Connecting Snowflake is admin-only, under Integrations, Apps, Snowflake in the dashboard.
Connect Snowflake
Have your Snowsight URL and a Snowflake username ready, then run the four-step wizard.1
Enter your account and user
Open Snowsight and copy the address from your browser, for example
app.snowflake.com/tsyqtjr/kt32003. Paste it into Clustr, enter the username Clustr should sign in as, and click Continue. A dedicated service user is recommended.2
Authorize with a key pair
Clustr generates a key pair and shows one statement. Run it once in a Snowflake worksheet as an admin:Click I’ve run it. Clustr keeps the private key. Only the public key is shared.
New Snowflake accounts block password sign-in for drivers, so Clustr uses key-pair auth. No password is ever stored.
3
Pick your destination
Choose a warehouse and database from the dropdowns, then pick an existing schema or create a new one (defaults to
EXPORTS). Click Continue.4
Connect and sync
Review the destination and click Connect to save the connection and run the first full export. Clustr writes to
<database>.<schema>.clustr_referral_paths.How It Works
Clustr writes a single table,<schema>.clustr_referral_paths, one flat, denormalized row per opportunity. Rows are upserted on id with a MERGE, so re-syncing never duplicates, and a full sync also removes opportunities that no longer exist in Clustr. Because it is keyed and idempotent, the table is safe to query live, build views on, or point a BI dashboard at.
Settings
The Snowflake panel shows connection status and sync controls.Table Schema
clustr_referral_paths is keyed on id (used for upserts); all other data fields are stored as text so the export never fails on type coercion. Full column reference:
Keys & metadata
Keys & metadata
Contact (client)
Contact (client)
Relationship quality
Relationship quality
Prospect
Prospect
Prospect company
Prospect company
Engagement
Engagement
Accounts and Connectors tables (optional)
Besides the warm intros, Clustr can export your Accounts and Connectors ledgers. Both are off by default. Turn them on in the connect form’s last step, or later under Integrations → Snowflake → Settings. Turning one on starts a sync straight away. They are written into the same schema as the warm intros, by the same sync, with the same rules: every row is upserted on its key, and rows that left the ledger are removed after a complete sync. Turning a table off stops writing it; the table and its rows stay.
All columns are text, like the warm-intros table.
Competitor monitoring tables (optional)
With competitor monitoring, Clustr can also export your competitors’ activity and the accounts they work. One switch writes both tables: Competitor monitoring, in the connect form’s last step or under Integrations → Snowflake → Settings. It is off by default, and turning it on starts a sync straight away. Both tables are written by every sync, including the one that follows each competitor scan, and each sync writes them whole: an interaction you ignore or a competitor you remove leaves them at the next sync. Turning the switch off stops writing them; the tables and their rows stay.clustr_competitor_activityhas one row per like or comment, as the Activity tab lists them.activity_idstays the same for the same interaction from one sync to the next.directionisoutboundwhen their person engaged someone’s post,inboundwhen someone engaged their person’s post.clustr_competitor_accountshas one row per account a competitor ever touched, and per company that buys from a competitor you watch (customer_onlyistruefor those, with no interactions).standingiscustomer,crmornew, as the Account column reads.has_open_deal,deal_stageanddeal_nameare the open deal in your CRM, the one the Accounts page shows.- Join either table to
clustr_accountsoncompany_id,account_linkedin_idorclustr_account_id.
Renaming a table
Every table Clustr writes carries a marker in its comment (clustr:referral_paths, clustr:accounts, clustr:connectors, clustr:competitor_activity, clustr:competitor_accounts). If you rename a table in your database, Clustr finds it by that marker and keeps writing to it under its new name. Clustr only writes the comment when the table has none, so a comment of your own is never overwritten; keep the marker text in it if you edit it.