Home > Destinations > Snowflake > Klaviyo

Connect Klaviyo to Snowflake

Connect Klaviyo to Snowflake and export selected accounts, metrics, and dimensions to your Google BigQuery project.

Configure the historical window, destination table, and recurring schedule without maintaining a Klaviyo API pipeline.

Klaviyo export job

First sync scheduled

Klaviyo Selected accounts

Configured job

Snowflake Destination table

Account Klaviyo · Client group A

Table daily_dump

Initial import Configured historical window

Schedule Daily · 06:00 UTC

Fields Selected metrics + dimensions

Partition date · eligible field

Illustrative job · configure values for your account Export ready

Used by the world's leading companies

Export Klaviyo data to Snowflake

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Klaviyo data in PostgreSQL

Bring all your Klaviyo data into your warehouse and make it available for analytics, machine learning, and internal applications.

Source

Klaviyo Emailing data

INaccounts PMcampaigns CUcontacts BLlists

Catchr pipeline IN PM CU Extract · normalize · load

Snowflake catchr_data.Klaviyo_raw

TableScopeStatus

accountsSelectedReady

campaignsSelectedReady

contactsSelectedReady

listsSelectedReady

Data freshness

Keep your Snowflake tables up to date

Automatically sync new data from Klaviyo so every dashboard, model, and report works with fresh information.

KlaviyoConfigured account

SnowflakeKlaviyo Metrics_raw

Rows processed Scheduled loads Example 24h

00:0006:0012:0018:00

Latest run Completed 06:00 UTC

New rows +428 4 tables updated

Next run Scheduled 12:00 UTC

accounts326 updated campaigns102 appended Warehouse up to date

Analysis

Unify Klaviyo with the rest of your business data

Join marketing, finance, CRM, and product data inside the same warehouse.

Business data model

model / business_360

Warehouse inputs

QuickBooks accounts · API - Active On Site Emailing

Marketingcampaign · spend · UTM Ads

CRMcontact_id · lifecycle Sales

Productaccount_id · event_date Usage

Match keys customer · date · campaign

Snowflake model business_360 Unified

FieldFrom

customer_idCRM

API - Active On Siteaccounts

ad_spendMarketing

lifecycle_stageCRM

active_usersProduct

Ready for SQL 5 business fields

Klaviyo metrics and dimensions available in Snowflake

Access 71 metrics and 57 dimensions from Klaviyo connectors including Emails Open Rate, Emails Clicked Rate, Shopify - Placed Order Value, Submitted Form, Subscribed to List, Campaign Name, Campaign Channel, Flow Name, List Name, Date and many more...

Metrics availables

Dimensions availables

View all Klaviyo Metrics metrics and dimensions

Connect Klaviyo to Snowflake in minutes

Move your data from Klaviyo to Snowflake with a simple setup. Once connected, Catchr handles the ingestion automatically so your warehouse stays up to date without manual work.

Step one

Connect your Klaviyo account

Authenticate your Klaviyo account securely in Catchr. No custom scripts, API maintenance, or engineering work required.

Connect now

Client A · Connected sources

5 sources ready

Klaviyo 3 advertising accounts Connected

Google Ads 2 advertising accounts Connected

Google Analytics 4 1 web property Connected

HubSpot 1 CRM portal Connected

Step two

Choose the Snowflake destination

Add the account host, user, and database schema. Use a password for compatible users or a PEM private key for service accounts and stricter policies.

Destination / Snowflake Required fields

Authentication Choose one

Password

Key pair

Host Required

xy12345.eu-west-1

Username Required

catchr_service

Database Required

MARKETING.RAW

Private key passphrase Optional

••••••••••••

Private key Required for key pair

-----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6TAbBgkqhkiG9w0BBQMw... -----END ENCRYPTED PRIVATE KEY-----

Step three

Keep your Snowflake tables updated

Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your PostgreSQL table.

Export job / PostgreSQL Example

Schema Destination

marketing_raw

Table Per job

linkedin_ads_daily

Recurring schedule Choose a cadence

Every 6 hours

Daily · 07:00

Weekly · Mon

First sync scheduledSelected fields · configured history

07:00 UTC

Review 30-day Klaviyo email campaign performance in SQL.

This example summarizes delivery, opens, clicks, and engagement rates by email campaign.

30-day window

SELECT
  campaign_name,
  SUM(sent) AS sent,
  SUM(delivered) AS delivered,
  SUM(opens) AS opens,
  SUM(clicks) AS clicks,
  SAFE_DIVIDE(
    SUM(opens),
    SUM(delivered)
  ) AS open_rate,
  SAFE_DIVIDE(
    SUM(clicks),
    SUM(delivered)
  ) AS click_rate
FROM `your_project.marketing_raw.klaviyo_campaign_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY campaign_name
ORDER BY delivered DESC;

Illustrative SQL — adapt it to the fields and schema selected in your export. Standard SQL

Choose what to load into Snowflake.

Each connector has its own entities, fields, historical limits, and reporting uses. Open a source page for the details that belong to that platform.

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Emailing

Before you schedule the job.

Answers about PostgreSQL setup, available source data, schedules, table updates, and SQL use cases.

How do I start a scheduled Klaviyo import into Snowflake?

Start with a connected Klaviyo source and an existing Snowflake database. Create a datastream between them, then configure the accounts, fields, schedule, and "segments" table.

Which Klaviyo entities can become Snowflake tables?

Select concrete Klaviyo fields such as API - Active On Site, API - Added To Card, API - Placed Order, and Day of the month. You can rename the chosen columns, preview the result, and write them to Snowflake tables such as accounts, campaigns, and contacts.

Does Catchr support an initial fetch for Klaviyo data in Snowflake?

Set an initial fetch period for Klaviyo, then choose the frequency and lookback window for the job writing to "segments". Catchr rewrites that selected period on each run.

Which partition setting keeps Klaviyo Snowflake rows updated?

The partition field tells Catchr which Klaviyo rows in "segments" belong to the period being refreshed. If you omit it, every run appends records rather than updating them.

What is a practical SQL use case for Klaviyo data?

With Klaviyo data, a Snowflake query can summarize delivery, opens, clicks, and engagement rates by email campaign. A query built around API - Active On Site and API - Added To Card can support trend reviews, account comparisons, and operational reporting.

Does my Snowflake database need to exist before I connect it?

Yes. Connect an existing Snowflake database first. The Catchr job creates and populates the destination table you configure inside that database.

Can I load several marketing sources into the same Snowflake database?

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.

Still have a question ?

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100+ sources

Used by the world's leading companies

Export Klaviyo data to Snowflake

Centralize Klaviyo data in PostgreSQL

Keep your Snowflake tables up to date

Unify Klaviyo with the rest of your business data

Klaviyo metrics and dimensions available in Snowflake

Connect Klaviyo to Snowflake in minutes

Connect your Klaviyo account

Choose the Snowflake destination

Keep your Snowflake tables updated

Review 30-day Klaviyo email campaign performance in SQL.

Choose what to load into Snowflake.

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