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https://github.com/thanhloc81/customer-segmentation
✨ Analyze customer segments of Adventure World dataset
https://github.com/thanhloc81/customer-segmentation
bigquery google-cloud powerbi sql
Last synced: about 1 month ago
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✨ Analyze customer segments of Adventure World dataset
- Host: GitHub
- URL: https://github.com/thanhloc81/customer-segmentation
- Owner: thanhloc81
- Created: 2024-05-21T09:33:38.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-07-15T17:13:10.000Z (4 months ago)
- Last Synced: 2024-09-30T10:41:23.174Z (about 2 months ago)
- Topics: bigquery, google-cloud, powerbi, sql
- Homepage:
- Size: 6.13 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Customer Analysis Dashboard for Adventureworks Cycles
Click here to View the Dashboard!
## Company:
Adventureworks Cycles, a leading multinational manufacturer, produces and distributes bicycles, accessories, and materials to North American, European, and Asian markets. After a successful financial year, the company aims to expand its market share by focusing sales efforts on its best customers and reducing production costs to lower sales expenses.
## Objective:
This dashboard analyzes customer behavior using RFM (Recency, Frequency, Monetary) metrics to identify the best customers across all product lines. Key questions include:
- Who are Adventureworks Cycles' top customers?
- Which customers should the sales team focus on to build long-term relationships?
- What are the most popular products and their popularity levels among different customer segments?
## Tools:
- **Google BigQuery:** Using SQL for data retrieval and transformation. Also utilized for creating data models.
- **PowerBI:** Visualization.
## Analysis Context:
- **Stakeholder:** Sales Department Manager
- **Report Date:** July 10, 2014
- **Data Analysis Period:** The past two years, specifically 2013 and 2014
This dashboard provides detailed and visual insights to help the Sales Manager make strategic decisions for optimizing sales efforts and nurturing key customer relationships.
## Insight:
- The percentage of new customers is 18.5%, and lost customers is 7.8% over the past two years.
- The average number of days since a customer last placed an order is 184 days.
- The average amount spent by a customer is $6,225.
- There are 11 customer segments based on order quantity, total order value, and recency:
- **Promising:** New customers with recent purchases, high spending but infrequent orders (1-2 orders).
- **New Customer:** Recently made a purchase, low basket value, infrequent orders.
- **Hibernating:** Long time since last purchase, low spending and infrequent orders.
- **At Risk:** Long time since last purchase, previously frequent buyers with moderate spending.
- **Cannot Lose Them:** Long time since last purchase, previously frequent and high spenders.
- **Need Attention:** Moderate spending and order frequency, recently inactive.
- **Potential Loyalist:** Recently made a purchase, moderate spending, multiple purchases.
- **Loyal:** Frequent purchases (3-4 orders), moderate to high spending.
- **About to Sleep:** Long time since last purchase, low spending and infrequent orders.
- **Champions:** Frequent buyers (4-12 orders), high spending, recent purchases.
- **Lost Customer:** Long time since last purchase, very low spending and frequency.
- Promising customers make up the largest segment at nearly 24%, followed by New Customers at 18.5%. Champions, Loyal, and Potential Loyal customers each make up only 2-3%.
- Customers who spend the most typically make 4-12 purchases. Key order milestones generating high revenue are 4, 8, and 12 orders.
- High-value customers often make another purchase within 50-150 days (1-2 quarters).
- Frequent buyers tend to have a shorter time since their last purchase.
- The **Water Bottle - 30 oz** is the best-selling product across most customer groups, while **Mountain -200-Black 38** provides the best net value for the company.
- Champions prefer **Bikes** and **Clothing**, making the most purchases in these categories compared to other groups, indicating these products' strong customer retention potential.
- Analyzing customer groups versus product sales reveals that Champions often start with **Accessories** and **Clothing** before transitioning to the core **Bikes** products.
## Recommendations:
- **Increase Champions and Reduce At-Risk Segments:**
- Focus on growing the Champions segment and reducing the About to Sleep, Hibernating, and Lost segments for sustainable revenue growth.
- **Retain Champions:**
- Special attention should be given to Champions with loyalty programs and personalized gifts to keep them engaged. Promote high-value products or combos (e.g., Bikes and Clothing) to maximize their spending.
- **Encourage Loyal and Potential Loyal Customers:**
- Implement spending threshold incentives (e.g., “Spend over $1000 for a gift”) and cross-promotions (e.g., discounts on Bikes with purchases of Accessories over a certain amount). Encourage referrals with rewards for introducing new customers.
- **Nurture New and Promising Customers:**
- Provide excellent care and personalized experiences to convert these customers into repeat buyers. Use thank-you notes, feedback requests, and welcome vouchers to foster relationships and encourage repeat purchases.
- **Re-engage At-Risk and Needing Attention Customers:**
- Investigate dissatisfaction reasons and address them before launching sales or marketing campaigns. Conduct surveys to identify issues such as product quality or market competition.
- **Revive Inactive Customers:**
- For About to Sleep, Hibernating, and Lost customers, employ campaigns to re-engage them, such as personalized emails, social media interactions, or calls. Use return incentives like vouchers and exclusive offers.
## Conclusion
To drive sales growth, the sales team must strategically target the right customer groups. This approach reduces marketing costs and builds stronger, long-term relationships with customers. Moving forward, focus on core segments like Champions, Loyal, and Potential Loyal, as well as promising segments like New Customers and Promising, to maximize revenue growth.