Take A Tour: Treasure Data CDP Technology

Get access to more than 400 out-of-the-box integrations to work with your existing tech stack. Our CDP integrates with virtually any system using API, JDBC, ODBC, batch, and more.

Integrations span stream and batch data collection, native integration with external BI, analytics, modeling, measurement and reporting tools, and external marketing execution and customer experience interaction tools.

You can also transfer your data through SFTP, S3, or a raw data upload.

Want to build your own integration? We provide a custom scripting environment where you can script your own custom integration.

Treasure Data CDP is a managed cloud-based SaaS data platform. We use AWS data centers, giving you the option to select which region will host your data.

Our proprietary database is columnar, achieving high compression rates that make our data storage more cost-effective and suitable for reading large volumes of data.

There are no data storage limits, and you can customize your data retention policy. You also have complete control over when to delete or move your data to external systems.

With Treasure Data CDP, there are no barriers to the type of data ingested. Offline, online, batch, or true real-time streaming data, we provide an extensive framework for data integration that supports a range of website, mobile, and application SDKs and data connectivity with S3, SFTP, and database systems.

Our CDP uses a schemaless approach to data ingestion. It supports structured, semi-structured, and unstructured data types and reduces the coding and maintenance required to build and maintain schema and data pipelines.

Once your data is ingested into the platform, a series of automated workflows run to ensure the data is clean and consistent.

Data cleaning and normalization can include string clean-up, fuzzy matching, PII and third-party validation, and data quality report card.

Build repeatable, end-to-end data pipelines, securely transferring data across systems. Run SQL analysis across your data and share the insights. Create workflows that query your customer data and manage complex tasks that support audience identification, profiling, and tracking.

Use policy-based access control to control access at a granular level. Admins can set read or write permissions across platform features, such as user-defined workflows, databases, segment configuration, segments, and segment folders.

All policies can be applied to multiple sets of users in bulk.

We also support multi-brands and multi-organizations with best-in-class security features. Control data access using role-based permissions applied by brand, company, territory, products, or privacy policy.

The CDP provides data masking to protect sensitive data and comprehensive auditing that includes security/privacy alerts and notifications. Data is transferred securely across systems and encrypted at rest in Treasure Data storage.

Leverage second and third-party data to enrich your existing customer profiles. This data, including demographic, social, purchase, psychographic, intent, behavioral, and location data, comes via a vast ecosystem of partners and data providers or custom datasets.

As part of our identity resolution process, we provide proprietary data hygiene. Or get data hygiene and normalizing services through pre-built integrations with best-of-breed third-party data providers, such as Acxiom, LiveRamp, Allant, and Mapbox.

We also support compliant data sharing for those who want to create partnerships to share data, find ways to build scale and enable activation.

Treasure Data enables users to build actionable audiences with drag-and-drop, intuitive rules across customer attributes, real-time behaviors, predictive scores, and segment memberships. In-app analytics offer insights into segment makeup and reach, and help guide customer journeys.

We use server-side cookie identifiers for pseudonymous audience building, unifying interactions across devices. Upon identification, anonymous data and historical data become linked to named identities. Partnerships with third-party data providers such as LiveRamp, Tapad, and Trade Desk help enhance addressability.

For both anonymous and customer audiences, create segments with common rules and use built-in predictive propensity modeling to enrich profiles. Auto-segmentation groups similar profiles based on behavior and attribute data. Or use your own ML models, leveraging scores in segmentation and activation.

You can schedule and automate activations for each channel.

Use AI and ML models out of the box, including Content Affinity, Next Best Action, Look-alike, CLTV Prediction, and more, to drive value from your data.

Data scientists, analysts and data engineers can implement ML models through application SDKs using a range of external tool connectors, including Hivemall, Spark, Python, R, and SQL implementations. Or use custom scripting using any Python package.

Teams can also run predictive modeling in third-party providers like Databricks, importing the model scores into the CDP at the profile level for use in segmentation and analytics.

Assess consumer behaviors and customer journeys using a robust set of analytics, exploration, and visualization tools, including Predictive Scoring, Segment Insights, and Content Affinity. There’s also a solutions library packed with pre-built code, components, and visualizations. 

Use ML to prescribe Next Best Action, Next Best Product, Next Best Channel, Next Best and Contact Day & Time. Or identify Predictive Churn or Propensity to Buy scores that you can use for segmentation and activation in ML models and real time.

Improve marketing ROI by better understanding campaign effectiveness and constantly improving your campaigns. Track activity in multiple ways, including UTM parameters, referrer, pixel tracking, and connectors, ensuring the most up-to-date information for customers.

Treasure Data provides a library of dashboards, including templates for campaign attribution analytics with customizable attribution logic.

Or integrate with external BI and reporting tools, such as Tableau and PowerBI.