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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 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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marketing growth channels in 2022

Marketing Growth Channels in 2022

In their quest for multichannel engagement, marketers are integrating push and mobile messaging alongside email campaigns. Despite these additions, email marketing remains the predominant player. According to Salesforce Marketing Cloud product data, which draws from trillions of message sends, email usage has seen a year-over-year increase, comprising 80% of all outbound messaging. Additionally, the volume of outbound emails has surged by 15% in the past year. Customers affirm the enduring effectiveness of email, ranking it among their preferred channels to interact with brands, second only to the phone. Email maintains an 84% usage share, surpassing push and SMS marketing. Marketing Growth Channels in 2022. Amidst evolving customer expectations, marketers face increased challenges, with 71% expressing that meeting these expectations is more difficult than a year ago. For marketers, personalization extends beyond targeted messaging to encompass a hyper-personal understanding of individual needs. Recent research reveals that 73% of customers expect companies to comprehend their unique needs and expectations. In response, 83% of marketers leverage dynamic customer insights to tailor their strategies and enhance the impact of each interaction. Regardless of their approach to a multichannel strategy, marketers are dedicated to delivering exceptional customer experiences, with high-performing marketers taking this commitment seriously. A notable 82% of high-performing marketers identify customer experience as a key competitive differentiator, expressing confidence in their progress towards deciphering the code. Furthermore, 86% of high-performing marketers engage with customers in real time across multiple channels, showcasing their proficiency in unlocking actionable data. Marketing Growth Channels in 2022. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more

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Salesforce Data Cloud

Salesforce Data Cloud vs Snowflake

A Comprehensive Comparison In the today’s data-driven world, businesses increasingly turn to cloud-based data platforms for managing, analyzing, and deriving insights from their customer data. Among the prominent options available, Salesforce Data Cloud and Snowflake stand out from the crowd. While both platforms offer robust capabilities, they exhibit distinct strengths and weaknesses. This insight looks into the comparison of Salesforce Data Cloud vs Snowflake. Salesforce Data Cloud: Salesforce Data Cloud is a hyperscale customer data platform (CDP) designed to help businesses consolidate all their customer data, including engagement data sourced externally. It establishes a unified view of the customer, empowering businesses to personalize experiences, enhance decision-making, and foster growth. Snowflake: Snowflake is a cloud-based data warehousing platform that facilitates the storage, analysis, and sharing of data for businesses. It encompasses a wide array of features, including an awesome SQL engine, elastic scalability, and compatibility with various data sources. Salesforce Data Cloud vs Snowflake Feature Salesforce Data Cloud Snowflake Focus Customer data General data Strengths Data enrichment, personalization, real-time updates Scalability, analytics, SQL support Weaknesses Less flexible than Snowflake, limited analytics capabilities Not as user-friendly as Salesforce Data Cloud Pricing Based on data volume Based on usage The ideal platform for you will be contingent on your specific needs and requirements. If your primary focus is on managing customer data and enhancing customer engagement, Salesforce Data Cloud proves to be a suitable option. On the other hand, if you require a more versatile data platform capable of handling a broad range of data types and workloads, Snowflake emerges as a better choice. Additional considerations include: Ultimately, the most effective way to determine the right platform for you is to experiment with both and assess which one aligns better with your preferences. Contact Tectonic today to explore Data Cloud and Snowflake for your data needs. Like2 Related Posts Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

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Salesforce Logo

Spring ’24 Enhancements to Salesforce Analytics, Data Cloud, Einstein, and Net Zero Cloud

Discover the Spring ’24 Enhancements to Analytics Data Cloud Einstein and Net Zero Cloud Enhancements to Salesforce Analytics, Data Cloud, Einstein, and Net Zero Cloud in Spring’24. Reports and Dashboards for Data Cloud Enhancements Analytics Create custom report types, more core semantics, calculated insights, and date and time formulas. Analytics Collection Components Analytics Curate related analytics assets for better organization and easier consumption. Embed a specific collection directly into Lightning pages to easily access the insights you need right in your workflow. Enhanced Dashboard Customization Analytics Easily create and remember custom colors for widgets. Save hours in development time by applying layouts and colors to all widgets in a dashboard with just a few clicks. Revenue Intelligence Enhancements Analytics A new streamlined setup helps you get started even faster, and a library of KPI components lets you further customize Forecast Insights. To better understand conversation rates, use the new Win Rate Funnel view. Data Graphs Data Cloud Combine multiple data model objects and calculated insights into a unified view. New Profile API improves query performance to power near real-time use cases across Customer 360. Bring Your Own Lake with Snowflake Data Cloud Share data between Data Cloud and Snowflake with zero-ETL. With Data Federation, you can now share your data bidirectionally and access Snowflake datasets in Salesforce to enrich your unified customer profiles and unlock new insights. Bring Your Own Lake with Google BigQuery Data Cloud Share data between Data Cloud and Google BigQuery with zero-ETL. With seamless data access, you can enrich your unified customer profiles with BigQuery datasets, helping you unlock new insights and better power your Google Analytics and AI models. Streaming Data Ingest for Salesforce CRM Connector Data Cloud Ingest changes to Salesforce standard and custom objects in near real-time with streaming data ingest for the Salesforce CRM Connector. Now, existing batch ingestion checks for more frequent updates to your Salesforce objects. Einstein Copilot Einstein Embed Einstein Copilot—a conversational AI assistant—across all Salesforce applications to help teams be more productive. Automate steps or tasks with out-of-the-box actions, or create custom actions that call flows, Apex, or MuleSoft APIs. Prompt Builder Einstein Create, test, and refine prompt templates easily without code. Ground prompts with dynamic CRM data, including merge fields and flows. Invoke prompted workflows across the Einstein 1 Platform through Flow, Lightning Web Components, and Apex. ESG (Environmental, Social, and Governance) Disclosure Authoring with Generative AI Net Zero Cloud Use Einstein to generate more efficient Corporate Sustainability Reporting Directive (CSRD), Global Reporting Initiative (GRI), and Carbon Disclosure Project (CDP) reports. Einstein can access and use the internal information you’ve uploaded to Net Zero Cloud to write and answer specific questions required for these reporting standards. Disclosure and Compliance Hub Plugin for Microsoft Word Net Zero Cloud Net Zero Cloud now provides sustainability managers more flexibility to support multiple authoring formats using Microsoft Word Office 365. Multiuser collaboration, easy navigation, and rich text support create a cleaner and easier experience. Marginal Abatement Cost Visualizations Net Zero Cloud With marginal abatement cost visualizations, customers can gain insights into required investments for various programs and forecast future emissions based on the cost to offset carbon. Sustainability Program Visualizations Net Zero Cloud Visualize the combined effects of multiple environmental, social, and corporate governance (ESG) initiatives and gain a deeper understanding into different ESG projects and specific metrics within these projects. Improved Emissions Factors Management Net Zero Cloud Automatically integrate emissions factors from Net Zero Marketplace into Net Zero Cloud to easily manage and apply the data, for improved transparency and visibility in one location. Stay tuned to Tectonic’s Insights for more details and news from Salesforce. Enhancements to Salesforce Analytics, Data Cloud, Einstein, and Net Zero Cloud. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce Einstein Copilot

What’s Included in Einstein Copilot Studio?

Christmas came early this year with Salesforce’s announcement of Einstein Copilot Studio. Einstein Copilot Studio will encompass the following features: By Tectonic’s Salesforce Marketing Consultant, Shannan Hearne Like1 Related Posts Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Sales Cloud Einstein Forecasting Salesforce, the global leader in CRM, recently unveiled the next generation of Sales Cloud Einstein, Sales Cloud Einstein Forecasting, incorporating Read more

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Salesforce Copilot

Spring ’24 Release in Salesforce Einstein and Data Cloud

Revolutionizing Data Management with Salesforce’s Einstein and Data Cloud While Artificial Intelligence (AI) has taken the spotlight, there’s an unsung hero eagerly waiting for its moment – Salesforce’s Data Cloud, formerly known as Genie. This product, a source of pride for Salesforce, is set to play a crucial role in powering AI on the Einstein 1 platform, offering a glimpse into the future at World Tour New York, accompanied by some exciting updates. Salesforce Einstein and Data Cloud appear to be in for a makeover. Spring ‘24 Release Highlights: The anticipation for Einstein Copilot & Search, part of the Einstein GPT products, is set to end in February 2024. Additionally, Data Cloud’s unstructured support will enter its pilot phase in the same month. While there are no indications of new AI products in the upcoming Salesforce Spring ‘24 release, the main release dates in February raise expectations for potential surprises when the Spring ‘24 Release Notes are unveiled. Salesforce may have Salesforce Einstein and Data Cloud enhancements up their sleeves. Elevating Einstein 1 Platform: Salesforce unveiled a major update to the Einstein 1 platform at World Tour New York, combining the prowess of Data Cloud and AI. This alliance empowers users to manage unstructured data efficiently through Data Cloud. While enabling Einstein Copilot to search, retrieve, and comprehend vast amounts of information seamlessly. According to IDC, 90% of business data is unstructured, including PDFs, emails, social media posts, and audio files. Forrester predicts that the volume of unstructured data managed by enterprises will double by 2024. Which is just around the corner, folks. The GenAI solution addresses the need to sift through this unstructured data. GenAI is offering a comprehensive platform for organizations. Key Benefits for Organizations of Salesforce Einstein and Data Cloud: This innovative offering by Salesforce, integrated into Data Cloud, requires the use of a Vector Database provided by Salesforce. Familiar automation tools like Flow and Apex can be employed to monitor changes in this data. Additionally it can trigger workflows. Data Cloud Vector Databases – A Closer Look: Salesforce’s Data Cloud, in conjunction with AI capabilities, largely will transform how organizations manage and leverage unstructured data. Thereby opening new possibilities for innovation and customer satisfaction. The age of Salesforce Einstein and Data Cloud are upon us! Contact Tectonic today to learn more about Data Cloud. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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How Good is Our Data

How Data Cloud and Salesforce Success Depend on Data Quality

Optimizing AI’s Impact on Your Business: The Crucial Role of Data Quality in Salesforce In the ever-evolving digital landscape, the convergence of data quality and artificial intelligence (AI) is a linchpin for organizational success. Success depends on data quality within the Salesforce ecosystem. The synergy between Einstein, an advanced AI system, and Data Cloud underscores the pivotal role of high-quality, comprehensive, and real-time data. Thereby unleashing the full potential of AI-driven insights and interactions with customers and prospects. Let’s explore how data quality profoundly influences these two emerging features. This insight will be shedding light on the repercussions of poor data quality and how Einstein and Data Cloud can elevate your organization to greater levels of sales success. Understanding Data Value Depends on Data Quality: Quality data extends beyond merely addressing duplicate records or inaccurate phone numbers It isn’t just about ensuring the area code field doesn’t contain zip codes. It is more than aligning contacts to accounts. It encompasses factors such as completeness, accuracy, and timeliness in your CRM: Consequences of Bad Data: Poor-quality data leads to inefficiencies and wasted time. Oftentimes causing flawed decision-making and strains on organizational resources. More critically, these poor business decisions often lead to tangible financial losses.  Transforming bad data into quality data is imperative. Quality is key for relying on it to enhance company performance, requiring ongoing strategies rather than a one-stop solution. The Financial Impact of Accurate Data: Accurate data holds immense value. With data volumes projected to exceed 180 zettabytes by 2025, organizations must harness the power of their data. Proactive handling of data quality not only ensures higher data quality but also mitigates the financial impact of poor data quality. The sooner a plan is implemented to enhance and sustain data quality, the fewer negative repercussions organizations face in leveraging their data for growth.  Your next decision is based on your last data.  Is it going to help you or hurt you? Salesforce Einstein and the GIGO Principle: Salesforce Einstein, positioned as Artificial Intelligence for everyone, underscores trust as a core value. The system’s ability to create relevant and timely content and interactions is contingent on the quality of the data it operates on. Similar to the historical concept of “Garbage In, Garbage Out” (GIGO), AI results are only as reliable and valuable as the completeness and accuracy of the input data. No surprise, right? Introduction to Salesforce Data Cloud: Enter Salesforce Data Cloud, a platform allowing the organization and segmentation of customer data from any source. This open, extensible platform enables data enrichment from various sources, creating an optimal customer record. This enriched record empowers Sales, Service, and Marketing teams to perform intelligently and swiftly, ultimately driving enhanced results for the company. The WIIFM Factor: Amidst discussions about AI and Data Cloud, addressing the “What’s in it for me?” (WIIFM) question is crucial for organization adoption. Individual organizations must evaluate the reliability and accuracy of their data and determine forward-looking strategies for maintaining quality data, regardless of the source. The common theme remains: for data to yield valuable insights, it must be complete, timely, relevant, and accurate. Ultimately, success depends on data quality. Like2 Related Posts Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more

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Salesforce CDP

Utilizing a CDP

In the current digital landscape, customer data stands as a pivotal asset for organizations aiming to craft personalized and targeted experiences. Yet, the primary challenge for utilizing a CDP lies in the aggregation and consolidation of this data, often dispersed across a multitude of sources. This is where the significance of Customer Data Platforms (CDPs) becomes evident. Configured for optimal use, your data is good to go. A CDP functions as a software system that integrates customer data from various sources, encompassing marketing automation, AdTech, commerce, service, analytics, procurement, production, logistics, compliance, and more. The consolidated data is housed within a unified platform for analysis and marketing purposes. By serving as a single source of truth, CDPs empower organizations to create more pertinent, real-time, contextual, and compliant experiences for their customers. Operating as a connector within existing tech stacks, CDPs play a crucial role in filtering and binding siloed and fragmented customer data from diverse teams. This results in actionable insights, more profitable interactions, and a foundation for the growth of customer value. CDPs extend their utility beyond marketing, offering advantages to sectors like healthcare, where they can unify patient data, eliminate data silos, and furnish timely information to enhance patient outcomes. By addressing prevalent challenges such as unconnected data, non-optimized work efforts, operational inefficiencies, and encumbered time-to-market, CDPs prove instrumental in fostering organizational success. It’s important to highlight that a CDP is not a substitute for a CRM solution, especially in large enterprise settings. Integration with critical data-source systems beyond the martech stack is essential for extracting hidden value from the organization’s data. Utilizing a CDP As the digital marketing industry navigates the transition to a cookieless future, and first-party data takes precedence, the value of CDPs is set to grow. However, to unlock their full potential, the adoption of CDPs should extend beyond marketers. CDPs must evolve into interconnected sources of truth across all departments and interactions, both physical and digital. By functioning as cohesive data aggregators, they enable organizations to harness vast volumes of customer-impacting data and insights, delivering optimized, hyper-personalized, and differentiating experiences. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Data Quality A Challenge and A Priority

Data Quality A Challenge and A Priority

Data accuracy — and confidence in data accuracy — is a key component of trusted data. This makes Data Quality A Challenge and A Priority. Departments closest to the data, like data and analytics teams, have the highest confidence in their data accuracy. Confidence among line-of-business leaders is lower, revealing an opportunity to instill data confidence across marketing, sales, and service teams. 57% of data and analytics leaders have complete confidence in their data’s accuracy. Overall, there is room for improvement. Increased tracking of critical metrics, such as data quality, data utilization, data management and costs, data services delivery, and the ROI of data initiatives, could be one giant leap forward in making such an improvement. Surging Data Overwhelms Users — And Poses an Opportunity Business leaders’ second biggest data challenge, dealing with overwhelming volumes of data, shows no signs of abating. Over two-thirds of analytics and IT leaders expect data volumes to increase 22% on average over the next year. They expect similar growth rates across a variety of sources including third-party data and device data. For data leaders, increasing and diverse data sources require more effort to standardize data. This is likely to worsen a major challenge for analytics and IT leaders: lack of data harmonization (i.e., standardizing data from different sources). Overcoming this challenge presents an opportunity for differentiation. Almost two-thirds (65%) of customers say they expect companies to adapt experiences to match their changing needs, yet 80% of business leaders say personalization is difficult to scale. For companies looking to serve more tailored experiences, mature data management capabilities are a key competitive advantage. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Slack and AI

Just When You Thought We Were GPT’d Out, Here Comes Slack and Generative AI

Since its public introduction in 2014, Slack has transformed from its original concept, a searchable log of all conversation and knowledge, into a comprehensive productivity platform that has reshaped how work and co-working is conducted. Get ready! Here comes Slack and Generative AI! In a recent release, Salesforce Slack unveiled a next-generation platform. A platform designed to facilitate seamless automation and integration for users of all technical levels, regardless of coding proficiency. This platform simplifies the utilization of data within Slack, offering enhanced automation and intelligence, allowing for the creation of no-code workflows, custom integrations, and the incorporation of generative AI. Steve Wood, Slack’s SVP of Product and Platform, highlights the significance of placing automation and generative AI tools directly into users’ hands as a pivotal step in Slack’s journey to redefine not only how people work but also how machines and humans interact in the future. Wood delves into the unique features of the new Slack platform, emphasizing its modular architecture grounded in building blocks like functions, triggers, and workflows. These components are remixable, reusable, and seamlessly integrate with the data flow within Slack. The platform enables developers to create tailored solutions, such as integrating with Salesforce, fostering more efficient collaboration, and automating workflows across various business functions. The introduction of generative AI, like Slack GPT, further enhances the platform’s capabilities.  Slack GPT can use Einstein GPT to gain actionable data from Salesforce Customer 360 and Data Cloud.  Wood underscores the potential of this combination to revolutionize work interactions by simplifying automation into reusable building blocks, accessible to both humans and machines. He emphasizes the transformative power of pairing data with AI and automation, anticipating a significant shift in how technology is leveraged in the workplace. Slack and GPT Wood also explains the recent Slack GPT news, detailing its native integration into the Slack user experience. Slack GPT brings generative AI directly into the platform, allowing users to summarize conversations, catch up on missed messages, and edit content effortlessly. The integration of Einstein GPT into Slack expands the conversational interface to Customer 360, providing real-time customer insights directly in Slack. This can be used to automatically generate case summaries based on data from Service Cloud AND Slack. As AI evolves over time, Wood shares his excitement about observing how people utilize Slack GPT in real-world scenarios. The focus remains on empowering platform users through native generative AI and leveraging data and behaviors to enhance the product continuously. Historical Content Wood emphasizes the historical context stored within Slack, highlighting the collective past as a valuable resource for future decision-making. Integrating AI technologies into this rich dataset within Slack presents a substantial opportunity for improving workflows and tools. Regarding the integration of Slack with Salesforce Customer 360, Wood stresses the importance of having relevant information easily accessible in one place. Slack serves as the hub where work occurs, and by incorporating generative AI, the platform aims to enhance transparency, alignment, and effectiveness in decision-making. Drawing in and analyzing the data from Slack as well as the other Salesforce platforms provides vital customer information. In reflection on the rapid adoption of this technology, Wood acknowledges the unique challenges presented by the unknown behavior of generative AI. Stability, accuracy, and safety are top concerns, with ethical and responsible development practices crucial for building trust. The future, as Wood sees it, hinges on maintaining a commitment to ethical development, ensuring customers feel confident in trusting the transformative capabilities of generative AI in the workplace and the Slack platform. Like1 Related Posts CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Integration of Salesforce Sales Cloud to Google Analytics 360 Announced In November 2017, Google unveiled a groundbreaking partnership with Salesforce, outlining their commitment to develop innovative integrations between Google Analytics Read more

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Salesforce Data Cloud

Salesforce Data Cloud Explained

Salesforce Data Cloud, previously recognized as Salesforce CDP/Genie, made its debut at Dreamforce 2022, hailed by Salesforce as one of the most significant innovations in the company’s history. A hyperscale data platform built into Salesforce. Activate all your customer data across Salesforce applications with Data Cloud. Data Cloud facilitates the intake and storage of real-time data streams on a massive scale, empowering automated tasks that result in highly personalized experiences. Data can be sourced from diverse Salesforce data outlets, including Mulesoft, Marketing Cloud, and others, along with customers’ proprietary applications and data sources. Subsequently, it can dynamically respond to this real-time data by automating actions across Salesforce CRM, Marketing Cloud, Commerce, and more, inclusive of automating actions through Salesforce Flow. What is the Salesforce data cloud? Data Cloud is the fastest growing organically built product in Salesforce’s history (i.e. Salesforce built it themselves, not via acquisitions). Data Cloud could be described as the ‘Holy Grail of CRM’, meaning that the data problem that’s existed since the infancy of CRM is now finally solvable. Data Cloud is the foundation that speeds up the connectivity between different ‘clouds’ across the platform. However, Data Cloud is also a product that can be purchased. While not all Salesforce customers have licensed Data Cloud, being at the foundation means they are still taking advantage of Data Cloud to a degree – but this all becomes even stronger with Data Cloud as a personalization and data unification platform. What is the history of Data Cloud? Salesforce has gone through several iterations with naming its CDP product: Customer 360 Audiences → Salesforce CDP → Marketing Cloud Customer Data Platform → Salesforce Genie → Salesforce Data Cloud.  In some instances, changes were made because the name just didn’t stick – but what’s more important to note, is that some of the name changes were to indicate the significant developments that happened to the product. Salesforce Data Cloud Differentiators Data Cloud, in itself, is impressive. While many organizations would consider it expensive, if you were to flip the argument on its head, by buying your own data warehouse, building the star schema, and paying for ongoing compute storage, you’d be looking to spend 5 to 10 times more than what Salesforce is charging for Data Cloud. Plus, data harmonization works best when your CRM data is front and center. There are other key differentiators that helps Data Cloud to stand out from the crowd: Is data cloud a data lakehouse? That means that Data Cloud is now not just a really good CDP, it’s now a data lake which will be used in sales and service use cases. But it also means that we can start to fundamentally move some of our higher-scale consumer products like Marketing and Commerce onto the platform. Is Snowflake a data Lakehouse? Snowflake offers customers the ability to ingest data to a managed repository, in what’s commonly referred to as a data warehouse architecture, but also gives customers the ability to read and write data in cloud object storage, functioning as a data lake query engine. What is the benefit of Salesforce data cloud? Data Cloud empowers Salesforce Sales Cloud with AI capabilities and automation that quickly closes deals and boosts productivity across every channel. It drives customer data from all the touchpoints and unifies it separately in individual customer profiles.  Salesforce Data Cloud is a powerful data warehouse solution that allows companies to effectively manage and analyze their data. What is the difference between Salesforce CDP and data lake? Talking abut Salesforce CDP is a little bit like a history lesson. While a CDP provides a unified, structured view of customer data, a data lake, on the other hand, is more of a raw, unstructured storage repository that holds a vast amount of data (more than just customer data) in its native format until it’s needed. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce Flow

Einstein GPT Integration with Flow and Data Cloud Now Available

Salesforce has recently unveiled exciting new capabilities for Flow, Einstein GPT Integration with Flow and Data Cloud. Introducing Einstein GPT and Data Cloud features to its growing family of automation tools. This development empowers everyday administrators, eliminating the need for extensive engineering teams to harness large datasets for automation purposes. The groundbreaking aspect lies in the ability to achieve this in real-time, using a user-friendly interface without the need for coding. Introduction to Einstein GPT: Einstein GPT builds upon ChatGPT technology, combining public and private AI models with CRM data within Salesforce. This allows users to pose natural-language prompts directly within Salesforce CRM, receiving AI-generated content that adapts continuously to changing customer information and needs. The learning capability of Einstein GPT ensures ongoing improvement based on user input, aligning with best practices. Einstein GPT for Flow: When integrated with Salesforce Flow, Einstein GPT enables users to create and modify automations through a conversational interface, simplifying the flow creation process significantly. This fusion lowers barriers for non-technical users, enhancing the overall experience with Flow Builder and ensuring adherence to best practices. Key benefits of Einstein GPT for Flow include: Pricing details for Einstein GPT products are pending confirmation, and Salesforce will soon announce pilot program dates to broaden accessibility. Data Cloud for Flow: Introduced at Dreamforce 2022, Salesforce Data Cloud, formerly Genie, facilitates highly personalized customer experiences in real-time. Serving as a command center for customer data, Data Cloud integrates real-time data streams with Salesforce data, powering Flow with actionable insights. By combining Data Cloud with Flow, users can automate complex workflows and trigger actions based on real-time changes without the need for extensive IT involvement. This approach streamlines the process of designing, building, and testing custom integrations, reducing the burden on IT teams. Key advantages of Data Cloud for Flow include: These announcements bring forth transformative capabilities, making data utilization more accessible and streamlining the automation process within Salesforce. The combination of Einstein GPT and Data Cloud for Flow opens up possibilities for creating personalized and interconnected customer experiences across different sectors. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce Data Cloud

Salesforce Data Cloud vs Salesforce CDP

Salesforce Genie, hailed as the most significant innovation in Salesforce’s history, has morphed into Salesforce Data Cloud. Operating on a grand scale, Data Cloud seamlessly processes and stores real-time data streams, integrating them with Salesforce data to unlock highly personalized customer experiences. Salesforce Data Cloud vs Salesforce CDP – which one is for me? You might wonder if this aligns with what Data Cloud (formerly Salesforce CDP) accomplishes—unifying versions of individuals across applications and providing customer experiences based on diverse data sources. To clarify, while Data Cloud shares similar goals and benefits with CDP, it represents an evolution beyond the technology of the former Salesforce CDP. In the words of Eric Stahl, EVP Marketing at Salesforce, “With [Data Cloud], we moved the real-time data capabilities into the [Salesforce] platform so we can ingest, manage and activate data from anywhere. It’s also nested with Einstein for AI and Flow for automation.” Data Cloud vs. Salesforce CDP: Key Differences Data Cloud inherits the capabilities of Salesforce CDP but extends its benefits across the entire “Customer 360,” covering Salesforce’s product portfolio. Here are key differences: Data Cloud, the successor to Salesforce CDP, extends beyond traditional CDP definitions. With a focus on diverse use cases beyond marketing and a zero-data copy architecture, Data Cloud stands as one of Salesforce’s most promising products. While Data Cloud shares purposes and benefits with CDPs, it represents a new era in Salesforce’s commitment to customer data unification, activation, and insight generation. Salesforce CDP remains available and operational, providing users with distinct options tailored to their specific needs. If it is time to explore the power of Salesforce Data Cloud to your sales and marketing efforts, contact Tectonic today. Like2 Related Posts CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Marketing Cloud Account Engagement and Salesforce Campaigns The interplay between Account Engagement and Salesforce Campaigns often sparks confusion and frustration among users. In this insight, we’ll demystify Read more Consent Management Analytics and Data Quality Understanding Data Analytics Consent and Consent Management Why Consent Management is Crucial Consent Management Analytics and Data Quality. With laws Read more

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Salesforce CDP

When Was Salesforce CDP Released?

Customer Data Platforms (CDPs) allow marketing organizations to have a single and complete source of truth around their customer data.  Salesforce CDP Released to address this need. Salesforce CDP Released In May 2021, Salesforce launched their own Customer Data Platform (CDP), an enhancement of the product formerly known as Customer Audience 360 (CA360). The customer data platform (CDP) is one of the fastest-growing categories of marketing technology today. Customer Data Platform, formerly Salesforce CDP, helps you connect and unify customer data. Across systems, power the connected and personalized marketing experiences that your customers expect, and analyze cross-channel engagement behavior. Activate loyalty, transaction, engagement attributes, and more from Customer Data Platform. Marketers can send additional customer profile information to marketing platforms, like Marketing Cloud Engagement, to enhance personalized communications. As a developer, you can use the CDP Python connector to leverage the power of Query API to extract data from Customer Data Platform into your environment. What is the difference between Salesforce CRM and CDP? Ultimately the difference between a CDP and CRM comes down to who primarily uses these tools and how each collects data. In short, CRMs organize and manage customer-facing interactions with your team while CDPs collect data from across your tech stack to understand customer behavior and traits more broadly. Is Salesforce Genie the same as CDP? Although Salesforce CDP and Genie are both beneficial tools for organizations, they have different functions. Salesforce CDP is certainly a superior option if you’re trying to increase your marketing and sales activities. Salesforce CDP Is Now Customer Data Platform The name change doesn’t change the functionality of Customer Data Platform. Is Salesforce CDP now data cloud? Salesforce Data Cloud is not a replacement for formerly Salesforce CDP – you will still be able to purchase, and use, Salesforce CDP. No doubt that there’s plenty on the horizon for Data Cloud, arguably Salesforce’s hottest product. Salesforce’s CDP offering was has been renamed a few times: Customer 360 Audiences → Salesforce CDP → Marketing Cloud Customer Data Platform → Salesforce Data Cloud. Content updated November 2023. Like1 Related Posts CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more Salesforce Government Cloud: Ensuring Compliance and Security Salesforce Government Cloud public sector solutions offer dedicated instances known as Government Cloud Plus and Government Cloud Plus – Defense. Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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