← Back to Analysis Directory Sample Report: Customer Cohort Retention Analysis

Context and Data Preparation

Analysis Overview and Data Quality

OV

Analysis Overview

Cohort Retention Configuration

Analysis overview and configuration

Cohort Retention
SaaS Company
Analyze customer cohort retention patterns
Module Configuration
cohort_period month
retention_periods 6
include_churned TRUE
Processing ID
test_1766220231
IN

Key Insights

Analysis Overview

Purpose

This section provides insights into the cohort retention analysis conducted for a SaaS company, focusing on key metrics, data characteristics, and significant findings.

Key Findings

  • Overall Health Rate: 86% - Indicates the healthiness of the customer base.
  • Delinquent Rate: 10% - Shows the proportion of customers with payment issues.
  • Retention Rates: Consistently high, with an average of 93.03% across different periods.

Interpretation

The analysis reveals a generally healthy customer base with a high retention rate. The company has a low churn rate (4%) and a moderate delinquent rate (10%). The cohort retention rates are stable over time, indicating good customer loyalty.

Context

The analysis provides valuable insights into customer behavior and retention patterns but does not delve into the specific reasons behind churn or delinquency. Further investigation may be needed to understand the drivers of these metrics.

IN

Key Insights

Analysis Overview

Purpose

This section provides insights into the cohort retention analysis conducted for a SaaS company, focusing on key metrics, data characteristics, and significant findings.

Key Findings

  • Overall Health Rate: 86% - Indicates the healthiness of the customer base.
  • Delinquent Rate: 10% - Shows the proportion of customers with payment issues.
  • Retention Rates: Consistently high, with an average of 93.03% across different periods.

Interpretation

The analysis reveals a generally healthy customer base with a high retention rate. The company has a low churn rate (4%) and a moderate delinquent rate (10%). The cohort retention rates are stable over time, indicating good customer loyalty.

Context

The analysis provides valuable insights into customer behavior and retention patterns but does not delve into the specific reasons behind churn or delinquency. Further investigation may be needed to understand the drivers of these metrics.

PP

Data Preprocessing

Data Quality & Completeness

0
Final Customers

Data preprocessing and column mapping

Data Pipeline
0
Initial Records
0
Clean Records
Column Mapping
customer_id
Customer ID
created_at
Created
delinquent
Delinquent
account_balance
Account Balance
metadata
Metadata
0 Records
MCP Analytics
IN

Key Insights

Data Preprocessing

Purpose

This section details the data preprocessing steps, including data quality checks, retention rate calculation, and data split information.

Key Findings

  • Initial Rows: 0 - No data rows were present initially.
  • Final Rows: 0 - After preprocessing, no data rows were retained.
  • Rows Removed: 0 - No rows were removed during preprocessing.
  • Retention Rate: 100% - Indicates that all data was retained without any loss.

Interpretation

The data preprocessing section shows that there was no data available for analysis, resulting in no rows being retained after processing. The perfect retention rate suggests that no data cleaning or filtering was necessary.

Context

The absence of data in this section may impact the overall analysis by limiting the insights that could have been derived from the preprocessing steps. It is essential to ensure data availability for meaningful analysis and decision-making.

IN

Key Insights

Data Preprocessing

Purpose

This section details the data preprocessing steps, including data quality checks, retention rate calculation, and data split information.

Key Findings

  • Initial Rows: 0 - No data rows were present initially.
  • Final Rows: 0 - After preprocessing, no data rows were retained.
  • Rows Removed: 0 - No rows were removed during preprocessing.
  • Retention Rate: 100% - Indicates that all data was retained without any loss.

Interpretation

The data preprocessing section shows that there was no data available for analysis, resulting in no rows being retained after processing. The perfect retention rate suggests that no data cleaning or filtering was necessary.

Context

The absence of data in this section may impact the overall analysis by limiting the insights that could have been derived from the preprocessing steps. It is essential to ensure data availability for meaningful analysis and decision-making.

Executive Summary

Key Findings and Recommendations

TLDR

Executive Summary

Key Findings & Recommendations

86
Health Rate

Key Performance Indicators

Overall health rate
86
Total customers
50
Unique cohorts
11
Delinquent customers
5

Cohort Retention Summary

Key findings

finding value impact
Overall Customer Health Rate 86% Healthy
Best Performing Cohort 2024-01 (100% healthy) Benchmark for improvement
Cohort Needing Attention 2024-04 (50% healthy) Focus retention efforts here
Customers at Payment Risk 5 customers ($33,500 at risk) Revenue at risk
Average Retention at Month 3 93% Good

Executive Summary

Bottom Line: Customer health rate is 86% across 50 customers in 11 cohorts.

Key Findings:
• Overall health rate of 86% indicates strong customer retention
• 5 customers (10%) have payment issues
• 2 customers have churned (4%)
• $33,500 in account balance at risk from delinquent customers
• Data spans 309 days from 2024-01-05 to 2024-11-08

Recommendations:
• Focus retention efforts on cohorts with lowest health rates
• Implement early intervention for delinquent customers
• Analyze best-performing cohorts to identify successful acquisition strategies
• Monitor retention at Month 1-3 when most churn typically occurs

IN

Key Insights

Executive Summary

Purpose

This section provides a concise overview of the key findings and metrics from the executive summary of the cohort retention analysis. It aims to highlight critical insights for decision-makers.

Key Findings

  • Overall Health Rate: 86% - Indicates strong customer retention.
  • Delinquent Customers: 5 (10%) - Some customers have payment issues.
  • Churned Customers: 2 (4%) - A small percentage of customers have churned.
  • Total Balance at Risk: $33,500 - From delinquent customers.
  • Date Range: Spans 309 days from 2024-01-05 to 2024-11-08.

Interpretation

The analysis reveals a relatively healthy customer base with a notable retention rate. However, attention is needed for delinquent customers to mitigate financial risks. Understanding churn patterns and cohort performance can guide targeted retention strategies.

Context

The recommendations provided in the data profile suggest focusing on cohorts with lower health rates, early intervention for delinquent customers, and learning from successful acquisition strategies. Executives should consider these insights for optimizing customer retention and revenue protection strategies.

IN

Key Insights

Executive Summary

Purpose

This section provides a concise overview of the key findings and metrics from the executive summary of the cohort retention analysis. It aims to highlight critical insights for decision-makers.

Key Findings

  • Overall Health Rate: 86% - Indicates strong customer retention.
  • Delinquent Customers: 5 (10%) - Some customers have payment issues.
  • Churned Customers: 2 (4%) - A small percentage of customers have churned.
  • Total Balance at Risk: $33,500 - From delinquent customers.
  • Date Range: Spans 309 days from 2024-01-05 to 2024-11-08.

Interpretation

The analysis reveals a relatively healthy customer base with a notable retention rate. However, attention is needed for delinquent customers to mitigate financial risks. Understanding churn patterns and cohort performance can guide targeted retention strategies.

Context

The recommendations provided in the data profile suggest focusing on cohorts with lower health rates, early intervention for delinquent customers, and learning from successful acquisition strategies. Executives should consider these insights for optimizing customer retention and revenue protection strategies.

Retention Heatmap

Cohort Retention Matrix

HTM

Retention Heatmap

Cohort Retention by Period

11
Cohorts

Retention rates across cohorts and time periods

11
unique cohorts
6
retention periods
IN

Key Insights

Retention Heatmap

Purpose

This section presents a retention heatmap tracking 11 cohorts over 6 periods to visualize retention rates. It helps identify which signup periods yield the most loyal customers and reveals trends in customer retention over time.

Key Findings

  • Retention Rate: Mean of 93.03% across all cohorts and periods - Indicates strong customer loyalty.
  • Customer Count: Average of 4.55 customers per cohort - Shows the typical cohort size.
  • Retention Patterns: Consistent high retention rates (mostly 100%) in early months, potentially indicating effective onboarding.

Interpretation

The high average retention rate and stable customer count suggest a healthy customer base with good retention. The consistent high retention in initial months implies successful customer engagement strategies early in the customer lifecycle.

Context

Understanding retention patterns is crucial for assessing customer loyalty and the effectiveness of acquisition strategies. However, further analysis may be needed to explore factors influencing retention rates over time.

IN

Key Insights

Retention Heatmap

Purpose

This section presents a retention heatmap tracking 11 cohorts over 6 periods to visualize retention rates. It helps identify which signup periods yield the most loyal customers and reveals trends in customer retention over time.

Key Findings

  • Retention Rate: Mean of 93.03% across all cohorts and periods - Indicates strong customer loyalty.
  • Customer Count: Average of 4.55 customers per cohort - Shows the typical cohort size.
  • Retention Patterns: Consistent high retention rates (mostly 100%) in early months, potentially indicating effective onboarding.

Interpretation

The high average retention rate and stable customer count suggest a healthy customer base with good retention. The consistent high retention in initial months implies successful customer engagement strategies early in the customer lifecycle.

Context

Understanding retention patterns is crucial for assessing customer loyalty and the effectiveness of acquisition strategies. However, further analysis may be needed to explore factors influencing retention rates over time.

Retention Curves

Retention Decay by Cohort

CRV

Retention Curves

Retention Decay by Cohort

86
Health Rate

Retention decay curves by cohort

86
overall health rate
11
unique cohorts
IN

Key Insights

Retention Curves

Purpose

This section displays retention decay curves for 11 cohorts, with an overall customer health rate of 86%. It helps assess customer retention over time and compare the quality of customers acquired in different periods.

Key Findings

  • Overall Health Rate: 86% - Indicates the general health of the customer base.
  • Unique Cohorts: 11 - Represents the distinct groups of customers being analyzed.
  • Retention Rate: Mean of 93.03% - Shows the average percentage of customers retained over time.

Interpretation

The retention curves provide insights into how well cohorts of customers are retained over time. A higher retention rate suggests better customer loyalty and satisfaction. Comparing cohorts can reveal trends in customer behavior and the effectiveness of acquisition strategies.

Context

The retention curves section focuses on understanding customer churn patterns and the effectiveness of retention strategies. It helps evaluate the success of acquiring high-quality customers and retaining them over time. Limitations may include the need for additional data to delve deeper into specific cohort behaviors.

IN

Key Insights

Retention Curves

Purpose

This section displays retention decay curves for 11 cohorts, with an overall customer health rate of 86%. It helps assess customer retention over time and compare the quality of customers acquired in different periods.

Key Findings

  • Overall Health Rate: 86% - Indicates the general health of the customer base.
  • Unique Cohorts: 11 - Represents the distinct groups of customers being analyzed.
  • Retention Rate: Mean of 93.03% - Shows the average percentage of customers retained over time.

Interpretation

The retention curves provide insights into how well cohorts of customers are retained over time. A higher retention rate suggests better customer loyalty and satisfaction. Comparing cohorts can reveal trends in customer behavior and the effectiveness of acquisition strategies.

Context

The retention curves section focuses on understanding customer churn patterns and the effectiveness of retention strategies. It helps evaluate the success of acquiring high-quality customers and retaining them over time. Limitations may include the need for additional data to delve deeper into specific cohort behaviors.

Cohort Distribution

Customer Acquisition and Health

DST

Cohort Distribution

Customer Count by Cohort

50
Customers

Customer count and health status by cohort

50
total customers
43
healthy customers
5
delinquent customers
IN

Key Insights

Cohort Distribution

Purpose

This section illustrates the distribution of cohorts based on customer count and health status. It helps identify trends in customer acquisition over time and highlights cohorts with a higher proportion of at-risk customers.

Key Findings

  • Total Customers: 50 - Indicates the total customer base.
  • Healthy Customers: 43 - Represents the number of customers without payment issues.
  • Delinquent Customers: 5 - Reflects the count of customers facing payment problems.
  • Health Rate: 86.06% - Average health rate of customers across cohorts.

Interpretation

The data reveals that most cohorts have a high health rate, with a small proportion of delinquent customers. Understanding the distribution of healthy and at-risk customers over time can help in targeting retention efforts towards cohorts with higher delinquency rates.

Context

The section provides a snapshot of customer health status by cohort but does not delve into the specific reasons for delinquency or strategies to address it. Further analysis may be needed to understand the factors influencing customer health rates and retention within each cohort.

IN

Key Insights

Cohort Distribution

Purpose

This section illustrates the distribution of cohorts based on customer count and health status. It helps identify trends in customer acquisition over time and highlights cohorts with a higher proportion of at-risk customers.

Key Findings

  • Total Customers: 50 - Indicates the total customer base.
  • Healthy Customers: 43 - Represents the number of customers without payment issues.
  • Delinquent Customers: 5 - Reflects the count of customers facing payment problems.
  • Health Rate: 86.06% - Average health rate of customers across cohorts.

Interpretation

The data reveals that most cohorts have a high health rate, with a small proportion of delinquent customers. Understanding the distribution of healthy and at-risk customers over time can help in targeting retention efforts towards cohorts with higher delinquency rates.

Context

The section provides a snapshot of customer health status by cohort but does not delve into the specific reasons for delinquency or strategies to address it. Further analysis may be needed to understand the factors influencing customer health rates and retention within each cohort.

Average Retention Trend

Overall Customer Lifecycle Pattern

AVG

Average Retention

Overall Retention Trend

86
Retention

Average retention trend across all cohorts

86
overall health rate
6
retention periods
IN

Key Insights

Average Retention

Purpose

This section displays the average retention trend across all cohorts, highlighting the typical customer lifecycle pattern. The shaded band represents the range of retention rates observed across different cohorts, aiding in identifying critical periods of churn and guiding retention strategies.

Key Findings

  • Average Retention: 93.04 - Indicates the average retention rate across all cohorts.
  • Minimum Retention: 75 - Represents the lowest retention rate observed.
  • Maximum Retention: 100 - Shows the highest retention rate recorded.
  • Pattern Observed: A gradual decline in retention rates over time, with the most significant drop occurring towards the end of the retention period.

Interpretation

The average retention rate of 93.04 suggests that, on average, a high percentage of customers are retained over the specified period. The variation between the minimum and maximum retention rates (75 to 100) indicates the range of retention performance across different cohorts, emphasizing the importance of targeting interventions during critical churn periods.

Context

Understanding the average retention trend and its variability provides insights into the overall health of customer retention efforts. However, it is essential to delve deeper into cohort-specific behaviors to tailor retention strategies effectively.

IN

Key Insights

Average Retention

Purpose

This section displays the average retention trend across all cohorts, highlighting the typical customer lifecycle pattern. The shaded band represents the range of retention rates observed across different cohorts, aiding in identifying critical periods of churn and guiding retention strategies.

Key Findings

  • Average Retention: 93.04 - Indicates the average retention rate across all cohorts.
  • Minimum Retention: 75 - Represents the lowest retention rate observed.
  • Maximum Retention: 100 - Shows the highest retention rate recorded.
  • Pattern Observed: A gradual decline in retention rates over time, with the most significant drop occurring towards the end of the retention period.

Interpretation

The average retention rate of 93.04 suggests that, on average, a high percentage of customers are retained over the specified period. The variation between the minimum and maximum retention rates (75 to 100) indicates the range of retention performance across different cohorts, emphasizing the importance of targeting interventions during critical churn periods.

Context

Understanding the average retention trend and its variability provides insights into the overall health of customer retention efforts. However, it is essential to delve deeper into cohort-specific behaviors to tailor retention strategies effectively.

Cohort Summary

Detailed Metrics by Cohort

SUM

Cohort Summary

Detailed Cohort Metrics

11
Cohorts

Detailed metrics for each cohort

11
unique cohorts
IN

Key Insights

Cohort Summary

Purpose

This section presents detailed metrics for each of the 11 cohorts, including customer count, health rate, delinquency rate, and retention at key milestones (Month 1, 3, 6). Understanding these metrics helps identify benchmark cohorts and those needing attention in terms of customer health and retention rates.

Key Findings

  • Health Rate: Mean of 86.06% indicates the average health rate across cohorts.
  • Delinquency Rate: Mean of 10.15% highlights the average delinquency rate.
  • Retention at Month 3: Mean of 93.03% shows the average retention rate at the 3-month mark.
  • Pattern Observed: Cohorts vary in health and retention rates, with some needing improvement in delinquency rates.

Interpretation

The data reveals varying health, delinquency, and retention rates across cohorts, indicating the performance and stability of customer segments over time. Cohorts with lower health and retention rates may require targeted strategies to improve customer engagement and reduce churn.

Context

These metrics provide a snapshot of cohort performance but may not capture individual customer behaviors. Understanding cohort dynamics can guide strategic decisions to enhance customer relationships and overall business performance.

IN

Key Insights

Cohort Summary

Purpose

This section presents detailed metrics for each of the 11 cohorts, including customer count, health rate, delinquency rate, and retention at key milestones (Month 1, 3, 6). Understanding these metrics helps identify benchmark cohorts and those needing attention in terms of customer health and retention rates.

Key Findings

  • Health Rate: Mean of 86.06% indicates the average health rate across cohorts.
  • Delinquency Rate: Mean of 10.15% highlights the average delinquency rate.
  • Retention at Month 3: Mean of 93.03% shows the average retention rate at the 3-month mark.
  • Pattern Observed: Cohorts vary in health and retention rates, with some needing improvement in delinquency rates.

Interpretation

The data reveals varying health, delinquency, and retention rates across cohorts, indicating the performance and stability of customer segments over time. Cohorts with lower health and retention rates may require targeted strategies to improve customer engagement and reduce churn.

Context

These metrics provide a snapshot of cohort performance but may not capture individual customer behaviors. Understanding cohort dynamics can guide strategic decisions to enhance customer relationships and overall business performance.

Risk Analysis

Payment Delinquency Assessment

RSK

Risk Analysis

Payment Risk Assessment

Payment risk and delinquency analysis

IN

Key Insights

Risk Analysis

Purpose

This section focuses on analyzing payment risk and delinquency within the customer cohort. It highlights the number of delinquent customers, the overall delinquent rate, and the total balance at risk to provide insights for monitoring and early intervention strategies.

Key Findings

  • Delinquent Customers: 5 customers - Indicates the number of customers with overdue payments.
  • Overall Delinquent Rate: 10% - Represents the proportion of delinquent customers in the total customer base.
  • Total Balance at Risk: $33,500 - Reflects the total amount of outstanding payments from delinquent customers.

Interpretation

The presence of 5 delinquent customers, accounting for 10% of the total, poses a risk to the revenue stream. Monitoring these customers closely for payment recovery is crucial to mitigate financial losses and maintain a healthy customer base.

Context

Understanding the delinquency metrics provides valuable insights into the financial stability and risk management strategies within the customer cohort. It aligns with the broader goal of ensuring sustainable revenue streams and customer retention in the analysis context.

IN

Key Insights

Risk Analysis

Purpose

This section focuses on analyzing payment risk and delinquency within the customer cohort. It highlights the number of delinquent customers, the overall delinquent rate, and the total balance at risk to provide insights for monitoring and early intervention strategies.

Key Findings

  • Delinquent Customers: 5 customers - Indicates the number of customers with overdue payments.
  • Overall Delinquent Rate: 10% - Represents the proportion of delinquent customers in the total customer base.
  • Total Balance at Risk: $33,500 - Reflects the total amount of outstanding payments from delinquent customers.

Interpretation

The presence of 5 delinquent customers, accounting for 10% of the total, poses a risk to the revenue stream. Monitoring these customers closely for payment recovery is crucial to mitigate financial losses and maintain a healthy customer base.

Context

Understanding the delinquency metrics provides valuable insights into the financial stability and risk management strategies within the customer cohort. It aligns with the broader goal of ensuring sustainable revenue streams and customer retention in the analysis context.