Einstein Salesforce AI - gettectonic.com - Page 3
Salesforce Flow
24Dec

Einstein Flow and Generative AI

By Shannan Hearne, Tectonic Marketing Consultant Based on Nov 2023 Salesforce post from Cesar Castro As part of the ongoing evolution of Salesforce’s Einstein AI, Salesforce provided an update on how Einstein is impacting one of your favorite tools in your Salesforce admin toolkit: Salesforce Flow. Flow, with its numerous powerful capabilities, has been instrumental in helping Salesforce Admins streamline and automate their work, delivering value to all end users in their organizations.  Often without the need for any additional Salesforce development assistance! Einstein Flow and Generative AI are powering a whole new brand of Salesforce actions. Salesforce Flow is a blanket term for everything in the Salesforce ecosystem that allows you to create, manage, and run automation with clicks not code.  Those of you who are using Flow on the regular?  You are known as Flownatics! Working With Einstein Flow and Generative AI In preparation for Einstein for Flow, content was collaborated on with Ajaay Ravi, Einstein for Flow Product Manager, Cesar Castro, Product Manager for Einstein Flow, and Vera Vetter, Director of Product Management, AI Research. Together, as product managers, they are actively working on enhancing Einstein for Flow. As Tectonic’s Salesforce Marketing Consultant I am very excited to share the news with you! Generative AI Einstein for Flow is a generative artificial intelligence (AI) tool that utilizes large language models (LLMs). To drive process automation across multiple Salesforce products. Whether you are a new Flow user or an experienced admin, Einstein for Flow aims to assist in learning and adopting this capability. By aiding in the creation of more complex flows and time saving automations.  Many of Salesforce Flow’s capabilities allow you to do what used to require Apex developers. The powerhouse behind Einstein for Flow is CodeGen, Salesforce’s in-house LLM released by Salesforce AI Research in 2022 to transform software development. CodeGen is the driving force behind the tailored AI solution for the needs of Salesforce users. So, how does Einstein for Flow operate? It’s as straightforward as describing your flow requirement in plain language through a natural language prompt. Einstein then invokes code to interpret and generate the natural flow data. To handle intricate flows, a concept called a “chain of thought” is introduced. By breaking down the flow into manageable steps, sequentially creating each part, and merging them to produce the final flow. In tis way Einstein is ensuring accuracy in meeting your business automation needs. Looking ahead, Salesforce’s roadmap for Einstein for Flow includes exciting features. One notable feature is the ability to use Einstein to edit an existing flow. This is irrespective of whether Einstein created it. Salesforce’s goal is to make flow building more accessible by enabling editing of both new and existing flows. In upcoming releases, an Einstein assistive interface will be integrated. Thereby allowing you to open and edit flows by conversing with Einstein in natural language. For all you Star Trek fans out there, the age of the Enterprise doing your verbal bidding is upon us! Einstein Suggestions Einstein will suggest changes and present a list of interconnected updates resulting from the proposed modifications. Designed to be user-friendly yet advanced, you can inspect recommended changes. Then review step by step, and view individual modifications. Additionally, a history of all changes suggested and made by Einstein will be available for those interested in maintaining an audit trail of AI-driven alterations. This is just the beginning for Einstein for Flow. As Salesforce launched a pilot program with diverse customers, they plan to go general availability (GA) in Spring ’24, with capabilities to generate flows for both standard and custom objects. Customer feedback will play a crucial role in shaping their future roadmap as they continue to explore more use cases and capabilities for Einstein for Flow. Flows are such a powerful tool, they are like visual coding created with clicks. Unlike code requiring only an understanding of programming concepts and logic. Examples of Flow Automation Use Cases: Stay tuned for updates as we ride the Einstein for Flow wave. It’s a game-changer! Tectonic will be watching and implementing with Einstein Flow and look forward to helping you do the same. 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 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 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

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December 24, 2023in Salesforce Einstein, Salesforce Implementation Services, Salesforce Managed Services
Salesforce Einstein Copilot
18Dec

Introducing Salesforce Einstein Copilot

Einstein Copilot introduces a cutting-edge generative A. Powered by a conversational assistant seamlessly embedded within every Salesforce application. Its strategically enhancing workflow and yielding substantial gains in productivity.  Announced at Dreamforce 2023, in case you missed it, read on. The newly integrated Einstein 1 Data Cloud, part of the Einstein 1 Platform, allows customers to establish a unified customer profile. By connecting any data source. This integration infuses AI, automation, and analytics into every customer experience, fostering a comprehensive approach. Salesforce Einstein Copilot Studio Einstein Copilot Studio provides organizations with the flexibility to tailor Einstein Copilot. A Salesforce tool used according to specific business requirements. It incorporates the Einstein Trust Layer, ensuring the protection of sensitive data while leveraging trusted information to enhance generative AI responses. Unlike other generative AI copilot solutions, Einstein Copilot is natively integrated into the world’s leading AI CRM – Salesforce. Seamlessly tapping into data from various Salesforce applications. This integration ensures more accurate AI-powered recommendations and content generation. Data Cloud The Data Cloud serves as the foundation for Einstein Copilot. Data Cloud offers real-time, consolidated views of customers or entities. With Data Cloud, creating a data graph is simplified, enabling the generation of AI-powered apps with a single click, eliminating the need for manual data queries or joins. Einstein Trust Layer The Einstein Trust Layer, an integral part of the Einstein 1 Platform, ensures the secure retrieval of relevant data from Data Cloud. Before sending it to the Language Model (LLM), proprietary, sensitive, or confidential information is masked, maintaining a high level of data security and compliance. Copilot for Sales aligns with existing CRM access controls and user permissions. Salesforce requires ensuring administrators and users have the necessary permissions for customization and data management within Copilot for Sales. Salesforce Copilot service functions similarly to other generative AI tools in the customer experience landscape, responding to customer queries automatically with personalized answers grounded in company data. Einstein Copilot & Search, anticipated for availability from February 2024, is set to leverage Data Cloud unstructured support. It will be ushering in a new era where Generative AI-based apps redefine the user interface. Thereby allowing seamless interactions and conversations with applications. This transformative shift signifies a significant milestone in Enterprise Software, with Salesforce actively participating in this evolving landscape. Copilot for Sales How is Copilot for Sales different from Copilot for Microsoft 365? Microsoft Copilot for Sales is an AI assistant designed for sellers that brings together the capabilities of Copilot for Microsoft 365 with seller-specific insights and workflows. What Salesforce just did is drop the GPT name and go with Copilot, By endorsing the Microsoft branding it announced earlier this year with Microsoft Copilot for Microsoft 365 and CoPilot for Dynamics 365. Like 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 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

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December 18, 2023in Einstein 1 Platform, Salesforce Data Cloud
Salesforce Tableau Pulse
02Dec

Tableau Pulse

Tableau Pulse, fueled by Tableau Artificial Intelligence and exclusive to Tableau Cloud, revolutionizes the data ingestion experience. The ability to empower business users with intelligent, personalized insights seamlessly integrated into their workflows. Whereas once upon a time AI for the lay user was about as friendly as asking Siri a question which she Googles for an answer and reads back to you. It saves a few clicks and a little typing, but it isn’t exactly thinking outside of the box – or phone. In the current data analytics demanding world, characterized by generative AI, the Internet of Things (IoT), and automation, the landscape is evolving. Data is at the core of these transformative technologies, and our interaction with said data is changing rapidly. As businesses worldwide confront an inflection point, embracing data-driven decision-making becomes crucial for staying competitive and building robust customer relationships. Tableau Pulse is a reimagined data experience, democratizing data accessibility for all users, irrespective of their familiarity with data visualization tools. Exclusively available to Tableau Cloud users, Tableau Pulse harnesses Tableau AI’s power to deliver more personalized, contextual, and intelligent data experiences in an easy-to-understand format. Key Features of Tableau Pulse: Upcoming Tableau Pulse Features in 2024: Tableau Pulse aims to breathe new life into analytics for everyone, capitalizing on the potential of generative AI, automation, and sensors to redefine how businesses interact with data. In a landscape where success hinges on data utilization, Tableau Pulse is poised to empower every employee with personalized, contextual, and intelligent insights directly within their workflow, fostering a truly data-driven organizational culture. Imaging the industry specific use cases for travel and tourism, manufacturing, health and life sciences, and the public sector? If you have data you aren’t able to utilize, reach out to Tectonic today to discover how Tableau Pulse could solve your challenges. 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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December 2, 2023in Life Sciences Cloud, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Manufacturing Automotive Energy, Salesforce Tableau
Salesforce Chat GPT
17Nov

Chat GPT and Salesforce

It’s more likely that you vacationed on Gilligan’s island than remain unfamiliar with ChatGPT. Since its introduction, this tool has emerged as an essential extension to Salesforce solutions, owing to its remarkable generative AI capabilities. From automating content creation to validating rules ChatGPT excels in some areas. By crafting Apex code, developing Lightning Web Components (LWC), summarizing conversations, and composing knowledge articles, ChatGPT has demonstrated its value. The integration of Chat GPT and Salesforce holds the potential to streamline substantial segments of organizational processes, leading to significant time savings. This not only enhances CRM data management, now fortified by generative AI, but also elevates the customer experience to unprecedented heights. While Salesforce has its own Einstein AI tools, Chat GPT and Salesforce remain a viable tool combination. This article will explore in detail how ChatGPT can seamlessly integrate with Salesforce. Understanding ChatGPT: When I questioned ChatGPT about its nature, and its response is as follows: ChatGPT is a language model created by OpenAI. It operates as a deep generative language neural network, having been trained on an extensive volumes of text to generate coherent and meaningful responses to user queries and commands. In essence, ChatGPT is essentially a chatbot, akin to Einstein bots. However, it distinguishes itself with its robust capabilities. Developed on the OpenAI GPT-3.5 family of large language models, incorporating both supervised and reinforcement learning techniques, ChatGPT has been trained on an extensive dataset of internet text up until January 2022. It excels in natural language processing tasks such as text generation, question answering, translation, and text classification. The underlying technology of ChatGPT is sophisticated, evolving continually through the application of machine learning and deep learning techniques. In 2023, OpenAI introduced two new models: ChatGPT-3.5 Turbo and ChatGPT-4, with the latter being notably superior. For instance, GPT-4 is multimodal, adept at processing both textual and visual inputs, comprehending and describing images effectively. It has also reduced the likelihood of generating nonsensical or “AI hallucinations” by 19-29%. In terms of security, GPT-4 incorporates robust measures from the outset, generating only 0.73% “toxic” responses compared to GPT-3.5’s 6.48%. It excels in maintaining context, with enhanced memory of the conversation, and improved context length to handle more extensive inputs. In summary, the mentioned improvements position GPT-4 as a more advanced and versatile option. ChatGPT Models: Every AI tool relies on models to discern patterns and make decisions from data. The OpenAI API is powered by a family of models with distinct capabilities and pricing scales. Users can also tailor their base models for specific use cases. The primary models include: This serves as a brief overview, and further exploration is possible here. OpenAI retires old models to introduce safer and more advanced versions. When a model becomes obsolete, it is promptly deactivated, with a specified shutdown date. Legacy models, those not receiving updates, are clearly labeled, signaling developers to transition to newer alternatives. Salesforce Consulting Services: Tectonic provides Salesforce consulting services geared toward catalyzing your company’s growth with Chat GPT and Salesforce, or by implementing a customized business solution or enhancing an existing implementation. Use Cases for ChatGPT in the Salesforce Ecosystem: The million-dollar question arises: how can ChatGPT be effectively utilized in Salesforce? Here are several Chat GPT and Salesforce use cases: Precautions with ChatGPT: While ChatGPT proves beneficial in areas like marketing, sales, and service, its application across the organization should be approached with caution. It’s a powerful tool, offering coherent and logical responses, but it cannot replace every role in every area. As of now, it functions as a valuable virtual assistant for specific tasks, but it shouldn’t be the sole source of information. Proper utilization of this tool can positively impact your Salesforce solution, but precautions must be taken. According to the “Generative AI Trends for Sales” report, 73% of sales professionals express concerns about the security risks associated with this technology, with 49% admitting to not knowing how to use it safely at work. Additionally, ChatGPT often lacks context, leading to potential inaccuracies in responses. Therefore, Salesforce recommends taking the following precautions before adopting any integration of Chat GPT and Salesforce: It’s essential not to overestimate ChatGPT while still leveraging its advantages. Currently, it can serve as a virtual assistant to assist with specific tasks, but it should not be the sole source of information. Prudent use of this tool can positively impact your Salesforce solution, but precautions should be taken. It’s advisable to make the most of generative AI capabilities within Salesforce, especially considering the developments in 2023. Salesforce has introduced multiple solutions incorporating this technology, not only with a comprehensive suite of GPT products but also a significant leap in Einstein. Since the past Dreamforce, Einstein Platform 1 has evolved into the CRM’s trusted AI, offering a high-performance real-time conversational assistant, Einstein Copilot, and an Infinite Capability Studio. Being part of Salesforce’s ecosystem eliminates potential data security and privacy gaps, facilitating integration with other platform solutions. ChatGPT marked the inception of the generative AI revolution and stands as a powerful tool. It’s crucial to remember that OpenAI releases versions frequently, addressing major issues promptly. There’s undoubtedly much more to explore and experience with ChatGPT. If you’re considering implementing it in your organization, Tectonic is prepared to assist you in achieving this goal. 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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November 17, 2023in Salesforce, Salesforce Einstein
ethical ai consumer trust vs expectations
06Nov

Ethical AI-Consumer Trust Vs Expectations

Consumer Trust and Responsible AI Implementation Ethical AI Consumer Trust vs Expectations Research indicates that while consumers have low trust in AI systems, they expect companies to use them responsibly. Around 90% of consumers believe that companies have a duty to contribute positively to society. However, despite guidance on responsible technology use, many consumers remain apprehensive about how companies are deploying technology, particularly AI. ethical ai consumer trust vs expectations A global survey conducted in March 2021 revealed that citizens lack trust in AI systems but still hold organizations accountable for upholding principles of trustworthy AI. To earn customers’ trust in AI and mitigate brand and legal risks, companies need to adopt ethical AI practices centered around principles such as Transparency, Fairness, Responsibility, Accountability, and Reliability. Developing an Ethical AI Practice Over the past few years, industry professionals like have focused on maturing AI ethics practices within companies like Salesforce. This journey toward ethical AI maturity often begins with an ad hoc approach. Ad Hoc Stage In the ad hoc stage, individuals within organizations start recognizing unintended consequences of AI and informally advocate for considering bias, fairness, accountability, and transparency. These early advocates spark awareness among colleagues and managers, prompting discussions on the ethical implications of AI. Some advocates eventually transition to full-time roles focused on building ethical AI practices within their companies. Organized and Repeatable Stage With executive buy-in, companies progress to the organized and repeatable stage, establishing a culture where responsible AI practices are valued. This stage involves: Achieve Ethical AI Consumer Trust vs Expectations During this stage, companies must move beyond superficial “ethics washing” by actively integrating ethical principles into their operations and fostering a culture of responsibility. Additionally, the independence and empowerment of individuals in responsible AI roles are crucial for maintaining integrity and honesty in ethical AI practices. Final Insight Thoughts As companies progress through the maturity model for ethical AI practices, they strengthen consumer trust and mitigate risks associated with AI deployment. By prioritizing transparency, fairness, and accountability, organizations can navigate the ethical complexities of AI implementation and contribute positively to society. ethical ai consumer trust vs expectations 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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November 6, 2023in Salesforce Einstein
Salesforce Service Cloud Intelligence
03Nov

Salesforce Service Cloud Service Intelligence Enhancements

Service Intelligence, a data-centric solution, showcases vital performance metrics within the contact center. Recent Service Intelligence Enhancements have given even greater insights. In a significant launch, Salesforce introduced Service Intelligence. Service Intelligence an advanced analytics app for Service Clou. It is aimed at boosting agent efficiency, reducing costs, and elevating customer satisfaction. Service Intelligence Enhancements and updates within this Salesforce product aim to bolster operational efficiency and take customer satisfaction to unprecedented heights. Representing a new milestone for Service Cloud, the Winter ’24 innovations redefine how businesses approach customer service and optimize operations. Fueled by Data Cloud, Salesforce’s real-time hyperscale data engine, Service Intelligence provides users with direct access to all their data within Service Cloud, eliminating the need to switch between screens for information. Pre-built and customizable dashboards in Service Intelligence offer a comprehensive view of essential metrics, including customer satisfaction and individual and team workloads. With Einstein Conversation Mining, service professionals can leverage AI to analyze customer chat and email conversations, uncover insights, assess the likelihood of complaint escalation, and proactively address issues with customers. The relevance of AI is emphasized, with an 88% increase in AI adoption among service professionals from 2020 to 2022. With 63% acknowledging that AI will help them serve customers faster. Service professionals are embracing AI enabling to make informed decisions swiftly, gaining a competitive edge. Service Intelligence Enhancements As of 2023, Service Intelligence is now generally available. Key features include pre-built service dashboards offering AI-powered insights through Einstein Conversation Mining, providing visibility into key metrics across cases. Einstein Conversation Mining employs AI to analyze customer conversations. Einstein Conversation mining enables quick identification of trends and top customer issues. Tableau integration allows users to seamlessly explore data in Tableau directly from a Service Intelligence dashboard, maintaining data context from their service console. Service Intelligence encompasses Data Cloud, CRM Analytics, and Einstein Conversation Mining. There by offering a wealth of information such as customer data and key performance indicators (KPIs) to help service teams enhance operations and reduce costs. Einstein for Service accelerates customer communication and satisfaction by generating email responses based on knowledge articles. The Winter ’24 release introduces the Lightning Article Editor and Article Customization in Salesforce Service Cloud, marking a significant advancement in knowledge management. The Lightning Article Editor simplifies content creation and editing. Thus enabling support and customer service teams to produce informative material efficiently. These enhancements in Service Cloud streamline operations, empower agent performance, and usher in a new era of customer satisfaction. Explore these exciting updates to transform your organization’s strategy. Embrace the future of service excellence with the Winter ’24 release for Service Cloud. Like Related Posts 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 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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November 3, 2023in Salesforce Data Cloud, Salesforce Einstein, Salesforce Sales Cloud, Salesforce Service Cloud, Salesforce Tableau
Tableau CRM Refresh Button With LWC
29Oct

Tableau CRM Refresh Button With LWC

Revitalize your Tableau CRM (formerly known as Einstein Analytics) dashboards with a custom Refresh button, enhancing user experience and analytical efficiency. This button serves as a simple yet powerful tool to reset applied filters and revert the dashboard to its default state, facilitating seamless exploration of data insights. Tableau CRM Refresh Button With LWC. What exactly is a Tableau CRM Refresh Button With LWC? It’s a user interface component that, upon activation, clears all applied filters, restoring the dashboard to its initial configuration. This feature proves particularly beneficial in scenarios where users seek to initiate fresh analyses or when dealing with intricate filter structures. To embark on this enhancement journey, you’ll require three essential components: Once equipped, follow these steps to integrate the Refresh button seamlessly: Step 1: Crafting a Lightning Web Component (LWC) Initiate the creation process by developing a Lightning Web Component (LWC) within Salesforce. This component will seamlessly embed into your Tableau CRM dashboard. Step 2: Designing the HTML Framework Within the HTML file of your LWC (let’s name it refreshButton.html), define the structural blueprint for your button. Below is a sample markup: phpCopy code<template> <div class=”reset-btn_container”> <lightning-button variant=”base” label=”&#xe912;” aria-label=”Clear Filters” onclick={clearFilters} class=”slds-m-right_x-small hpe-icon-button hpe-icon-bare” ></lightning-button> </div> </template> This markup establishes a container for the button, utilizing a lightning-button element to create the button itself. Key attributes such as label, variant, and onclick event handler are set accordingly. Step 3: Implementing JavaScript Logic In the JavaScript file of your LWC (refreshButton.js), define the logic to execute filter clearance upon button activation. Here’s an illustrative example: typescriptCopy codeimport { LightningElement, api, track } from ‘lwc’; export default class DceResetDashboardButton extends LightningElement { @api getState; @api setState; @api refresh; @track initialState = null; clearFilters() { const {state, pageId} = this.getState(); const newState = { state: { …state, datasets: this.initialState.state.datasets, steps: Object.fromEntries(Object.entries(state.steps).map(([k, v]) => { return [k, { …v, values: [] }] })), }, pageId, } this.setState({ …newState, replaceState: true }); } connectedCallback() { this.initialState = this.getState(); } } This JavaScript snippet encompasses crucial elements such as property definition, filter clearance methodology, and initialization of the dashboard’s initial state. Step 4: Deploying the Lightning Web Component With your LWC crafted, proceed to deploy it within your Salesforce organization. Step 5: Integrating the LWC into Your Dashboard Edit your Tableau CRM dashboard, adding a new “Custom Component” widget and configuring it to utilize your deployed LWC as the custom component. Step 6: Testing Your Refresh Button Upon completion, navigate to your Tableau CRM dashboard to confirm the presence of the Refresh Button. A simple click on this button will swiftly clear all filters, providing a seamless experience for resetting your analysis. By incorporating this Refresh button into your Tableau CRM dashboard, you enhance user satisfaction and analytical agility. Take advantage of this tutorial to elevate your dashboards and witness the appreciation from your users firsthand! If you need assistance building a refresh button in your Tableau CRM dashboard, contact Tectonic today. 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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October 29, 2023in Salesforce, Salesforce Tableau
How Good is Our Data
28Oct

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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October 28, 2023in Salesforce Data Cloud, Salesforce Einstein, Salesforce Financial Cloud, Salesforce Managed Services, Salesforce Sales Cloud
Retrieval Augmented Generation in Artificial Intelligence
26Oct

RAG – Retrieval Augmented Generation in Artificial Intelligence

Salesforce has introduced advanced capabilities for unstructured data in Data Cloud and Einstein Copilot Search. By leveraging semantic search and prompts in Einstein Copilot, Large Language Models (LLMs) now generate more accurate, up-to-date, and transparent responses, ensuring the security of company data through the Einstein Trust Layer. Retrieval Augmented Generation in Artificial Intelligence has taken Salesforce’s Einstein and Data Cloud to new heights. These features are supported by the AI framework called Retrieval Augmented Generation (RAG), allowing companies to enhance trust and relevance in generative AI using both structured and unstructured proprietary data. RAG Defined: RAG assists companies in retrieving and utilizing their data, regardless of its location, to achieve superior AI outcomes. The RAG pattern coordinates queries and responses between a search engine and an LLM, specifically working on unstructured data such as emails, call transcripts, and knowledge articles. How RAG Works: Salesforce’s Implementation of RAG: RAG begins with Salesforce Data Cloud, expanding to support storage of unstructured data like PDFs and emails. A new unstructured data pipeline enables teams to select and utilize unstructured data across the Einstein 1 Platform. The Data Cloud Vector Database combines structured and unstructured data, facilitating efficient processing. RAG in Action with Einstein Copilot Search: RAG for Enterprise Use: RAG aids in processing internal documents securely. Its four-step process involves ingestion, natural language query, augmentation, and response generation. RAG prevents arbitrary answers, known as “hallucinations,” and ensures relevant, accurate responses. Applications of RAG: RAG offers a pragmatic and effective approach to using LLMs in the enterprise, combining internal or external knowledge bases to create a range of assistants that enhance employee and customer interactions. Retrieval-augmented generation (RAG) is an AI technique for improving the quality of LLM-generated responses by including trusted sources of knowledge, outside of the original training set, to improve the accuracy of the LLM’s output. Implementing RAG in an LLM-based question answering system has benefits: 1) assurance that an LLM has access to the most current, reliable facts, 2) reduce hallucinations rates, and 3) provide source attribution to increase user trust in the output. Retrieval Augmented Generation in Artificial Intelligence Content updated July 2024. 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 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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October 26, 2023in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Data Cloud
Einstein Email Insights Explained
18Oct

Einstein Email Insights Explained

In 2016, Salesforce ventured into the realm of artificial intelligence (AI) with the introduction of Salesforce Einstein. Far from a standalone product, Salesforce Einstein represents a technological layer seamlessly integrated into the Salesforce Lightning platform and various other Salesforce cloud products. Insights for Sales Specifically designed for sales professionals, Einstein Email Insights proves to be a valuable tool. It provides crucial information within the email interface, empowering salespeople to respond to customers more effectively and at the opportune moment. Einstein Email Insights offers sales representatives essential context related to sales alongside pertinent inbound emails. By specifying criteria for email content analysis, users can extract the most relevant insights. Einstein ensures that contextual sales information is surfaced while composing emails, facilitating the delivery of optimal responses at the right time. This feature is available with Sales Cloud Einstein, Inbox, High Velocity Sales, or Revenue Intelligence, albeit with an additional cost. It is accessible for Salesforce Enterprise, Performance, and Unlimited editions, subject to an extra charge. The Einstein Family If you are using Einstein Activity Capture with a Sales Cloud Einstein or Inbox license, Email Insights is automatically activated upon enabling Einstein Activity Capture. However, users without these licenses must read and agree to the Email Insights terms of service before utilizing the feature. The insights derived from Einstein Conversation Insights go beyond mere data points; they offer actionable intelligence. Businesses can leverage these insights to refine products, optimize customer service processes, and make informed decisions that positively impact the overall customer experience. Salesforce Einstein Insights ensures that every action taken by your sales representatives is calculated and meaningful, aiming to convert prospects into customers. Statistics show that Salesforce Einstein Insights can boost conversion rates by 43%. This AI-powered platform compiles data from accounts, opportunities, call histories, and even news sources to predict business outcomes, empowering your team to strategize with confidence at every stage of customer engagement. Salesforce has recently introduced new email features in its Marketing Cloud to enhance the efficiency of email capabilities. The new Einstein Email capabilities enable modern marketers to increase productivity, send more personalized emails, and drive greater customer engagement. Additionally, Salesforce’s acquisition of Rebel, an interactive email provider, brings forth the ability to create interactive emails, allowing recipients to take action directly within the email. This functionality, akin to AMP for Gmail, enables users to browse image carousels, fill out forms, register for events, and more, directly from their inbox. Salesforce plans to launch this pilot early in 2020, integrating it with Email Studio and Journey Builder. Like2 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 Public Sector Salesforce Solutions Public Sector Solutions revolutionize public service delivery through flexible and secure e-government tools supporting both service providers and constituents. Designing Read more

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October 18, 2023in Einstein Insights, Salesforce Einstein
Salesforce Tableau Pulse
25Sep

Tableau Pulse and Tableau GPT

Most of us are quite familiar with Chat GPT, the revolutionary Large Language Model from Open AI that is transforming the world of AI interactions far beyond research labs. Recently, Tableau unveiled Tableau GPT at TC 2023, a new tool leveraging generative AI. But what is Tableau GPT, and how does it integrate with Tableau’s current array of product offerings? Tableau Pulse and Tableau GPT work together. Complementing Tableau GPT’s natural language capabilities is the newly launched user interface, Tableau Pulse. Designed as a personal data guide, Pulse presents you with a curated, ‘newsfeed’-like view of your key metrics, a game changer for business leaders needing to keep a close eye on performance indicators. So Tableau AI is a suite of capabilities that brings trusted predictive and generative AI to the entire Tableau Platform to simplify and democratize data analysis and insight consumption at scale. Tableau GPT: Tableau GPT is an assistant utilizing advanced generative AI to streamline and democratize the data analysis process. Developed in collaboration with OpenAI, it is derived from Einstein GPT, a recently introduced Salesforce product. Tableau GPT seamlessly incorporates generative AI into Tableau’s user experience, aiming to enhance productivity, accelerate learning, and improve communication. During the TC keynote’s Devs on Stage segment, Matthew Miller, Senior Director of Product Management, showcased Tableau GPT’s ability to generate calculations. With a prompt like “Extract email addresses from JSON,” Tableau GPT swiftly provided a calculation that could be easily integrated into the calculation window. Tableau Pulse: Additionally, Tableau GPT also powers the new Tableau tool named Tableau Pulse, enabling users to generate powerful insights rapidly. In this tool, Tableau Pulse offers “data digests” on the user’s personalized metrics homepage, allowing customization. Users can have a curated, ‘newsfeed’-like experience of key KPIs, personalized over time as Pulse learns user preferences. Tableau Pulse provides metrics to pay attention to, based on recent data trends recognized by Tableau GPT. Users can follow KPIs and receive the latest values, visual trends, and AI-generated insights. Moreover, Tableau Pulse responds to natural language queries about data. For instance, when asked, “What is driving change in Appliance Sales?” Tableau Pulse provides a quick answer with a visualization. Tableau Pulse helps everyone in your organization integrate data into their daily jobs to make better, faster decisions. Without having to learn a new tool or build comprehensive visualizations, Tableau Pulse helps you go beyond the how and what and shows you the why behind your data. After obtaining insights from Tableau Pulse, users can drill down further by asking follow-up questions. For example, asking, “What else should I know about air fryers?” reveals an insight that the “inventory fill rate” for air fryers is forecasted to fall below the predetermined threshold. Knowing where, when, and why to pay attention to your business has never been easier. Within Tableau Pulse, the Insights platform automatically detects drivers, trends, contributors, and outliers for the metrics you follow. It proactively flags changes that matter to you. Using natural language and supporting visual explanations, Now Tableau Pulse summarizes the insights so you can make appropriate and timely decisions. Tableau Pulse and Tableau GPT Tableau GPT and Pulse are poised to transform the interaction with Tableau products. These tools will expedite the creation of visualizations, a hallmark of Tableau, and provide non-technical users with quick data comprehension without additional development time. Users access Tableau Pulse from the Tableau Cloud navigation menu, but the metrics in Tableau Pulse aren’t part of the project content hierarchy in Tableau Cloud or governed by project-based permissions. The ability to create or see metrics is based on permission to connect to and access data in a data source. 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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September 25, 2023in Salesforce
Google 360 Analytics Dashboard in Marketing Cloud
13Sep

Salesforce Audience Insights

Salesforce Audience Insights By Tectonic’s Marketing Consultant, Shannan Hearne Salesforce Marketing Cloud is so much more than just an email sending platform. This insight explores how it can power your advertising.; Marketing Cloud offers robust audience segmentation capabilities, empowering marketers to effectively segment their customer base. The integration of AI through Audience Insights enhances this power. Formerly known as Advertising Studio, the platform is now recognized as Marketing Cloud Advertising. Audience Insights provides a deeper understanding of customers by unveiling unique characteristics, interests, and behaviors of user groups interacting with your ads and converting. By connecting Marketing Cloud Advertising to paid media channels, you can optimize your audience strategy, gaining a unified, cross-channel view and assessing the effectiveness of first-party audiences through a dedicated dashboard. Key features of Audience Insights include: To leverage Audience Insights, your Marketing Cloud Intelligence admin needs to configure it before connecting Advertising to paid media channels. This integration allows you to analyze the effectiveness of first-party audiences with a single, cross-channel perspective. As a Marketing Cloud Advertising customer with a Marketing Cloud Intelligence license, you gain access to comprehensive audience and campaign analytics through Audience Insights for Marketing Cloud Advertising. This application is conveniently available in the Marketing Cloud Intelligence Marketplace. Utilize the Audience Insights for Advertising Studio dashboard to refine campaigns using first-party audiences. Additionally, the Marketing Insights for Sales Cloud solution facilitates a deeper understanding of how marketing efforts and spend translate into revenue, offering insights into the sales funnel and guiding strategic decisions. Salesforce Audience Insights The Marketing Insights for Sales Cloud solution utilizes objects such as Leads, Opportunities, Accounts, Contacts, Campaigns, and Campaign Members to provide a holistic view of marketing and sales alignment. Setting up your digital advertising strategy within Salesforce, particularly through Advertising Studio, yields significant benefits. Integration with Google Analytics 360 expands your digital marketing and analytics possibilities. Advertising Studio seamlessly connects with advertising platforms like Google Display Ads, Facebook Ads, Instagram, Pinterest, Twitter, LinkedIn, AdWords, Gmail, and YouTube. Are you ready to employ the full power of Salesforce Marketing Cloud and Advertising Studio? Contact Tectonic today. Like3 Related Posts 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 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 Salesforce Data Studio Data Studio Overview Salesforce Data Studio is Salesforce’s premier solution for audience discovery, data acquisition, and data provisioning, offering access Read more

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September 13, 2023in Marketing Automation, Salesforce Einstein, Salesforce Marketing Cloud, Salesforce Marketing Cloud Advertising, Salesforce Sales Cloud
Sales Cloud Einstein
11Sep

How Einstein Lead Scoring Works on Your Prospect Data

How Einstein Lead Scoring Works on Your Prospect Data By Shannan Hearne, Tectonic Marketing Consultant The love hate relationship between sales and marketing is based on lead quality.  Each party is tempted to blame the other for deals that fail to close.  Either marketing thinks the sales team dropped the ball following up with the prospect. Or the sales team thinks marketing failed to properly qualify the lead.  With Einstein Lead Scoring, the relationship between sales and marketing can improve. Not every lead holds the same significance, and relying on arbitrary details for accurate scoring is ineffective. Clicks, opens, and form fills vary in value for each lead, and visiting the Careers page does not necessarily diminish a lead’s potential.  Humans from both sales and marketing have to work together to craft scoring criteria that reflects behavior that great customers took before becoming customers.  The development of the scoring model is key to making Einstein Lead Scoring Works on Your Prospect Data. Einstein Lead Scoring, integrated with Sales Cloud Einstein, leverages artificial intelligence to enhance sales conversion efficiency. By automatically analyzing historical sales data and identifying key factors influencing lead conversion, sales reps can effectively segment and prioritize leads. With data supplied by Einstein running lead scoring in the background.  While the human factor is important, the speed of artificial intelligence to analyze data cannot be beaten. Tailored to individual business needs, Einstein Lead Scoring models analyze both standard and custom fields associated with the Lead object. By using predictive models like Logistic Regression, Random Forests, and Naive Bayes (definitions below). The system autonomously selects the best model based on a sample dataset, eliminating the need for statistical or mathematical expertise.  No more pouring through hours of spreadsheets sorting and creating pivot tables. Model Updates Regular model updates ensure accuracy. With leads being scored every hour using the latest model. This allows quick response to changes, ensuring that the prioritization of leads remains effective. The scoring factors are prominently displayed on the lead record page. Thus enabling sales reps to prepare for calls or emails efficiently with accurate engagement data. The true strength of Einstein Lead Scoring lies in its machine learning capabilities. Einstein is continuously refining predictions based on the latest Salesforce data. If new patterns emerge, such as VP titles in a specific industry showing interest in demos, Einstein automatically rescores leads meeting this criteria. Key benefits of Einstein Lead Scoring include increased connection and conversion rates, accelerated engagement with top leads, and a clear understanding of lead scoring factors. Important features encompass zero setup requirements, custom lead score-driven workflows for task assignments, and smart lead lists that prioritize the best leads for reps. Einstein Lead Scoring Works on Your Prospect Data For businesses utilizing or considering Salesforce Sales Cloud, consulting with Tectonic about integrating Einstein Lead Scoring can lead to faster implementation and deal closures. As your Salesforce implementation partner, Tectonic ensures a tailored Salesforce solution. Remaining aligned with your business needs, incorporating the powerful capabilities of Einstein tools within your Salesforce ecosystem.  Contact Tectonic today. Logistic regression estimates the probability of an event occurring, such as voted or didn’t vote, based on a given dataset of independent variables. Random forest is a commonly-used machine learning algorithm trademarked by Leo Breiman and Adele Cutler. It combines the output of multiple decision trees to reach a single result. Its ease of use and flexibility have fueled its adoption, as it handles both classification and regression problems. The Naïve Bayes classifier is a supervised machine learning algorithm, which is used for classification tasks, like text classification. It is also part of a family of generative learning algorithms, meaning that it seeks to model the distribution of inputs of a given class or category. 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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September 11, 2023in Einstein Insights, Salesforce Sales Cloud
Salesforce Data Cloud
08Sep

Salesforce Data Cloud Evolution

Data Cloud stands as the fastest-growing organically built product in Salesforce’s history, signifying a significant milestone in solving the enduring data problem within Customer Relationship Management (CRM). Salesforce Data Cloud Evolution since its beginnings is an interesting story. With an average of 928 systems per company, identity resolution becomes challenging, especially when managing more than one system. Salesforce’s expansion into AI-powered CRM emphasizes the synergy between AI and data, recognizing that AI’s optimal functionality requires robust data support. Data Cloud acts as the foundation accelerating connectivity across different ‘clouds’ within the Salesforce platform. While it’s available for purchase, even Salesforce customers without licensed Data Cloud still benefit from its foundational advantages, with increased strength when utilized as a personalization and data unification platform. The history of Data Cloud reflects its evolution through various iterations, from Customer 360 Audiences to Salesforce Genie, ultimately settling as Data Cloud in 2023. This journey marked significant developments, expanding from a marketer’s tool to catering for sales, service, and diverse use cases across the Salesforce platform. Data harmonization with Data Cloud simplifies the complex process, requiring fewer efforts compared to traditional methods. It comes pre-wired to Salesforce objects, reducing the need for extensive data modeling and integration steps. The technical capability map showcases a comprehensive integration of various technologies, making Data Cloud versatile and adaptable. Data Cloud’s differentiators include being pre-wired to Salesforce objects, industry-specific data models, prompt engineering capabilities, and the inclusion of the Einstein Trust Layer, addressing concerns related to generative AI adoption. Looking ahead, Data Cloud continues to evolve with constant innovation and features in Salesforce’s major releases. The introduction of Data Cloud for Industries, starting with Health Cloud, signifies ongoing enhancements to cater to industry-specific needs. Closing the skills gap is crucial for effective Data Cloud implementation, requiring a blend of developer skills, data management expertise, business analyst skills, and proficiency in prompt engineering. Salesforce envisions Data Cloud, combined with CRM and AI, as the next generation of customer relationship management, emphasizing the importance of sound data and skillful implementation. Data Cloud represents the ‘Holy Grail of CRM,’ offering a solution to the long-standing data challenges in CRM. However, its success as an investment depends on the organization’s readiness to demonstrate return on investment (ROI) through solid use cases, ensuring unified customer profiles and reaping the rewards of this transformative technology. FAQ When did Salesforce introduce data cloud? Customer 360 Audiences: Salesforce’s initial CDP offering, launched in 2020. Salesforce CDP: The name changed in 2021 to align with how the blooming CDP market was referring to this technology. Does Salesforce data cloud compete with Snowflake? They offer distinct capabilities and cater to diverse business needs. Salesforce Data Cloud specializes in data enrichment, personalization, and real-time updates, while Snowflake boasts scalable data warehousing and powerful analytics capabilities. What is the data cloud in Salesforce? Deeply integrated into the Einstein 1 Platform, Data Cloud makes all your data natively available across all Salesforce applications — Sales Cloud, Service Cloud, Marketing Cloud, Commerce Cloud, Tableau, and MuleSoft — to power automation and business processes and inform AI. Is Salesforce Genie now data cloud? Announced at Dreamforce ’22, Salesforce Genie was declared the greatest Salesforce innovation in the company’s history. Now known as Data Cloud, it ingests and stores real-time data streams at massive scale, and combines it with Salesforce data. This paves the way for highly personalized customer experiences 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 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 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

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September 8, 2023in Salesforce Data Cloud, Salesforce Einstein

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