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Snowflake Data Clean Room (DCR) – A New Era in Retail CPG Industry

The blog highlights the significance of Snowflake Data Clean Rooms (DCR) in the retail CPG industry. It explains how DCRs enable secure data sharing, empower marketing attribution, and facilitate closed-loop measurements. The blog emphasizes the importance of data transparency, collaboration, and personalized marketing in staying competitive. The future of retail and CPG lies in secure and connected data, leading to enhanced customer experiences and optimized marketing strategies.

The Data Revolution in the Retail CPG Industry

In the era of Data and AI, the Retail Consumer Packaged Goods (CPG) industry generates a huge amount of data. This data helps analysts understand the market better and make decisions that increase sales, retain customers, and improve costs.

Today, Advanced analytics and Artificial Intelligence (AI) – Machine learning (ML) is utilized majorly to gain valuable insights and data drive decision-making in retail CPG industry businesses. By analyzing large volumes of data, businesses can identify:

  1. Sales analytics (Lead Scoring, Demand Forecasting)
  2. Marketing Analytics (Marketing channel attribution, Customer Segmentation, Product NPS and more.)
  3. Customer Analytics (RFM Analysis, Customer Lifetime Value (CLV), Customer Satisfaction, more…)
  4. Customer Support Analytics (Sentiment Analysis, Agent scoring/ quality, Churn prediction)

Additionally, advanced analytics can enable personalized marketing campaigns and enhance customer segmentation, improving customer journey satisfaction and loyalty. Overall, leveraging advanced analytics with AI-ML empowers retail CPG businesses to make data-driven decisions and stay competitive.

Over the past several years, especially around data privacy in retail, CPG data cloud is becoming a huge focus area. Both consumers and retailers produce several questions, like, where is the data source? How will the retailer investigate consumer data? Does the retail CPG industry have opt-in, opt-out? Does the consumer feel comfortable sharing the online and offline transaction data?

Understanding the Concept of Snowflake Data Clean Rooms

Concept of Snowflake Data Clean Rooms (DCR)
Source: Snowflake

Snowflake Data Clean Room is an innovative framework and design for safeguarded and collaborative multi-party endeavors. There are some traditional clean rooms that require physical infrastructure, but modern data clean rooms don’t need to be moved; it can remain secure and governed within your Snowflake environment.

Snowflake offers exclusive technologies that enable the creation of data clean rooms, allowing seamless collaboration between multiple Snowflake accounts. This process occurs without any data transfer, ensuring analysis is conducted directly on the real-time data. Snowflake Data Clean Room (DCRs) can be leveraged by companies for marketing analytics and data sharing, etc. in the following ways:

  1. Enable secure data sharing and collaboration between multiple Snowflake accounts.
  2. Enables Privacy-preserving techniques like secure multiparty computation and differential privacy protect individual-level data.
  3. Facilitate joint data analysis across different sources, improving marketing effectiveness and customer segmentation.
  4. Provides a secure and auditable environment for data sharing, ensuring compliance and governance.
  5. Enhancing marketing attribution is possible by combining and analyzing data from various channels.
  6. Helps in connecting data points for a comprehensive, real-time understanding of consumer data relationships.
  7. Improves data transparency between brands and retailers, enables cooperative promotions and valuable insights.
  8. Empowers personalized marketing, optimized campaigns, and enhanced customer experiences.

Need of Snowflake DCRs – Empowering Marketing Attribution and Closed-Loop Measurements

The retail sector is narrowing the divide and ensuring a smooth customer experience by implementing and establishing a Snowflake data clean room. This safeguards the sharing of transaction data with the consumer-packaged goods (CPG) industry for marketing attribution and closed-loop measurements.

Retail & CPG industries can use marketing mix modeling to discover fresh avenues to integrate information. This approach aids in enhancing marketing strategies, promotional endeavors, product development (especially in creating new product categories), and supply chain management (such as determining optimal distribution quantities for specific distribution centers).

These models rely on data from CPG companies and POS data from retailers, which can be securely combined in a Data Clean Room. By examining billions of credit card transactions, retailers and CPGs can gain insights into purchasing patterns, resulting in a refined and personalized customer experience.

Snowflake data clean room allows the retail CPG industry to provide data and to feel comfortable that their data is protected according to the enterprise privacy and safeguarding data by collaborating with consumers on their own retail data clean room before pushing data to the environment.

The Evolving Landscape of Data Clean Rooms

The future of retail and CPG (Consumer Packaged Goods) is tied to the future of data clear rooms in a rapidly changing environment. Because DCRs are fueled by advanced technologies Like machine learning and Artificial Intelligence, will continue to advance, becoming increasingly powerful.

Connecting various data points in the Retail and CPG industries’ cloud will result in a comprehensive, real-time understanding of consumer data relationships. There will be more improved data transparency between brands and retailers. This will benefit both parties while increasing the power of data collaboration which opens the doors for cooperative promotions, advertising, and valuable insights to enhance offline and online marketing strategies. Ultimately, the future lies in the value of secure and connected data.

According to the CX trends research, 70% of consumers want their online retail journey tailored to their personal preference and their understanding which is leveraged by data and insights. DCRs are a valuable tool for e-commerce retail and CPG enterprises looking to take personalization, maximize campaign effectiveness, and optimize costs to the next level.


Retail & CPG organizations are experiencing a worldwide transformation in how consumers, retailers, and brands engage. Finding reliable data and insights to navigate uncertainties in the industry is becoming more challenging.

In the digital era, the rise of eCommerce, evolving customer expectations, and supply chain transformations have intensified the need for adaptation. To address these progressive changes effectively, the industry needs a Snowflake retail cloud platform with DCRs that removes data barriers, ensuring secure and controlled data access. This is on how a Snowflake data clean room can facilitate the sharing of transaction data between the retail sector and the CPG industry, specifically for attribution and closed-loop measurements.

Furthermore, it explains that marketing mix modeling relies on data from CPG companies and point-of-sale (POS) data from retailers, which can be securely combined in a Data Clean Room.

Anblicks’ predictive marketing solution enables enterprises to connect with their customers. And together with Snowflake, we recognize that it is time to unlock the power of customer data optimization with CustomerAI, a machine learning-based learning based on Snowflake, which the retail and CPG industry can accomplish with data.

The mention of the Snowflake data clean room emphasizes its importance in protecting data according to enterprise privacy standards. It enables the retail CPG industry to collaborate with consumers, ensuring their data is protected before being pushed into the environment.

Are you ready to join the future of CPG? Check out our latest whitepaper on “Optimize your marketing spending using Customer Data” Authored by Munwar Shariff, CTO at Anblicks. This whitepaper focuses on optimizing marketing spending for customer acquisition, including guidelines for marketers implementing a scalable ML solution with Snowflake.

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