Consumer Shopping Habits & Trends

Columns

• Customer ID: A unique identifier for each individual customer, enabling the tracking and analysis of their shopping behaviour over time. (Valid records: 3900)
• Age: The customer's age, providing demographic information for segmentation and targeted marketing. (Range: 18-70 years; Mean: 44.1 years; Valid records: 3900)
• Gender: The customer's gender identification, a key demographic variable influencing product preferences and purchasing patterns. (Male: 68%; Female: 32%; Valid records: 3900)
• Item Purchased: The specific product or item selected by the customer during a transaction. (e.g., Blouse, Pants; Valid records: 3900)
• Category: The broad classification or group to which the purchased item belongs. (e.g., Clothing: 45%; Accessories: 32%; Valid records: 3900)
• Purchase Amount (USD): The monetary value of the transaction in United States Dollars, indicating the cost of the purchased item(s). (Range: $20-$100; Mean: $59.8; Valid records: 3900)
• Location: The geographical location where the purchase was made, offering insights into regional preferences and market trends. (50 unique locations; e.g., Montana: 2%, California: 2%; Valid records: 3900)
• Size: The size specification (if applicable) of the purchased item, relevant for apparel and certain consumer goods. (e.g., M: 45%, L: 27%; Valid records: 3900)
• Color: The colour variant or choice associated with the purchased item, influencing customer preferences and product availability. (e.g., Olive: 5%, Yellow: 4%; Valid records: 3900)
• Season: The seasonal relevance of the purchased item, impacting inventory management and marketing strategies. (e.g., Spring: 26%, Fall: 25%; Valid records: 3900)
• Review Rating: A numerical or qualitative assessment provided by the customer regarding their satisfaction with the purchased item. (Range: 2.5-5.0; Mean: 3.75; Valid records: 3900)
• Subscription Status: Indicates whether the customer has opted for a subscription service, offering insights into loyalty and potential recurring revenue. (True: 27%; False: 73%; Valid records: 3900)
• Shipping Type: Specifies the method used to deliver the purchased item. (e.g., Free Shipping: 17%, Standard: 17%; Valid records: 3900)
• Discount Applied: Indicates if any promotional discounts were applied to the purchase, shedding light on price sensitivity and promotion effectiveness. (True: 43%; False: 57%; Valid records: 3900)
• Promo Code Used: Notes whether a promotional code or coupon was utilised during the transaction, aiding in the evaluation of marketing campaign success. (True: 43%; False: 57%; Valid records: 3900)
• Previous Purchases: Provides information on the number or frequency of prior purchases made by the customer. (Range: 1-50; Mean: 25.4; Valid records: 3900)
• Payment Method: Specifies the mode of payment employed by the customer. (e.g., PayPal: 17%, Credit Card: 17%; Valid records: 3900)
• Frequency of Purchases: Indicates how often the customer engages in purchasing activities, a critical metric for assessing customer loyalty and lifetime value. (e.g., Every 3 Months: 15%, Annually: 15%; Valid records: 3900)

Distribution

Usage

• Crafting targeted marketing strategies by understanding customer demographics and preferences.
• Optimising product offerings based on purchase history and popular categories, sizes, and colours.
• Enhancing customer satisfaction by analysing review ratings and shopping experiences.
• Driving sales and loyalty through insights into discount effectiveness, subscription status, and purchase frequency.
• Analysing regional market trends using location data.

Coverage

• Geographic Scope: Features data from 50 unique geographical locations, with examples including Montana and California, suggesting a broad, likely United States-based, coverage given the use of USD for purchase amounts.
• Time Range: The specific time range of the data collection is not specified within the available information.
• Demographic Scope: Includes customer age (18-70 years) and gender (68% Male, 32% Female).
• Data Availability: All columns contain 100% valid data with no missing entries, ensuring high data quality for analysis.

License

Who Can Use It

• Analysts and Researchers: To delve into the intricacies of consumer decision-making processes.
• Businesses and Retailers: For tailoring strategies, optimising product lines, and improving customer relations.
• Marketing Professionals: To develop more effective and targeted promotional campaigns.
• Product Developers: To identify popular features, colours, and sizes for future product designs.
• E-Commerce Managers: To understand online shopping behaviour, shipping preferences, and payment methods.

Dataset Name Suggestions

• Consumer Shopping Habits & Trends
• E-Commerce Customer Behaviour
• Retail Purchase Patterns Data
• Online Shopping Dynamics Dataset

Attributes