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Slack and ChatGPT

Slack and ChatGPT

Salesforce Inc announced its collaboration with OpenAI, the creator of ChatGPT, to integrate the chatbot technology into its Slack collaboration software and broaden the use of generative artificial intelligence across its business software. The San Francisco-based company unveiled EinsteinGPT, a technology merging its own AI capabilities with those of external partners like OpenAI. This collaboration aims to assist businesses in tasks such as drafting emails, managing customer accounts, and even generating computer code. Additionally, ChatGPT will integrate with Slack to help users summarize conversations and handle various queries. This strategic move reflects the competitive landscape among tech giants racing to enhance their platforms with generative AI, which can generate text, images, and other content based on historical data inputs. Microsoft Corp, for example, leveraging its investment in OpenAI, has integrated generative AI into its Teams product, enabling functionalities like generating meeting notes and suggesting email responses through its Viva Sales subscription. This places Teams in direct competition with Slack. Clara Shih, a general manager at Salesforce, highlighted during a press briefing that this announcement addresses the growing demand from businesses for advanced AI capabilities. She emphasized that Salesforce’s proprietary data and AI models would differentiate their offerings in the market. Salesforce’s initiative in generative AI is poised to transform customer engagement strategies for businesses, according to Shih, enabling them to innovate profoundly in their interactions with customers. In addition to this integration, Salesforce also unveiled a new fund aimed at investing in startups specializing in generative AI technologies. 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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ChatGPT and Einstein GPT

ChatGPT and Einstein GPT

Artificial intelligence (AI) has been rapidly advancing globally, with breakthroughs captivating professionals across various sectors. One milestone that has gained significant attention is the emergence of ChatGPT, a cutting-edge language model revolutionizing the tech landscape. This development has profoundly impacted businesses relying on Salesforce for their customer relationship management (CRM) needs. In March 2023, Salesforce unveiled its latest AI innovation, Einstein GPT, promising to transform how companies engage with their clientele. In this article, we explore what Salesforce Einstein GPT entails and how it can benefit teams across diverse industries. When OpenAI introduced ChatGPT in November 2022, they didn’t expect the overwhelming response it received. Initially positioned as a “research preview,” this AI chatbot aimed to refine existing technology while soliciting feedback from users. However, ChatGPT quickly became a viral sensation, surpassing OpenAI’s expectations and prompting them to adapt to its newfound popularity. Developed on the foundation of the GPT-3.5 language model, ChatGPT was specifically tailored to facilitate engaging and accessible conversations, distinguishing it from its predecessors. Its launch attracted a diverse user base keen to explore its capabilities, prompting OpenAI to prioritize addressing potential misuse and enhancing its safety features. As ChatGPT gained traction, it caught the attention of Salesforce, a leading CRM provider. In March 2023, Salesforce unveiled Einstein GPT, its own AI innovation, poised to transform customer engagement. Built on the GPT-3 architecture and seamlessly integrated into Salesforce Clouds, Einstein GPT promised to revolutionize how businesses interact with their clientele. Einstein GPT boasts a range of features designed to personalize customer experiences and streamline workflows. From generating natural language responses to crafting personalized content and automating tasks, Einstein GPT offers versatility and value across industries. By leveraging both Einstein AI and GPT technology, businesses can unlock unprecedented efficiency and deliver superior customer experiences. Despite its success, OpenAI acknowledges the need for ongoing refinement and vigilance, emphasizing the importance of responsible deployment and transparency in the development of AI technology. Exploring Einstein GPT Salesforce presents Einstein GPT as the premier generative AI tool for CRM worldwide. Utilizing the advanced GPT-3 architecture, Einstein GPT seamlessly integrates into all Salesforce Clouds, including Tableau, MuleSoft, and Slack. This groundbreaking technology empowers users to generate natural language responses to customer inquiries, craft personalized content, and compose entire email messages on behalf of sales personnel. With its high degree of customization, Einstein GPT can be finely tuned to meet the specific needs of various industries, use cases, and customer requirements, delivering significant value to businesses of all sizes and sectors. Objectives of Salesforce AI Einstein GPT Salesforce AI Einstein GPT is designed to achieve several key objectives: Distinguishing Einstein GPT from Einstein AI Einstein GPT represents the latest evolution of Salesforce’s Einstein artificial intelligence technology. Unlike its predecessors, Einstein GPT integrates proprietary Einstein AI models with ChatGPT and other leading large language models. This integration enables users to interact with CRM data using natural language prompts, resulting in highly personalized, AI-generated content and triggering powerful automations that enhance workflows and productivity. By leveraging both Einstein AI and GPT technology, businesses can achieve unparalleled efficiency and deliver exceptional customer experiences. Features of Einstein GPT in Salesforce CRM Key features and capabilities of Salesforce Einstein chatbot GPT include: Utilizing Einstein GPT for Business Improvement Einstein GPT can be leveraged across various domains to enhance business operations: Integration with Salesforce Data Cloud Salesforce Data Cloud, a cloud-based data management system, enables real-time data aggregation from diverse sources. Einstein GPT utilizes unified customer data profiles from the Salesforce Data Cloud to personalize interactions throughout the customer journey. OpenAI on ChatGPT Methods We trained this model using Reinforcement Learning from Human Feedback (RLHF), using the same methods as InstructGPT, but with slight differences in the data collection setup. We trained an initial model using supervised fine-tuning: human AI trainers provided conversations in which they played both sides—the user and an AI assistant. We gave the trainers access to model-written suggestions to help them compose their responses. We mixed this new dialogue dataset with the InstructGPT dataset, which we transformed into a dialogue format. To create a reward model for reinforcement learning, we needed to collect comparison data, which consisted of two or more model responses ranked by quality. To collect this data, we took conversations that AI trainers had with the chatbot. We randomly selected a model-written message, sampled several alternative completions, and had AI trainers rank them. Using these reward models, we can fine-tune the model using Proximal Policy Optimization. We performed several iterations of this process. ChatGPT is fine-tuned from a model in the GPT-3.5 series, which finished training in early 2022. You can learn more about the 3.5 series here. ChatGPT and GPT-3.5 were trained on an Azure AI supercomputing infrastructure. Limitations ChatGPT and Einstein GPT Salesforce Einstein GPT signifies a significant advancement in AI technology, empowering businesses to deliver tailored customer experiences and streamline operations. With its integration into Salesforce CRM and other platforms, Einstein GPT offers unprecedented capabilities for personalized engagement and automated insights, ensuring organizations remain competitive in today’s dynamic market landscape. When OpenAI quietly launched ChatGPT in late November 2022, the San Francisco-based AI company didn’t anticipate the viral sensation it would become. Initially viewed as a “research preview,” it was meant to showcase a refined version of existing technology while gathering feedback from the public to address its flaws. However, the overwhelming success of ChatGPT caught OpenAI off guard, leading to a scramble to capitalize on its newfound popularity. ChatGPT, based on the GPT-3.5 language model, was fine-tuned to be more conversational and accessible, setting it apart from previous iterations. Its release marked a significant milestone, attracting millions of users eager to test its capabilities. OpenAI quickly realized the need to address potential misuse and improve the model’s safety features. Since its launch, ChatGPT has undergone several updates, including the implementation of adversarial training to prevent users from exploiting it (known as “jailbreaking”). This technique involves pitting multiple chatbots against each other to identify and neutralize malicious behavior. Additionally,

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Salesforce Lightning

Why Migrate From Salesforce Classic to Salesforce Lightning?

Why Switch from Salesforce Classic to Lightning? Salesforce is actively advancing the Lightning interface, and the reasons are compelling. The Lightning platform offers numerous advantages, including an improved user interface, quicker development times, and extensive customization options. With user-friendly features like drag-and-drop functionality, Lightning enhances the overall user experience (UX). Many companies are opting to migrate from Salesforce Classic to Salesforce Lightning to leverage these benefits and more. Salesforce Classic Salesforce Classic served as the primary interface until 2016, but today, it is considered outdated. Investing in Lightning Experience is driven by the desire to deliver a superior user experience, adopt features solving business challenges, enhance processes, and gain access to Lightning innovation and rapid app development technology. Given that Salesforce Lightning is faster, provides advanced customization features, and boasts easier navigation compared to Classic, transitioning to Lightning in 2023 can be a strategic decision for your business. Lightning also integrates Salesforce Einstein, offering reporting, analytics, and generative AI capabilities. Salesforce Lightning In contrast to Classic, the Lightning development platform enables non-technical users to effortlessly create customized apps without programming knowledge. Due to its sleek UI, faster performance, regular feature releases, and comprehensive usability, Salesforce Lightning has become the preferred CRM for businesses. Migration However, migrating from Salesforce Classic to Lightning, or any other CRM to Lightning, presents challenges, including high implementation time. Opting for a phased rollout is an effective approach to overcome these challenges. While challenges may arise, a strategic plan executed by experienced Salesforce Lightning Support can ensure a seamless and timely migration. If you’re ready to migrate to Salesforce Lightning, especially if your Salesforce is highly customized, it’s crucial to document all changes made in Classic and identify corresponding solutions in Lightning. If handling the complexities of Classic seems daunting, consider engaging a Salesforce Migration partner like Tectonic to conduct a full Salesforce audit before migrating to Salesforce Lightning, ensuring a smooth transition. Content updated December 2023. 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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Digital Transformation for Life Sciences

Digital Transformation for Life Sciences

In hindsight, one remarkable aspect of the COVID crisis was the speed with which vaccines passed through regulatory approval processes to address the pandemic emergency. Approvals that would typically take years were expedited to mere months, a pace not usually seen in the life sciences industry. It was an extraordinary situation, as Paul Shawah, Senior Vice President of Commercial Strategy at Veeva Systems, notes: “There were things that were unnaturally fast during COVID. There was a shifting of priorities, a shifting of focus. In some cases, you had the emergency approvals or the expedited approvals of the vaccines that you saw in the early days, so there was faster growth. Everything was kind of different in the COVID environment.” Today, the industry is not operating at that same rapid pace, but the impact of this acceleration remains significant: “What it did do is it challenged companies to think about why can’t we operate faster at a steady state? There was an old steady state, then there was COVID speed. The industry is trying to get to a new steady state. It won’t be as fast as during COVID because of unique circumstances, but expectations are now much higher. This drives a need to modernize systems, embrace the cloud, become more digital, and improve efficiency.” Companies like Veeva, alongside enterprise giants such as Salesforce, SAP, and Oracle, specialize in this market and play crucial roles in life sciences digitization. According to a McKinsey study, about 45% of tech spending in life sciences goes to three key technologies: applied Artificial Intelligence, industrialized Machine Learning, and Cloud Computing. Over 80% of the top 20 global pharma and medtech companies are operating in the cloud to some extent. However, a study by Accenture found that life sciences firms are among the lowest in achieving benefits from cloud investments, with only 43% satisfied with their results and less than a quarter confident that cloud migration initiatives will deliver the promised value within expected time frames. This presents both a challenge and an opportunity. Frank Defesche, SVP & GM of Life Sciences at Salesforce, sees it as the latter, stating: “The life sciences industry faces increased competition, evolving patient expectations, and ongoing pressure to bring devices and drugs to market faster. With rising drug costs, frustrated doctors, and varying regulatory scrutiny, life sciences organizations must find ways to do more with less.” The industry also contends with an unprecedented influx of data and disparate systems, making it difficult to move quickly. Addressing changes one by one is too slow and costly. Defesche believes that a systemic solution, fueled by connected data and Artificial Intelligence (AI), is key to overcoming these challenges. Paul Shawah of Veeva emphasizes the unique challenges of the life sciences sector: “Life sciences firms primarily do two things: discover and develop medicines, and commercialize them by educating doctors and getting the right drugs to patients. The drug development cycle includes clinical trials, managing everything related to drug safety, the manufacturing process, and ensuring quality. They also manage regulatory registrations. On the commercial side, it’s about reaching out to doctors and healthcare professionals.” Veeva’s Vault platform is designed for life sciences, with customers like Merck, Eli Lilly, and Boehringer Ingelheim. Shawah acknowledges it’s “still relatively early days” for cloud computing adoption but notes successes in areas like CRM, where Veeva achieved over 80% market share by standardizing processes and reducing technical debt. Other areas, like parts of the clinical trials process, remain largely untapped by cloud computing. Shawah sees opportunities to improve patient experiences and make the process more efficient. AI represents a significant area of opportunity. Shawah explains Veeva’s approach: “I’ll break AI into two categories: traditional AI, Machine Learning, and data science, which we’ve been doing for a long time, and generative AI, which is new. We’re focusing on finding use cases that create sustainable, repeatable value. We’re building capabilities into our Vault platform to support AI.” Joe Ferraro, VP of Product, Life Sciences at Salesforce, emphasizes AI’s critical role: “We are born out of the data and AI era, and we’re taking that philosophy into everything we do from a product standpoint. We aim to move from creating a system of record to a system of insight, using data and AI to transform how users interact with software.” Ferraro highlights the need for change: “Organizations told us, ‘Please don’t build the same thing we have now. We are mired in fragmented experiences. Our sales and marketing teams aren’t talking, and our medical and commercial teams don’t understand each other.’ Life Sciences Cloud aims to move the industry from these fragmented experiences to an end-to-end, AI-powered experience engine.” The COVID crisis highlighted the critical role of the life sciences industry. There’s a massive opportunity for digital transformation, whether through specialists like Veeva or enterprise players like Salesforce, Oracle, and SAP. Data must be the foundation of any solution, especially amidst the current AI hype cycle. Ensuring this data is well-managed is a crucial starting point for industry-wide change. 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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Order Management Enhancements Commerce Cloud

Order Management Enhancements Commerce Cloud

Salesforce Order Management Enhancements stands out for its scalability, catering to both small startups and large enterprises by offering customization to meet specific needs. Its adaptability facilitates seamless integration with other systems, presenting a comprehensive solution for e-commerce requirements. Explore the latest features in Salesforce Order Management and Lightning B2B Commerce, including process exception management, return merchandise authorizations, and various enhancements. Salesforce Order Management now provides tools to identify and address process exceptions during order processing interruptions. The addition of a new return order data model aids in managing return merchandise authorizations. Further updates include improved order summary flows, customization of payment methods, and the creation of order summaries with custom numbers and statuses. Enhancements to Lightning B2B Commerce introduce new components for deliveries and order summaries, improved searchability, an integration dashboard, and the Price Book Workspace. The integration dashboard consolidates management of integrations, providing a centralized overview. Order Management serves as the central hub for handling the entire order lifecycle, covering order capture, fulfillment, shipping, payment processing, and service. Customers can submit orders through any commerce channel, and merchants can efficiently manage fulfillment, shipping, invoicing, and service using integrated and customizable workflows. Salesforce Mobile App allows easy access to data on the go, although certain console features are not available. Order Management offers various resources, including preconfigured permission sets, Salesforce Payments integration for seamless payment processing, and extensive documentation for setup, administration, and extension. Salesforce Order Management utilizes Einstein Generative AI to enhance the overall experience, providing smarter service to customers. High-scale orders are supported on Hyperforce, offering increased capacity for order processing. For post-implementation monitoring and optimization, tracking key performance indicators (KPIs) such as order processing time, customer satisfaction, and inventory levels is crucial. Salesforce analytics aid in making data-driven improvements, and troubleshooting tools are available for resolving common issues like order discrepancies and payment failures. The Salesforce Order Management Implementation Guide outlines steps from initial setup and data migration to workflow customization, payment, and shipping integrations. Real-world case studies demonstrate successful implementations, showcasing the platform’s benefits, scalability, and advanced features. The retirement of Commerce Cloud Order Management is announced, with Salesforce Order Management positioned as the new product built within the Salesforce core platform. For further details or assistance, users are advised to contact their account manager or refer to Salesforce Order Management Help documentation. 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 SOQL Tools and AI

Salesforce SOQL Tools and AI

Salesforce Object Query Language (SOQL) is a robust instrument empowering users to retrieve data from Salesforce efficiently. With SOQL, you can interrogate any Salesforce object, spanning from custom objects to user permissions like profile and permission set perms. Salesforce SOQL Tools and AI. As a seasoned Salesforce Admin, crafting SOQL queries can often prove cumbersome. Not only must you master the syntax, but you must also ensure the queries are both effective and precise. Salesforce SOQL Tools and AI Fortunately, the advent of generative artificial intelligence (AI) tools offers a solution to this challenge. Generative AI tools, capable of producing text, code, and creative content, have emerged as invaluable aids in generating SOQL queries. Among these, Bard and ChatGPT have emerged as particularly helpful tools for crafting SOQL queries. In this discourse, I’ll illustrate how to leverage prompts to generate SOQL queries using these generative AI tools, providing query examples and resources to kickstart your journey with SOQL in your organization. Initiating SOQL Queries with Generative AI Tools To start, it’s essential to furnish the generative AI tool with pertinent information about the intended query. For instance, one might instruct the tool to generate a query retrieving all open opportunities. Subsequently, upon prompting: “Write SOQL that returns all open opportunities in Salesforce.” ChatGPT furnishes the following response: “SELECT Id, Name, StageName, CloseDate, Amount FROM Opportunity WHERE IsClosed = false” This query selects Opportunity records and retrieves their pertinent attributes, filtering the results to include only open opportunities based on the IsClosed field. Bard echoes a similar sentiment with its rendition of the query: “SELECT Id, Name, StageName, Amount, CloseDate FROM Opportunity WHERE IsClosed = false” However, the essence of prompt writing and critical thinking lies in refining the generated response. For instance, by slightly altering the prompt to include additional criteria: “Write SOQL that returns all open opportunities in Salesforce, including all standard fields and filtering results by StageName.” ChatGPT furnishes an adapted query: “SELECT Id, Name, AccountId, Amount, CloseDate, CreatedBy.Name, CreatedDate, LastModifiedBy.Name, LastModifiedDate, StageName FROM Opportunity WHERE StageName != ‘Closed Won’ AND StageName != ‘Closed Lost’” It’s worth noting that ChatGPT lacks insight into the specifics of your organization’s structure, necessitating occasional guidance to accommodate custom fields. However, through conversational cues, you can educate it accordingly: “My Salesforce org includes a custom field with the API name of NonProfit__c for Opportunity. It’s a boolean field. Please include it in all future SOQL queries on Opportunity.” To which ChatGPT responds: “Certainly! To include the custom field NonProfit__c in all future SOQL queries on Opportunity, you can modify the query as follows: SELECT Id, Name, AccountId, Amount, CloseDate, CreatedBy.Name, CreatedDate, LastModifiedBy.Name, LastModifiedDate, StageName, NonProfit__c FROM Opportunity WHERE StageName != ‘Closed Won’ AND StageName != ‘Closed Lost’” By incorporating NonProfit__c into the SELECT statement, the custom field is seamlessly integrated into the query results. Leveraging SOQL for User Permissions Reporting One particularly advantageous application of SOQL for Salesforce Admins is reporting on user permissions. By utilizing the SOQL Query tool in Code Builder or the Developer Console, admins can scrutinize permissions assigned to users via permission sets, profiles, objects, and fields. Here are a few illustrative examples of user permission SOQL queries, collaboratively devised with the assistance of ChatGPT: Check user permissions on an object: SELECT PermissionsRead, PermissionsCreate, PermissionsEdit, PermissionsDelete FROM ObjectPermissions WHERE ParentId IN (SELECT Id FROM PermissionSet WHERE PermissionSet.Name = ‘Your_Permission_Set_Name’) AND SObjectType = ‘Your_Object_Name’ AND PermissionsRead = true Check user permissions on a field: SELECT PermissionsRead, PermissionsEdit FROM FieldPermissions WHERE ParentId IN (SELECT Id FROM PermissionSet WHERE PermissionSet.Name = ‘Your_Permission_Set_Name’) AND SObjectType = ‘Your_Object_Name’ AND Field = ‘Your_Field_Name’ AND PermissionsRead = true Determine which permission sets grant Edit access for a specific field: SELECT ParentId, Parent.Name, Parent.Type, Field, PermissionsEdit, PermissionsRead, SobjectType FROM FieldPermissions WHERE Parent.IsOwnedByProfile = true AND Field = ‘ADM_Work__c.Subject__c’ AND PermissionsEdit = True Identify users assigned managed packages: SELECT Id, UserId, PackageLicense.NamespacePrefix FROM UserPackageLicense WHERE PackageLicense.NamespacePrefix = ‘YOUR_PREFIX_HERE’ Embark on Efficient SOQL Query Generation Today With generative AI tools, initiating sample SOQL queries becomes a n easier process, alleviating the need to grapple with syntax intricacies. For admins who occasionally require SOQL queries and find themselves toggling between documentation and references to commence, leveraging generative AI represents a compelling alternative. Here are some additional pointers for harnessing generative AI tools to craft SOQL queries effectively: Be precise: Furnish the tool with specific instructions to ensure accuracy and efficiency in query generation. Provide examples: Supplying the tool with query examples aids in generating more tailored queries. Test rigorously: Following query generation, ensure thorough testing to verify the returned results align with expectations. Ultimately, by harnessing the power of generative AI, admins can streamline the process of crafting SOQL queries, thereby enhancing productivity and efficiency in Salesforce data management endeavors. Data analysis serves as a cornerstone of business strategy, yet crafting custom SOQL queries to import specific Salesforce data can prove complex and time-consuming, particularly for those without coding expertise. When you add the necessity to amalgamate data from various systems, the process becomes even more cumbersome and inefficient. Coefficient Salesforce SOQL Tools and AI In this insight, we’ll demonstrate how Coefficient’s Formula Builder, powered by GPT, streamlines the creation of custom SOQL functions, and how Coefficient facilitates direct data imports from Salesforce within Google Sheets, all seamlessly integrated into your workflow without ever leaving your spreadsheet. To get started, launch the Coefficient add-on directly within your Google Sheets. If you haven’t already installed Coefficient, simply navigate to the Google Workspace Marketplace to acquire it. Here’s how to install Coefficient: Now that you have Coefficient installed, you can effortlessly import your live Salesforce data. In the Coefficient sidebar within Google Sheets, follow these steps: To do this, follow these steps: The Formula Builder will promptly generate a custom SOQL query based on your specifications. Simply copy this query, and you’re ready to go. With Coefficient, data analysis becomes more efficient and accessible, empowering users of all skill levels to harness the power of Salesforce data seamlessly within Google

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Salesforce Sales Cloud

Salesforce Sales Cloud Explained

Salesforce Sales Cloud is Salesforce’s premier product, originating with the company’s birth in 1999, and currently commands the largest market share among all available Customer Relationship Management (CRM) solutions. With a core mission to expedite the sales cycle, Sales Cloud furnishes companies with an array of tools for efficient management of leads, opportunities, businesses, and individual contacts. While it predominantly caters to Business-to-Business (B2B) enterprises, Sales Cloud encompasses features like quoting, product management, and forecasting tailored to meet the needs of sales managers. In addition to its foundational features, Sales Cloud offers a suite of add-on products that further enhance its capabilities. These include Sales Cloud Einstein, Inbox, Salesforce Maps, Lightning Dialer, Lightning Scheduler, Salesforce Engage, Einstein Sales Analytics, and Revenue Analytics. These supplementary products provide advanced functionalities and analytics, elevating the overall sales experience for businesses utilizing Sales Cloud. What does Salesforce do? It helps teams work better together. Your business may use a single Customer 360 app, or a combination of many. By improving team communications, automating repetitive tasks, and surfacing more insights with the help of AI, our customers drive greater business success. Connect the dots between marketing and sales. Bring all your customer data together in one place to inform campaign strategy, audiences, and content. Use generative AI to create personalized messages and send them to prospects right where they are most likely to engage with them. When customers click on your ad or website, an automated message is sent to sales, notifying the team of a new lead. Tectonic is please to announce our Sales Cloud Implementation Solutions. 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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Roles in AI

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 Elm furniture store on University Avenue in Palo Alto. A group of artificial intelligence enthusiasts within Salesforce, seeking to enhance the impact of machine learning models, embarked on this mission two years ago. While shoppers checked out furniture above, they developed a system to automate the creation of machine learning models. Thus Salesforce’s Quest for AI for the Masses started. Despite being initially named after the Transformers leader, the tie-in was abandoned, and Salesforce named its AI program Einstein. This move reflects the ambitious yet practical approach Salesforce takes in the AI domain. In March, a significant portion of Einstein became available to all Salesforce users, aligning with the company’s tradition of making advanced software accessible via the cloud. Salesforce, although now an industry giant, retains its scrappy upstart identity. When the AI trend gained momentum, the company aimed to create “AI for everyone,” focusing on making machine learning affordable and accessible to businesses. This populist mission emphasizes practical applications over revolutionary or apocalyptic visions. Einstein’s first widely available tool is the Einstein Intelligence module, designed to assist salespeople in managing leads effectively. It ranks opportunities based on factors like the likelihood to close, offering a practical application of artificial intelligence. While other tech giants boast significant research muscle, Salesforce focuses on providing immediate market advantages to its customers. Einstein Intelligence The Einstein Intelligence module employs machine learning to study historical data, identifying factors that predict future outcomes and adjusting its model over time. This dynamic approach allows for subtler and more powerful answers, making use of various data sources beyond basic Salesforce columns. Salesforce’s AI team strives to democratize AI by offering ready-made tools, ensuring businesses can benefit from machine learning without the need for extensive customization by data scientists. The company’s multi-tenant approach, serving 150,000 customers, keeps each company’s data separate and secure. Salesforce’s Quest for AI for the Masses To scale AI implementation across its vast customer base, Salesforce developed Optimus Prime. This system automates the creation of machine learning models for each customer, eliminating the need for extensive manual involvement. Optimus Prime, the AI that builds AIs, streamlines the process and accelerates model creation from weeks to just a couple of hours. Salesforce plans to expand Einstein’s capabilities, allowing users to apply it to more customized data and enabling non-programmers to build custom apps. The company’s long-term vision includes exposing more of its machine learning system to external developers, competing directly with AI heavyweights like Google and Microsoft in the business market. Originally published in WIRED magazine on August 2, 2017 and rewritten for this insight. 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 CRM for AI driven transformation

Salesforce Artificial Intelligence

Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust AI technologies directly into users’ workspaces. The Einstein Platform offers administrators and developers a comprehensive suite of platform services, empowering them to create smarter applications and tailor AI solutions for their enterprises. What is the designated name for Salesforce’s AI? Salesforce Einstein represents an integrated array of CRM AI technologies designed to facilitate personalized and predictive experiences, enhancing the professionalism and attractiveness of businesses. Since its introduction in 2016, it has consistently been a leading force in AI technology within the CRM realm. Is Salesforce Einstein a current feature? “Einstein is now every customer’s data scientist, simplifying the utilization of best-in-class AI capabilities within the context of their business.” Is Salesforce Einstein genuinely AI? Salesforce Einstein for Service functions as a generative AI tool, contributing to the enhancement of customer service and field service operations. Its capabilities extend to improving customer satisfaction, cost reduction, increased productivity, and informed decision-making. Salesforce Artificial Intelligence AI is just the starting point; real-time access to customer data, robust analytics, and business-wide automation are essential for AI effectiveness. Einstein serves as a comprehensive solution for businesses to initiate AI implementation with a trusted architecture that prioritizes data security. Einstein is constructed on an open platform, allowing the safe utilization of any large language model (LLM), whether developed by Salesforce Research or external sources. It offers flexibility in working with various models within a leading ecosystem of LLM platforms. Salesforce’s commitment to AI is evident through substantial investments in researching diverse AI areas, including Conversational AI, Natural Language Processing (NLP), Multimodal Data Intelligence and Generation, Time Series Intelligence, Software Intelligence, Fundamentals of Machine Learning, Science, Economics, and Environment. These endeavors aim to advance technology, improve productivity, and contribute to fields such as science, economics, and environmental sustainability. Content updated April 2023. 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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