Dark Mode
Marketing Customer Campaign Response Data
Data Science and Analytics
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
Provides a detailed analysis of a company's customer base, specifically curated for understanding and optimising marketing campaigns. The data tracks 2,240 individual customer profiles, combining crucial demographic factors such as birth year, education level, marital status, and annual income with specific purchase behaviours and household composition (number of young children and teenagers). The primary purpose of this dataset is to facilitate customer segmentation, evaluate the success of five distinct promotional efforts, and map spending habits across six key product categories (wines, fruits, meat, fish, sweets, and gold products). This information is highly valuable for identifying the company’s ideal customers and refining future marketing strategies.
Columns
The dataset contains 30 columns detailing customer information and interaction metrics:
- Unnamed: 0: Index of the record.
- ID: Unique identifier for each customer.
- Year_Birth: Birth year of the customer (ranging from 1893 to 1996).
- Education: The customer's level of education (e.g., Graduation, PhD).
- Marital_Status: The customer's marital status.
- Income: Annual income of the customer.
- Kidhome: Number of young children residing in the household.
- Teenhome: Number of teenagers residing in the household.
- Dt_Customer: The date the customer was enrolled with the company.
- Recency: Number of days elapsed since the customer's last purchase.
- MntWines: Amount spent on wines in the last two years.
- MntFruits: Amount spent on fruits in the last two years.
- MntMeatProducts: Amount spent on meat products in the last two years.
- MntFishProducts: Amount spent on fish products in the last two years.
- MntSweetProducts: Amount spent on sweet products in the last two years.
- MntGoldProds: Amount spent on gold products in the last two years.
- NumDealsPurchases: Number of purchases made utilising a discount.
- NumWebPurchases: Number of purchases transacted through the web channel.
- NumCatalogPurchases: Number of purchases made using a printed catalogue.
- NumStorePurchases: Number of purchases made directly in physical stores.
- NumWebVisitsMonth: Number of visits to the company's website per month.
- AcceptedCmp1 through AcceptedCmp5: Binary flags indicating whether the customer accepted each of the five individual marketing campaigns (Campaign 1, 2, 3, 4, and 5).
- Complain: Indicates whether the customer registered a complaint.
- Z_CostContact: Cost associated with contacting the customer.
- Z_Revenue: Revenue generated from the campaign.
- Response: Binary flag indicating whether the customer responded to the current campaign effort.
Distribution
The data is typically provided in a structured data file, such as CSV format. The file,
marketing_campaign.csv, is approximately 234.72 kB in size. The structure includes 30 columns and contains 2,240 valid records for most fields. Notably, the 'Income' column has a small percentage of missing values (1%).Usage
This dataset is ideally suited for:
- Data Analytics and Visualisation: Performing exploratory data analysis (EDA) to find correlations between demographics and spending patterns.
- Customer Segmentation: Building models to group customers based on their purchasing habits (e.g., high wine spenders versus high meat product spenders).
- Marketing Effectiveness Measurement: Analysing the response rates across Campaigns 1 through 5 to determine which promotion method was most successful.
- Predictive Modelling: Developing machine learning models to predict a customer’s likelihood of responding to a future marketing campaign.
- Data Cleaning and Storytelling: Utilising the data to practice data hygiene and communicate business insights effectively.
Coverage
The data encompasses customer enrollment over a period spanning from July 2012 to June 2014. Demographic data is rich, covering a wide age range based on birth years from 1893 up to 1996. The expected update frequency for this type of data is annually.
License
CC0: Public Domain
Who Can Use It
- Marketing Managers: To refine targeting strategies and allocate resources based on proven customer response metrics.
- Data Scientists: For training and evaluating classification and clustering algorithms related to consumer behaviour.
- Academics and Students: As a high-quality, real-world case study for marketing analytics, data visualisation, and statistical modelling projects.
- Business Intelligence Analysts: To generate reports and dashboards tracking customer lifetime value and campaign performance indicators.
Dataset Name Suggestions
- Marketing Customer Campaign Response Data
- Consumer Demographics and Spending Habits
- Customer Segmentation Marketing Analysis
- Annual Customer Profile and Campaign Data
Attributes
Original Data Source: Marketing Customer Campaign Response Data
QUALITYLoading...