Here’s a sample dataset for Customer Demographics and Behavior that you can use for analysis in Power BI. The dataset includes columns for customer profiles, purchase history, website traffic, and customer service interactions.
Data Source: Customer profiles, purchase history, website traffic, customer service data
Key Metrics: Age, gender, location, average spending per customer, churn rate, customer lifetime value (CLV), frequency of visits, and top performing channels (social media, search, email).
1. Customer Profiles
| CustomerID | FirstName | LastName | Age | Gender | Location | DateJoined | LastLogin | Status | |
|---|---|---|---|---|---|---|---|---|---|
| 1001 | John | Doe | 28 | Male | New York, USA | john.doe@email.com | 2023-03-01 | 2024-12-20 | Active |
| 1002 | Jane | Smith | 34 | Female | Los Angeles, USA | jane.smith@email.com | 2022-07-15 | 2024-12-19 | Active |
| 1003 | Sam | Green | 42 | Male | Chicago, USA | sam.green@email.com | 2021-10-20 | 2024-12-10 | Inactive |
| 1004 | Emma | Brown | 27 | Female | London, UK | emma.brown@email.com | 2023-01-10 | 2024-12-22 | Active |
| 1005 | Olivia | White | 55 | Female | Sydney, AUS | olivia.white@email.com | 2020-11-05 | 2024-12-25 | Active |
2. Purchase History
| CustomerID | ProductID | ProductName | Category | PurchaseDate | Quantity | TotalAmount | PaymentMethod | DiscountApplied | OrderStatus |
|---|---|---|---|---|---|---|---|---|---|
| 1001 | 101 | Wireless Mouse | Electronics | 2024-12-01 | 1 | 20.00 | Credit Card | 5% | Delivered |
| 1002 | 105 | Office Chair | Furniture | 2024-12-05 | 2 | 250.00 | PayPal | 10% | Delivered |
| 1003 | 102 | Laptop Stand | Electronics | 2024-11-28 | 1 | 30.00 | Credit Card | 0% | Canceled |
| 1004 | 106 | Desk Organizer | Office Supplies | 2024-12-10 | 3 | 45.00 | Debit Card | 0% | Delivered |
| 1005 | 103 | Ergonomic Keyboard | Electronics | 2024-12-12 | 1 | 65.00 | Credit Card | 15% | Delivered |
3. Website Traffic
| CustomerID | SessionID | SessionStart | SessionEnd | PagesVisited | DeviceType | ReferralSource | SessionDuration (min) | Conversion |
|---|---|---|---|---|---|---|---|---|
| 1001 | S001 | 2024-12-01 10:05 | 2024-12-01 10:30 | 5 | Desktop | 25 | Yes | |
| 1002 | S002 | 2024-12-05 14:20 | 2024-12-05 14:45 | 8 | Mobile | 25 | No | |
| 1003 | S003 | 2024-11-28 09:00 | 2024-11-28 09:15 | 4 | Tablet | Organic Search | 15 | No |
| 1004 | S004 | 2024-12-10 13:00 | 2024-12-10 13:45 | 6 | Desktop | 45 | Yes | |
| 1005 | S005 | 2024-12-12 16:30 | 2024-12-12 17:00 | 10 | Mobile | 30 | Yes |
4. Customer Service Interactions
| CustomerID | InteractionID | InteractionDate | IssueType | ResolutionStatus | SupportAgent | ResolutionTime (hrs) | SatisfactionScore |
|---|---|---|---|---|---|---|---|
| 1001 | I001 | 2024-12-02 | Shipping Delay | Resolved | Mike | 2 | 4 |
| 1002 | I002 | 2024-12-06 | Product Defect | Resolved | Sarah | 3 | 5 |
| 1003 | I003 | 2024-11-29 | Refund Request | Pending | John | 1 | N/A |
| 1004 | I004 | 2024-12-11 | Delivery Issue | Resolved | Chris | 4 | 3 |
| 1005 | I005 | 2024-12-13 | Incorrect Billing | Resolved | Emma | 5 | 4 |
Additional Notes:
- Customer Profiles contain basic demographic and engagement data.
- Purchase History gives insights into the types of products customers are buying, including transaction details.
- Website Traffic shows user sessions, engagement, and conversion status (whether a purchase or goal was achieved).
- Customer Service Interactions track the type of issues, resolution status, and customer satisfaction with the support received.
This data can be imported into Power BI to create insightful visualizations, such as:
- Customer demographics and purchase behavior (age, gender, location, products bought)
- Website traffic analysis (session duration, conversion rates, referral sources)
- Customer service metrics (issue resolution time, satisfaction score trends)