Lecture Notes on Big Data and Marketing Strategies

A set of flashcards covering key vocabulary and concepts from the lecture on big data, marketing strategies, A/B testing, user-generated content, and network dynamics.

Big Data

Large and complex data sets that cannot be easily managed or analyzed using traditional data processing methods.

Primary Data

Data that is collected for specific research questions.

Secondary Data

Data collected for non-research purposes, often used in big data applications.

Tall Data

Data characterized by many observations but few variables.

Wide Data

Data characterized by few observations but many variables.

Personalization

The use of recommendation algorithms to enhance user experience.

Churn Reduction

Models that predict customer churn by analyzing past behaviors.

Always-On Data Collection

Real-time data collection and analysis capabilities.

Algorithmically Confounded

Bias in results due to the design of platforms affecting data accuracy.

A/B Testing

A method where users are randomly divided into two groups to compare outcomes from different stimuli.

Multivariate Testing

A method that tests multiple variables simultaneously to find the most effective combinations.

Cold Start Problem

Difficulty in making recommendations due to lack of ratings for new items or users.

Content-Based Filtering

Recommends items based on their attributes and user preferences.

Collaborative Filtering

Utilizes similarities between users or items to make recommendations.

User-Generated Content (UGC)

Digital content produced by end users, which is often voluntarily and publicly available.

Prospect Theory

A theory suggesting consumers perceive losses more acutely than gains.

Fake Reviews

Inaccurate reviews often written to misrepresent a product's quality.

Degree Centrality

The number of direct connections an individual has in a network.

Social Contagion

The spread of behaviors or information among consumers through their connections.

Influentials

Consumers who have a significant impact on spreading marketing messages.

Market Structure Analysis

Investigates brand positioning and competitor similarities through surveys.

Recommendation Systems

Systems that enhance product discovery through customized suggestions based on user data.