The total revenue a business can expect from a customer throughout their relationship, guiding marketing investment.

Structured Query Language used for managing and manipulating relational databases, essential for data extraction.

A versatile programming language widely used for data analysis, enabling complex calculations and visualizations.

The process of retrieving data from various sources for analysis, crucial for building a CLV model.

Strategies aimed at improving marketing effectiveness and ROI based on data-driven insights.

Ensuring the accuracy and quality of data before analysis, critical for reliable CLV calculations.

An approach to analyzing datasets to summarize their main characteristics, often using visual methods.

The process of correcting or removing inaccurate records from a dataset to improve analysis quality.

Software applications used to create graphical representations of data, making insights easier to understand.

The strategic distribution of a marketing budget across various channels based on performance metrics.

Methods used to create predictive models, such as regression analysis, for estimating CLV.

A performance measure used to evaluate the efficiency of an investment relative to its cost.

Detailed analyses of real-world examples used to illustrate successful applications of CLV in marketing.

Conditions taken for granted in modeling that can affect the accuracy of the CLV predictions.

Dividing a customer base into groups for targeted marketing strategies based on specific characteristics.

A plan for managing data assets to support business goals, including analytics and marketing optimization.

The process of collecting, analyzing, and interpreting data to derive actionable insights.

Using statistical algorithms and machine learning techniques to identify the likelihood of future outcomes.

Metrics used to measure the success of marketing strategies and overall performance.

Evaluating different strategies or case studies to identify best practices and lessons learned.

Recording processes, methodologies, and findings to ensure clarity and reproducibility in analysis.

A compelling way to communicate findings, ensuring clarity and engagement with the audience.

A comprehensive plan formulated to achieve marketing objectives and improve customer engagement.

Conclusions drawn from data analysis that inform business decisions and strategies.

The study of how individuals make decisions to spend their resources on consumption-related items.