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Editor’s note: The post is part of a series showcasing our partners, and their solutions, that are Built with BigQuery.Your customers aren’t just looking for the best prices, they’re looking for better experiences, too. Personalization sets the great companies apart from the rest. But it’s a constant challenge for businesses to try and understand consumer behavior, preferences, and needs, to deliver memorable, personalized experiences. According to McKinsey, companies that are leaders in customer experience achieved more than double the revenue growth of “customer experience laggards.” And those that excel at personalization generate 40% more revenue from those activities than those that do not.Data silos create missed opportunitiesWithout access to both real-time and historical customer data, such as purchase history, browsing behavior, in-store visits or personal preferences, marketers don’t have a singular view of their customers, making it difficult to optimize marketing strategies and identify revenue growth opportunities. While most marketers have the potential to be gathering valuable customer data at the many touch points along the purchasing journey, collecting, managing and analyzing large datasets requires costly infrastructure and complex data integration processes. So, these customer insights remain trapped in data silos, leaving marketers with missed opportunities and suboptimal customer experiences.Unlock and utilize customer engagement data Bloomreach Engagement is an omnichannel marketing automation platform that leverages data analytics and machine learning to deliver personalized and relevant content. It combines data-driven personalization, content optimization, and real-time recommendations to home in on individual customers and give them a highly tailored and engaging digital experience.A core component of the platform is its Customer Data Engine (CDE). It’s responsible for gathering and managing the customer data that’s key to building these personalized experiences. The CDE allows marketers to plug in their individual data source, as well as existing data lakes and warehouses, as well as any CDP they already have, to then gain a singular view of their customers that allows for the real-time personalization to occur.Engagement comes with its own real-time data storage, but for those who want to use Engagement data outside of the platform and store it within a wider data analytics stack, there’s Engagement BigQuery (EBQ). In this data integration package, the BigQuery platform is hosted and managed by Bloomreach, providing a fully featured data warehouse experience that’s pre-populated with the full Engagement data. This provides Bloomreach Engagement users with the power of Google’s BigQuery platform and ecosystem.Specifically, it helps marketers transform customer experiences through:Seamless integration with various data sources such as websites, CRM systems, POS terminals or loyalty programs, enabling businesses to consolidate customer data into a single customer viewAdvanced marketing intelligence that provides a single source of truth for data-driven decision-making and driving business growthCloud-based infrastructure that eliminates the need for businesses to invest in and maintain their own data infrastructure, resulting in cost savingsFast data processing and analytics that enable businesses to derive valuable insights from large datasets in seconds, improving time-to-insightsMarketers accessing these capabilities through Bloomreach see a range of benefits, including improved conversion rates, customer lifetime value (CLTV), customer engagement, faster time-to-insights, flexible data integration, increased revenue, and cost savings through mitigating media waste. Multiple Bloomreach customers are exporting data through EBQ every day. The biggest value they find is in the ability to have the data available in their Business Intelligence (BI) tools, structured in the same way as in Bloomreach Engagement. Their analyst teams are then able to connect it with other data sources within the company and create a single source of truth for the entire company. It makes Bloomreach data more accessible to the whole organization, with everyone being able to access reports and high-level data to make data-driven business decisions every day. And this impact is felt outside of marketing, as important business metrics such as average order amounts, return rates, customer churn, and more, are valuable for many other teams, e.g., customer service, logistics, sales, and operations.Better Together: Bloomreach Engagement and BigQuery Bloomreach Engagement's advanced personalization and marketing automation capabilities deliver hyper-personalized customer experiences powered by Google Cloud technologies, including BigQuery, smoothly integrating into the Bloomreach Engagement environment. Bloomreach EBQ synchronizes data collecting and processing through Bloomreach Engagement with a dedicated instance of the secure, highly scalable BigQuery data warehouse analytics that’s fully managed by Bloomreach for each customer. Through EBQ, data scientists and analysts have access to comprehensive data about their customers and the full power of the BigQuery platform, including the built-in, easy-to-use and scalable machine learning capabilities from BigQuery ML. Through this, they are able to gain a deeper understanding of customer behavior, preferences, and engagement patterns that inform business decisions and strategies that can be activated by Bloomreach Engagement. Together, Bloomreach Engagement and BigQuery are empowering businesses to leverage customer data and unlock insights to improve customer experiences and boost revenue.To see how Bloomreach Engagement works for yourself, book a demo. If you want to find more information about Bloomreach Engagement, visit the Bloomreach website to discover all the ways we can help you grow.The Built with BigQuery advantage for ISVs and data providersGoogle is helping companies like Bloomreach build innovative applications on Google’s data cloud with simplified access to technology, helpful and dedicated engineering support, and joint go-to-market programs through the Built with BigQuery initiative. Participating companies can: Accelerate product design and architecture through access to designated experts who can provide insight into key use cases, architectural patterns, and best practices. Amplify success with joint marketing programs to drive awareness, generate demand, and increase adoption.BigQuery gives ISVs the advantage of a powerful, highly scalable data warehouse that’s integrated with Google Cloud’s open, secure, sustainable platform. And with a huge partner ecosystem and support for multi-cloud, open source tools and APIs, Google provides technology companies the portability and extensibility they need to avoid data lock-in.Click here to learn more about Built with BigQuery.
Analysis Summary
# Industry News: Bloomreach and Google Cloud Partner to Deepen Data Integration via "Engagement BigQuery"
## Summary
Omnichannel marketing platform Bloomreach has deepened its integration with Google Cloud through the "Built with BigQuery" initiative, launching Engagement BigQuery (EBQ). The solution allows enterprises to unify siloed customer data into a single source of truth, enabling real-time personalization and advanced machine learning analytics.
## Key Details
- **Date:** September 18, 2023
- **Companies Involved:** Bloomreach (Marketing Automation) and Google Cloud (Data Analytics)
- **Category:** Product Launch / Strategic Partnership
## The Story
Bloomreach has integrated its Customer Data Engine (CDE) directly with Google BigQuery to address the persistent challenge of "data silos" in the marketing sector. While Bloomreach provides the execution layer for omnichannel marketing, many enterprises struggle to export that data into broader business intelligence (BI) stacks for deeper analysis.
The new Engagement BigQuery (EBQ) offering provides a fully managed, pre-populated data warehouse experience. By hosting a dedicated BigQuery instance for each customer, Bloomreach allows marketing teams to synchronize real-time engagement data with historical datasets (CRM, POS, loyalty programs) without the overhead of maintaining their own infrastructure. This integration specifically leverages BigQuery ML, allowing data scientists to build predictive models regarding customer behavior directly on the platform where the data resides.
## Business Impact
### For the Companies Involved
- **Bloomreach:** Strengthens its "stickiness" by becoming a central hub for business intelligence beyond just marketing execution.
- **Google Cloud:** Expands the footprint of its "Built with BigQuery" ecosystem, capturing high-velocity marketing data and driving consumption of its BigQuery ML and analytics services.
### For Competitors
- Competitors in the Customer Data Platform (CDP) and Marketing Automation space (such as Adobe or Salesforce) face increased pressure to provide similarly seamless, low-latency integrations with cloud data warehouses to prevent customer churn to the Google/Bloomreach ecosystem.
### For Customers
- **Marketers:** Gain a "singular view" of the customer, reducing media waste and increasing conversion rates through better personalization.
- **Data Analysts:** Benefit from consistent data structures between the marketing platform and BI tools, reducing the time spent on ETL (Extract, Transform, Load) processes.
### For the Market
- This reflects the "Composite CDP" trend, where companies move away from monolithic, proprietary data silos toward open data architectures that reside in centralized cloud warehouses.
## Technical Implications
The solution utilizes "Built with BigQuery" architectural patterns, allowing for fast data processing and the use of BigQuery ML. By managing the instance for the customer, Bloomreach eliminates the technical barrier of complex data integration pipelines, offering a "plug-and-play" data warehouse.
## Strategic Analysis
- **Market Positioning:** Bloomreach is positioning itself as a data-first platform rather than a simple messaging tool, moving up the value chain into the enterprise analytics space.
- **Competitive Advantage:** The use of Google’s "Built with BigQuery" badge provides a stamp of scalability and security, which is critical for handling sensitive consumer data.
- **Challenges:** Organizations must still navigate the internal politics of data ownership between Marketing, IT, and specialized Data teams to fully realize the "single source of truth."
## Industry Reactions
- **Analyst Opinions:** Analysts (citing McKinsey) highlight that personalization leaders grow revenue 40% faster than laggards, validating the strategic necessity of this integration.
- **Market Response:** High adoption is reported among existing Bloomreach customers who require their marketing data to be accessible for non-marketing functions like logistics and sales.
## Future Outlook
- **Predictions:** Expect more ISVs (Independent Software Vendors) to follow this "Managed Data Warehouse" model, where the vendor manages the cloud infrastructure on behalf of the client to reduce friction.
- **What to watch for:** Increased use of generative AI and warehouse-native ML models to automate the creation of personalized marketing content based on the unified data in EBQ.
## For Security Professionals
From a cybersecurity and governance perspective, this move consolidates the attack surface by reducing the need for multiple data transfers between disparate systems. However, security practitioners should note:
1. **Third-Party Risk:** Bloomreach is managing a dedicated BigQuery instance for the customer; this requires a review of their managed service security controls.
2. **Data Residency:** As data is synchronized across Bloomreach and Google Cloud, teams must ensure compliance with regional regulations (GDPR/CCPA) regarding where customer data is stored and processed.
3. **Identity & Access Management (IAM):** With high-level data becoming "accessible to the whole organization," granular IAM policies will be required to prevent unauthorized access to PII (Personally Identifiable Information).