Data Export

botBrains lets you export conversations, messages, and user data for compliance, custom analytics, or backup. All exports respect your project permissions.

Export Methods

	Full Dataset Export	Entity-Specific Export
What	Complete snapshot of all project data	Filtered download of one entity type (Conversations, Messages, or Users)
Format	JSONL (Users → Conversations → Messages hierarchy)	CSV, JSONL, Excel, or Markdown
How	Settings → Data Export, processed in the background, download link sent by email	Export button on any Conversations, Messages, or Users list page, downloads immediately
Limits	2 per day per project; download link valid for 7 days	10,000 rows per export
Use when	Full backups, GDPR requests, AI analysis across all data	Filtered subsets, spreadsheet analysis, sharing with stakeholders

Full Dataset Export settings dialog showing export options in the Data Export settings page

Export Formats

Format	Best for
CSV	Excel, Google Sheets, quick manual analysis
JSONL	Programmatic processing, data pipelines, preserving nested data (Users → Conversations → Messages)
Excel (CSV)	Microsoft Excel with correct UTF-8 encoding and date handling
Markdown	Copying conversations into an LLM (ChatGPT, Claude) for ad-hoc analysis

Entity-specific export dialog on the Conversations list page showing format and filter options

If CSV displays special characters incorrectly in Excel, use the Excel (CSV) format or import via Excel’s “Get Data” feature with UTF-8 encoding.

Formulas. So that spreadsheets don’t run exported text as a formula, CSV and Excel (CSV) put an apostrophe (') before text a spreadsheet could read as one, such as text starting with =, +, -, or @.

Attributes

Conversation exports include the values of your conversation attributes: every custom and managed attribute and every scorecard, identified by its key. Built-in attributes such as topic and status have their own fields.

Format	How attributes appear
JSONL	An `attributes` object keyed by attribute key, with typed values: `true` or `false`, numbers, the option value, a list of option values for multi select, and dates as `YYYY-MM-DD`
CSV	One `attributes.<key>` column per attribute, with the option value, multi select values separated by commas, and an empty cell when the conversation has no value
Excel (CSV)	Like CSV, with decimal commas, such as `66,67`
Markdown	One `<Attribute label>: <value>` line per attribute that has a value, after the labels, with option labels, Yes or No, and scores out of 100, such as `67/100`

For example, for a conversation with negative sentiment, two frustration triggers, and a CX Score of 66.67, the attributes look like this:

{"attributes": {"sentiment": "negative", "frustration_triggers": ["dead_end", "repetition"], "cx_score": 66.67}}

attributes.sentiment,attributes.frustration_triggers,attributes.cx_score
negative,"dead_end, repetition",66.67

Sentiment: Negative
Frustration Triggers: Dead end, Repetition
CX Score: 67/100

Scorecards. A scorecard exports its score from 0 to 100. While a scorecard is awaiting review, the conversation has no score, and the export leaves it empty. Pick attributes. Exports include every attribute by default. In the export dialog, attributes sit in their own Attributes group below the other fields. Tick Attributes to export all of them, or click Choose to pick individual ones. In the API, request attributes in fields for every attribute, or attributes.<key> for single ones. Filters. An export from the conversation list uses its current filters, including attribute filters, so you can export only conversations with negative sentiment, for example. In the API, send the filter in the request body as described in Filter by Attributes. Full Dataset Export. Each conversation carries all its attribute values in attributes, typed as in JSONL, plus its topic (topic_name), channel (integration_type), and AI involvement (involvement_type).

Media Files in Exports

Exports include time-limited download URLs for media attachments (images, files), not the files themselves. These URLs expire after 7 days. Download media files after exporting if you need permanent copies.

Custom Analysis with AI Tools

The Full Dataset Export (JSONL) works well with AI tools like ChatGPT or Claude. Upload the file and use this prompt template:

You are a data analyst, using your Code Interpreter / Python Interpreter tools
to write code and answer my questions. You've been given a JSON Lines file, of
the conversations had by the ai-assistant, operators (human agents) and
customers. Each line is a user profile, with all their conversations and all
messages within those conversations, including metadata. For legacy reasons, not
all conversations have a user, so a mock user with
ID 00000000-0000-0000-0000-000000000000 is assigned all other conversations.

Follow this workflow:
1. Familiarize yourself with the data model by looking at the first 5 lines.
2. Think about my question and the appropriate chart / way to answer my question
   with the given values.
3. Work to write the code and find appropriate outputs format (chart-type,
   tables, singular values...) for the data.

Question: [Your question here]

Example questions:

“Which users send the most messages? Show a table sorted by message count.”
“What common issues do users with external_attributes.plan = PREMIUM describe?”
“Find conversations rated 1–2 and categorize the top complaint themes.”

For best results, ask the AI to first filter by your criteria (poor ratings, specific attributes), then analyze the message content to identify patterns.

You are responsible for ensuring exported data complies with your organization’s data policies (GDPR, CCPA, etc.) before uploading to external AI tools.

Analyze

ServiceLens

Data Management

Export Methods

Export Formats

Attributes

Media Files in Exports

Custom Analysis with AI Tools

Next Steps

Conversations

Metrics

​Export Methods

​Export Formats

​Attributes

​Media Files in Exports

​Custom Analysis with AI Tools

​Next Steps

Conversations

Metrics

Export Methods

Export Formats

Attributes

Media Files in Exports

Custom Analysis with AI Tools

Next Steps