Klaviyo Integrations: Sync Your Marketing Data to Any Destination in Real Time

Klaviyo is one of the most widely used marketing automation platforms in ecommerce. It powers email, SMS, and push campaigns while helping businesses segment customers, track engagement, and personalize outreach.

But marketing data alone rarely tells the full story. Customer journeys also include purchases, support requests, and website behavior. When Klaviyo data stays siloed, it’s harder to connect those signals with the rest of your business.

That’s where a Klaviyo connector becomes essential. By syncing data into common destinations like Snowflake, BigQuery, Databricks, or MongoDB, companies can build unified profiles, measure campaign performance against revenue, and feed real-time events into dashboards or AI models.

Instead of relying on CSV exports or batch ETL tools, modern Klaviyo integrations combine real-time streaming with reliable backfills for complete, accurate data. This guide explains what Klaviyo integration means, the challenges of legacy approaches, and how Estuary Flow’s native Klaviyo connector provides a scalable, real-time solution.

Want to try this yourself? Sign up for Estuary Flow and start streaming your Klaviyo data in minutes.

What is Klaviyo Integration?

At its core, Klaviyo integration means connecting the marketing data you collect in Klaviyo with other systems in your data ecosystem. Instead of treating Klaviyo as a standalone platform, integration ensures that campaigns, events, and customer profiles flow into the tools where your business already runs analytics, reporting, and personalization.

So what does this look like in practice? Imagine sending Klaviyo events like email opens or coupon redemptions directly into BigQuery, where you can join them with ecommerce sales from Shopify or Magento. Or streaming Klaviyo profile updates into Snowflake to enrich customer segmentation models. For many companies, this level of integration is the key to building a true Customer 360.

Klaviyo integration supports use cases such as:

• Marketing performance analytics: See campaign outcomes side by side with actual purchase data.
• Personalization at scale: Feed real-time events into AI models that power recommendations.
• Cross-channel reporting: Track how email, SMS, and paid ads influence customer journeys.
• Data governance and storage: Archive Klaviyo interactions in cloud storage systems like S3 or GCS for compliance or historical analysis.

Without integration, teams are often stuck with exports, manual workflows, or delayed reports. That makes it difficult to act quickly on new customer signals. The real value comes when Klaviyo is part of a continuous data pipeline that updates in real time. After all, what good is a customer behavior event if you only see it days later?

Challenges with Traditional Klaviyo Connectors

Integrating Klaviyo data isn’t always simple. Traditional methods like CSV exports or older third-party connectors often create more friction than value.

The most common issue is latency. Batch-based tools refresh data on a schedule, sometimes only once a day, which makes it difficult to act on new customer signals in real time. On top of that, the Klaviyo API uses eventual consistency, so if delayed events are missed during a single capture, they may never appear in downstream systems.

Scalability is another concern. High-volume ecommerce brands generate massive streams of events, and older connectors often struggle to keep up, especially during backfills. The result is incomplete datasets, reporting gaps, and extra work for data teams.

These limitations leave businesses asking the same question: how can Klaviyo data be integrated with both speed and reliability?

Estuary’s Native Klaviyo Connector: What’s New

To solve the limitations of older connectors, Estuary built a new native Klaviyo connector from the ground up. This connector was designed with both performance and reliability in mind, so teams no longer have to choose between real-time speed and complete historical coverage.

Some of the key improvements include:

• 15+ supported data resources: Campaigns, Events, Profiles, Segments, Metrics, Forms, and more are automatically mapped into Flow collections for easy downstream use.
• Dual-stream ingestion: Each data resource receives data from: a real-time stream that captures events as they happen as well as a delayed lookback stream that ensures eventual consistency by filling in any missing records.
• Faster backfills: Parallel processing enables fast backfills, so teams can catch up on historical data without long waits.
• Scalable streaming: Since all data resources can be processed in parallel, pipelines stay responsive even as event volumes grow.
• Enterprise flexibility: Configure start dates and window sizes to match your specific operational or compliance needs.

This new connector reflects Estuary’s focus on building integrations that can handle enterprise-scale workloads. By combining real-time updates, reliable backfills, and schema-aware pipelines, it offers a foundation for businesses to trust their Klaviyo data across every downstream system.

How Estuary Flow Works for Klaviyo Integration

Estuary Flow is designed to make real-time data movement both simple and reliable. At a high level, it follows a capture → collections → materialization model. Understanding this flow helps explain how Klaviyo data moves seamlessly from source to destination.

• Capture: The Klaviyo connector acts as a capture, continuously pulling data from Klaviyo’s API. Each selected resource, such as campaigns, profiles, or events, is ingested into Flow.
  
• Collections: Once captured, the data is written into collections. A collection is like a real-time data lake backed by cloud storage, validated against schemas, and ready for transformation or analysis. Every Klaviyo resource maps cleanly to its own collection, so you know exactly where your data lives.
  
• Materialization: From there, you can materialize the collections into any supported destination. That could be a warehouse like Snowflake or BigQuery, a database like PostgreSQL or MongoDB, or even an analytics engine like Elasticsearch or Pinecone.

The advantage of Flow’s design is that you don’t need separate pipelines for real-time streaming and historical backfills. Both are handled within the same pipeline, ensuring accuracy and consistency. Plus, with declarative configuration and schema enforcement, you reduce the risk of mismatches or incomplete syncs.

In practice, this means your Klaviyo data can move from campaign events to dashboards, personalization engines, or AI applications in just minutes — without manual exports or fragile scripts.

Step by Step: Klaviyo to BigQuery with Estuary Flow

In this example, we’ll show you how to connect Klaviyo to BigQuery using Estuary Flow. The same process applies if you want to send data to Snowflake, Redshift, Databricks, or another supported destination — just select a different connector in the final step.

Prerequisites

• Klaviyo account with Admin or Owner permissions
• Klaviyo Private API Key
• Google Cloud project with a BigQuery dataset created
• Google Cloud Storage bucket in the same region as your dataset
• Google service account JSON key with roles:
  • roles/bigquery.dataEditor
  • roles/bigquery.jobUser
  • roles/bigquery.readSessionUser
  • roles/storage.objectAdmin

Step 1: Configure Klaviyo as the Source

1. Log in to Estuary Flow and go to the Sources tab.
2. Click + NEW CAPTURE. Search for Klaviyo and select the Klaviyo (real-time, first-party) connector.
   
   

   
3. On the Klaviyo connector page, fill in:
   
   

   
   • Name: Example klaviyo_capture
   • Data Plane: Select your data plane
   • Start Date: Choose a UTC date-time (default = 30 days back if blank)
   • Authentication: Select API Key and paste your Klaviyo Private API Key
   • Window Size (optional): Set the backfill window, e.g. P30D or PT6H
4. Choose which Klaviyo resources to capture (Campaigns, Events, Profiles, Segments, etc.).
5. Click NEXT > SAVE AND PUBLISH. Your Klaviyo data now streams into Flow collections.

Step 2: Configure BigQuery as the Destination

1. After publishing the capture, click MATERIALIZE COLLECTIONS in the pop-up. You can also open the Destinations tab and click + NEW MATERIALIZATION.
2. Search for BigQuery and select the connector.
   
   

   
3. On the BigQuery connector page, fill in:
   
   

   
   • Name: Example bq_marketing
   • Data Plane: Select your data plane
   • Project ID: Your GCP project ID
   • Service Account JSON: Paste the JSON key
   • Region: Must match your GCS bucket region
   • Dataset: Your BigQuery dataset name
   • Bucket: The staging GCS bucket name
   • Bucket Path: Optional folder within the bucket
   • Billing Project ID: Defaults to Project ID if not specified
4. Click NEXT to continue.

Step 3: Link Collections and Publish

1. In the Source Collections section, link your Klaviyo capture.
2. Map each collection (e.g. klaviyo/events, klaviyo/campaigns) to a table in your BigQuery dataset.
3. Confirm the configuration, then click SAVE AND PUBLISH.

Your pipeline is now live. Klaviyo data will stream into BigQuery in near real time, with historical backfills handled automatically.

👉 Get started with Estuary today: Create your free account or talk to our team if you’d like help setting up your Klaviyo pipeline.

Popular Destinations for Klaviyo Data Integration

One of the biggest advantages of using Estuary Flow is flexibility. Once your Klaviyo data is captured into Flow collections, you can send it to almost any downstream system without rebuilding pipelines. This makes it easy to join marketing data with ecommerce transactions, customer support records, or product analytics, wherever these resources reside.

Here are some of the most common destinations for Klaviyo data:

Data Warehouses

• Google BigQuery, Snowflake, Amazon Redshift, Databricks: These platforms are ideal for centralizing data across your business. By pushing Klaviyo events and profiles into a warehouse, you can:
  
  
  • Build marketing performance dashboards that show opens, clicks, and conversions side by side.
  • Join Klaviyo engagement with actual order or revenue data from your ecommerce platform.
  • Run advanced analytics or feed data into AI models.

Databases

• PostgreSQL, MySQL, MongoDB, SQL Server: Traditional databases are a great choice when you need operational access to Klaviyo data. For example, you might enrich CRM records with Klaviyo profiles or store campaign events for use in internal applications.

Real-Time Analytics and AI Systems

• Elasticsearch, Rockset, Pinecone, Tinybird: These tools are designed for fast queries and AI-driven workloads. Imagine streaming Klaviyo events into Pinecone to power real-time product recommendations, or indexing data in Elasticsearch to analyze campaign performance instantly.

Cloud Storage

• Amazon S3, Google Cloud Storage, Azure Blob: Storing Klaviyo data in object storage is useful for compliance, auditing, or low-cost long-term archiving. You can export data as CSV or Parquet files, making it accessible for downstream processing or ad hoc analysis.

Ecommerce Pairings

• Because Estuary also supports connectors for platforms like Shopify, you can capture Klaviyo message clicks alongside ecommerce orders. This pairing gives a complete view of how marketing campaigns directly influence revenue.

The question is, which destination makes the most sense for your business? Many teams start by streaming Klaviyo events into a warehouse for analytics, then expand to real-time systems or storage as new use cases arise.

Looking for inspiration? Explore how companies use Estuary Flow in our customer success stories

Advanced Features for Klaviyo Integration

Integrating Klaviyo data isn’t just about moving records from one system to another. The real power comes from advanced features that ensure accuracy, scalability, and flexibility as your business grows. Estuary Flow’s native Klaviyo connector includes several capabilities that set it apart.

Backfill Support

Need to bring in months of past campaign data? The connector supports full historical backfills alongside real-time streaming. With parallel processing, event backfills can run up to five times faster, so you don’t have to wait days to get caught up.

Lookback Window for Eventual Consistency

Some events from Klaviyo’s API can be “eventually consistent” or delayed. Instead of risking missed data, Flow uses a lookback window to re-check past intervals. This ensures late-arriving events are still captured. Wouldn’t you rather have complete data instead of guessing what got lost?

Schema Evolution

Marketing platforms evolve, and Klaviyo is no exception. When new fields or changes are introduced in the API, Flow supports schema evolution so your collections remain valid. This helps downstream systems like BigQuery or Snowflake stay in sync without manual rework.

Transformations with Derivations

Sometimes raw data isn’t enough. With Flow derivations, you can transform Klaviyo events before sending them downstream. For example, you might filter out test campaigns, enrich profile data with ecommerce fields, or aggregate events by time window.

Secure and Scalable by Design

Finally, integration doesn’t have to mean compromising security. Flow supports enterprise deployment options including Bring Your Own Cloud (BYOC) and Private deployment, so data stays under your control while scaling to high event volumes.

With these features, Klaviyo integration goes beyond basic data sync. You get pipelines that are fast, reliable, and built for growth.

Klaviyo Integration Best Practices

Once your Klaviyo pipeline is live, there are a few proven practices that help you get the most out of it. These aren’t just technical tips — they’re habits that make your data more reliable and your analysis more impactful.

Pair Klaviyo with Ecommerce Data

On its own, Klaviyo tells you how customers interact with your campaigns. But what about the sales that follow? Connecting Klaviyo with ecommerce platforms like Shopify lets you measure the true impact of marketing. Did that email click lead to an order? Did a coupon code boost conversions? Linking the two gives you real business answers.

Optimize Window Size for Large Event Volumes

Klaviyo can generate millions of events, especially for brands with large customer bases. When backfilling, smaller window sizes help the connector checkpoint progress more often. This reduces the risk of timeouts and keeps the pipeline moving smoothly.

Keep an Eye on Schema Changes

Klaviyo’s API evolves over time, and new fields may appear. Monitor your collections to ensure downstream systems like BigQuery or Snowflake can handle these changes. With Estuary Flow, schema evolution is supported, but it’s still smart to verify how updates affect your analytics.

Monitor Pipelines with Built-in Observability

Don’t wait until someone notices missing data. Flow exposes metrics and logs so you can track throughput, latency, and errors in real time. Make monitoring part of your integration workflow — is your data arriving as expected, and at the right speed?

Use Derivations for Smarter Data

Raw Klaviyo events are valuable, but they can also be noisy. Consider using Flow derivations to filter out test campaigns, enrich customer profiles, or pre-aggregate metrics before they land in your warehouse. Clean data in means better insights out.

By following these practices, you’ll avoid common pitfalls and make sure your Klaviyo integration delivers reliable, actionable data for the teams that need it most.

Conclusion

Klaviyo generates valuable marketing data that helps ecommerce businesses understand customer behavior, optimize campaigns, and drive growth. But its full value comes when that data is connected with the rest of your business systems. By integrating Klaviyo with destinations like BigQuery, Snowflake, or Databricks, you can combine engagement metrics with sales data, build unified customer profiles, and support advanced analytics and personalization.

Estuary Flow’s native Klaviyo connector makes this integration straightforward. It captures 15+ data resources in real time, provides fast and reliable backfills, and ensures delayed events are not missed. With support for schema evolution, many destinations, and enterprise-grade deployment options, Flow allows businesses to move Klaviyo data at scale while maintaining accuracy.

Getting started is simple: configure Klaviyo as a source, choose your destination, and publish the pipeline. From there, your data continues to flow automatically, powering analytics and applications with fresh insights.

👉 Start integrating Klaviyo with Estuary Flow to bring your marketing and business data together in real time. Sign up free or contact us to see how we can help.