Modern Marketing Starts with a Customer 360 on Snowflake
The best decision for your MarTech stack is the Snowflake Data Cloud
Co-Authors: Lourenço Mello and Luke Ambrosetti
Since the release of Snowflake Data Sharing in 2019, our customers have increasingly come to us on how to best manage their customer data. To build a robust marketing foundation, one of the most popular options for the better part of the past decade has been to purchase a Customer Data Platform (CDP); however, our customers have invested time and resources in their Data Cloud and want to make sure they’re making the best decision for their data strategy and their brand, while simplifying their implementations and eliminating redundancies in their stack.
A foundational step for marketers to modernize their data driven marketing efforts is to effectively implement a robust and agile Customer 360. At a high level, a Customer 360 is a centralized datastore for both humans and business systems to have a single view of an organization’s customers, consisting mainly of their first-party data. The detailed definition of a Customer 360 will be unique to each organization’s specific needs — a retail store and a bank will need Customer 360s that look very different and are tailored to their specific business needs. Said in another way, a Customer 360 is primarily a data product for a brand’s marketing team.
In this blog, we’ll look at the technical components of a Customer 360 data product, how Snowflake can help, and also how our partner ecosystem helps customers accelerate and enhance their Customer 360 on the Data Cloud to maximize the value of their marketing efforts.
Creating a Customer 360
The first step organizations need to take to create an effective Customer 360, is to identify the end use-cases that will drive the highest level of business impact. This typically requires internal alignment between technical and marketing teams to identify clear strategic pain points that need to be addressed by the organization.
Once priority use-cases are identified, organizations can begin executing on their implementation by working backwards. Specifically this involves identifying the outputs needed for the marketing team to be successful. From that starting point, organizations can identify the right inputs that ensure that their Customer 360 delivers on their unique business challenges. Below are examples of common outputs and inputs that we have seen organizations work with to build their Customer 360:
- Common Outputs — Basic Customer Information, Opt-In Status/Consent, Last Action Date, Last Interaction Date/Channel, Last Purchase Date/Category, Channel Preference, Lifetime Value (LTV), Predictive Modeling (e.g. Churn Score), etc.
- Common Inputs — Behavioral Data, Application Data, SaaS Data, Partner Data, Form Data, Survey Data, Point of Sale Data, Product Data, Third-Party Data, etc.
This is just a small sampling, so it’s easy to see how daunting this may look for organizations, when there are hundreds of outputs that need to be delivered while remaining compliant with regulations like GDPR and CCPA. It’s also a large reason why picking and implementing the right first-party data strategy for a brand can be a tall task and one that has strategic implications for an organization’s growth and/or retention strategy. To meet those inputs/outputs, a platform needs to execute on the following capabilities:
- Data Lake that ingests all types of data from any source in real-time
- Data Engineering for identity/entity resolution
- Data Governance for compliance and regulation
- Data Science for predictive analytics and a feature store (that is accessed in real-time)
- Data Collaboration to share partner data and access 3rd party data
It’s easy to see why brands have opted for a CDP that fits their needs rather than undertaking the complex and time-consuming task of building it themselves. However, a big reason for the massive growth of vendors in the CDP category is that previously, brands lacked an alternative approach to own their first-party data. That was until Snowflake came into the picture. With the Snowflake Data Cloud, that paradigm has changed and organizations can begin working with a secure, scalable, performant and easy-to-use platform capable of making this vision a reality, and providing the right foundation for modern, data driven marketing.
Customer 360 on the Snowflake Data Cloud
Before cloud data platforms, the effort to build this out in an on-prem data platform was monumental, and only accessible by some of the world’s largest and well-resourced organizations. Now, with Snowflake pioneering the separation of compute and storage in a cloud-native platform that allows near-limitless scalability, achieving this has become far more feasible. A subset of the core capabilities delivered by Snowflake that enable this vision are as follows:
Data Capture / Data Ingestion: Snowpipe and Snowpipe Streaming offer near real-time and real-time data ingestion into the Snowflake Data Cloud, which supports structured, semi-structured, and unstructured data.
Identity Resolution: Streams, Tasks, and Dynamic Tables offer support to help you build your data pipelines when resolving identities.
Data Governance: Snowflake deploys in your public cloud region of choice, and offers security features like Dynamic Data Masking to protect PII and sensitive data.
Predictive Analytics: Snowpark and Unistore can be used to build out a feature-rich customer profile that can be accessed in real-time.
Data Collaboration: Snowflake Data Sharing, Global Data Clean Rooms, and the Snowflake Marketplace can be leveraged to share data with partners securely, or access thousands of 3rd-party datasets to enrich your customer data. You can also activate data to downstream providers using Snowflake External Functions.
All of these capabilities, and multiple others not mentioned explicitly, make Snowflake the ideal data platform to implement your organization’s Customer 360. Most critically, buying the wrong CDP typically means creating yet another data silo for the brand, increasing risks to privacy and governance, data latency and costs. By building your Customer 360 as a data product on Snowflake, it ensures that your marketing team doesn’t have to go to multiple systems to execute on campaigns and programs and can operate from a unified view of the customer.
For a detailed example of how to build your Customer 360 on Snowflake, check out the recent post from our Frostbyte team.
Customer 360 Accelerators
While Snowflake gives you the tools to build and maintain your own Customer 360, it is not an out-of-the-box Customer Data Platform. Therefore, a critical component for your success is the rich partner ecosystem that works with your brand’s Snowflake Data Cloud, highlighted by the Modern Marketing Data Stack report that was released in late 2022. Taking ownership of your customer data is still daunting, but brands can choose the path of working with Snowflake to leverage the platform’s core capabilities, and complement it with leading applications from a broad and diverse set of martech partners. There are two types of accelerators that leverage the Data Cloud and our leading ecosystem for organizations looking to deliver on CDP capabilities on Snowflake:
Component Accelerators — The Composable CDP
You’ve likely already heard the term ‘composable’, ‘unbundled’, or ‘reverse-ETL’. The partners in this category can help accelerate specific aspects of your Customer 360 and turn your Data Cloud into the core of your marketing engine, whether that’s in data ingestion, transformation, or activation. In a nutshell, these partners help create your Customer 360, or they help action on it by activating the data to the right marketing channels. You can think of this option as an unbundled CDP that takes different components from leading partners on Snowflake and unifies them into a single solution.
One category to note specifically is the Snowflake Marketplace and Native Application framework. Snowflake is working with partners like LiveRamp, Neustar, and Truelty to build applications that are hosted inside of your Snowflake account to help with identity resolution and other capabilities. Affinio is another native app partner that helps with predictive modeling and analytics.
Most of the partners in the graphic above fit into the Snowflake “connected” or “native” application frameworks, meaning that your Snowflake Data Cloud will always retain ownership of the data. While some customers might adopt a full set of these tools to create and maintain their own Customer 360, most just pick one or a few to complement their existing stack and complete their solution. A few advantages of this approach are:
- Allows a brand to work with existing technology or specific best of breed applications.
- Offers increased control, flexibility and agility of customer model, data granularity and identity spine.
- Marketers can use live data for segmentation and activation on any channel, directly from their own Snowflake Data Cloud.
- Marketers can access all of their data without copying, synching or mapping, thus increasing security and privacy standards and compliance.
- Risk reduction for monolithic vendor lock-in.
Platform Accelerators — The Platform CDP
As mentioned earlier, Snowflake gives you the right tools to build a Customer 360, which is exactly why some CDPs chose to build their full solution on top of Snowflake.
In some cases, you might want to provide some datasets locked inside of your Data Cloud to a CDP. With these partners, which fit under the Snowflake “managed” application framework, you can use Snowflake Data Sharing to seamlessly share data with your preferred CDP provider, who then in turn help complete a Customer 360 for your brand. Some of the benefits of this option include:
- Solution for organizations that lack dedicated data resources and need a GUI for audience creation.
- Fully managed solution, ideal for organizations who may lack support of an IT team to manage data or create accounts and credentials.
- Reduced data latency, cost and increased governance with Data Sharing protocol.
When customers desire a full platform solution, we see customers choose providers like these, or other platform CDP partners that have built connectors, to work alongside their own Snowflake Data Cloud.
Next Steps
While there are a lot of options on how to best build a Customer 360 on Snowflake, the best one is going to depend heavily on your organization and data strategy. If you don’t have enough of the right resources to create your own Customer 360 and own your first-party data, then it’s typically best to lean towards a platform CDP that seamlessly integrates with your Data Cloud. If you do want to create your own Customer 360, then you have plenty of options — let us know how we can help!