Question 1

What Fathom data can Polytomic sync?

Accepted Answer

Three objects: meetings, teams, and team members. Meetings carry almost everything you would want, including the recording ID, title, share URL, scheduled and actual timings, transcript language, and whether the invitee list was internal only or included external participants. Nested on each meeting you get the transcript segments, action items with assignees, calendar invitees, the default summary, who recorded it, and Fathom's CRM matches covering contacts, companies, and deals.

Question 2

Are transcripts and action items separate tables?

Accepted Answer

No, they stay nested as arrays on each meeting record. There is no separate transcript or action item object, so a meeting arrives as one row with its transcript segments inside it, each carrying speaker, text, and timestamp. To query line by line you unnest that array in your data warehouse after the ETL sync, preserving the meeting identifier so you can aggregate back. That shape is simple to work with in SQL and means a meeting is always complete in one row rather than needing a join.

Question 3

How do incremental reads work, and what do they miss?

Accepted Answer

Meetings sync incrementally by sending a saved checkpoint as a created after filter, and you can additionally set a cutoff so the first run does not reach back forever. The important caveat is that the cursor is creation time, not modification time. A meeting whose transcript or summary finishes processing later, or whose action items get completed afterwards, will not be revisited by an incremental run. Teams and team members are full reads. A periodic full resync reconciles the gap if late updates matter.

Question 4

How useful are the CRM matches?

Accepted Answer

Useful as a starting point rather than an authoritative mapping. Fathom attempts to match meeting participants to CRM contacts, companies, and deals, and those matches come through with URLs and deal amounts, which saves you doing the join by email domain yourself. Treat them as evidence rather than truth though: a Fathom CRM match identifies a record in the external CRM and is not a guaranteed customer identity mapping. For reporting that has to be exact, reconcile against your own CRM data in the data warehouse.

Question 5

Why move meeting data into a data warehouse?

Accepted Answer

Because a recording tool can replay a call but cannot tell you what pattern it fits. Which objections appear before deals stall, whether accounts with more meetings retain better, and what customers say about a feature before they churn all need transcripts joined to CRM, product, and billing data. Running ETL into your data warehouse makes that possible on your own definitions, and reverse ETL on the same platform can push a meeting summary or coverage flag back onto the CRM record your team works in.

Fathom

Perfect pairings

Transcripts and summaries

CRM matches included

Action items with assignees

Example workflows

What you can sync

From Fathom

How it works

How to set up

Frequently asked questions

Why teams choose Polytomic

No engineering required

Flexible data modeling

Handles scale automatically

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