Connect and harmonize first-party customer data from any source, with prebuilt integrations for marketing, commerce, sales, service, and more.
Define rules for matching and conflict resolution to unify millions of records into a single, complete view of every customer.
Create dynamic customer segments with first-party data to activate personalized moments with trust across the customer journey.
Personalize more effectively with native integrations to your marketing analytics and business intelligence. Find out propensity to buy, customer lifetime value, and more using no-code and pro-code AI.
Connect and automate any data into your CDP with reusable connectors, integration templates, accelerators, and API designs for Salesforce, SAP, Oracle, and more. Empower every team to create connected customer and employee experiences faster, at scale.
Empower teams to securely build integrations and automations with clicks, not code. Create new ways to connect data and personalize moments across experiences and devices.
Improve productivity by automating everyday workflows, helping teams work seamlessly together with the customer at the center.
A customer data platform (CDP) is a type of software solution that usually includes a customer database, marketing automation, multichannel campaign management, and real-time interaction management.
Data Cloud for Marketing (formerly Salesforce CDP) is an evolution of Salesforce's Customer Data Platform product — featuring a hyperscale data store that allows users to act on their data in real time and at scale.
CDPs are an evolution of traditional CRM technologies, with additional high-scale, real-time capabilities to support modern marketing use cases.
Data Cloud for Marketing (formerly Salesforce CDP) saves time and optimizes spend by connecting data from any source, enabling smarter segments and engagement, and powering automated insights.
Customers expect personalization in an omni-channel way and expect companies to know them and their preferences. CDPs unify data for a deeper understanding of every single customer.
Choosing a CDP requires an assessment of key use cases across data integration and management as well as analytics and activation.
CDPs collect and unify data into a single customer profile that updates over time and can be used in segmentation and downstream personalization.
Some benefits of leveraging a CDP include increased conversion due to tailored messaging, reduced integration and maintenance costs, and streamlined processes across teams related to data access and usage.
User-level data from across the enterprise can be ingested into a CDP.
Data from a CDP can be activated to downstream marketing solutions to inform personalized messaging across channels, trigger actions or workflows, and more.
Unified data from within the CDP allows users to build smarter segments, leading to more targeted/tailored messaging and touchpoints that are both relevant and timely for customers.
Implementation of a CDP typically involves building a business case and getting stakeholder buy-in, defining key use cases, and auditing foundational data sources to inform design and configuration/build.
The length of a CDP implementation varies on many factors, including complexity of use cases, organizational structure, and more.
Successful CDP implementations required cross-functional alignment between departments -— including marketing, technology/IT, analytics, and more, to ensure the technology can properly support business processes.
Common pitfalls related to CDP implementation include, but are not limited to, a lack of executive alignment/buy-in, clearly defined marketing or customer experience processes, and understanding of data sources and attributes.
Key factors include definition of use cases and timeline for enabling CDP capabilities, organizational/team structures that align to proposed digital transformation initiatives, and a clear change-management strategy.
The business impact of a CDP can manifest in the form of decreased IT costs (custom integration and maintenance), increases in conversion and retention due to targeted segmentation and personalized messages, and increased marketing productivity due to democratization of data access and usage.
Foundational use cases include automated engagement and personalization across marketing channels, intelligent suppression, and generated insights that allow for strategy optimization.