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Customer 360 Data Model

Customer 360 Data Model

The Customer 360 Data Model simplifies the integration of data across cloud applications by providing standardized guidelines. It enables the extension of the data model for various purposes such as creating data lakes, generating analytics, training machine-learning models, and establishing a unified view of the customer. Organized into subject areas, the Customer 360 Data Model categorizes data into major business activities like customer information, product details, and engagement data. Each subject area comprises data model objects (DMOs), which serve as views of imported data from various sources such as data streams and insights. DMOs utilize attributes, or fields, to organize data in meaningful ways. They can be either standard DMOs, based on predefined schemas, or custom DMOs created directly within an organization. To utilize data imported into Data Cloud, it must be mapped to a DMO. This mapping process involves connecting a data source to Data Cloud and creating mapping sets between objects and fields within the source and the Customer 360 Data Model. The relationships between DMOs further consolidate disparate data, facilitating comprehensive analysis and utilization. The Customer 360 Data Model includes subject areas such as Case, Engagement, Loyalty, Party, Privacy, Product, and Sales Order, each serving specific organizational needs. Additionally, it encompasses individual and contact point objects, essential for complete data streams and ensuring consistency across applications and processes. Key object types within the Customer 360 Data Model include Individual, representing individuals dealt with in the system, and Contact Point objects like Email, Phone, Address, App, OTT Service, and Social handles. These objects capture essential information about individuals and their interactions. Moreover, attributes like Party Identification and Individual ID play crucial roles in data segmentation and identity resolution within Data Cloud. Individual ID Imported data customer identifiers must be mapped to the Individual ID field to drive identity resolution behavior and to receive accurate data when creating data segments. The Individual ID object is important to ensuring successful data in Data Cloud. When importing any customer information, it’s mapped to this object and remains consistent throughout the entire product. Data Cloud has a variety of data objects including data source objects (DSO), data lake objects (DLO), and data model objects (DMO). The Data Model offers a structured framework for organizing and utilizing data effectively, enabling organizations to derive actionable insights and enhance customer experiences across various applications and business processes. Tectonic is your source for Customer 360 Data Model from Salesforce. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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data cloud and marketing cloud personalization

Data Cloud and Marketing Cloud Personalization

Choosing the correct Customer Data Platform (CDP) for your organization is crucial for adapting to challenges and capitalizing on opportunities in the evolving marketing technology landscape. While AI, behavioral patterns, and infrastructure play pivotal roles in this decision-making process, it’s essential to understand the landscape. However, the same factors, including AI, behavioral habits, and infrastructure, can influence this decision. Data Cloud and Marketing Cloud Personalization together capture and utilize customer data. Selecting the right tools makes it easier to know and cater to your prospects and customers. Without them, you are firing into the darkness. You must understand the necessary infrastructure for a marketing technology team to meet challenges and leverage new opportunities. It integrates four essential AdTech (Advertising Technology) principles applicable to MarTech in the evolving landscape. The external market poses challenges, notably the discontinuation of third-party cookies by major browsers like Google. This shift impacts prospecting and underscores the significance of first-party data. The rise of AI, exemplified by technologies like ChatGPT and integrated into platforms like Salesforce’s Einstein, further complicates the landscape. The AI era raises concerns about data usage and collection, employment risks, and the ethical consideratins. Organizations rush to incorporate AI, with Salesforce introducing Einstein GPT shortly after the emergence of ChatGPT. In this dynamic environment, organizations grapple with managing diverse data sources, implementing AI/ML, and ensuring privacy. AdTech principles become imperative in MarTech for effective targeting, personalization, and measurement. The focus shifts to the role of a Customer Data Platform (CDP) within the MarTech stack. Distinguishing between Data Management Platforms (DMPs), CDPs, Data Warehouses, and Data Lakes sets the stage. The article explores three CDP types: Enterprise, Event-Based, and Real-Time Personalization. The significance of a Customer Data Platform (CDP) like Salesforce’s Data Cloud cannot be stressed enough. Bear in mind there are differences between DMPs, CDPs, Data Warehouses, and Data Lakes, each with their own use cases. And for your situation a DMP, Data Warehouse, or Data Lake might be required. Salesforce’s CDP platform undergoes scrutiny, aligning its features with AdTech principles. Read more about Tectonic’s thoughts on Data Cloud here. The CDP’s contribution to targeting, personalization, and both deterministic and probabilistic measurement is detailed. Salesforce’s Data Cloud and Marketing Cloud Personalization (Interaction Studio) emerge as solutions catering to distinct needs. In conclusion we must underscore the criticality of choosing the right CDP for organizational resilience, superior customer experiences, and addressing privacy concerns. A robust infrastructure facilitates efficient data management, collaboration, and scalability, empowering organizations to make informed decisions with AI/ML and business intelligence. #data-cloud-and-marketing-cloud-personalization Like2 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Marketing Cloud Intelligence For Data Integration

Marketing Cloud Intelligence For Data Integration

What exactly is Salesforce Datorama, now referred to as Marketing Cloud Intelligence? It is a versatile, cloud-based marketing data platform offering a suite of solutions aimed at enhancing data integration, reporting, analysis, and optimization. Marketing Cloud Intelligence For Data Integration. However, the question arises: Does Marketing Cloud Intelligence truly deliver the cloud-based Marketing Intelligence as Salesforce touts? Let’s dive into what this platform offers and dissect its capabilities without the fluff. Understanding the Platform: Salesforce’s Marketing Cloud Intelligence, formerly known as Datorama, serves as an analytics tool meticulously designed to integrate and visualize various forms of marketing performance data. It strikes a balance, catering to both analytically inclined marketers and seasoned analysts seeking to bridge data with conventional BI tools like Tableau. Flexible SaaS with Tailored Customization: Despite its Software-as-a-Service (SaaS) nature, Datorama surprises with its flexibility. It can function autonomously, handling data storage, modeling, ETL, and visualization, or seamlessly integrate with other platforms like Azure Databricks or Looker. While it accommodates numerous data use cases, its primary focus remains on Performance Marketing. Marketing Cloud Intelligence often gets misclassified as a traditional Business Intelligence or Analytics platform, but it truly excels in data management. For those contemplating its adoption, familiarity with its functionalities through resources like “Getting to Know Marketing Cloud Intelligence” or video walkthroughs is encouraged. Transition to Marketing Cloud Intelligence: The rebranding from Datorama to Marketing Cloud Intelligence was proposed in early 2022, gaining momentum recently. Despite the name change, the platform’s features and capabilities remain intact. Origins and Evolution: Originating from an Israeli-based technology firm in 2012, Datorama swiftly gained traction under the stewardship of its founders Ran Sarig, Efi Cohen, and Katrin Ribant. In 2018, Salesforce acquired Datorama, integrating it into the Marketing Cloud suite alongside Account, Engagement, Personalization, and Data Cloud platforms. However, as of February 2, 2023, the original founders and core engineering teams have moved on, possibly signaling a shift in the platform’s trajectory. Functionalities and Capabilities: Marketing Cloud Intelligence boasts robust data onboarding and connectivity features, with a rich assortment of connectors and retrieval mechanisms supporting popular data management platforms like SAP Hana, AWS, Oracle, Vertica, and SQL Server. It excels in ingesting and managing aggregated marketing performance data, with the capacity to handle event-level data as well. Pricing and Competitors: While its pricing model revolves around data row consumption and user seats, the platform may become cost-prohibitive at higher volumes. However, recent enhancements like Data Lake offer expanded row count flexibility without escalating costs. Its primary competitors include Domo, Adverity, NinjaCat, Improvado, Looker, PowerBI, and Google Data Studio. Use Cases and Industries: Marketing Cloud Intelligence serves marketers and advertisers across various industries, including communications, media, technology, healthcare, finance, manufacturing, automotive, retail, and publishing. Its versatility lies in supporting six specific marketing data use cases, ranging from building a single source of data to producing informative dashboards. Continuous Evolution: With frequent product releases, Marketing Cloud Intelligence remains dynamic, adapting to evolving market needs and technological advancements. Its commitment to enhancing analytics, visualization, connectivity, and marketplace apps ensures its relevance in the ever-changing landscape of marketing data management. Future Outlook: As Salesforce navigates the competitive analytics space, the future of Marketing Cloud Intelligence remains intriguing. While challenges like pricing pressures persist, the platform’s integration within the Marketing Cloud ecosystem and ongoing enhancements hint at a promising trajectory. Whether it evolves into a fully integrated analytics solution or retains its standalone utility, only time will tell. But one thing is certain: Salesforce’s promotion of Marketing Cloud Intelligence will continue to shape its evolution and market positioning moving forward. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. 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Salesforce Genie Announced

Salesforce Genie Announced

Salesforce Genie announced this year is an innovative data platform recently unveiled at Dreamforce 2022, heralding the world’s first real-time CRM. Genie is the driving force behind Salesforce’s entire Customer 360 platform, delivering hyper-scale, real-time data capabilities. With Genie, any business can harness the power of data to create magical customer experiences, offering seamless, personalized interactions across sales, service, marketing, and commerce. It adapts effortlessly to evolving customer needs. Consider scenarios we encounter daily: the frustration of lengthy customer support calls navigating purchase history, or the challenge of locating specific items on cluttered e-commerce websites. These situations underscore the demand for real-time updates in every customer interaction, a demand that Genie aims to fulfill. In the last 12 hours alone, the volume of stored customer data worldwide has doubled, explaining the delays in customer support. However, with Salesforce Genie, businesses can make sense of their data regardless of source, system, or channel. This unified data drives unprecedented levels of personalization, akin to magic. Salesforce Genie’s Key Features: Genie is pivotal for various industries leveraging Salesforce, like banks managing vast customer records and administrative tasks. Salesforce aims to enhance data utilization without altering existing approaches. Comparison with Salesforce CDP: Genie transcends traditional Customer Data Platforms (CDPs) by: How Genie Works: Genie ingests and stores real-time data streams at scale, integrating them seamlessly with Salesforce data. It consolidates data from diverse channels, legacy systems via MuleSoft, and proprietary data lakes through connectors. Core Pillars of Salesforce Genie: Salesforce Genie’s Extensibility: Genie partners with leading data providers such as Snowflake and Amazon SageMaker, enabling seamless integration and real-time data sharing without data movement. Unified Customer 360 Use Cases: Genie unifies data across Salesforce’s Customer 360 products for various departments: In essence, Salesforce Genie revolutionizes data integration and utilization, enabling businesses to deliver unparalleled customer experiences across all touchpoints. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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