous, cooperative agents to collaboratively discover and execute the best marketing operations. This technique can analyze customer behavior, identify patterns and […]

SARSA Algorithm

Definition The SARSA Algorithm, in the context of AI and marketing, is a method of reinforcement learning where the agent learns a policy that dictates what action to take under a specific situation. The acronym stands for State-Action-Reward-State-Action, representing the five key components used in learning. The algorithm aims to maximize the total reward over […]

StyleGANs

Definition StyleGANs, or Style Generative Adversarial Networks, is an AI technique used in marketing by generating hyper-realistic images mainly used to simulate customer personas or product designs. It operates by having two parts, a generator and a discriminator, that continuously learn from each other. This helps in creating high-quality, customizable, creative content, enhancing visual marketing […]

Sparse PCA

Definition Sparse PCA, or Sparse Principal Component Analysis, is an AI-based method used in marketing analytics. It’s a variation of Principal Component Analysis (PCA) that introduces sparsity to loadings, simplifying the interpretation of results. This approach provides a more targeted and efficient data analysis, aiding marketers in identifying and leveraging key influencing factors. Key takeaway […]

Stick-Breaking Process

Definition In the context of AI and marketing, a Stick-Breaking Process refers to a procedure in Bayesian non-parametric statistics. It is used for generating infinite dimensional probability distributions. This process is particularly useful in machine learning algorithms as it helps in understanding and predicting customer behavior, preferences, and trends. Key takeaway The Stick-Breaking Process is […]

Stacking

Definition In marketing, “stacking” refers to the practice of combining different AI technologies into a single platform, creating a system that’s more effective, advanced and comprehensive. This could include combining AI tools such as machine learning, natural language processing, or predictive analytics. The primary benefit of stacking is that it allows multiple AI solutions to […]

Support Vector Machines (SVMs)

Definition Support Vector Machines (SVMs) in AI marketing is a robust algorithm often used in classification or regression problems. This machine learning model constructs hyperplanes in a multidimensional space to separate different categories. This way, it helps marketers predict categories or behaviors of new data and makes business decisions accordingly. Key takeaway Support Vector Machines […]

Self-Organizing Maps (SOMs)

Definition Self-Organizing Maps (SOMs) are a type of artificial intelligence algorithm used in marketing to visualize and interpret complex, multidimensional data. They are employed to identify patterns, clusters, and anomalies by transforming data inputs into a two-dimensional, grid-like structure. SOMs enable businesses to understand their customer behaviour, segment customers, detect fraud, and improve product recommendations. […]

Singular Value Decomposition (SVD)

Definition In the context of AI and marketing, Singular Value Decomposition (SVD) is a mathematical technique used for dimensionality reduction or simplifying a data set. It’s a form of matrix factorization that breaks down a matrix into three resultant matrices, providing a way to visualize and process high-dimensional data. SVD is often used in recommender […]