About Prompt
- Prompt Type – Dynamic
- Prompt Platform – ChatGPT
- Niche – Media Analytics
- Language – English
- Category – Data Processing
- Prompt Title – ChatGPT Prompt for Analyzing Video Performance Metrics
Prompt Details
## Analyze Video Performance Metrics
**Objective:** To gain actionable insights from video performance data to optimize content strategy and improve video performance.
**Data Input Format:** Provide data in a structured format, preferably as a JSON object or a CSV file. Ensure the data includes at least the following metrics (include more if available):
* **video_id:** Unique identifier for each video. (string)
* **title:** Title of the video. (string)
* **publish_date:** Date the video was published. (YYYY-MM-DD format)
* **views:** Total number of views. (integer)
* **watch_time:** Total watch time in seconds. (integer)
* **average_view_duration:** Average view duration in seconds. (float)
* **audience_retention:** A list of percentage values representing audience retention at different time intervals (e.g., [10, 8, 7, 5] for 10%, 8%, 7%, and 5% retention at specific intervals). Specify the intervals used (e.g., every 10% of the video duration).
* **likes:** Number of likes. (integer)
* **dislikes:** Number of dislikes. (integer)
* **comments:** Number of comments. (integer)
* **shares:** Number of shares. (integer)
* **click_through_rate (CTR):** Click-through rate from an impression to a view. (float, between 0 and 1)
* **impressions:** Number of times the video thumbnail was displayed. (integer)
* **tags:** A list of tags associated with the video. (list of strings)
* **platform:** The platform where the video was published (e.g., YouTube, Facebook, Vimeo). (string)
**Analysis Tasks:** Perform the following analysis dynamically based on the provided data.
1. **Overall Performance Summary:** Provide a summary of the overall video performance, including key metrics like total views, average view duration, audience retention, and engagement (likes, comments, shares). Highlight top-performing videos and identify areas for improvement.
2. **Trend Analysis:** Analyze trends in video performance over time. Consider metrics like views, watch time, and engagement over different time periods (e.g., weekly, monthly, quarterly). Identify any seasonal patterns or significant changes in performance.
3. **Audience Retention Analysis:** Analyze audience retention data to identify drop-off points in videos. Provide insights on how to improve viewer engagement and retain audience attention throughout the video. If possible, correlate retention drops with specific content sections within the videos.
4. **Engagement Analysis:** Analyze engagement metrics (likes, dislikes, comments, shares) to understand how viewers are interacting with the videos. Identify factors that contribute to higher engagement and address any negative feedback or concerns expressed in comments. Calculate the engagement rate (e.g., (likes + dislikes + comments + shares) / views).
5. **Correlation Analysis:** Explore correlations between different metrics. For example, analyze the relationship between video length and average view duration, or between the use of specific tags and video performance.
6. **Platform Comparison (if applicable):** If data from multiple platforms is provided, compare the performance of videos across different platforms. Identify platform-specific trends and best practices.
7. **Content Optimization Recommendations:** Based on the analysis, provide actionable recommendations for optimizing future video content. This could include suggestions for video length, content topics, tagging strategies, and promotion tactics.
8. **Data Visualization (optional):** If possible, generate charts and graphs to visualize the data and insights, such as line charts for trend analysis, bar charts for comparing metrics, and scatter plots for correlation analysis.
**Output Format:** Provide the analysis in a clear, concise, and well-structured format. Use headings and subheadings to organize the information. Quantify your findings with specific data points and metrics. Prioritize actionable insights and recommendations.
**Example:**
“`json
[
{“video_id”: “123”, “title”: “Video Title 1”, “publish_date”: “2023-10-26”, “views”: 1000, “watch_time”: 60000, …},
{“video_id”: “456”, “title”: “Video Title 2”, “publish_date”: “2023-10-27”, “views”: 1500, “watch_time”: 90000, …}
]
“`
**Dynamic Prompt Adaptation:** This prompt is designed to be dynamic. Adjust the specific analysis tasks and output requirements based on the available data and your specific goals. For example, if you’re only interested in audience retention, focus the prompt on that aspect. You can also add specific questions related to your business objectives.
“`