Built with BigQuery: LiveRamp’s open approach to optimizing customer experiences

Editor’s note: The post is part of a series showcasing our partners, and their solutions, that are Built with BigQuery.

Data collaboration, the act of gathering and connecting data from various sources to unlock combined data insights, is the key to reaching, understanding, and expanding your audience. And enabling global businesses to accurately connect, unify, control, and activate data across different channels and devices will ultimately optimize customer experiences and drive better results.

LiveRamp is a leader in data collaboration, with clients that span every major industry. One of LiveRamp’s enterprise platforms, Safe Haven, helps enterprises do more with their data, and is especially valuable for brands constructing clean room environments for their partners and retail media networks. It enables four universal use cases to facilitate better customer experiences:

The core challenge: Creating accurate cross-channel marketing analytics

As brand marketers accelerate their move to the cloud, they struggle to execute media campaigns guided by data and insights. This is due to challenges in building effective cross-channel marketing analytics, which need to overcome the following hurdles:

• Lack of a common key to accurately consolidate and connect data elements and behavioral reports from different data sources that should be tied to the same consumer identity. Such a “join key” can not be a constructed internal record ID, as it must be semantically rich enough to work for both individual and household-level data across all the brand’s own prospects and customers, and across all of the brand’s partner data (e.g., data from publishers, data providers, co-marketing partners, supply-chain providers, agency teams).
• Reduced data availability from rising consumer authentication requirements makes it difficult to reach a sufficient sample volume for accurately driving recommendation and personalization engines, creating lookalikes, or for creating unbiased data inputs for incorporating into machine learning training.
• Brand restrictions on analytic operations to guard against data leaks of sensitive consumer personally-identifiable information (PII). By reducing operational access to consumer data, brands increase their data protections but decrease their data science team’s ability to discover key insights and perform cross-partner audience measurements.
• Decreased partner collaboration from using weak individual record identifiers, such as hashed emails, as the basis for record matching. Hashed emails are often produced by default by many customer data platforms (CDPs), but these identifiers are insecure due to their easy-reversibility and have limited capacity to connect the same individual and household across partners.

LiveRamp solves these challenges for marketers by building a suite of dedicated data connectivity tools and services centered on Google’s BigQuery ecosystem — with the objective of creating the ultimate open data-science environment for marketing analytics on Google Cloud.

The resulting LiveRamp Safe Haven environment is deployed, configured and customized for each client’s Google Cloud instance. The solution is scalable, secure and future-proof by being deployed alongside Google’s BigQuery ecosystem. As Google Cloud technology innovation continues, users of Safe Haven are able to naturally adopt new analytic tools and libraries enabled by BigQuery.

All personally-identifiable data in the environment is automatically processed and replaced with LiveRamp’s brand-encoded pseudonymized identifiers, known as RampIDs:

• These identifiers are derived from LiveRamp’s decades of dedicated work on consumer knowledge and device-identity knowledge graphs. LiveRamp’s identifiers represent secure people-based individual and household-level IDs that let data scientists connect audience records, transaction records, and media behavior records across publishers and platforms.
• Because these RampIDs are based on actual demographic knowledge, these identifiers can connect data sets with real person-centered accuracy and higher connectivity than solutions that rely on string matching alone.
• RampIDs are supported in Google Ads, Google’s Ads Data Hub, and hundreds of additional leading destinations including TV and Connected TV, Walled Gardens, ecommerce platforms, and all leading social and programmatic channels.

The Safe Haven data, because of its pseudonymization, presents a much safer profile for analysts working in the environment, with little risk to insider threats due to PII removal, a lockdown of data exports, transparent activity logging, and Google Cloud’s powerful encryption and role-based permissioning.

LiveRamp’s Safe Haven solutions on Google Cloud have been deployed by many leading brands globally, especially brands in retail, CPG, pharma, travel, and entertainment. Success for all of these brands is due in large part to the combination of the secure BigQuery environment and the ability to increase data connectivity with LiveRamp’s RampID ecosystem partners.

One powerful example in the CPG space is the success achieved by a large CPG client who needed to enrich their understanding of consumer product preferences, and piloted a focused effort to assess the impact of digital advertising on audience segments and their path to purchase at one large retailer.

Using Safe Haven running on BigQuery, they were able to develop powerful person-level insights, create new optimized audience segments based on actual in-store product affinities, and greatly increase their direct addressability to over a third of their regional purchasers. The net result was a remarkable 24.7% incremental lift over their previous campaigns running on Google and on Facebook.

Built with BigQuery: How Safe Haven empowers analysts and marketers

Whether you’re a marketer activating media audience segments, or a data scientist using analytics across the pseudonymized and connected data sets, LiveRamp Safe Haven delivers the power of BigQuery to either end of the marketing function.

Delivering BigQuery to data scientists and analysts

Creating and configuring an ideal environment for marketing analysts is a matter of selecting and integrating from the wealth of powerful Google and partner applications, and uniting them with common data pipelines, data schemas, and processing pipelines. An example configuration LiveRamp has used for retail analysts combines Jupyter, Tableau, Dataproc and BigQuery as shown below:

Data scientists and analysts need to work iteratively and interactively to analyze and model the LiveRamp-connected data. To do this, they have the option of using either the SQL interface through the standard BigQuery console, or for more complex tasks, they can write Python spark jobs inside a custom JupyterLab environment hosted on the same VM that utilizes a Dataproc cluster for scale.

They also need to be able to automate, schedule and monitor jobs to provide insights throughout the organization. This is solved by a combination of BigQuery scheduling (for SQL jobs) and Google Cloud Scheduler (for Python Spark jobs), both standard features of Google Cloud Platform.

Performing marketing analytics at scale utilizes the power of Google Cloud’s elasticity. LiveRamp Safe Haven is currently running on over 300 tenants workspaces deployed across multiple regions today. In total, these BigQuery instances contain more than 350,000 tables, and over 200,000 load jobs and 400,000 SQL jobs execute per month — all configured via job management within BigQuery.

Delivering BigQuery to marketers

SQL is a barrier for most marketers, and LiveRamp faced the challenge of unlocking the power of BigQuery for this key persona. The Advanced Audience Builder is one of the custom applications that LiveRamp created to address this need. It generates queries automatically and auto-executes them on a continuous schedule to help marketers examine key attributes and correlations of their most important marketing segments.

Queries are created visually off of the customers’ preferred product schema:

Location qualification, purchase criteria, time windows and many other factors can be easily selected through a series of purpose-built screens that marketers, not technical analysts, find easy to navigate and which quickly unlock the value of scalable BigQuery processing to all team members.

By involving business and marketing experts to work and contribute insights alongside the dedicated analysts, team collaboration is enhanced and project goals and handoffs are much more easily communicated across team members.

What’s next for LiveRamp and Safe Haven?

We’re excited to announce that LiveRamp was recently named Cloud Partner of the Year at Google Cloud Next 2023. This award celebrates the achievements of top partners working with Google Cloud to solve some of today's biggest challenges.

Safe Haven is the first version of LiveRamp’s identity-based platform. Version 2 of the platform, currently in development, is designed to have even more cloud-native integrations within Google Cloud. There will be more updates on the next version soon.

For more information on LiveRamp Safe Haven, visit the website here.

The Built with BigQuery advantage for ISVs and data providers

Built with BigQuery helps companies like LiveRamp build innovative applications with Google Data and AI Cloud. 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 unified AI lakehouse that’s integrated with Google Cloud’s open, secure, sustainable platform. Click here to learn more about Built with BigQuery.