New Customer Repurchase Analysis

I. Calculator Introduction

The New Customer Repurchase Analysis Calculator is a specialized tool for analyzing repurchase behavior of newly registered users after registration. By calculating 7-day and 30-day repurchase rates, this tool helps you gain deep insights into new customers' loyalty and repurchase potential, providing data support for developing new customer operation strategies.

Core Features

• 7-Day Repurchase Rate Analysis: Statistics on new customers' repurchase behavior within 7 days after registration (including registration day)
• 30-Day Repurchase Rate Analysis: Statistics on new customers' repurchase behavior within 30 days after registration (including registration day)
• Time Trend Analysis: Provides daily, weekly, and monthly repurchase rate trend charts to observe changes in repurchase behavior
• Grouped Statistics: Groups by registration month to display repurchase performance of new customers in different periods

Application Scenarios

• Evaluate the effectiveness of new customer operation strategies
• Identify characteristics of new customer groups with higher repurchase rates
• Compare repurchase performance of new customers across different periods
• Develop new customer activation and retention strategies

Target Customers

This calculator is suitable for all industries and scenarios that need to analyze new customer repurchase behavior, especially the following types of customers:

• Food & Beverage Industry: Restaurants, fast food chains, coffee shops, bubble tea shops, etc. Analyze new customers' repurchase after registration, evaluate the impact of food quality and service experience on new customer retention
• E-commerce Platforms: B2C e-commerce, C2C platforms, vertical e-commerce, etc. Analyze new users' repurchase rate after registration, optimize new customer operations and product recommendation strategies
• Retail Industry: Supermarkets, convenience stores, specialty stores, brand retail, etc. Understand new customers' repurchase habits, develop membership marketing and promotion strategies
• Life Services: Beauty salons, fitness clubs, car wash services, home services, etc. Evaluate how service quality promotes new customer repurchase
• Online Education: Online course platforms, training institutions, etc. Analyze new students' repurchase rates, optimize course content and learning experience
• Subscription Services: Video platforms, music platforms, reading platforms, etc. Analyze new users' renewal willingness and repurchase behavior after subscription
• Other B2C Businesses: Any business targeting individual consumers, as long as it involves new customer acquisition and repurchase conversion, can use this tool for analysis

Prerequisites: Your business needs to be able to provide data with user ID, order date, and registration date, and new customers typically have orders on the registration day.

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II. Algorithm Introduction

2.1 Core Concepts

Repurchase Definition

Repurchase: Users have multiple different order dates within a specified time window (count(distinct order_date) > 1).

For example:

• User A registered and placed an order on 2024-01-01, then placed another order on 2024-01-03 → Has repurchase
• User B registered and placed an order on 2024-01-01, placed multiple orders on the same day (but only 1 order date) → No repurchase

Time Window Definition

• 7-day window: From registration day to registration day + 6 days, totaling 7 days (including registration day)
• 30-day window: From registration day to registration day + 29 days, totaling 30 days (including registration day)

2.2 Calculation Logic

Step 1: Data Filtering

The system filters users who meet the following conditions:

1. Registration date must be provided: Users must have a valid registration date field
2. Must have order on registration day: Only users who placed orders on the registration day are counted; users without orders on registration day are excluded

Step 2: User Repurchase Judgment

For each qualified user:

1. Get all order dates (deduplicated) of the user within the specified time window after registration
2. Judge whether the number of order dates is greater than 1
   • If count(distinct order_date) > 1 → The user has repurchase
   • If count(distinct order_date) = 1 → The user has no repurchase

Step 3: Repurchase Rate Calculation

Overall repurchase rate:

Repurchase Rate = Number of users with repurchase / Total number of qualified users

Repurchase rate grouped by registration date:

Repurchase rate on a specific day = Number of users registered on that day with repurchase / Total number of users registered on that day

Step 4: Result Display

1. Overall Metrics:
   • 7-day repurchase rate: Repurchase rate of all new customers within 7 days after registration
   • 30-day repurchase rate: Repurchase rate of all new customers within 30 days after registration
2. Trend Charts:
   • 7-Day Repurchase Rate Daily Trend: Displays daily 7-day repurchase rates by registration date
   • 7-Day Repurchase Rate 30-Day Trend: Displays daily 30-day repurchase rates by registration date (Note: This chart shows the repurchase rate within 30 days after registration, not within 7 days)
3. Grouped Statistics Table:
   • Grouped by registration month
   • Displays new customer count, 7-day repurchase count, 30-day repurchase count, 7-day repurchase rate, and 30-day repurchase rate for each month

2.3 Data Filtering Rules

• Time Range: Charts and tables only display data from the last 2 years; historical data older than 2 years is automatically filtered
• Data Completeness: Records missing key fields (user ID, order date, registration date) are automatically excluded

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III. Usage Instructions and Notes

3.1 Data Preparation

Required Fields

Before importing data, please ensure your data file contains the following three fields:

1. User ID (user_id)
   • Description: Field that uniquely identifies users (user ID or phone number)
   • Format requirements: Text or numbers are acceptable
   • Examples: U001, 12345, 13800138000
2. Order Date (order_date)
   • Description: Date when the user placed the order
   • Format requirements: Supports multiple date formats (such as YYYY-MM-DD, YYYY/MM/DD, MM/DD/YYYY, etc.)
   • Notes: The system automatically recognizes common date formats; it is recommended to use standard date formats to ensure accurate parsing
3. Registration Date (first_order_date)
   • Description: User's registration date (used as label day)
   • Format requirements: Same as order date format
   • Important: This field must be provided; users missing this field will be excluded from the analysis

Data Format Requirements

• File Format: Supports CSV and Excel (.xlsx) formats
• Encoding: UTF-8 encoding is recommended
• Data Volume: It is recommended that the data volume for a single analysis does not exceed 1 million records to ensure calculation efficiency

3.2 Field Mapping

After uploading data, the system will ask you to map columns in your data file to the following fields:

• User ID Column → Select the column containing unique user identifiers
• Order Date Column → Select the column containing order dates
• Registration Date Column → Select the column containing user's registration date

3.3 Data Filtering (Optional)

The system supports filtering order dates and registration dates:

• Date Range Filtering: You can specify the time range for analysis, analyzing only data within the specified time period
• Usage Recommendation: If the data volume is large, it is recommended to filter to the last 1-2 years of data first to improve calculation speed

3.4 Result Interpretation

Metric Description

• 7-Day Repurchase Rate: Reflects new customers' repurchase activity within one week after registration, an important metric for measuring new customer activation effectiveness
• 30-Day Repurchase Rate: Reflects new customers' repurchase activity within one month after registration, an important metric for measuring new customer retention effectiveness

Trend Analysis

• Upward Trend: Repurchase rate shows an upward trend, indicating that new customer operation strategies are effective
• Downward Trend: Repurchase rate shows a downward trend, requiring attention to new customer quality or operation strategies
• High Volatility: May be affected by seasonal factors or operational activities

3.5 Notes

⚠️ Important Limitations

💡 Usage Recommendations

3.6 Frequently Asked Questions

Q1: Why are some users in my data not counted?

A: Possible reasons include:

• Users are missing registration date fields
• Users did not place orders on the registration day
• User order dates or registration dates cannot be parsed

Q2: Does repurchase rate calculation include orders on the registration day?

A: Yes. Repurchase judgment is based on "the number of different order dates." If a user placed an order on the registration day and has orders on other dates later, it counts as repurchase.

Q3: If a user places multiple orders on the same day, does it count as repurchase?

A: No. The definition of repurchase is "multiple different order dates." Multiple orders on the same day only count as 1 order date, so it does not count as repurchase.

Q4: What does "7-Day Repurchase Rate 30-Day Trend" in the chart mean?

A: This chart shows: For each registration date, the repurchase rate of users registered on that day within 30 days after registration. Note: The time window here is 30 days, not 7 days.

Q5: How to improve new customer repurchase rate?

A: It is recommended to start from the following aspects:

• Optimize new customer registration experience to improve user satisfaction
• Strengthen user outreach 3-7 days after registration, push coupons or activity information
• Establish a new customer exclusive benefits system to incentivize repurchase
• Analyze characteristics of new customers with high repurchase rates to optimize operation strategies

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IV. Summary

The New Customer Repurchase Analysis Calculator helps you fully understand new customers' repurchase behavior through scientific algorithms and intuitive visualizations. Proper use of this tool can:

• Quickly identify key metrics for new customer repurchase
• Discover repurchase rate trends and adjust operation strategies in time
• Compare new customer performance across different periods to evaluate operation effectiveness
• Provide data support for developing new customer activation and retention strategies

If you have any questions or need technical support, please contact the system administrator.