Setting up Klaviyo to Redshift Integration: 2 Easy Methods

Klaviyo is the best out there for seamlessly integrating with Shopify-powered online stores. It has a number of email automation and customer database management features that help you keep and engage lost customers. The platform is simple to use and ideal for agencies.

AWS Redshift is an Amazon Web Services data warehouse service. It’s commonly used for large-scale data storage and analysis, as well as large database migrations.

This article explains two different methods to set up Klaviyo to Redshift integration in a few easy steps. In addition to that, it also describes Klaviyo and Redshift briefly.

What is Klaviyo?

Klaviyo is a robust marketing platform that enables eCommerce store owners to give their customers a more personalized experience. Klaviyo has assisted brands all over the world in generating over $3.7 billion in revenue in just the last year. It’s never been easier to build deeper, higher-value customer relationships, which is why Klaviyo is attracting 67 new brands every day.

Klaviyo Email Marketing is frequently used in conjunction with platforms such as Shopify to assist business owners in creating a holistic marketing ecosystem. We’ll get into that a little more later.

You can also send bulk SMS Campaigns with Klaviyo and personalize each message using powerful automation. Content Management is straightforward and automated. Klaviyo enables you to create Multi-Channel Customer Experiences and manage them all from a single platform.

To increase reach and engagement, incorporate emails into full-fledged marketing campaigns. Whether it’s a one-time promotional blast, a recurring newsletter, or an automated flow, Klaviyo makes it simple to set up and schedule everything.

Key Features of Klaviyo

• 200+ Integrations: Our pre-built integrations bring together historical and real-time customer data from all of your software in one place, including one-click integrations for a variety of popular eCommerce platforms. One of the popular integrations is Klaviyo to Redshift.
• Real-time, Marketer Friendly Segmentation: Quick, simple, granular segmentation for purchased products, website browsing behavior, order value, and more—all ready to drop right into your customer communications.
• Real-time Customer Profiles: With our activity feeds, you can see everything your customers do—and what our data science predicts they’ll do—across all of your platforms and channels (email, SMS, web, etc.).
• Flexible Data Storage and Retention: Everything you need for data storage, retention, volume, fields, and age is included in our flexible NoSQL data platform.

Key Benefits of Klaviyo

Klaviyo’s main features include:

• Easy to Use: Klaviyo is designed to be simple to use from the start. The solution includes a WYSIWYG editor that makes it simple to create eye-catching emails.
• Powerful Segmentation: Klaviyo is a powerful marketing platform that makes segmentation a breeze. You can use behavioral and transactional data to precisely target your marketing campaigns with this software.
• 1-Click Integrations: Even better, Klaviyo is designed to do away with traditional marketing tools like spreadsheets. The software works in tandem with your existing tools, allowing you to pull data from ZOHO, Magento, Salesforce, Shopify, and other sources. Even better, Klaviyo has an Open API that you can use to build custom integrations to help you improve your marketing.
• Robust, Custom Web Tracking System: Klaviyo also has its web tracking system. The system keeps track of your potential customers’ browsing habits. This makes it simple to target customers who meet specific requirements.

What is Amazon Redshift?

AWS Redshift is Amazon Web Services’ solution for data warehousing. Amazon Redshift is a fully managed petabyte-scale cloud data warehouse product for storing and analyzing large data sets.

One of Amazon Redshift’s main strengths is its ability to handle large amounts of data – capable of processing unstructured and structured data up to exabytes. Data migrations of large scale can also be accomplished with the service. Redshift is AWS’ Data Warehousing Solution. Like other Data Warehouses, Redshift is used for Online Analytical Processing (OLAP) Workloads. 

Using Redshift, you can gather relevant insights from a vast amount of data. AWS provides a simple interface for automatically creating clusters, eliminating the need to manage infrastructure.

To know more about AWS Redshift, follow the official documentation here.

Key Features of Amazon Redshift

• Redshift allows users to write queries and export the data back to Data Lake.
• Redshift can seamlessly query the files like CSV, Avro, Parquet, JSON, and ORC directly with the help of ANSI SQL.
• Redshift has exceptional support for Machine Learning, and developers can create, train and deploy Amazon Sagemaker models using SQL.
• Redshift has an Advanced Query Accelerator (AQUA) which performs the query 10x faster than other cloud data warehouses.
• Redshift has a petabyte scalable architecture, and it scales quickly as per need.
• Redshift enables secure sharing of the data across Redshift clusters.

Key Benefits Of Amazon Redshift

• Speed: With the use of MPP technology, the speed of outputting large amounts of data is unprecedented. The cost AWS provides for services is unmatched by other cloud service providers.
• Data Encryption:  Amazon provides data encryption for all parts of your Redshift operation. The user can decide which processes need to be encrypted and which ones do not. Data encryption provides an additional layer of security. 
• Familiarity: Redshift is based on PostgreSQL. All  SQL queries work with it. In addition, you can choose the SQL, ETL (extract, transform, load), and Business Intelligence (BI) tools you are familiar with. You are not obligated to use the tools provided by Amazon.
• Smart Optimization: If your dataset is large, there are several ways to query the data with the same parameters. Different commands have different levels of data usage.
• Simultaneous Scaling: AWS Redshift automatically scales up to support the growth of concurrent workloads.
• Query Volume: MPP technology shines in this regard. You can send thousands of queries to your dataset at any time. Still, Redshift is never slowing down.
• AWS Integration: Redshift works well with other AWS tools. You can set up integrations between all services, depending on your needs and optimal configuration.
• Redshift API: Redshift has a robust API with extensive documentation. It can be used to send queries and get results using API tools. The API can also be used in Python programs to facilitate coding. 
• Safety: Cloud security is handled by Amazon, and application security in the cloud must be provided by the user. Amazon offers access control, data encryption, and virtual private clouds to provide an additional level of security.  
• Machine Learning: Machine-learning concepts are used by Redshift to predict and analyze queries. In addition to MPP, this makes  Redshift perform faster than any other solution on the market.  
• Easy Deployment: Redshift clusters can be deployed anywhere in the world from anywhere in minutes. In minutes, you’ll have a powerful data warehousing solution at a fraction of the price of your competitors.
• Consistent Backup: Amazon automatically backs up your data regularly. It can be used for recovery in the event of an error, failure, or damage. Backups are distributed in different locations. This eliminates the risk of confusion on your site.
• Partner Ecosystem: AWS is one of the first cloud service providers that started the market of Cloud Data Warehouses. Many customers rely on Amazon for their infrastructure.

Setting up Klaviyo to Redshift Integration

• Method 1: Using Hevo Data to Integrate Klaviyo to Redshift
• Method 2: Using Custom Code to Move Data from Klaviyo to Redshift

Method 1: Using Hevo Data to Integrate Klaviyo to Redshift

Hevo provides an Automated No-code Data Pipeline that helps you move your Klaviyo to Redshift. Hevo is fully-managed and completely automates the process of not only loading data from your 100+ data sources(including 40+ free sources)but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.

Using Hevo Data, you can connect Klaviyo to Redshift in the following 2 steps:

• Step 1: Configure Klaviyo as the Source in your Pipeline by following the steps below:
  • Step 1.1: In the Asset Palette, select PIPELINES.
  • Step 1.2: In the Pipelines List View, click + CREATE.
  • Step 1.3: Select Klaviyo on the Select Source Type page.
  • Step 1.4: Set the following in the Configure your Klaviyo Source page:
    • Pipeline Name: Give your Pipeline a unique name.
    • Private API Key: Your Klaviyo account’s private API key.
    • Historical Sync Duration: The time it takes to ingest historical data.

• Step 1.5: TEST & CONTINUE is the button to click.
• Step 1.6: Set up the Destination and configure the data ingestion.
• Step 2: To set up Amazon Redshift as a destination in Hevo, follow these steps:
  • Step 2.1: In the Asset Palette, select DESTINATIONS.
  • Step 2.2: In the Destinations List View, click + CREATE.
  • Step 2.3: Select Amazon Redshift from the Add Destination page.
  • Step 2.4: Set the following parameters on the Configure your Amazon Redshift Destination page:
    • Destination Name: A unique name for your Destination.
    • Database Cluster Identifier: Amazon Redshift host’s IP address or DNS.
    • Database Port: The port on which your Amazon Redshift server listens for connections. Default value: 5439
    • Database User: A user with a non-administrative role in the Redshift database.
    • Database Password: The password of the user.
    • Database Name: The name of the Destination database where data will be loaded.
    • Database Schema: The name of the Destination database schema. Default value: public.

• Step 2.5: Click Test Connection to test connectivity with the Amazon Redshift warehouse.
• Step 2.6: Once the test is successful, click SAVE DESTINATION.

Here are more reasons to try Hevo:

• Smooth Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to your schema in the desired Data Warehouse.
• Exceptional Data Transformations: Best-in-class & Native Support for Complex Data Transformation at fingertips. Code & No-code Flexibility is designed for everyone.
• Quick Setup: Hevo with its automated features, can be set up in minimal time. Moreover, with its simple and interactive UI, it is extremely easy for new customers to work on and perform operations.
• Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
• Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.

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Method 2: Using Custom Code to Move Data from Klaviyo to Redshift

This method explains how to get data from Klaviyo and migrate Klaviyo to Redshift.

Getting Data from Klaviyo

• Developers can access data on metrics, profiles, lists, campaigns, and templates using Klaviyo’s REST APIs. You can refine the information returned by using two to seven optional parameters in each of these APIs. A simple call to the Klaviyo Metrics API to retrieve data, for example, would look like this:

GET https://a.klaviyo.com/api/v1/metrics

• As a response, the GET request returns a JSON object containing all of the fields from the specified dataset. For any given record, all fields might not be available. The JSON may appear as follows:

{
  "end": 1,
  "object": "$list",
  "page_size": 50,
  "start": 0,
  "total": 2,
  "data": [
    {
      "updated": "2017-11-03 17:28:09",
      "name": "Active on Site",
      "created": "2017-11-03 17:28:09",
      "object": "metric",
      "id": "3vtCwa",
      "integration": {
        "category": "API",
        "object": "integration",
        "id": "4qYGmQ",
        "name": "API"
      }
    },
    {
      "updated": "2017-11-03 20:54:40",
      "name": "Added integration",
      "created": "2017-11-03 20:54:40",
      "object": "metric",
      "id": "8qYK7L",
      "integration": {
        "category": "API",
        "object": "integration",
        "id": "4qYGmQ",
        "name": "API"
      }
    ]
  }

Loading Data into Redshift

You can use Redshift’s CREATE TABLE statement to define a table that will receive all of the data once you’ve identified the columns you want to insert.

Create Table Command 

The creation of tables in Redshift is similar to how you create tables in other databases. Table constraints, column constraints, and attributes, such as column attributes and table attributes, are all defined in the create table syntax.

Syntax

CREATE [ [LOCAL ] { TEMPORARY | TEMP } ] TABLE 
[ IF NOT EXISTS ] table_name
( { column_name data_type [column_attributes] [ column_constraints ] 
  | table_constraints
  | LIKE parent_table [ { INCLUDING | EXCLUDING } DEFAULTS ] } 
  [, ... ]  )
[ BACKUP { YES | NO } ]
[table_attribute]

where column_attributes are:
  [ DEFAULT default_expr ]
  [ IDENTITY ( seed, step ) ] 
  [ GENERATED BY DEFAULT AS IDENTITY ( seed, step ) ]             
  [ ENCODE encoding ] 
  [ DISTKEY ]
  [ SORTKEY ]
  [ COLLATE CASE_SENSITIVE | COLLATE CASE_INSENSITIVE  ]

and column_constraints are:
  [ { NOT NULL | NULL } ]
  [ { UNIQUE  |  PRIMARY KEY } ]
  [ REFERENCES reftable [ ( refcolumn ) ] ] 

and table_constraints  are:
  [ UNIQUE ( column_name [, ... ] ) ]
  [ PRIMARY KEY ( column_name [, ... ] )  ]
  [ FOREIGN KEY (column_name [, ... ] ) REFERENCES reftable [ ( refcolumn ) ] 


and table_attributes are:
  [ DISTSTYLE { AUTO | EVEN | KEY | ALL } ] 
  [ DISTKEY ( column_name ) ]
  [ [COMPOUND | INTERLEAVED ] SORTKEY ( column_name [,...]) |  [ SORTKEY AUTO ] ]
  [ ENCODE AUTO ]

After you’ve created a table, you might want to migrate your data to Redshift by using INSERT statements to add data row by row. For inserting data one row at a time, Redshift isn’t designed for it. If you have a large amount of data to insert, save it to Amazon S3 and then load it into Redshift with the COPY command.

Insert Command

A query can be used instead of the ‘values’ in the Redshift INSERT statement. If the query’s results are compatible with the table column structure, Redshift will execute the query and insert all of the query’s resultant rows.

Syntax

INSERT INTO table_name [ ( column [, ...] ) ]
{DEFAULT VALUES |
VALUES ( { expression | DEFAULT } [, ...] )
[, ( { expression | DEFAULT } [, ...] )
[, ...] ] |
query }

Copy Command

A COPY operation can be performed with as few as three parameters: a Table Name, a Data Source, and Data Access Authorization.

Amazon Redshift extends the COPY command’s functionality to allow you to load data in a variety of formats from multiple data sources, control data access, manage data transformations and manage the load operation.

Syntax

COPY table-name 
[ column-list ]
FROM data_source
authorization
[ [ FORMAT ] [ AS ] data_format ] 
[ parameter [ argument ] [, ... ] ]

Keeping Klaviyo Data up to Date

• It’s not a good idea to duplicate all of your data every time your records are updated. This would be a painfully slow and resource-intensive process.
• Instead, identify key fields that your script can use to bookmark its progress through the data and return to as it searches for updated data. It’s best to use auto-incrementing fields like updated at or created at for this. 
• You can set up your script as a Cron Job or a continuous loop to get new data as it appears in Klaviyo once you’ve added this functionality.
• And, as with any code, you must maintain it once you’ve written it. You may need to change the script if Klaviyo changes its API, or if the API sends a field with a datatype your code doesn’t recognize. You will undoubtedly have to if your users require slightly different information.

Conclusion

This article talks about the distinct ways for Setting up Klaviyo to Redshift integration. It also gives an overview of Klaviyo and Redshift.

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