Background and Context

A Customer Data Platform (CDP) provides a monolithic view of the customer by collecting data from various sources to provide accessibility across different systems. CDPs are becoming increasingly vital as companies look to improve customer experience, engagement and personalization. Among the different CDP types, a Composable CDP commonly referred to as Deconstructed CDP distinguishes itself as it provides the flexibility and agility to customize or even interchange the components of CDP based on specific requirements such as security, governance etc. A key construct of a CDP is the identity resolution which follows a set of rules to decide how collected data is used to create a new entity or merged to an existing one. 

Lytics’ composable CDP approach

Lytics is a next generation composable CDP that enables companies to deploy a scalable CDP around their existing data warehouse/lakes, without losing control over their customer data and without compromising security and privacy to thrive in a cookieless future by tracking and identifying customer behavior. Lytics offers reverse ETL capabilities and the ability to deploy both private instance (Single Tenant hosted SaaS ) & private cloud (deployed fully in Customers GCP project) deployments directly into your GCP Project (VPC), Lytics’ unique data-driven approach enables enterprises to improve their data pipeline by simplifying creation of unified view , increase customer engagement by personalizing experiences and advancing interactiveness and drive more effective marketing ROI as a result of delivering more value to customers. 

Challenges in Data Sharing and Clean Rooms

More and more organizations have identified the benefits of securely sharing and organizing customer data as a means to improve business performance. Critical in the use case is the need to suppress PII during the process of enrichment while fully enabling data dependent teams, such as BI (Business Intelligence), Data Analysts, and Data Scientist, to stitch and enrich the data from multiple sources, while avoiding the risk of exposing any sensitive data.

As data sharing/clean rooms go become more prevalent, a set of new challenges need to be addressed namely: 

  1. Data residing in silos across different sources needs a method for relating two disparate sets of data to each other, identifiers, enabling the creation of a single view of the customer and all related attributes. A traditional solution such as an identity matching solution using a hashed identifier in the source data and customer’s dataset can help mitigate the technical challenge. 
  2. Latencies while working with a data warehouse and exchange can directly impact the agility for business teams to make real-time decisions. It is key to minimize the latencies in long running workflows
  3. Ever changing security, compliance, and regulation requirements can create major roadblocks and drastically slow down or prevent a businesses ability to engage with their customers.
  4. Flexibility is a must. Partners, vendors, and everyone in between provide a wide variety of requirements to navigate which prevents rigid, traditional, solutions from being viable. 

Solution: Lytics on Google Cloud

Lytics chose to build on Google Cloud because of its desire to leverage the Google Data Cloud, with BigQuery at the core, to offer this necessary infrastructure and scalability which unlocks Google Cloud AI/ML capabilities for enhanced entity identification using a unique identifier to stitch a user profile, enrichment of first-party data with external sources, and ultimately highly targeted audience segments built from multiple behavioral factors and proprietary engagement based behavioral scores. In addition to BigQuery, the Lytics solution integrates with a variety of Google Cloud products including Google Cloud Pub/Sub, Google Kubernetes Engine (GKE). Also, Lytics’ First-Party Modeled Audiences is powered by Google, a one-of-a-kind solution that expands the reach of existing Google Ads audiences by accessing YouTube’s user data via a Lytics/Google proprietary API to create the Modeled Audiences using Google Tag Manager and Google Ads products.

Lytics and Google have been developing a scalable and repeatable offering for securely sharing data which utilizes Google Cloud (BigQuery) and the Lytics Platform. BigQuery’s capabilities have enabled use cases from data aggregation, data analysis, data visualization, and activation, all of which are able to be executed with extremely low-latency. Furthermore, with the introduction of Analytics Hub, Lytics is now able to offer their own Data Clean Room solution on Google Cloud for Advertisers and Media built from the collaboration including Lytics, BigQuery, and Google Cloud Analytics Hub. The Lytics Data Clean Room offers a range of features for managing and processing data, including ingestion, consolidation, enrichment, stitching, and entity resolution. This solution’s privacy centric data enablement utilizes Google’s exchange level permissions as well as leverages the ability to unify data without the necessity of exposing PII, thereby allowing customers to leverage data across their organization, while avoiding data duplication and limiting privacy risks.

Lytics Conductor’s strength is in its ability to collect and unify first-party datasets into customer profiles followed by its hosting in Google Cloud and integrating with BigQuery. The integration with BigQuery makes Lytics Conductor an ideal application to simplify and unlock data sharing by unifying and coalescing datasets that helps businesses to build or expand existing BigQuery data warehouses. 

Lytics Conductor fuels Analytics Hub to create master data Exchanges for intra and inter sharing within organizations that house hundreds of listings to focus on secure, controlled consumption of critical datasets for Partners, Parent and child brands. 

Lytics Cloud Connect, Lytics’ reverse-ETL product, closes the activation loop by easily and securely associating this new data set with individual customer profiles. This enables further segmentation and activation across hundreds of out-of-the-box, real-time integrations with mission-critical marketing tools.

The key features of the solution are:

  • Gather and aggregate data from multiple data sources
  • Construct unified customer profiles using industry-leading identity resolution capabilities
  • Develop or augment BigQuery warehouse with event and profiles synchronization by coalescing data across systems
  • Build Data exchanges and Listings using Analytics Hub in a scalable, reliable and secure manner for both internal and external Partner consumption
  • Activate segments across critical marketing channels

Solution Architecture

Below is a block diagram of how Lytics, BigQuery, and Google Cloud Analytics Hub work together to power the solution:

  1. Data sources (batch and stream) map to a pre-built schema managed by Conductor.
  2. Conductor provides a vast ecosystem of pre-built connectors and APIs unify disparate data sources into profiles, which are delivered to BigQuery. These profiles are the core foundation of first-party data to build the customer 360 view.
  3. Analytics Hub helps in creating, publishing and searching listings, which is a subset of profiles and their attributes consumable as datasets. Analytics Hub establishes a natural data flow from producer to a consumer with a low-code, no-code solution.
  4. Cloud Connect consumes the listings via its inherent ability to use standard SQL to model data for direct activation across channel tools or enrichment of unified profiles in Conductor.
  5. Conductor directly interfaces with Decision Engine to build and explore segments of unified profiles.
  6. Cloud Connect and Decision Engine allow for direct activation of either SQL based data models or audience segments.

The joint partnership between Google Cloud and Lytics has yielded a highly scalable and secure solution with tighter control of mission critical data for faster activation. The real-time streaming capability of BigQuery contributes widely to the rapid activations. The solution is more repeatable and reachable as it builds on Lytics functionality and Google Cloud infrastructure. In addition, it can be future proof In the wake of stringent privacy constraints, industry compliance standards and newer regulations. 

How Lytics and Google Cloud are Better Together

The Lytics and Google Cloud story is one of collaboration and innovation on behalf of our current and future joint customer’s. 

Built on Google Cloud, Lytics is able to leverage the power of Google processing speeds and capabilities with no technical lift from the customer. Lytics Conductor and Google Analytics hub are able to provide complementary capabilities improving data management needs on behalf of our joint customers focusing on getting maximum value out of data. In particular, the capabilities and power of Analytics Hub and BigQuery have helped decrease the time to value in complex data sharing scenarios where partnership collaboration is safe and secure and cross brand activation can be done in hours rather than days or even weeks

Lytics is a long-standing partner with Google Cloud; the Lytics platform has exclusive and total residency built on GCP. There are no retrofits to the solution described above and it is uniquely positioned to seamlessly integrate GCP features with minimal to no technical lift for our joint customers. The solution described above is available today. Google Cloud provides Lytics a means to enable forward thinking data strategies, future proofing solutions with a Privacy Forward approach to data management, unparalleled global scale and access to the greatest technical team in the industry. 

The Built with BigQuery advantage for ISVs 

Google is helping tech companies like Lytics build innovative Solutions 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, launched in April as part of the Google Data Cloud Summit. Participating companies can: 

  • Get started fast with a Google-funded, pre-configured sandbox. 
  • Accelerate product design and architecture through access to designated experts from the ISV Center of Excellence 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.