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Salesforce Unified Knowledge

Salesforce Unified Knowledge

Salesforce Inc. is introducing a novel feature within its Data Cloud data lake, addressing the growing need for organizations to develop their own artificial intelligence models. This new feature, termed Unified Knowledge, integrates data from various third-party sources into the Data Cloud, facilitating the collection and curation of data crucial for training AI models, particularly for customer service agents. Unified Knowledge enables the importation of unstructured data into the Data Cloud, where it undergoes transformation, tagging, and quality assurance processes. This feature, developed in collaboration with Zoomin, primarily targets the enhancement of Salesforce’s Einstein for Service customer support application. However, its data integration capabilities extend to other Salesforce applications like Sales Cloud, Health Cloud, Financial Services Cloud, and Field Service. The administrative setup process for Unified Knowledge is described as relatively straightforward. Within Salesforce’s knowledge management tool, tagging tools are available, and once content is integrated into the system, much of the content can be automatically processed. Data from external sources such as Microsoft’s SharePoint, Atlassian’s Confluence, Google Drive and YouTube, Amazon Web Services’ S3 storage, Adobe’s Experience Platform, Guru Technologies’ Guru, Zendesk’s customer service platform, and company websites can be utilized to train customer-facing answer bots, streamline employee access to internal information, and facilitate quick searches within company knowledge bases. Unified Knowledge is available in a free beta test for Salesforce customers with Service Cloud Unlimited Edition, Einstein 1 Service Edition, or the Knowledge Add-On. A freemium version of Unified Knowledge will continue to be included with those applications, with Salesforce Lightning Knowledge being a requirement and Classic Knowledge not being supported. In essence, Unified Knowledge aims to consolidate organizational knowledge from disparate third-party systems into Salesforce, thereby improving service agent efficiency, resolving customer cases faster, and enhancing the quality and accuracy of generative AI content. By Tectonic Salesforce Marketing Architect, Shannan Hearne. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Salesforce Unified Knowledge

Salesforce Unified Knowledge

Salesforce Introduces Unified Knowledge: Empowering Service Excellence with Integrated Organizational Insights Salesforce has unveiled Unified Knowledge, a groundbreaking solution designed to integrate organizational knowledge from diverse third-party systems directly into Salesforce. This innovation aims to enhance the efficiency of service agents, enabling them to resolve customer cases more swiftly and effectively. Unified Knowledge, coupled with customer data from Salesforce Data Cloud, leverages this aggregated knowledge to generate precise and personalized AI-driven content. This capability ensures faster and more tailored customer experiences. Why It Matters In today’s service landscape, 79% of organizations are investing in AI to bolster their support capabilities. However, 76% of executives face challenges in scaling AI effectively due to fragmented systems and isolated data sources. Enhancing Service with AI: Einstein for Service Built on the Einstein Trust Layer, Einstein for Service harnesses AI to elevate service team productivity and enhance customer experiences. Historically, this capability has relied on structured and unstructured customer data within Data Cloud. Unified Knowledge: Integrating Comprehensive Data Sources Unified Knowledge enriches AI models by incorporating Salesforce knowledge articles and information from external platforms such as SharePoint, Confluence, Google Drive, and corporate websites. This holistic data foundation empowers Einstein for Service with robust generative AI capabilities, ensuring agents and AI assistants deliver timely and accurate solutions. Strategic Partnership with Zoomin Powered by a strategic collaboration with Zoomin, Unified Knowledge amplifies service capabilities through: Expansion Across Salesforce Ecosystem Unified Knowledge extends beyond Service Cloud to integrate seamlessly with Salesforce Field Service, Sales Cloud, Health Cloud, and Financial Services Cloud, ensuring comprehensive data utilization across various operational domains. Salesforce Perspective “In service, enhanced knowledge and context lead to superior outcomes for both agents and customers. Unified Knowledge complements Data Cloud’s customer insights by integrating external organizational data, facilitating widespread adoption of generative AI and enabling faster, more meaningful customer engagements.” – Kishan Chetan, EVP and GM, Service Cloud Customer Reaction “Unified Knowledge enables us to deliver proactive, predictive, and preventive service to our customers. By unifying our extensive resources through a single system, our agents can swiftly provide solutions, ensuring consistent service delivery and boosting organizational productivity.” – Dharam Rai, VP, Global Customer Success & Experience, Sonos Availability Unified Knowledge is available in open beta today for Salesforce customers using Service Cloud Unlimited Edition, Einstein 1 Service Edition, or the Knowledge Add-On. Knowledge Answers in Bots will be generally available in June 2024, while Einstein Copilot for Mobile Workers and Search Answers are available now. This strategic initiative underscores Salesforce’s commitment to enhancing service excellence through integrated, AI-driven solutions that empower organizations to deliver exceptional customer experiences. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Generative AI Self-Service and Unified Knowledge

Generative AI Self-Service and Unified Knowledge

Salesforce Announces Unified Knowledge to Boost Service Efficiency and Customer Experience Salesforce has introduced Unified Knowledge, a groundbreaking solution designed to integrate organizational knowledge from various third-party systems into Salesforce. This integration aims to enhance service agents’ efficiency and expedite customer case resolutions. By leveraging customer data in Salesforce Data Cloud, Unified Knowledge helps generate accurate and relevant AI-driven content, enabling faster and more personalized customer experiences. Generative AI Self-Service and Unified Knowledge. Key Importance Detailed Insights Built on the Einstein Trust Layer, Einstein for Service uses AI to boost service team productivity and customer experience. Traditionally, these AI capabilities have relied on unstructured and structured customer data within Data Cloud. Unified Knowledge enhances these AI models by incorporating Salesforce knowledge articles and resources from third-party platforms such as SharePoint, Confluence, Google Drive, and company websites. This robust data foundation empowers Einstein for Service and its generative AI capabilities to deliver precise answers to agents and AI assistants in real time. Generative AI Self-Service and Unified Knowledge Unified Knowledge, developed through a strategic partnership with Zoomin, offers several key capabilities: In addition to Service Cloud, Unified Knowledge integrates information into Salesforce Field Service, Sales Cloud, Health Cloud, and Financial Services Cloud. Salesforce’s Perspective Kishan Chetan, EVP and GM of Service Cloud, stated, “In service, more knowledge and more context translates to better answers for agents and customers. Agents and self-serve customers already benefit from a complete customer profile with information in Data Cloud. Now, with Unified Knowledge, they also have access to all external organizational data, creating a truly comprehensive foundation to fuel both the successful adoption of generative AI and the delivery of faster, more meaningful customer experiences.” Customer Reaction Dharam Rai, VP of Global Customer Success & Experience at Sonos, commented, “Unified Knowledge is helping us deliver proactive, predictive, and preventative service to our customers. We have over 500 agents educating our customers on different aspects of our products. Now, all our resources and data points can be unified through the same system quickly, enabling our agents to provide solutions faster. Every agent can deliver consistent and repeatable service to improve customer engagement and increase organizational productivity.” Availability Unified Knowledge is available today in open beta for Salesforce customers with Service Cloud Unlimited Edition, Einstein 1 Service Edition, or the Knowledge Add-On. Knowledge Answers in Bots will be generally available in June 2024, while Einstein Copilot for Mobile Workers and Search Answers are available now. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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beyond inc leverages salesforce

Salesforce Takes Beyond Inc Beyond Personalized Shopping Experiences

Beyond, Inc., the parent company of renowned e-commerce brands such as Bed Bath and Beyond, Overstock, and Zulily, has unveiled an expanded commitment to leveraging Salesforce’s cutting-edge data and marketing solutions. Beyond Inc leverages Salesforce is to foster customer loyalty and deliver deeply personalized shopping experiences across all its brand portfolios. Beyond will now utilize Salesforce Data Cloud, powered by the Einstein 1 Platform, to unify customer data across multiple brands and enterprise data systems. This unified data will provide invaluable insights into customer behavior, preferences, and engagement patterns across Beyond’s diverse brand ecosystem. Marcus Lemonis, Executive Chairman of the Beyond, Inc. Board of Directors, underscored the company’s commitment to revolutionizing its approach to customer data management, emphasizing the importance of adopting a profit-oriented mindset and investing in customers who demonstrate a propensity for repeat purchases and loyalty. Lemonis previously implemented Salesforce solutions at Camping World Holdings. Lemonis is also the host of CNBC’s The Profit. Beyond Inc Leverages Salesforce Carlisha Robinson, Chief Customer Officer at Beyond, hailed the collaboration with Salesforce as a pivotal moment ushering in a new era of growth for the company. She emphasized the pivotal role of digital technologies in driving Beyond’s growth agenda, highlighting the company’s strategic utilization of the Einstein 1 Platform to unlock the full potential of AI and data-driven insights. Through this expanded collaboration, Beyond aims to execute personalized journeys using Salesforce Marketing Cloud, thereby increasing customer loyalty and spend across its brands. Ariel Kelman, Chief Marketing Officer at Salesforce, lauded Beyond’s adoption of Salesforce’s AI, Data Cloud, and integration technologies as instrumental in fostering deeply engaging and personalized interactions with customers. Kelman emphasized that providing personalized experiences is paramount in today’s customer-connected world, and Beyond’s initiatives will help drive revenue growth and enhance customer relationships in a whole new way. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Salesforce Data Cloud

Tracking Money Flows with Data Cloud

In the digital era, banks face a significant challenge: obtaining a clear, reliable, and accurate understanding of their customers amidst a vast amount of fragmented data spread across different systems. Tracking Money Flows with Data Cloud. Despite the abundance of data, it often fails to provide a complete or accurate narrative. Simple questions like “Did a customer’s funds remain within the bank or exit entirely?” can be surprisingly challenging to answer due to this fragmented data. This disjointed view of customer behavior obstructs banks from leveraging valuable data to make informed decisions and enhance client engagement. Data Cloud and Data Strategy The solution lies not just in the data itself but in developing a robust strategy to consolidate customer data and make it actionable. By breaking down data silos and constructing comprehensive customer profiles, banks can unlock the true potential of their information. This leads to a deeper comprehension of their clients, enabling them to make intelligent decisions that drive engagement, predict customer needs, and manage attrition risks effectively. In today’s intricate economic landscape, this data-driven approach isn’t merely advantageous—it’s essential for banks to stay competitive and achieve sustained success. Tracking Money and Money Flows with Data Cloud Consider the case of William to illustrate the impact of data analytics. William, a sophisticated investor, continuously shifted his funds seeking the best returns. This presented a challenge for his bank, whose legacy systems were ill-equipped to track his dynamic financial activities effectively. The bank’s inability to follow William’s money hindered marketing and attrition management efforts. They needed to understand if funds were truly leaving the institution or just relocating within its ecosystem. The introduction of Data Cloud transformed the bank’s capabilities. By consolidating disparate data sources, they gained real-time insights into William’s financial activities, allowing them to understand his relationship with the bank better and make more reliable attrition predictions. Armed with this knowledge, the bank personalized their approach to William, showcasing tailored offerings aligned with his financial objectives. This personalized engagement transformed their relationship from transactional to collaborative, reducing attrition risk and maximizing mutual benefit. William’s case became a model for the bank, demonstrating the power of unifying data silos to understand customers’ financial behavior comprehensively. In today’s financial environment, overcoming fragmented data is paramount. Data Cloud offers a winning solution: Harnessing the abundance of data is crucial. By leveraging tools like Data Cloud, banks can unravel the mysteries of customer behavior and optimize their operations effectively. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Salesforce OmniStudio Summer 24 Release Notes

Salesforce OmniStudio Summer 24 Release Notes

In Summer ’24, OmniStudio (when the Managed Package Runtime setting is disabled) supports features from OmniStudio for Vlocity, including filling address fields in omniscripts with Google Map data, using Salesforce private connect for HTTP actions in integration procedures, and choosing whether to merge entries within a list in an integration procedure list action. Also, DataRaptor is now Omnistudio Data Mapper. For Winter ’25 upgrades, disable New Order Save Behavior. To prepare for future releases, remove organization and profile standard objects from data mappers, remove OmniStudio components with unlocked packages, and check the impact of the date change in the ADDDAY function return. Salesforce OmniStudio Summer 24 Release Notes. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Salesforce Einstein Summer 24 Release Notes

Salesforce Einstein Summer 24 Release Notes

Supercharge your workforce efficiency with predictive and generative AI. Salesforce Einstein Summer 24 Release Notes. Rights of ALBERT EINSTEIN are used with permission of The Hebrew University of Jerusalem. Represented exclusively by Greenlight. CLOUD FEATURES RELEASE NOTE June ’24 Analytics Report Formula Generation Add Calculated Fields to Your Data Cloud Reports with Einstein Generative AI Field Service Pre-Work Brief Customize the Pre-Work Brief with Prompt Builder Flow Builder Einstein for Flow Let Einstein Build a Draft Flow for You Industries: Contracts Contracts AI Tailor Your Default and New Field Prompts for Effective Data Extraction Industries: Health Cloud Assessment Generation Automate Assessment Generation With Einstein Generative AI Industries: Net Zero Cloud ESG Reports Einstein for Net Zero Cloud Overall Salesforce Scheduler Generate Personalized Appointment Invitation Emails with Prompt Builder Sales Enablement, Relationship Selling, Sales Emails Einstein for Sales Sales Einstein Conversation Insights Einstein Conversation Insights Service Article Recommendations, Feedback Management, Work Summaries Einstein for Service Service Service Catalog Einstein for Service Catalog Einstein Features Salesforce Einstein Summer 24 Release Notes Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Summer 24 Salesforce Data Cloud Release Notes

Summer 24 Salesforce Data Cloud Release Notes

Ingest, harmonize, unify, and analyze streaming and batch data with Data Cloud. Then use that data to unlock meaningful and intelligent experiences across Customer 360 applications and beyond. Summer 24 Salesforce Data Cloud Release Notes. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Salesforce Customer 360 Data Model

Salesforce Customer 360 Data Model

Customer 360 Data Model The Salesforce Customer 360 Data Model simplifies data integration across cloud applications by providing standardized guidelines. This model allows for the creation of data lakes, generation of analytics, training of machine-learning models, and building a unified view of the customer. Organization into Subject Areas The model is organized into various subject areas, each representing a significant business activity such as customer information, product data, or engagement data. Each subject area is comprised of Data Model Objects (DMOs). A DMO is a view of your data imported into Data Cloud from data streams, insights, and other sources. DMOs use attributes (fields) to organize data in specific and meaningful ways. The term “DMO” can refer to either the Salesforce-created and managed schema for a DMO or an instance of a DMO in an organization based on that schema. Types of DMOs Multiple types of DMOs can be created and used within an organization: Data Mapping and Integration Data imported into Data Cloud must be mapped to a DMO before it can be used for segmentation, activation, analytics, or other operations. To start mapping data, add a connected data source to Data Cloud. After connecting a source, Data Cloud allows you to create mapping sets between objects and fields within it and the Customer 360 Data Model. For more detailed information about DMOs and other object types used in Data Cloud, refer to Data Objects in Data Cloud. Data Relationship Diagram The Customer 360 Data Model connects disparate data by linking DMOs through relationships. Here’s the full data relationship diagram for the Customer 360 Data Model. Subject Area Diagram For an overview of the data model, you can view the Overview Data Model on the Salesforce Architect page. To further explore this topic, review the associated Trailhead module: Customer 360 Data Model for Data Cloud. Data Model Subject Areas Learn more about the different subject areas within Data Cloud: Individual and Contact Points When using the Customer 360 Data Model, Data Cloud prepares a list of Salesforce-published objects, fields, metadata, and relationships to ensure consistency across applications and business processes. Individual and contact point objects are crucial for successful and complete data streams. For more detailed diagrams and information, visit the Salesforce Architect page and explore the related Trailhead module. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Einstein Copilot for Tableau in Public Beta

Einstein Copilot for Tableau in Public Beta

Salesforce Introduces Einstein Copilot for Tableau in Public Beta In early April, Salesforce unveiled the public beta availability of Einstein Copilot for Tableau, an innovative AI-powered assistant aimed at assisting users across various roles and functions in exploring and interacting with data within Tableau. This groundbreaking tool enables deep dives into data by leveraging Tableau’s analytical engine through natural language queries, accessing data from spreadsheets, cloud and on-premises data warehouses, and Salesforce Data Cloud. The public release of Copilot for Tableau is anticipated to be widely available to customers by summer 2024. Key Features of Einstein Copilot for Tableau Einstein Copilot for Tableau offers several features tailored to enhance user experience and streamline data exploration: Recommended Questions: The assistant automatically analyzes data and suggests relevant questions, allowing users to interact with data effortlessly without the need for specialized data analysis skills. Conversational Data Exploration: Users can iterate and refine their data exploration process seamlessly while maintaining context, enabling them to ask follow-up questions and delve deeper into insights as if they were engaging in a conversation with their data. Guided Calculation Creation: Copilot guides users through the process of creating calculations and parsing information, simplifying complex tasks such as extracting specific data elements from text fields. Enhancing Accuracy and Trust To ensure accuracy and contextual relevance, Einstein Copilot for Tableau leverages trusted company data from Data Cloud, fostering trust among users by delivering precise and relevant outputs based on internal data sources. Future Outlook Salesforce’s approach to introducing generative AI assistants for specific product types and use cases underscores the importance of function-specific training to meet users’ specific needs. As the technology matures, vendors may transition from premium license fees to consumption-based models, reflecting the evolving landscape of AI assistant technology adoption. The rollout of Einstein Copilot for Tableau represents a significant step forward in making data analysis accessible to a broader audience, reinforcing Salesforce’s commitment to innovation and customer-centric solutions in the realm of AI-powered analytics. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Data Cloud and Snowflake Bidrectional Data Sharing

Data Cloud and Snowflake Bidrectional Data Sharing

Salesforce Data Cloud and Snowflake are excited to announce that bidirectional data sharing between Snowflake, the Data Cloud company, and Salesforce Data Cloud is now generally available. In September, we introduced the ability for organizations to leverage Salesforce data directly in Snowflake via zero-ETL data sharing, enabling unified customer and business data, accelerating decision-making, and streamlining business processes. Today, we’re thrilled to share that customers can now also share Snowflake data into the Salesforce Data Cloud, using the same zero-ETL innovation to reduce friction and quickly surface powerful insights across sales, service, marketing, and commerce applications. Data Cloud and Snowflake Bidrectional Data Sharing. Data Cloud and Snowflake Bidrectional Data Sharing Enterprises generate valuable customer data within Salesforce applications, while increasingly relying on Snowflake as their preferred data platform for storing, modeling, and analyzing their full data estate. This integration between Salesforce and Snowflake minimizes friction, data latency, scale limitations, and data engineering costs associated with using these two leading platforms. The Snowflake Marketplace also offers customers the opportunity to acquire new data sets to enhance or fill gaps in their existing business data, driving innovation. By combining enterprise data and third-party data from Snowflake Marketplace with valuable customer data from Salesforce applications, organizations can unify their data and build powerful AI solutions to surface rich insights, driving superior and differentiated customer experiences. “Zero-ETL data sharing between Salesforce Data Cloud and Snowflake is game-changing. It has opened up new frontiers of data collaboration. We’re excited to see how customers are powering their customer data analytics and developing innovative AI solutions with near real-time data from Salesforce and Snowflake, generating incredible business value. Now that this integration is generally available, this kind of innovation will be broadly accessible,” says Christian Kleinerman, SVP of Product, Snowflake. Power Personalized Experiences with Salesforce and Snowflake Data sharing between Salesforce Data Cloud and Snowflake brings together holistic insights, empowering multiple customer-facing departments within any organization to create a truly robust customer 360. As Snowflake’s Chief Marketing Officer, Denise Persson, often states, a true, enterprise-wide customer 360 is the beating heart of a modern, customer-facing organization. The applicability of this integration spans various industries and unlocks new growth opportunities. For example: The bidirectional integration enables data sharing across business systems, Salesforce clouds, and operational systems, facilitating data set analysis and future action planning. This brings actionable insights and drives actions, unleashing a new level of customer experience and business productivity. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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WhatsApp Integration Brings Service and Marketing Together

WhatsApp Integration Brings Service and Marketing Together

Salesforce has announced the general availability of Unified Conversations for WhatsApp, transforming one-way marketing promotions and service requests into dynamic, two-way conversations from a single WhatsApp number. WhatsApp Integration Brings Service and Marketing Together. Now, instead of managing separate threads for promotions and support, customers can receive personalized opt-in marketing promotions and individual support all within a single WhatsApp chat. This unified approach allows companies like Agibank to leverage Salesforce data from over 900 hubs within WhatsApp to deliver personalized loan proposals, resolve issues faster, and better support customers in a single conversation. Why It Matters A significant 79% of customers expect consistent interactions across departments, and 75% prefer to communicate with brands through messaging. However, businesses often fail to meet these expectations, with disconnected experiences being a top customer frustration. Salesforce Perspective “With over two billion people using WhatsApp, Salesforce’s Unified Conversations for WhatsApp enables brands to connect with customers in a unified, trusted manner,” said Steve Hammond, EVP and GM of Salesforce Marketing Cloud. “This helps brands break down internal barriers and build stronger relationships throughout the customer journey, ensuring personalized engagement at the right time and context.” Go Deeper Unified Conversations for WhatsApp is powered by Salesforce Data Cloud, allowing companies to consolidate data into Salesforce and create a unified customer profile. This shared profile provides marketers and service agents with the relevant context to deliver trusted experiences in a single chat thread. Innovation in Action Unified Conversations for WhatsApp combines marketing and service conversations, enabling: Customer Perspective Matheus Girardi, Chief Marketing and Customer Officer at Agibank, shared, “Our customers rely on WhatsApp to engage with us. Unifying our data in Salesforce for WhatsApp has improved our user experience by personalizing loan proposals, resolving concerns, and supporting customers. Salesforce’s previous integration with WhatsApp tripled our digital sales, and we are excited to do more.” Roberto Maia, Chief Information Officer at YDUQS, added, “WhatsApp is the preferred messaging app for our students across Brazil. We look forward to utilizing Unified Conversations to better engage and serve them and convert leads faster.” Availability Unified Conversations for WhatsApp is now generally available. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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