# Analytics 6 min read Analytics reports (e.g., user engagement) are available via API or also via Unique UI. The article explains which reports are available out of the box and how to get them. Unique continuously enriches the service with additional reports. * * * # Definitions **Active Users:** A user with a minimum of one interaction (question & answer) over a defined period of time **Unique Users:** A user counted only once no matter how many times they interacted (question & answer) over a defined period of time. # User information anonymization You can anonymize user email addresses in analytics exports by enabling the environment variable `ANONYMIZED_CHAT_INTERACTIONS_EXPORT`. - Set: `ANONYMIZED_CHAT_INTERACTIONS_EXPORT=true` - Effect: Email addresses will be anonymized in the export output. When enabled, exported data will return anonymized identifiers in place of raw email addresses, as shown below. Anonymization causes identifiers such as email addresses to be randomized every time you export analytics data, if this behavior is unwanted as it may become difficult to correlate data across exports you can enable idempotent anonymization `ANONYMIZED_CHAT_INTERACTIONS_EXPORT_TYPE` which are stable pseudonyms. - Set: `ANONYMIZED_CHAT_INTERACTIONS_EXPORT_TYPE=idempotent` - Effect: User ID or Email addresses will be anonymized using a stable pseudonym. # Available Reports ## Usage statistics - Chat Interactions - Active Users - Document Reference Statistics # Work with Reports ## How to download Reports - A user with the [required role](https://docs.unique.ai/it-operators/identity-and-access-management-iam/understand-roles-and-permissions) is able to request an analytics export. - A user can filter the data request: - By date - with for a specific Assistant by spec - When a user requests for a report, the system will create an order entry in the Analytics order table. After the request is completed, a report is available for the user to download. - A user can delete the report after it has been processed or downloaded. You can also filter down report for a specific Assistant before exporting. ## Interpret reports ### Chat Interactions With this analytics you can evaluate the following: - Which assistant is most used - Number of interactions per assistant - Most active user - **Email:** The email of the user, who interacted with the assistant - **Date:** The date of the interaction - **Assistant:** The assistant used for the interaction - **Count:** Number of interactions (question & answer) the user had on the indicated date with the selected assistant ### Active Users With this analytics you can evaluate the overall engagement of the users on the platform: - How many **unique** daily active users (DAU) are on the platform? - How many **unique** weekly active users (WAU) are on the platform? - How many **unique** monthly active users (MAU) are on the platform? - How did the DAU/WAU/MAU develop over time? - **Period:** month (relevant for MAU), week (relevant for WAU), day (relevant for DAU) - **Date:** The date of the interaction. The date for the weekly interaction always indicates the end of a 7-day period, e.g. week 10.02.24 means the week 04.02.-10.02.2024. - **Value:** Number of _unique_ users who had at least one interaction (request) in the specified period. A user who has 10 interactions ( questions & answers) within one day is only counted once (unique user). ### Reference Statistics With this analytics you can evaluate the overall engagement of the users on the platform: - Who uploaded which documents? - Which documents are most asked about? - Which documents are uploaded to which scopes? - **File Uploaded Date:** The date the file was initially ingested (connected via Sharepoint or manually uploaded) - **File name:** The name of the file (as also shown in the knowledge center) - **File uploader:** The email address of the user who uploaded or connected the file. For Sharepoint it is currently just one generic user ID, which will be changed in the future. - **Source:** UNIQUE_BLOB_STORAGE refers to the manual upload of files and MICROSOFT_365_SHAREPOINT to documents ingested via Sharepoint - **Reference Count:** The number a document was referenced on the platform when answering a question. - **Scope:** The scope a file was uploaded to ### Detailed Chat Interactions This report gives you a detailed export of the chat interactions. The report contains mainly every message of the user and answer of Unique AI in the specified time frame. The user is as default anonymised. But on special request by a customer Unique can change this to contain the users data. (Not available on multi tenant instance) - **Username:** The name of the user or anonymised: Unknown - **Timestamp:** The date and time the user sent the message - **Space:** Which space the user has used for this message - **Chat ID:** Identifying which messages belongs together (the same chat) - **Device Category:** Which device the user used (mobile, desktop, tablet) - **Message:** The message that was sent - **Answer:** The answer of Unique AI > Note the **Message** and **Answer** columns are returned if the user requesting the data has the `chat.data.admin` role ### Ingestion Report The Ingestion Report helps you to understand which users are using the ingestion services and how. The report delivers the following metrics: - Total Contents (Files) ingested per user for the given timeframe - Total pages ingested per user for the given timeframe - **UserId:** The unique identifier of the user who ingested the content - **Email:** The email address of the user who uploaded/ingested content - **ContentCount:** Number of documents/content items the user ingested within the selected date range - **PageCount:** Total number of pages processed from all content ingested by the user ### Date Range - Default range: Last **180 days** - Maximum allowed range: **365 days** - Custom start and end dates can be specified ### Privacy Features The report respects company privacy settings: - **Pseudonymization**: User identifiers may be anonymized based on company configuration - **Authorization**: Requires `CHAT_FEEDBACK_READ` or `CHAT_DATA_ADMIN` role to access ### Product Metrics This report provides key engagement metrics — **DAU**, **WAU**, and **MAU** — representing the number of unique users who interact with the **Chat** or **Agentic Table** interfaces over specific time periods (daily, weekly, and monthly). - **Daily Active Users (DAU)** measure how consistently users engage with the Chat or Agentic Table in their day-to-day work. An increase in DAU indicates that users are finding recurring value in these interfaces, while a decline may suggest reduced relevance or potential usability issues. - **Weekly Active Users (WAU)** highlight short-term engagement patterns, showing how often users return within a week. WAU is especially useful for identifying cyclical usage — for example, users engaging around specific workflows or reporting periods. - **Monthly Active Users (MAU)** represent the overall reach and adoption of the Chat and Agentic Table over time. A steady or growing MAU signals healthy user retention and expansion, while a decline could point to disengagement or lack of sustained adoption. The tables below provide an overview of all metrics currently being tracked: #### **Chat Metrics** | **Metric Name** | **Explanation** | | `space_interaction` | This is triggered when a new space is created | | `context_window_interaction` | This is triggered when a user open the context window | | `select_files_to_chat` | This is triggered when a user selects a file to chat. | #### **RAG Metrics** | **Metric Name** | **Explanation** | | `kb_visit` | This is triggered when a new space is created | | `kb_document_upload` | This is triggered when a user uploads a file to the knowledge base | | `kb_scope_created` | This is triggered when a user creates a new folder | | `kb_document_search` | This is triggered when a user searches a file in the knowledge base | #### **Agentic Table Metrics** | **Metric Name** | **Explanation** | | `agentic_table_sheet_creation` | Triggered when a user [creates a new sheet](https://docs.unique.ai/users/spaces/agentic-table). | | `agentic_table_library_sheet_creation` | Triggered when a new [answer library sheet](https://docs.unique.ai/users/spaces/agentic-table/answer-library) is created within an Agentic Table space. | | `agentic_table_sheet_deletion` | Triggered when a user deletes a sheet via the [Landing page](https://docs.unique.ai/users/spaces/agentic-table). | | `agentic_table_sheet_completion` | Triggered when a user marks a non-library sheet as [completed](https://docs.unique.ai/users/spaces/agentic-table/answer-library). | | `agentic_table_library_sheet_completion` | Triggered when a user marks a library sheet as completed. | | `agentic_table_cell_update` | Triggered whenever a user edits an existing cell or adds a new one in a sheet. | | `agentic_table_metadata_added_existing_sheet` | Triggered when sources or question files are added to an existing sheet. | | `agentic_table_metadata_added_new_sheet` | Triggered whenever sources or question files are added during the creation of a [new sheet](https://docs.unique.ai/users/spaces/agentic-table). | | `agentic_table_row_submitted_initial` | Triggered when rows are submitted for the first time (initial run). Unlike other metrics, the value increases per submitted row, not per unique user. | | `agentic_table_row_submitted` | Triggered when rows are submitted (including re-runs). Unlike other metrics, the value increases per submitted row, not per unique user. | **Important Note** All metrics are tracked **per unique user**. This means that multiple actions by the same user within a given day count as a single event for that metric. Example Product Metrics Export