What data can be analyzed?

Gravite is designed to ingest customer conversations and interactions in their raw form. The most common sources are:

• Phone calls — automatically transcribed and analyzed by AI
• Emails and support tickets — imported from your tools (Zendesk, Intercom…)
• Chats and written exchanges — any structured conversation between an agent and a customer

But QM can also process less conventional data: customer feedback, forms, verbatims — useful for example to detect legal risks or evaluate perceived satisfaction on indirect channels.

If you haven't yet connected your data sources to Gravite, refer to the Integrations chapter, which covers connection with Aircall, Zendesk, Intercom and others.

Structuring your data in Gravite

Once your sources are connected, Gravite allows you to organize and structure your data directly in the platform. This step is often underestimated, but it directly determines the relevance of your analyses.

Well-structured data means, for example:

• Calls correctly attributed to an agent and a team
• Tickets categorized by type of request or channel
• Usable metadata (date, duration, language, status…)

The cleaner and better organized your data, the more precise and actionable the AI-generated scores will be.

What conditions analysis quality

A few best practices to keep in mind:

• Volume matters: a grid evaluated on 10 conversations will produce less reliable trends than one evaluated on 500
• Regularity too: data arriving continuously enables far more useful tracking over time than a one-off import
• Source relevance: evaluating billing emails with a grid designed for sales calls will produce poorly usable results — it's better to segment