Setting Up the Analytics List
Introduction
The analytics list should cover all variables and measures needed to assess KPIs, evaluate the coaching program's effectiveness, or answer research questions.
Steps to Define the Analytics List
Step 1: Identify Required Variables and Measures
Identify all the variables and measures necessary to evaluate the defined KPIs and objectives. This ensures you have the data needed.
Step 2: List of Variables and Measures
Create a detailed list of variables and measures. This list should include all the data points required to track the progress of your KPIs and evaluate additional metrics related to the coaching program and research questions.
Examples
User Engagement Metrics
- Daily Active Users (DAU) - automatically tracked by the app
- Weekly Active Users (WAU) - automatically tracked by the app
- Session Duration - automatically tracked by the app
- Frequency of Use - automatically tracked by the app
- Retention Rate - automatically tracked by the app
- Engagement with Specific Content: Interaction with particular lectures, quizzes, or modules.
User Feedback and Satisfaction
- User Ratings: Average rating on a scale (e.g., 1-5 stars).
- Net Promoter Score (NPS): Measure user loyalty and satisfaction.
- Feedback Forms: Qualitative insights from user comments and suggestions.
Performance and Progress Metrics
- Goal Completion Rate: Percentage of users achieving their set goals.
- Task Completion Time: Time taken by users to complete specific tasks.
- Milestone Achievement: Track progress toward key milestones.
Behavioral Analytics
- Feature Usage: Frequency of use for different features.
- Drop-off Points: Stages where users commonly disengage or leave the app.
Health Outcomes
- Physical Health Metrics: Changes in physical health indicators (e.g., weight, blood pressure).
- Mental Health Metrics: Improvements in mental well-being (e.g., stress levels, mood).
Additional Metrics
- User Demographics: Age, gender, location, etc.
- Adherence to Recommendations: Tracking how well users follow through on recommended actions.
Structuring the Analytics List
Organize your analytics list in a structured format. Here’s a sample structure:
| Measure | Description | Data Type | Frequency / Time of Collection | Source | Relevant Variable(s) |
|---|---|---|---|---|---|
| Daily Active Users (DAU) | Number of unique users active per day | Integer | Daily | App Analytics | DailyActiveUsers |
| User Ratings | Average app store rating given by users | 1-5 scale | One-Time | User Feedback Form | $ratingUser |
| Completion Rate Activity Goal | Percentage of users achieving the activity goal | Percentage | Monthly | Coaching Intervention | $goalCompleted |
| Usage Blood Pressure Diary | Frequency of use of the Blood Pressure Diary | Count | Continous | App Analytics | UsageDiary |
| Blood Pressure Change | Change in systolic blood pressure | Integer (mmHg) | Monthly | Blood Pressure Diary | DataDiary |