Customer data platforms (CDPs) are a new type of operational data environment that ingests customer data from all sources – whether batch or streaming; first-, second-, or third-party; and structured or unstructured – that provides an always on, always updating golden record and makes it continually available at low latency to all touchpoints and users across the enterprise.
The key performance characteristics of a customer data platform includes agility, precision, scale, speed, and accessibility. RedPoint Global put together this selection guide for customer data platforms to provide organizations a way to analyze all vendors in this space based on the criteria that Forrester Research and Gartner have identified as being key capabilities that you need to have.
Forrester published a definition in November 2016 of a type of CDP they refer to as a big data fabric, which “offers enterprise architecture (EA) pros a platform that helps them discover, prepare, curate, orchestrate, and integrate data across sources by leveraging big data technologies in an automated manner.”
In the Forrester Wave – Big Data Fabric, Q4 2016, Forrester outlined four high-level criteria to access and leverage big data with a modern architecture:
➤ Delivers new actionable insights with minimal effort – Big data fabric offers the ability to aggregate, transform, cleanse, and integrate data from multiple big data sources, to deliver insights with zero to minimal coding.
➤ Secures big data end-to-end – Big data fabric enables centralized data access and control.
➤ Enables real-time integrated data across the business – Big data fabric enables data and metadata sharing between peers, employees, partners, and customers. It allows any application, process, dashboard, tool, or user to access any integrated data, regardless of where the data is physically or logically located and regardless of the data format.
➤ Delivers a self-service data platform for business users – Big data fabric emphasizes self-service data preparation, curation, orchestration, and integration services that nontechnical personnel can leverage for improved decision making.
|Forrester Criteria||RedPoint’s CDP Provides…|
|Delivers new actionable insights with minimal effort||…drag-and-drop tools that enable businesses to integrate, transform, and match data with no programming required, and has proven to save over 80 percent of the manual effort in preparing data for advanced analytics while delivering higher quality insights|
|Secures big data end-to-end||…a single customer view or golden record, underpinned by a persistent superkey and its sub-keys, is accessible across the enterprise, while providing business users the tools for master data management (MDM) so that the business is in charge of the customer data, e.g., defining the matching rules and tolerance levels to automatically de-duplicate data, and providing data stewardship and governance reeded to truly drive enterprise-wide customer engagement|
|Enables real-time integrated data across the business||…the golden record is updated in real-time, incorporates real-time identity resolution, and is accessible across the enterprise to fuel real-time analytics, next-best-actions, and customer engagement systems in real time|
|Delivers self-service data platform to business users||…data preparation, curation, orchestration, and integration services through drag-and-drop tools so that businesses are closer to the data used to drive analytic models and highly automated and personalized customer engagement; MDM capabilities also put data closer to the edge where it is used, enabling business functions to master customer data with easy to use but powerful MDM functionality|
Gartner published a report focused on CDPs in November 2016 that defines the CDP as “an integrated customer database managed by marketers that unifies a company’s customer data from online and offline channels to enable modeling and drive customer experience.” Gartner also outlined CDP selection criteria in this report, which was titled Innovation Insight for Understanding Customer Data Platforms:
➤ Identity – How is customer data linked, persisted, and refreshed? Can it do deterministic cross-device matching and probabilistic matching?
➤ Data connectors – Assess which existing tools will be supported out of the box by each CDP. Consider how data is collected, whether via APIs, server to server, uploads, or tags.
➤ Channels supported – Some CDPs integrate data from channels better than others.
➤ Data processing – CDPs should feature batch and streaming data processing and offer greater scalability and flexibility than a traditional customer database.
➤ Segmentation – Consider how the CDP handles segment discovery. Is it rule-based, or does it allow for statistical techniques, such as clustering?
➤ Predictive modeling – Most CDPs feature propensity models or lead scoring or allow analysts to incorporate their own models. Increasingly, CDPs are incorporating next-best-offer recommendations and other decision-support features.
➤ Orchestration – Marketers will generally still need execution systems for the final mile, but CDPs will support cross-channel orchestration and personalization by managing rules, instructions, and messages.
|Gartner Criteria||RedPoint’s CDP Provides…|
|Identity||…the most advanced algorithms in the market for probabilistic matching, as well as persistent key management, the ability to manage identities from unknown to known states through progressive profiles, and the ability to resolve identities at multiple levels (person, household, digital address, business, device);
RedPoint is ranked #1 for operational and transactional data quality and #1 for data integration in Gartner’s Critical Capabilities for Data Quality Tools report
|Data connectors||…hundreds of out-of-the-box connectors to ingest data from any source, whether unstructured big data from a Hadoop cluster, or traditional structured data from a relational database; a software development kit (SDK) also provides ease of implementation for any customer connectors needed|
|Channels supported||…an open garden architectural approach, so that data can be integrated from any engagement systems of record, whether proprietary or widely used third-party channels, social media networks, devices or any other touchpoint|
|Data processing||…processing of batch and streaming data, at a scale 5x-20x faster than other solutions evaluated by industry analysts, providing the ability to operate at the speed of the customer; RedPoint has compressed the time from data-to-action by up to 99 percent for high volume clients|
|Segmentation||…rules-based, clustering models and machine learning algorithms to segment the customer base, enabling enterprises to scale to a true segment-of-one while maintaining a clear point of operational control|
|Predictive modeling||…predictive models and machine learning to optimize customer decisions, with the option to ingest predictive models from an enterprise’s library, third-party libraries, or RedPoint’s library of advanced models|
|Orchestration||…the underpinning of RedPoint Customer Engagement Hub, which provides in-line analytics and intelligent orchestration to provide a single point of control over customer next-best-actions and decisions to personalize engagement across all systems of engagement|