Completed
18,955
67.67% conv.
01 — Conversion funnel
Order funnel analysis
Tracking user progression from order placement through payment, transaction completion, to full-price completion. Each stage reveals where potential revenue is lost.
Key finding: The largest drop-off (18.32 pp) occurs between payment and completion, indicating a substantial refund rate. 14.01% of orders that were placed were never paid, while 21.36% of paid orders resulted in partial or full refunds.
02 — Daily performance
Daily KPI trends
Core metrics tracked by payment date, covering the observation window of February 1 through February 10, 2020.
| Date |
Orders |
Completed |
GMV (¥) |
ARPU (¥) |
Conv. % |
Refund % |
| Feb 01 | 163 | 87 | 7,031 | 80.82 | 53.37 | 89.66 |
| Feb 02 | 199 | 107 | 8,508 | 79.51 | 53.77 | 91.59 |
| Feb 03 | 239 | 136 | 11,317 | 83.21 | 56.90 | 78.68 |
| Feb 04 | 417 | 254 | 21,926 | 86.32 | 60.91 | 66.54 |
| Feb 05 | 328 | 191 | 15,495 | 81.13 | 58.23 | 72.25 |
| Feb 06 | 128 | 72 | 6,025 | 83.68 | 56.25 | 81.94 |
| Feb 07 | 157 | 96 | 7,185 | 74.84 | 61.15 | 64.58 |
| Feb 08 | 2 | 1 | 38 | 38.00 | 50.00 | 100.00 |
| Feb 09 | 352 | 266 | 22,123 | 83.17 | 75.57 | 32.33 |
| Feb 10 | 24 | 16 | 1,010 | 63.13 | 66.67 | 56.25 |
Key finding: Feb 04 and Feb 09 emerge as peak days with GMV exceeding ¥21,000. The anomaly on Feb 08 (only 2 orders) suggests a data collection gap or system event. Feb 09 shows the highest conversion rate (75.57%) paired with the lowest refund rate (32.33%), representing the healthiest transaction day in the dataset.
03 — Temporal patterns
Hourly and weekly distribution
Understanding when customers transact helps optimize marketing spend, inventory management, and customer service staffing.
Hourly transaction volume
Completed orders by hour (0:00 to 9:00, partial data)
Weekly transaction volume
Revenue distribution across weekdays
Key finding: The midnight hour (0:00) shows unexpectedly high activity with 683 completed orders, likely driven by post-midnight browsing behavior. Revenue peaks sharply at 9:00 AM with ¥94.6K. On a weekly basis, Friday generates the highest revenue (¥352.9K), while Sunday and Monday are the slowest days, suggesting that weekday marketing investments may yield better returns.
04 — Geographic distribution
Revenue by province (Top 10)
Transaction concentration across Chinese provinces, ranked by total completed revenue.
01Shanghai (上海)¥264,067
2,470 orders · 73.67% conv.
02Beijing (北京)¥166,470
1,489 orders · 72.49% conv.
03Jiangsu (江苏)¥159,377
1,459 orders · 68.63% conv.
04Guangdong (广东)¥147,845
1,585 orders · 64.35% conv.
05Zhejiang (浙江)¥141,686
1,438 orders · 69.77% conv.
06Sichuan (四川)¥127,668
1,380 orders · 68.35% conv.
07Shandong (山东)¥103,930
1,145 orders · 63.47% conv.
08Tianjin (天津)¥90,001
838 orders · 72.68% conv.
09Liaoning (辽宁)¥74,698
812 orders · 68.41% conv.
10Chongqing (重庆)¥71,525
691 orders · 66.70% conv.
Key finding: Shanghai dominates with ¥264K in revenue and the highest conversion rate (73.67%) among major provinces. Tier-1 cities (Shanghai, Beijing) demonstrate both higher volume and higher conversion rates compared to other regions. Notably, Guangdong, despite ranking 4th in order volume, has the lowest conversion rate (64.35%) in the top 10, suggesting potential regional differences in purchase intent or product-market fit. The average ticket size is highest in Beijing (¥111.80) and Tianjin (¥107.40).
05 — Methodology
Technical approach
End-to-end data pipeline from raw CSV ingestion to interactive dashboard.
Data pipeline
Three-stage processing workflow
1. Ingestion: CSV (UTF-8 with Chinese characters) imported into MySQL 8.0 via a custom Python script to handle encoding issues.
2. Transformation: SQL-based cleaning including province name standardization, derived date fields, order status classification, and refund flags.
3. Visualization: Tableau Desktop connected to MySQL, with both live queries and custom SQL data sources powering the dashboard.
Metric definitions
Consistent calculation methodology
GMV: Sum of buyer's actual payment where amount > 0
Conversion rate: Completed orders / Total orders placed
ARPU: GMV / Number of completed orders
Refund rate: Orders with refund / Completed orders