Bayesian Optimization

Definition Bayesian Optimization in AI marketing is a model-based optimization technique designed to make the most efficient use of resources during a marketing campaign. It uses a concept from Bayesian statistics to predict the most promising marketing strategies, by creating a probabilistic model that maps different input variables to an output. This model is then […]

Bandit Algorithms

Definition Bandit Algorithms in marketing are AI-based decision-making strategies designed to improve the efficiency of AB testing. They allocate more traffic to the best-performing option based on real-time data, minimizing losses while continually learning and optimizing. This enables marketers to test multiple strategies simultaneously and quickly identify the most effective one. Key takeaway Bandit Algorithms […]


Definition BiGANs, or Bidirectional Generative Adversarial Networks, are a type of AI used in marketing that simulate and generate new data mimicking existing ones. The “bidirectional” aspect refers to their ability to learn both the generation process and the inference process, thereby improving the model’s understanding. This can be helpful in marketing for analyzing patterns, […]

Boltzmann Machines

Definition Boltzmann Machines, in AI marketing, refer to a type of artificial neural network that utilize stochastic processing for solving complex problems, typically binary. Boltzmann Machines can identify patterns and make predictions based on given data sets. They are used for optimization tasks, including improving marketing strategies by predicting customer behavior or segmenting markets based […]


Definition Boosting in AI marketing refers to an iterative algorithmic process used to optimize predictive models. It works by repeatedly running a weak learning algorithm on a dataset and adjusting the model after each iteration to improve accuracy and strengthen predictions. The goal of boosting is to reduce bias and variance in machine learning algorithms, […]

Bellman Equation

Definition The Bellman Equation, named after Richard Bellman, is a fundamental concept in reinforcement learning and artificial intelligence. It helps in making optimal decisions by breaking down larger problems into smaller, overlapping subproblems. In marketing, it can be used to determine the optimal marketing strategy by evaluating the future value of current marketing decisions. Key […]


Definition Backpropagation in AI marketing refers to a supervised learning methodology used primarily in training neural networks. This method uses an algorithm to adjust the weights and biases in the network by calculating gradients, or errors, from the output layer back to the input layer. The ultimate goal is to improve the predictive accuracy of […]

Batch Learning

Definition Batch learning in AI marketing is a type of machine learning where the entire training data set is used at once to train a model. This method does not require the model to be updated in real-time as new data becomes available. The model is typically updated periodically, based on a set schedule or […]

Blogging Schedule

Definition A blogging schedule in marketing is a strategic plan that outlines the frequency and timing of blog posts to be published on a company’s website. It’s typically designed to ensure consistent content creation, which can improve SEO and engage the target audience. This schedule can be categorized by topic, author, or type of post, […]

Bayesian Nonparametric Models

Definition Bayesian Nonparametric Models in AI marketing refer to statistical models that are not defined by a predetermined set of parameters. These models rely on Bayesian statistics, dealing with probability distributions to infer or predict unknown quantities. They set no a priori limit to the amount of information they can learn, making them adaptable and […]