Dark Mode
Synthetic Marketing Customer Metrics
Synthetic Data Generation
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This synthetic marketing dataset is designed for advanced customer segmentation, focusing on the core principles of Recency, Frequency, and Monetary (RFM) analysis. The data provides detailed metrics on customer behaviour, including order frequency and total spending, allowing analysts to gauge customer value and predict future engagement. It features 100,000 clean records, providing a robust foundation for building machine learning models aimed at improving customer retention strategies and targeted campaigns.
Columns
- Customer Value Metric (Recency proxy): A metric ranging from 0 to 100,000, with a mean value of 50,000. This column is useful for segmenting customers based on their engagement time frame or responsiveness.
- qtt_order: Represents the total number of orders placed by the customer, indicating purchase frequency. Values range up to 1370, with a typical mean of 104 orders.
- total_spent: Represents the total amount spent by the customer across all orders, serving as the monetary value indicator. Spending amounts are substantial, ranging from £561.60 upwards, highlighting diverse customer economic profiles.
Distribution
The dataset is structured with 100,000 individual records, perfectly suited for immediate analysis without the need for extensive cleaning. All records are valid, with zero missing or mismatched entries across the key metrics. The source file is typically provided in a standard CSV format.
Usage
This data is ideal for:
- Developing and testing RFM segmentation models to identify high-value customer groups.
- Training machine learning models to forecast Customer Lifetime Value (CLV).
- Conducting detailed behavioural analysis to understand purchasing patterns and drivers of loyalty.
- Benchmarking customer retention performance and efficacy of marketing interventions.
Coverage
The data is entirely synthetic, simulating typical retail or e-commerce customer transactions. While not tied to a specific geography or time period, the structure reflects general consumer purchasing dynamics. The value ranges provided ensure a varied distribution suitable for rigorous statistical testing.
License
CC0: Public Domain
Who Can Use It
- Marketing Analysts: To perform precise customer segmentation and design targeted advertising campaigns.
- Data Scientists: To build predictive models for churn reduction and lifetime value estimation.
- Business Intelligence Professionals: To generate reports and dashboards tracking key performance indicators related to customer loyalty and spending.
Dataset Name Suggestions
- RFM Customer Segmentation Data
- Synthetic Marketing Customer Metrics
- E-commerce Customer Value Inputs
- Customer Order Frequency and Spend Records
Attributes
Original Data Source: Synthetic Marketing Customer Metrics
QUALITYLoading...