> ## Documentation Index > Fetch the complete documentation index at: https://docs.oration.ai/llms.txt > Use this file to discover all available pages before exploring further. # History > How to review, analyze, and extract insights from your conversation history in Oration AI ## Overview The **History** section in Oration AI provides a comprehensive view of all your past conversations. Here, you can review call details, listen to recordings, analyze transcripts, inspect dynamic variables, and run post-call analysis to extract actionable insights. *** ## 1. Conversation History Overview History Overview The master view displays a list of all calls made by your agents. For each conversation, you can see: * **Agent Name:** The agent who handled the call. * **Created At:** The date and time the call was initiated. * **Talk Time:** Duration of the conversation. * **Customer Phone Number:** The number of the customer involved in the call. * **End Reason:** Why the call ended (e.g., user hangup, completed). * **Conversation Type:** The channel used (e.g., telephony). * **Actions:** Play the call recording or copy the conversation ID for reference. You can filter, sort, and change the view to quickly find the conversations you’re interested in. *** ## 2. Call Transcript and Details Call Transcript and Details Clicking on a conversation opens a detailed view, where you can: * **See Talk Time, End Reason, Status, and Phone Number:** At the top, key call metrics and metadata are displayed. * **Transcript Tab:** Review the full transcript of the conversation, with clear separation between agent and customer messages, including timestamps. * **Playback Controls:** Listen to the call recording directly within the interface. This helps you audit conversations, understand customer interactions, and ensure quality. *** ## 3. Dynamic Variables Dynamic Variables The **Dynamic Variables** tab shows all the placeholders and values used during the conversation. These variables can be referenced in your agent’s prompts and responses to personalize the experience. **Examples:** * `customerName`: The name of the customer. * `amount`: Financial details relevant to the call. Dynamic variables make your agents more context-aware and responsive. *** ## 4. Post Call Analysis Post Call Analysis The **Post Call Analysis** feature lets you extract structured insights from every conversation using AI. * **Is Enabled:** Toggle to automatically run analysis after every call. * **Prompt:** Write a custom prompt to instruct the AI on what to analyze in the transcript, or click **Generate Prompt** for AI assistance. * **Schema:** Define the tags or events you want to capture from the transcript. For each event, specify: * **Type:** The data type (e.g., String). * **Event Name:** The label for the event (e.g., Callback). * **Description:** Describe the event, including scenarios, possible values, criteria, and examples. **Example:**\ To detect if a customer requested a callback, set: * Type: String * Event Name: Callback * Description: "Indicates if the customer asked for a callback. Values: 'yes', 'no'. Criteria: Look for phrases like 'please call me back', 'can you call later', etc. Example: 'I missed your call, can you call me again?'" This structured analysis helps you track key outcomes, monitor agent performance, and identify trends for continuous improvement. *** ## Best Practices * **Regularly review transcripts and recordings** to ensure quality and compliance. * **Leverage dynamic variables** for personalized and context-rich agent responses. * **Use post call analysis** to automate insight extraction and drive data-driven decisions. * **Define clear schemas(event)** for events you want to track, and update them as your business needs evolve. *** > Need more help? Reach out to our team at [support@oration.ai](mailto:support@oration.ai)