Churn Prediction and Prevention with AI

Definition In the marketing term: Churn Prediction and Prevention with AI, AI refers to Artificial Intelligence. It’s a technology used to analyze data to identify patterns and trends, which can predict customer behaviors that indicate a likelihood to churn or stop doing business with the company. Prevention strategies are then driven by these insights, aiming […]

Competitive Intelligence

Definition Competitive Intelligence in AI marketing refers to the gathering and analysis of information about competitors using advanced AI tools and techniques. This helps in understanding competitors’ strategies, strengths, and weaknesses, aiding in strategic decision making. It involves monitoring market trends, competitor products, sales, and marketing methods to gain a competitive edge. Key takeaway Competitive […]

Closed Captioning

Definition In marketing, closed captioning refers to the AI-generated or manually created text transcript that appears on screen during a video. This text encapsulates spoken dialogue and important sounds, allowing deaf or hard-of-hearing viewers to fully understand the content. In a marketing context, closed captions can also improve viewer engagement and extend a video’s reach […]

CutMix

Definition CutMix is an AI technique used in marketing that involves image data augmentation. It works by cutting and pasting patches between images and labels, which helps to improve the performance and efficiency of image classification tasks. It allows marketers to enhance their visual content, offering more variety and enhanced AI learning. Key takeaway CutMix […]

CatBoost

Definition CatBoost is a machine learning algorithm from Yandex that uses gradient boosting on decision trees to optimize prediction accuracy. In marketing, CatBoost helps analyze complex patterns in data and predict future trends or behaviors by learning from past experiences. It stands out for handling categorical variables effectively and providing high-performing models with less data […]

Convolutional Neural Networks (CNNs)

Definition Convolutional Neural Networks (CNNs) are a type of artificial intelligence used in marketing that processes information similar to the human brain. They are especially suited for analyzing visual imagery, as they are designed to automatically and adaptively learn spatial hierarchies of features from training data. In a marketing context, CNNs are used to understand […]

Cognitive Computing

Definition Cognitive computing in marketing refers to the use of artificial intelligence and machine learning to simulate human thought processes in a computerized model. This enables businesses to analyze customer behavior or preferences, anticipate future behaviors, and deliver personalized marketing experiences. It aids in achieving better customer interaction, decision-making, and automation of tasks. Key takeaway […]

Cooperative Learning

Definition Cooperative Learning in AI marketing refers to the approach where multiple AI models collaboratively learn and refine their strategies from data. They share insights and information with each other to improve efficiency and accuracy of predictions. This method leverages collective intelligence to achieve more effective marketing results. Key takeaway Cooperative Learning refers to a […]

Collaborative Learning

Definition Collaborative Learning in AI marketing refers to the concept where artificial intelligence systems learn from each other by sharing data and insights. It helps in improving performance, expanding their knowledge base, and making more accurate predictions. This shared learning process enhances efficiency and effectiveness within marketing campaigns or strategies. Key takeaway Collaborative learning in […]

Curriculum Learning

Definition Curriculum Learning in AI and marketing refers to a training strategy in which models learn from easy examples first, then progressively from more complex ones, akin to a human educational curriculum. The idea is to structure the learning process, improving the efficiency and effectiveness of training the model. This methodology optimizes model performance and […]