Introduction
EnderGPT helps you analyze large volumes of calls and chats and turn conversation content into useful business insights. It can help answer questions such as:
What are the most common customer questions or concerns?
Why do customers react negatively to a product, service, or offer?
Which problems are mentioned repeatedly?
In which situations do agents show the biggest knowledge gaps?
What recurring process or communication issues can be identified?
What positive and negative patterns appear across conversations?
The goal is not to analyze as much data as possible. The goal is to select the conversations that can answer your business question and give EnderGPT clear instructions.
EnderGPT is designed specifically for conversation analysis. It is not a general-purpose chatbot and is not intended for tasks unrelated to calls and chats.
Key Benefits of EnderGPT Conversation Analysis
Time-Saving Efficiency: Review patterns across many conversations much faster than by reading every call or chat manually.
Focused Analysis: Use Topics, Tags, filters, and Summaries to reduce irrelevant information and focus on the conversations that matter.
Improved Decision-Making: Identify recurring customer concerns, process issues, knowledge gaps, and other patterns that can support business decisions.
Multiple Angles: Analyze the same conversation data from different perspectives, for example customer reactions, agent behavior, or process issues.
Customizability: Adjust the selected data, questions, constraints, and response format to match the purpose of the analysis.
Scalable Analysis: Use structured conversation data to analyze larger samples efficiently, especially when suitable Summaries are available.
Concept
EnderGPT works best when the analysis range is specified :
All Conversations → Topics → Tags and Filters → Summary → Prompt → Answer
Topics describe what a conversation is about.
Tags identify additional characteristics of a conversation.
Filters such as “date range” can further narrow the sample.
Summaries contain structured information extracted from conversations and should be used whenever a suitable Summary is available.
The more relevant and focused the selected sample of conversations is, the better the quality of the analysis.
A good prompt cannot fully compensate for an irrelevant or noisy dataset.
Step-by-Step Guide
To run an EnderGPT analysis, prepare:
A clear business question;
A relevant conversation sample;
A suitable Summary, when available;
A structured prompt.
1. Define the Business Question
Start by writing down exactly what you want to learn.
Good example: What are the most common reasons customers are dissatisfied with this process?
Avoid very broad requests such as: Analyze everything.
A focused question makes it easier to select the right conversations and produces a more useful answer.
2. Select the Relevant Conversations
Before writing the prompt, narrow the conversation sample.
Use Topics to select conversations about the subject you want to analyze.
Use Tags when they help narrow the sample further.
Use the date range and other available filters only when they make the selected conversations more relevant.
Do not select more conversations simply to increase the sample size. More data does not automatically mean a better answer.
3. Use a Summary When Available
A Summary contains structured information extracted from a conversation. When a suitable Summary exists, use it instead of the full transcript whenever possible.
More Accurate: Focused, structured content reduces noise.
Faster: Less text has to be processed.
More Cost-Efficient: Fewer tokens are required.
If no suitable Summary exists, EnderGPT can analyze full conversation transcripts. Full-content analysis contains more text and more noise, so filtering becomes especially important.
Without a Summary, fewer conversations can be analyzed in one query because of the model context-window limit.
4. Build the Prompt
A useful prompt normally contains five elements:
Role: Define the analytical perspective EnderGPT should use.
Context: Explain what data is being analyzed and who participates in the conversations.
Task or Questions: State exactly what you want to find out.
Guidelines and Constraints: Explain what EnderGPT should not assume or invent.
Response Format: Specify how the final answer should be organized.
Example prompt
Role: You are a Customer Experience Analyst.
Context: You will analyze selected conversation summaries between agents and customers about a service.
Task: Identify the most common positive and negative customer reactions, recurring questions or concerns, and any repeated communication or process issues.
Guidelines and Constraints: Use only information available in the selected conversation data. Do not invent missing facts or present assumptions as facts. If the available data is insufficient, state this clearly.
Response Format: Provide an Overall Summary, Main Positive Reactions, Main Negative Reactions, Recurring Questions or Concerns, Process or Communication Issues, and Key Conclusions.
5. Run the Analysis and Review the Result
Check whether the answer addresses the original business question.
If the result is not useful, first review the selected conversations before making the prompt longer. Remove unrelated Topics or Tags, reduce an unnecessarily broad date range, make the question more specific, or add missing Context and Guidelines.
Best Practices for Maximizing EnderGPT's Value
Keep the Sample Focused: Select only conversations that can answer the business question.
Use Summaries Whenever Possible: Structured summaries reduce noise and make analysis faster and more efficient.
Be Specific in the Prompt: Clearly define the task, important constraints, and the expected response format.
Do Not Ask the Model to Invent Missing Information: If the data does not support a conclusion, the answer should say so.
Use Follow-Up Questions: Once EnderGPT identifies an important pattern, ask follow-up questions to explore it in more detail.
Use Structured Data for Exact Figures: EnderGPT is best used for trends, recurring patterns, qualitative insights, and the bigger picture. For precise figures, use structured platform data and charts based on Tags and structured Summaries whenever possible.
The key principle is simple: select the right conversations, ask a clear question, and give EnderGPT clear instructions.