> **Cohort Analysis for [App Name] - [Cohort Name/Period]**

This report presents a detailed analysis of user cohorts for the period of [Start Date] to [End Date]. The goal is to analyze user behavior, retention, engagement, and other key metrics based on user cohorts, providing insights into how different user groups interact with the app over time.


---

## 1. **Report Overview**

* **Cohort Group:** [Cohort Name or Identifier, e.g., "Users who signed up in January 2025"]
* **Analysis Period:** [Start Date] to [End Date]
* **Objective:**  [Describe the main objective of the cohort analysis, e.g., "To examine how retention and engagement rates differ across users who signed up during different months."]
* **Key Metrics Tracked:**
  * **Retention Rate:** Percentage of users who return after [X] days/weeks.
  * **Engagement Rate:** Average actions or sessions per user during a given period.
  * **Conversion Rate:** Percentage of users who achieve a predefined goal (e.g., completing a purchase).
  * **Lifetime Value (LTV):** The total revenue generated by a user throughout their lifecycle.

---

## 2. **Cohort Segmentation**

### **Cohort Definition:**

* **Cohort Group:** Users who first interacted with the app in [Month/Year], based on the following characteristics:
  * [Characteristic 1] (e.g., "First-time app users")
  * [Characteristic 2] (e.g., "Users who completed onboarding")
### **Segmentation Criteria:**

* **Segment 1:** [e.g., "Users who signed up through referral links"]
* **Segment 2:** [e.g., "Users from specific geographic regions"]
* **Segment 3:** [e.g., "Users who engaged with a specific feature in the first week"]

---

## 3. **Analysis Methodology**

* **Metrics Evaluated:**
  * **Retention Rate:** The percentage of users returning after a certain number of days/weeks (e.g., Day 1, Day 7, Day 30).
  * **Engagement Rate:** Average number of sessions or actions performed by users within the cohort.
  * **Conversion Rate:** The percentage of users who complete a desired action (e.g., make a purchase, subscribe to a service).
  * **Lifetime Value (LTV):** The average revenue generated by users over their active lifecycle.
* **Time Period:**
  * **Retention Metrics:** [Days/Weeks] (e.g., "Measured at Day 1, Day 7, and Day 30")
  * **Engagement & Conversion Metrics:** Measured over [X] period after first interaction (e.g., "First 30 days after sign-up").

---

## 4. **Cohort Performance Overview**

### **Retention by Cohort:**

|Cohort Group|Day 1 Retention|Day 7 Retention|Day 30 Retention|Day 90 Retention|
|---|---|---|---|---|
|[Cohort 1]|[Value]|[Value]|[Value]|[Value]|
|[Cohort 2]|[Value]|[Value]|[Value]|[Value]|
|[Cohort 3]|[Value]|[Value]|[Value]|[Value]|

### **Engagement by Cohort:**

|Cohort Group|Avg. Sessions per User|Avg. Actions per Session|Avg. Time Spent per User|
|---|---|---|---|
|[Cohort 1]|[Value]|[Value]|[Value]|
|[Cohort 2]|[Value]|[Value]|[Value]|
|[Cohort 3]|[Value]|[Value]|[Value]|

### **Conversion by Cohort:**

|Cohort Group|Conversion Rate|Purchase Rate|Sign-Up Rate|
|---|---|---|---|
|[Cohort 1]|[Value]|[Value]|[Value]|
|[Cohort 2]|[Value]|[Value]|[Value]|
|[Cohort 3]|[Value]|[Value]|[Value]|

### **Lifetime Value (LTV) by Cohort:**

|Cohort Group|LTV per User|
|---|---|
|[Cohort 1]|[Value]|
|[Cohort 2]|[Value]|
|[Cohort 3]|[Value]|


---

## 5. **Key Insights & Interpretation**

### **Retention Insights:**

* **[Cohort Name]:**  [Interpret the retention trends for each cohort, e.g., "Cohort 1, users who signed up in January 2025, showed strong retention, with a Day 7 retention rate of 45%, which is 15% higher than the previous cohort."]
### **Engagement Insights:**

* **[Cohort Name]:**  [Interpret the engagement trends, e.g., "Cohort 2 exhibited high engagement, with an average of 5 sessions per user in the first 30 days, suggesting that users who interacted with [Feature X] early are more likely to stay engaged."]
### **Conversion Insights:**

* **[Cohort Name]:**  [Interpret the conversion trends, e.g., "Cohort 3 showed an increase in conversion rates, particularly those who engaged with targeted email campaigns."]
### **Lifetime Value Insights:**

* **[Cohort Name]:**  [Interpret LTV, e.g., "Cohort 1 users who were exposed to premium features had a higher LTV, suggesting that early access to premium features leads to higher user value."]

---

## 6. **Conclusion**

* **Key Findings:**  [Summarize the most important insights from the analysis, e.g., "Cohort 1 shows the highest retention, while Cohort 2 has the best engagement metrics, indicating the importance of early feature engagement."]
* **Recommendations:**  [Based on the insights, provide actionable recommendations, e.g., "Consider replicating the onboarding process used for Cohort 1 across all new users to improve retention rates."]
* **Next Steps:**
  * [What additional analysis or changes should be explored? e.g., "Test different onboarding strategies for Cohort 3 to improve conversion rates."]
  * [Long-term monitoring suggestions, e.g., "Monitor retention and engagement metrics for the next quarter to ensure sustained growth."]

---

## 7. **Appendices**

### **Cohort Raw Data:**

* [Link to raw data or attach CSV/Excel files]
### **Charts & Visuals:**

* [Insert any relevant charts or graphs showing cohort retention trends, engagement levels, etc.]

---

**Prepared by:**[Your Name][Your Job Title][Date of Report]


---

> **Note:** This template is customizable for any type of cohort analysis, whether it’s tracking new users, paid users, or user behavior changes over a specific period.