Businesses across all industries crave data to better understand their customers and drive sales. Imagine a major consumer packaged goods brand that primarily sells through a large retailer. This brand could gain valuable insights by understanding the key actions / high-value assets (HVAs) customers take on the retailer's website before making a purchase. Although this makes good business sense, retailers are hesitant to share sensitive customer data, making collaboration difficult. 

Boards, CEO’s and CFO’s are turning to CMO’s (and marketing orgs) to get an answer. This brings us to the key points, on what modern marketers are truly looking for from data:

• Get detailed level insights: Safely analyze data from different sources without compromising privacy

• Use those insights for smarter decisions: Use powerful AI tools to uncover hidden patterns and opportunities

• Drive business success: Fuel growth with targeted marketing and personalized customer experiences

The single thread connecting the above three areas is the data clean room that offers a secure, privacy-compliant solution, empowering modern marketers to unlock valuable insights from collaborative data analysis across various industries, driving strategic decision-making and business growth.

Google BigQuery data clean Room: the secure solution

BigQuery data clean rooms, introduced in 2023, offers a secure environment for sharing, collaborating, and analyzing sensitive data, all while leveraging the benefits of the BigQuery ecosystem.

How it works and its architecture

BigQuery data clean rooms is a specialized application of Analytics Hub, a platform within BigQuery for secure data sharing and exchange. Analytics Hub enables organizations to build a data ecosystem where datasets are shared in-place, granting providers control and visibility into data usage.

Leveraging Analytics Hub and BigQuery's serverless architecture, BigQuery data clean rooms establish a secure environment for multi-party collaboration. Data remains in its original location, allowing participants to run queries and share aggregated results, ensuring data privacy.

Behind the scenes: the architecture

At its core, BigQuery serves as the data platform where data contributors and subscribers store their datasets. Google Cloud BigQuery is a fully managed, serverless data warehouse that enables scalable and cost-effective analysis of massive datasets. It stands out for its decoupled architecture, separating compute and storage, allowing independent scaling for optimal performance and cost efficiency. 

It leverages the concept of shared datasets from Analytics Hub, allowing the clean room owner to contribute their dataset along with specific egress and analysis rules. These rules dictate what kind of outputs are permissible from the clean room, ensuring data privacy. You can refer to the Google Cloud Documentation for a detailed understanding of the architecture.

Industry use cases

Data clean rooms are transforming businesses across industries. Let's look at a few use cases.

Use case 1: measuring new customer acquisition from digital advertising

A company runs a digital advertising campaign across various platforms to attract new customers or re-engage lapsed ones. Once the campaign concludes, the ad platform data (impressions, clicks, etc.) is brought into a data clean room.

Within this secure environment, the company can combine advertising campaign data with their own internal customer data. This allows them to match ad interactions (like clicks) with actual customer conversions. The clean room ensures that sensitive customer information remains private and is only used for aggregated analysis. The company can then see key metrics, like how many new customers were acquired through the campaign, the cost per acquisition, and the overall return on ad spend. These insights help them evaluate the campaign's success and make informed decisions for future advertising strategies.

Use case 2: retailer-CPG collaboration

When retail media networks collaborate with their consumer packaged goods (CPG) brand partners, BigQuery data clean rooms can unlock new and valuable insights. Through this collaboration, a CPG company can evaluate the effectiveness of its advertising campaigns conducted on the retailer's platform, specifically for audiences that overlap between the two entities. The CPG company gains insights into the impact of its campaigns on the retailer's platform, allowing for more informed decision-making and optimization of marketing strategies.

• CPG data: CPG offers data on their existing audience data (1p).

• Retailer data: Retailer possesses data indicating which customers made purchases.

• Data clean room: A secure and privacy-preserving environment known as the data clean room enables CPG and Retailer to match hashed customer IDs. This allows them to determine whether the targeted customers went on to purchase the advertised products.

CPG can evaluate the effectiveness of their ads and enhance their campaigns. Simultaneously, Retailer can demonstrate the worth of their advertising platform to CPG partners.

Use case 3: retailer-publisher collaboration

A retailer could collaborate with a publisher, like a streaming service. The retailer brings its loyalty data and mobile data, while the streaming service contributes its engagement data. The data clean room acts as a secure, neutral environment where these datasets can be combined and analyzed without either party directly accessing the other's raw data.

The retailer can understand the viewing habits of its loyalty program members and identify potential new customers. Meanwhile, the streaming service can gain insights into subscribers' shopping behaviors and personalize content recommendations. Both can benefit from combined data analysis, gaining competitive intelligence and identifying market trends and customer behavior across platforms.

Use case 4: retailer-manufacturer collaboration

A retailer can collaborate with a manufacturer within a data clean room by sharing its sales and inventory data, while the manufacturer shares its product data.

The combined data allows them to uncover insights and generate actionable recommendations. This can lead to optimized product assortments, strategic pricing, and targeted marketing campaigns.

Beyond marketing: internal secure collaboration

It's worth noting that data clean rooms can be used for various internal collaboration use cases, enabling organizations to leverage sensitive data across internal teams while upholding strict privacy standards. By anonymizing or pseudonymizing information, teams can collaborate effectively without compromising individual privacy.

Use cases

• HR analytics: HR departments can partner with data science teams to analyze employee data, identify trends in performance and turnover, and develop predictive models for talent retention. Data clean rooms ensure sensitive employee information remains protected throughout the analysis process.

• Employee engagement: Internal communications teams can analyze employee sentiment through surveys and social media data while preserving anonymity. This empowers organizations to understand employee perspectives and identify areas for improvement without compromising individual privacy.

Data clean rooms facilitate secure internal collaboration across various departments, enabling data-driven decision-making while safeguarding sensitive information. This fosters a culture of trust and compliance, empowering organizations to unlock the full potential of their data without compromising privacy.

So what are the actionable strategies for modern marketers?

Data clean rooms empower businesses to:

• Unlock insights: Extract actionable intelligence from data while maintaining privacy and security

• Fuel innovation: Enable data-driven decisions that enhance customer experiences and drive growth

• Foster collaboration: Break down silos and enable secure data sharing

For modern marketers, AI-powered data clean rooms are a strategic advantage. By identifying use cases, establishing data-sharing agreements, leveraging AI tools, and monitoring results, they can harness the power of data to drive their businesses forward. Read more details about how BigQuery data clean rooms work and explore the architecture. Your data team can get started today with a free trial of BigQuery.