Composable CDP built on Snowflake

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Researched by
GrowthLoop Editorial Team
verified by
Anthony Rotio

Key Takeaways:

  • A Snowflake composable CDP sits on top of your Snowflake Data Cloud and allows your team to activate customer data across various marketing destinations.
  • Both data and marketing teams should be involved in implementing a Snowflake composable CDP.
  • When setting up Snowflake as part of your composable CDP, look for modular solutions with components that are compatible with Snowflake Data Cloud and any other solutions you currently use.
  • Data hygiene, data governance, and ongoing policies are all part of setting up and maintaining a Snowflake composable CDP.

Table of Contents

What is a composable CDP built on Snowflake?

A composable customer data platform (CDP) is a marketing technology infrastructure built from multiple interchangeable components. It sits on top of a company's cloud data warehouse, which provides a single source of truth for all customer data. The composable CDP then activates that data across various channel destinations, such as a CRM or email platform. 

A composable CDP’s flexible, data warehouse-based structure allows marketing teams to build cross-channel campaigns that pull from one, centralized customer data record.  Composable CDPs differ from traditional or packaged CDPs by being modular and customizable, allowing teams to add and remove channel destinations as their audience needs change.

The Snowflake Data Cloud offers tools to store data within a simple architecture and with various management and machine learning (ML) features. A composable CDP built on Snowflake is a composable CDP that uses Snowflake as the data warehouse in its foundation. 

A diagram of a composable CDP
A Snowflake composable CDP sits on top of a single source of truth (your Snowflake Data Cloud) and activates data to various marketing destinations.

Why would I want to build a composable CDP on Snowflake? 

Compared to a traditional CDP solution, a composable CDP offers more direct control over your organization’s data. Rather than going through a third party solution, your company uses Snowflake’s tools to store the data and then selects the tools or users to access the data. 

This means that your data warehouse, which you control, becomes the single source of truth for all your data instead of storing your data in multiple places. Having a single source of truth means you’ll have more accurate and consistent customer data, leading to more effective and personalized campaigns. A single data source also reduces your security risk, as there are fewer opportunities for a breach. 

Because a composable CDP can work with various data collection, storage, and management tools your teams can continue using the tools they already use. A modular solution lets you select the best-in-breed or best-fit solutions for your needs. 

What features should I look for in a composable CDP that works with Snowflake?

Key features to look for in a Snowflake composable CDP

When setting up Snowflake as part of your composable CDP, look for modular solutions with components that are compatible with Snowflake Data Cloud and any other solutions you currently use. You may need to contact vendors to see if they have solutions that work with Snowflake, or if they can customize a solution for your technology stack.

Consider the following criteria when vetting solutions for your Snowflake composable CDP.

  • Security and compliance: Verify that any composable CDP components meet regulations and standards for all data laws your company and industry are subject to. When in doubt, consult your legal team or a lawyer.
  • Identity resolution: Your data warehouse needs a way to consolidate duplicate or unaffiliated data about the same customer into one entry. This helps clean and streamline your data and gives you a clearer picture of your customers.
  • Data activation:  Once your tools collect data, you need to activate that data across various channels and destinations. You can think of an inactive customer profile as a folder of index cards with individual facts but nothing connecting them. You need data activation tools to process that data into information your marketing applications can use.
  • Machine learning (ML) and artificial intelligence (AI): Snowflake is compatible with a variety of tools that use ML algorithms to automate some functions of your marketing process. Look for Snowflake-compatible tools that can meet your team’s needs. 
  • Data portability: If you don’t already have a Snowflake instance set up, you may need to transfer your data from existing sources into your Snowflake instance. There are a variety of methods outlined on the Snowflake Docs site and instructions for setting up their Snowpipe pipeline solution.
An illustration and diagram of a Snowflake composable CDP
A Snowflake composable CDP allows you to build audiences in the Snowflake Data Cloud and activate those audiences across different marketing destinations.

How do I know a composable CDP on Snowflake is right for my company?

A composable CDP is an ideal solution for organizations that have a data warehouse and are struggling to find the right support from a traditional, packaged CDP. This may include companies with strict data regulations or compliance needs, ones with too much data for their current CDP solution, those that operate on a hub-and-spoke model (such as an airline or sports team), or any business-to-business (B2B) data models that don’t fit in traditional CDP solutions.

Snowflake Data Cloud is compatible with the three most popular cloud hosting solutions: Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. That means it may be a good solution for your company regardless of which platform currently houses your data. This also gives your company more choice in setting up your other tools, as you can consider tools that aren’t exclusive to Amazon, Google, or Microsoft.

When setting up Snowflake as part of your composable CDP, look for modular solutions with components that are compatible with Snowflake Data Cloud and any other solutions you currently use.

How do I set up Snowflake to work with a composable CDP?

Before you begin, you should have a set of data collection, data activation, and marketing tools that are all compatible with Snowflake and with each other. You should also set some clear and attainable data-related goals, so that you can measure what success looks like and identify any adjustments to make in the future. For example, if you have incomplete customer profiles or profiles missing some key data points, determine a percentage of customers you want that data for, and then plan how you will collect it.

Creating a composable CDP on Snowflake is a big project that likely needs funding, cross-functional support, and buy-in from other teams in your company. After getting buy-in, funding, and your components figured out, it’s a process of connecting everything together, setting rules and policies for your data, and then checking in to ensure the tools meet your goals. 

What team members do I need to implement a composable CDP on Snowflake?

Many components of a composable CDP are tools designed for data analysts, data scientists, and marketers. This means you will likely need those individuals on your team. It also means you likely need less support from your technology and infrastructure teams (although you may still benefit from developing rapport with those teams if anything comes up). 

Data and analytics teams will have the clearest picture of your company’s data, data hygiene, and data governance, (see section below for more information). This gives you a “clean slate” to work from, and gets all of your teams on the same page about your data and how your composable CDP will work. Getting the teams’ expertise early in the process helps you configure your tools and build tests to verify that the composable CDP and Snowflake Data Cloud both work properly.

Your marketing team will know the use cases for your organization's customer data. They likely already have goals, which the Snowflake composable CDP can help them meet. Ask about any data gaps they have now, and work with them to determine how a composable CDP can provide them access. Also, dig into what they need to activate your data across marketing channels, such as tools or dashboards they use to monitor data during campaigns.

How can I get buy-in for building a composable CDP on Snowflake?

When seeking buy-in for a new solution like a Snowflake composable CDP, aim to demonstrate how your new idea will make your colleagues’ lives easier. Start by asking about any pain points the data and marketing teams have with your data warehouse and any connected solutions. Show how the Snowflake composable CDP will be a solution for their problems.

For example, if your data and marketing teams complain of inaccurate data across reports or systems, show how the Snowflake solution will resolve these issues by providing a single source of truth across all platforms and dashboards. With data flowing to and from one, centralized location, there will be fewer data discrepancies.

You can also present your research and solutions to executive leadership, as they can help drive your change from the top. They will want a clear plan for implementation, problems the composable CDP on Snowflake will solve, and any short- and long-term costs. 

What steps are involved in connecting a composable CDP to Snowflake? 

When leading a project to set up a composable CDP on Snowflake Data Cloud, you have several key stages related to preparing the data, building policies about your data, connecting your modules, and ongoing maintenance procedures. At a high level, you will need to take the following steps:

Data hygiene

Cleaning your data involves removing any unused, duplicate, uncategorized, outdated, or otherwise erroneous data from your database. Ask your data team to build SQL queries to find data that needs cleaning up, such as incomplete profiles, long-gone customers, or unused test data. Then, archive, delete, or complete it. Having a set of clean data before putting it into your Snowflake Data Cloud also gives you a chance to start from a “known good” state (a point-in-time where you know the data was clean) in your database.

Additionally, the queries that help you identify these unresolved data inconsistencies can also help you develop data governance policies.

Data governance and security

Data governance includes rules for how you collect and format data and any regulations or laws that you need to follow that relate to your data. 

  • Formatting rules: Not all of your data sources will collect data the same way. Sit down with your data analytics and marketing teams to define details like the type of data used in each field and the date and name formats you will use. This process will ensure all data will be organized in the  correct format within your data warehouse.
  • Laws and regulations: Many countries and regions have laws surrounding the data you can collect, how it’s stored, and how to dispose of it. Your data governance rules will need to keep these regulations in mind. For example, medical information in the United States is governed by the Health Information Portability and Accountability Act (HIPAA), while general personally identifiable information (PII) in the European Union (EU) falls under the General Data Protection Regulation (GDPR). Consider speaking to your legal team before finalizing any data governance policies based on your legal obligations.

Configuring composable CDP modules

You will need to consult Snowflake’s documentation and your data teams to properly configure your composable CDP. As many composable CDP solutions are cloud-based, this process may involve getting your cloud solutions to connect and share data. This stage is also where you may want assistance from your technical teams to troubleshoot anything that doesn’t connect properly to your tech stack. As an example of what to look for, try to find something similar to GrowthLoop’s documentation on connecting to Snowflake.

You’ll also need to ensure the composable CDP can activate data to your different channel destinations, such as your CRM or email platform. While you can connect every destination  at once, consider creating a slower plan to attach these components over several weeks. Starting with a few key use cases and testing those use cases is a great place to start.  This allows you to identify when issues arise, and troubleshoot or roll back the last solutions you implemented to prevent inaccuracies in your data.

Ongoing testing and procedures

While connecting new components to Snowflake and channel destinations, test them to ensure they are giving you the desired results. Verify that you can track results against your goals, so you can compare campaign performance and make adjustments as necessary.

Develop procedures for the data and marketing teams to follow in the event that  data problems arise. These plans should include teams or people to contact to resolve issues, as well as instructions for resolving those issues if the contacts are not available. 

For example, if a sales rep finds a customer profile that they know has inaccurate information, either empower them to make corrections or tell them who to contact. If they notice multiple wrong entries, tell them which data team members they should alert to investigate any root causes. Write down these procedures and publicize where teams can find the latest versions.

What best practices should I keep in mind when using a composable CDP with Snowflake?

As you begin using your composable CDP built on the Snowflake Data Cloud, remember that composable CDPs are modular. This means that as your team’s needs evolve, you can replace and swap your channel destinations as needed.

The following tips will also help you set up and maintain your Snowflake composable CDP:

  • Maintain a list of tools that interact with your composable CDP and Snowflake. Check the list periodically to ensure your tools are running the latest versions and to verify that there aren’t any compatibility or availability issues. 
  • Instill a culture of ownership over your data. Deputize anyone who interacts with the data for the data team, and give them specific procedures to follow if they see anything that looks like it’s breaking down. 
  • Publish a complete set of data hygiene policies that anyone can access, and make sure people know where to find them.
  • Periodically check in with your composable CDP and tools, ensuring that all of your tools are still collecting the data and operating properly.
Published On:
April 4, 2024
Updated On:
April 16, 2024
Read Time:
5 min
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