Every company leaves a trail. Each message, ticket, call and document is a small record of how your team thinks and works. Taken together, that trail is your operational data.
Operational data, defined
Operational data is information produced as a by-product of running the business, not data you collected to sell. It differs from:
- Marketing data (audiences, ad performance), which buyers rarely want here
- Public data (your website, press releases), which labs already have
- Customer personal data in itself, which is removed before any licensing
What makes operational data valuable to AI labs is that it captures process and judgment: the question, the discussion, the decision and the outcome.
The main types buyers name
| Type | Common sources | Why it’s useful to AI |
|---|---|---|
| Internal chat | Slack, Microsoft Teams | Real-time coordination and decisions in context |
| Gmail, Outlook archives | Long-form negotiation, escalation and follow-up | |
| CRM history | HubSpot, Salesforce | Multi-step sales processes over months |
| Support tickets | Zendesk, Intercom, Jira | Problem → diagnosis → resolution chains |
| Documentation | SOPs, wikis, knowledge bases | How work is supposed to be done |
| Project history | Asana, Jira, Linear, Drive | Planning, hand-offs, and outcomes |
| Call recordings | Gong, Zoom, phone systems | Spoken reasoning and objection handling |
| Finance and ERP | QuickBooks, NetSuite exports | Structured operational decisions |
Polyshares lists Slack, email, Drive, spreadsheets, CRM history, support tickets, design files, call recordings and accounting/ERP exports. micro1 lists SOPs, knowledge bases, CRM data, project histories, QA processes, internal documentation, decision-making patterns and human feedback on AI outputs.
Not sure if your data qualifies? The intake takes a few minutes.
What makes some records worth more
- Depth over volume. Years of history in one system often beat a large but shallow dump.
- Visible reasoning. Threads where people explain why are more useful than status updates.
- Specialized domain. Legal, financial, technical and regulated-industry workflows are hard to find.
- Clean structure. Consistent ticket fields, tagged CRM stages and maintained wikis make data easier to use.
For a full pricing breakdown, see How much is company data worth?
What usually gets excluded
- Personal identifiers (names, emails, phone numbers, account numbers), which are stripped before transfer
- Data you hold on behalf of clients, which Polyshares states its license does not cover
- Privileged legal communications and regulated records (health, financial) unless counsel clears them
- Anything your contracts prohibit sharing
Browse by data type
Each source has its own quirks. Start with the one you have the most of: Slack, email, CRM, support tickets, call recordings, or ERP and accounting.
Frequently asked questions
Is customer data part of operational data?
Customer records often sit inside operational systems like a CRM or helpdesk, but personal details are stripped before licensing. Data you hold on behalf of a client is usually excluded entirely.
Do I need all of these data types to qualify?
No. A single deep, well-kept system, such as several years of support tickets or a detailed knowledge base, can be enough to start a conversation with a buyer.
Does old data still have value?
Often more. Long operating history is one of the main things buyers say increases value, because it shows how decisions evolved over time.