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Salesforce to Acquire Own
25Feb

Elevating Data Resilience, Compliance & Security

Elevating Data Resilience, Compliance & Security with Own on Salesforce Platform A New Era of Data Protection Following Salesforce’s acquisition of Own Company in 2024, we’re proud to integrate Own’s industry-leading data protection solutions into the Salesforce Platform. This powerful combination delivers unmatched data resilience, compliance assurance, and enterprise-grade security—trusted by over 7,000 customers worldwide. Fortify Your Data Resilience 1. Salesforce Backup & Recover (Formerly Own Recover – #1 Enterprise SaaS Backup on G2) “Recover a single deleted opportunity record from yesterday’s accidental purge in 2 clicks.” 2. Salesforce Discover “Analyze 3 years of seasonal sales patterns directly from archived data.” 3. Archive “Reduce production org storage costs by 40% while maintaining compliance.” Streamline Compliance & Development 4. Enhanced Data Mask & Seed “Create a fully masked sandbox with production-like data in minutes.” Next-Gen Security for the AI Era 5. Shield 2.0 6. Security Center 2.0 “Identify and remediate excessive Agentforce permissions before deployment.” Why This Matters Now “With Own’s technology now native to Salesforce Platform, customers gain an enterprise data safety net that works seamlessly with their existing CRM, AI, and analytics workflows.” – Salesforce Product Leadership Next Steps: Available now for all Enterprise Edition customers. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 25, 2025in Data, Enterprise, Salesforce, Technology
Storing and Querying Log Data with Event Log Objects
25Feb

Storing and Querying Log Data with Event Log Objects

The Event Log Object framework provides a structured way to access event data stored in Salesforce. Unlike Event Log Files, which present event data as downloadable CSV files, Event Log Objects allow users to query event logs directly using SOQL. This approach offers a more integrated and dynamic way to analyze security, performance, and user activity data within Salesforce. Key Features of Event Log Objects Availability and Requirements Enabling Event Log Objects To enable Event Log Objects, follow these steps in Setup: Querying Event Log Data Event Log Objects provide valuable insights through SOQL queries, allowing organizations to track activity across security, application performance, and user engagement. Sample Queries by Use Case Security Analysis Identify users exporting the most rows via reports: sqlCopyEditSELECT UserIdentifier, SUM(RowCount) FROM ReportEventLog WHERE Origin=’ReportExported’ AND DAY_ONLY(Timestamp) > LAST_N_DAYS:10 GROUP BY UserIdentifier ORDER BY SUM(RowCount) DESC Application Performance Monitoring (APM) Track unexpected Apex exceptions by category: sqlCopyEditSELECT ExceptionCategory, COUNT(Timestamp) FROM ApexUnexpectedExcpEventLog WHERE DAY_ONLY(Timestamp) > LAST_N_DAYS:10 GROUP BY ExceptionCategory ORDER BY COUNT(Timestamp) DESC Product Intelligence Determine the most loaded Lightning pages: sqlCopyEditSELECT COUNT(Timestamp), PageUrl FROM LightningPageViewEventLog WHERE DAY_ONLY(Timestamp) > LAST_N_DAYS:10 GROUP BY PageUrl ORDER BY COUNT(Timestamp) DESC Key Considerations Available Event Log Objects Salesforce provides a wide range of Event Log Objects, each designed to capture specific types of system events: Visualizing Log Data with CRM Analytics Organizations can transform raw log data into actionable insights using Salesforce Direct in CRM Analytics. This enables users to: Best Practices for Event Log Objects To maximize the value of Event Log Objects, follow these best practices: By effectively leveraging Event Log Objects, organizations can enhance security monitoring, troubleshoot performance issues, and gain deeper insights into Salesforce activity. For more details on Event Log Objects and their use cases, refer to the Salesforce Object Reference Guide. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 25, 2025in Data, Enterprise, Hyperforce, Salesforce, Salesforce Shield
Salesforce’s AI Energy Score
08Feb

Salesforce’s AI Energy Score

Salesforce’s AI Energy Score: Setting a New Standard for AI Sustainability Understanding AI’s Environmental Impact As AI adoption accelerates globally, concerns about its environmental footprint have grown. Due to AI’s reliance on power-intensive data centers, the technology consumes vast amounts of energy and water, raising sustainability challenges. To address this, Salesforce, in collaboration with Hugging Face, Cohere, and Carnegie Mellon University, has introduced the AI Energy Score—a pioneering tool designed to measure and compare AI models’ energy efficiency. The AI Energy Score Launch The AI Energy Score will debut at the AI Action Summit on February 10, 2025, where leaders from over 100 countries, along with private sector and civil society representatives, will convene to discuss AI’s role in sustainability. Recognized by the French Government and the Paris Peace Forum, this initiative marks a significant step toward transparent and accountable AI development. “We are at a critical moment where the rapid acceleration of both the climate crisis and AI innovation intersect,” says Boris Gamazaychikov, Head of AI Sustainability at Salesforce.“AI’s environmental impact has remained largely opaque, with little transparency around its energy consumption. The AI Energy Score provides a standardized framework to disclose and compare these impacts, removing a key blocker to making sustainable AI the norm.” What Is the AI Energy Score? Developed in partnership with Hugging Face, Cohere, and Carnegie Mellon University, the AI Energy Score aims to establish clear and standardized energy consumption metrics for AI models. “The AI Energy Score is a major milestone for sustainable AI,” says Dr. Sasha Luccioni, AI & Climate Lead at Hugging Face. “By creating a transparent rating system, we address a key blocker for reducing AI’s environmental impact. We’re excited to launch this initiative and drive industry-wide adoption.” Key features of the AI Energy Score include: ✅ Standardized energy ratings – A framework for evaluating AI models’ energy efficiency✅ Public leaderboard – A ranking of 200+ AI models across 10 common tasks (e.g., text and image generation)✅ Benchmarking portal – A platform for submitting and assessing AI models, both open and proprietary✅ Recognizable energy use label – A 1–5 star system for easy identification of energy-efficient models✅ Label generator – A tool for AI developers to create and share standardized energy labels The Impact of the AI Energy Score The introduction of this score is expected to have far-reaching implications for the AI industry: 🔹 Driving market preference – Transparency will push demand for more energy-efficient AI models🔹 Incentivizing sustainable development – Public disclosure will encourage AI developers to prioritize efficiency🔹 Empowering informed decisions – AI users and businesses can make better choices based on energy efficiency data Salesforce’s Commitment to Sustainable AI Salesforce is leading by example, becoming the first AI model developer to disclose energy efficiency data for its proprietary models under this framework. This aligns with the company’s broader sustainability goals and ethical AI approach. Agentforce: AI Efficiency at Scale Salesforce’s Agentforce platform, introduced in 2024, is designed to deploy autonomous AI agents across business functions while maintaining energy efficiency. “Agentforce is built with sustainability at its core, delivering high performance while minimizing environmental impact,” explains Boris Gamazaychikov.“Unlike DIY AI approaches that require energy-intensive model training for each customer, Agentforce is optimized out of the box, reducing costly and carbon-heavy training.” Organizations are already leveraging Agentforce for impact-driven efficiencies: ✅ Good360 uses Agentforce to allocate donated goods more efficiently, cutting waste and emissions while saving 1,000+ employee hours annually✅ Businesses can reduce operational costs by optimizing AI model energy consumption “Reducing AI energy use isn’t just good for the environment—it lowers costs, optimizes infrastructure, and improves long-term profitability,” says Suzanne DiBianca, EVP & Chief Impact Officer at Salesforce.“We’re proud to work with industry leaders to build a more transparent AI ecosystem.” Addressing the AI Energy Challenge With AI-driven data center power usage projected to double by 2026, the AI Energy Score is a timely solution to help organizations manage and reduce their AI-related environmental impact. “The AI Energy Score isn’t just an energy-use metric—it’s a strategic business advantage,” adds Boris Gamazaychikov. “By helping organizations assess and optimize AI model energy consumption, it supports lower costs, better infrastructure efficiency, and long-term profitability.” As AI continues to evolve, sustainability must be part of the equation. The AI Energy Score is a major step in ensuring that the AI industry moves toward a more responsible, energy-efficient future.: Setting a New Standard for AI Sustainability Understanding AI’s Environmental Impact As AI adoption accelerates globally, concerns about its environmental footprint have grown. Due to AI’s reliance on power-intensive data centers, the technology consumes vast amounts of energy and water, raising sustainability challenges. To address this, Salesforce, in collaboration with Hugging Face, Cohere, and Carnegie Mellon University, has introduced the AI Energy Score—a pioneering tool designed to measure and compare AI models’ energy efficiency. The AI Energy Score Launch The AI Energy Score will debut at the AI Action Summit on February 10, 2025, where leaders from over 100 countries, along with private sector and civil society representatives, will convene to discuss AI’s role in sustainability. Recognized by the French Government and the Paris Peace Forum, this initiative marks a significant step toward transparent and accountable AI development. “We are at a critical moment where the rapid acceleration of both the climate crisis and AI innovation intersect,” says Boris Gamazaychikov, Head of AI Sustainability at Salesforce.“AI’s environmental impact has remained largely opaque, with little transparency around its energy consumption. The AI Energy Score provides a standardized framework to disclose and compare these impacts, removing a key blocker to making sustainable AI the norm.” What Is the AI Energy Score? Developed in partnership with Hugging Face, Cohere, and Carnegie Mellon University, the AI Energy Score aims to establish clear and standardized energy consumption metrics for AI models. “The AI Energy Score is a major milestone for sustainable AI,” says Dr. Sasha Luccioni, AI & Climate Lead at Hugging Face. “By creating a transparent rating system, we address a key blocker for reducing AI’s

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February 8, 2025in Agentforce Platform, Data, Salesforce, Technology
Agentforce Redefines Generative AI
16Jan

Agentforce Redefines Generative AI

Agentforce: Redefining Generative AI in Salesforce Many Dreamforce attendees who expected to hear about Einstein Copilot were surprised when Salesforce introduced Agentforce just a week before the conference. While it might seem like a rebranding of Copilot, Agentforce marks a significant evolution by enabling more autonomous agents that go beyond summarizing or generating content to perform specific actions. Here’s a breakdown of the transition and what it means for Salesforce users: Key Vocabulary Updates How Agentforce Works Agents take user input, known as an “utterance,” and translate it into actionable steps based on predefined configurations. This allows the system to enhance performance over time while delivering responses tailored to user needs. Understanding Agentforce 1. Topics: Organizing Agent Capabilities Agentforce introduces “Topics,” a new layer of organization that categorizes actions by business function. When a user provides an utterance, the agent identifies the relevant topic first, then determines the best actions to address it. 2. Actions: What Agents Can Do Actions remain largely unchanged from Einstein Copilot. These are tasks agents perform to execute plans. 3. Prompts: The Key to Better Results LLMs rely on prompts to generate outputs, and crafting effective prompts is essential for reducing irrelevant responses and optimizing agent behavior. How Generative AI Enhances Salesforce Agentforce unlocks several benefits across productivity, personalization, standardization, and efficiency: Implementing Agentforce: Tips for Success Getting Started Start by using standard Agent actions. These out-of-the-box tools, such as opportunity summarization or close plan creation, provide a strong foundation. You can make minor adjustments to optimize their performance before diving into more complex custom actions. Testing and Iteration Testing AI agents is different from traditional workflows. Agents must handle various phrasing of the same user request (utterances) while maintaining consistency in responses. The Future of Salesforce with Agentforce As you gain expertise in planning, developing, testing, and deploying Agentforce actions, you’ll unlock new possibilities for transforming your Salesforce experience. With generative AI tools like Agentforce, Salesforce evolves from a traditional point-and-click interface into an intelligent, agent-driven platform with streamlined, conversational workflows. This isn’t just an upgrade — it’s the foundation for reimagining how businesses interact with their CRM in an AI-assisted world. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 16, 2025in Agentforce Platform, AI Tools, Data, Generative AI, Salesforce
Salesforce Spring ’25 Release
09Jan

Salesforce Spring ’25 Release

Salesforce Spring ’25 Release: Key Features and Enhancements Salesforce delivers triannual updates—Spring, Summer, and Winter—to introduce new features, enhancements, and fixes to the platform. These updates are applied automatically to Salesforce environments, ensuring all users benefit from the latest innovations without needing manual upgrades. The Spring ’25 functionality is now available in Preview Developer Orgs, allowing users to explore and test upcoming features before the general release. Preview Developer Orgs: Exploring the Future Preview Developer Orgs provide sandbox environments or developer editions equipped with new release functionality during the preview window. These allow admins and developers to: With access to a Preview Org, you can explore the following cutting-edge features: 1. Reactive Screen Actions Enhanced Screen Flow Reactivity: This feature enables screen flow components to update dynamically in real-time based on changes in other components. Users no longer need to navigate away or manually refresh to see updates, ensuring smoother, more interactive experiences. New in Spring ’25:You can now create an autolaunched flow to fetch data reactively from the database and display it immediately on the screen, eliminating the need for an action button. Use Case:When creating an Opportunity, the ZIP code of the associated Account determines the follow-up owner based on a reference table stored in a custom object. With reactive screen actions, selecting an Opportunity row dynamically displays the Account, Owner, and Assigned Person without additional clicks. 2. Progress Indicator for Flow Stages Salesforce introduces a built-in Progress Indicator for screen flows, providing users with a visual tracker of their progress through multi-step flows. Key Features: Limitations:The progress indicator does not yet support user-driven navigation through stages. 3. Immediate Input Validation in Screen Flows Validation functionality in flows has been upgraded to support real-time error detection. What’s New: 4. Email Action Attachment Support Email Action Enhancements: Spring ’25 introduces the ability to attach files to emails directly within flows. How It Works: Note: Files do not need to be made public for attachments, as long as the flow user has access to the files. 5. Get Records with a Specified Limit The LIMIT operator, commonly used in SOQL, is now available in flows. Benefits: 6. New Flow Modal Enhancements Salesforce has redesigned the Flow Type Picker modal, making it easier for users to select the right automation type. What’s New: 7. UI and Accessibility Improvements Conclusion The Salesforce Spring ’25 release is packed with features designed to enhance efficiency, usability, and innovation. From reactive screen flows and real-time validation to email action attachments and improved UI elements, this release sets a new standard for how users interact with the Salesforce platform. Stay ahead by leveraging Preview Developer Orgs to test these enhancements and ensure a smooth transition to the production environment. As Salesforce continues to innovate, these updates are just the beginning of a more seamless, intelligent platform experience. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 9, 2025in Data, Salesforce

Service Cloud or Sales Cloud for Service

4 Reasons to Use Salesforce Service Cloud Over Sales Cloud’s Standard Case Functionality When businesses aim to elevate their customer support operations, Salesforce is often their platform of choice. While Sales Cloud and Service Cloud both help manage customer interactions, their core purposes differ. Sales Cloud focuses on managing the sales pipeline, whereas Service Cloud is specifically designed to optimize customer service and support processes. Here are four compelling reasons to choose Service Cloud for your customer support needs. 1. Advanced Case Management Features Service Cloud offers robust tools to manage customer cases with efficiency, far surpassing the basic case functionality available in Sales Cloud. Key Service Cloud Features: While Sales Cloud does support basic case management, it lacks these advanced features. Attempting to replicate them in Sales Cloud often requires extensive customization and development. 2. Omni-Channel Support for Seamless Customer Communication Modern customer service spans multiple channels, including chat, email, phone, and social media. Service Cloud provides powerful omni-channel capabilities to unify communication across all these touchpoints—something Sales Cloud does not offer. Key Service Cloud Features: Sales Cloud’s functionality centers on sales processes, leaving it without native support for omni-channel routing or social media integrations for customer support. 3. Knowledge Base for Self-Service and Agent Efficiency Service Cloud enables organizations to build and maintain a knowledge base, empowering both customers and agents with quick access to solutions. Key Service Cloud Features: Sales Cloud does not include tools for creating a knowledge base, self-service portals, or case deflection, as it is designed primarily for sales teams. 4. Entitlements and Service Contracts for Enhanced Customer Support Service Cloud provides specialized tools for managing entitlements and service contracts, ensuring customers receive the level of support they’re entitled to. Key Service Cloud Features: Sales Cloud does not offer dedicated features for managing entitlements or service contracts, limiting its utility for businesses focused on structured customer support. Why Service Cloud is the Better Choice for Customer Support While Sales Cloud is a powerful tool for managing sales pipelines, it falls short in addressing the complex needs of modern customer support. Service Cloud provides: If your priority is delivering exceptional customer support and enhancing customer satisfaction, Service Cloud is the clear choice. With its comprehensive features, your support team will be empowered to work more efficiently, resolve issues faster, and provide outstanding service across all channels. Invest in Service Cloud to transform your support operations and create seamless, satisfying experiences for your customers. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 6, 2025in Salesforce, Salesforce Service Cloud
Agentic AI is Here
02Jan

Agentic AI Revolution

The Agentic AI Revolution: Lead, Follow, or Get Out of the Way The era of agentic AI is here, and the message is clear—if you’re not leading the charge, you’re falling behind. Companies like Wiley and OpenTable are reshaping their industries with autonomous AI agents that don’t just assist but also analyze, strategize, and execute tasks with unparalleled efficiency. As these organizations demonstrate, the key to AI success lies in rewriting the rules of your industry rather than playing catch-up. Rewriting Industry Standards with Agentic AI Wiley: The education giant leveraged Agentforce, a digital labor platform for deploying autonomous AI agents, to transform its customer service operations. By onboarding representatives 50% faster and improving case resolution by 40%, Wiley streamlined its processes in just a few weeks. AI agents now handle registration and payment inquiries, directing students to resources and reducing the workload on human representatives. OpenTable: As the go-to reservation platform for 1.7 billion diners annually, OpenTable deploys AI agents to manage reservation changes and loyalty points. This allows employees to focus on customer relationships. Even a two-minute efficiency gain per interaction translates to massive operational savings. Salesforce Help Site: With over 60 million annual visits, the Salesforce Help site integrated Agentforce to resolve 83% of queries without human involvement. In just weeks, Agentforce doubled its capacity, handling over 32,000 automated conversations. These examples showcase a new era of digital labor where AI agents orchestrate high-value, multistep tasks, working tirelessly to deliver results. Far from replacing humans, they supercharge productivity and innovation, enabling companies to do more than ever before. How to Empower Your Workforce with AI Empowering your workforce for the next wave of AI doesn’t require months of preparation or millions of dollars. You don’t need to build or train your own large language model (LLM). Instead, integrating AI with existing data, automation, and workflows is the key to success, as demonstrated by leaders like Wiley and OpenTable. Here’s how to get started: 1. Real-Time Data Access AI thrives on real-time, high-quality data. Platforms like Salesforce Data Cloud unify structured and unstructured data, connecting it seamlessly to the LLM. Techniques such as retrieval-augmented generation (RAG) and semantic search ensure AI agents can access the most relevant data for any task. 2. Advanced Reasoning AI agents aren’t just about answering queries—they execute complex, multistep tasks. For example, they can process returns, reorder items, and even flag anomalies. Powered by reasoning engines, these agents draw data from systems like CRM, refine plans, and adapt dynamically until the task is completed correctly. 3. Built-In Security AI agents must operate within clear guardrails, knowing their limits and handing tasks off to humans when necessary. Strong permissions and security protocols are essential to ensure data protection and prevent unauthorized actions. 4. Action-Oriented Workflows Generative AI’s real value lies in action. By integrating tools like Salesforce Flow for task automation and MuleSoft APIs for system connectivity, AI agents can execute business workflows such as fraud detection, customer outreach, and case management. 5. Human-AI Collaboration The future of work isn’t AI replacing humans—it’s AI and humans working together. While agents handle data-intensive and repetitive tasks, humans bring strategic thinking, empathy, and creativity. This synergy leads to smarter decisions and redefines workflows across industries. Why Training Your Own LLM May Not Be the Answer Many companies assume training a proprietary LLM will give them a competitive edge. In reality, this process is costly, time-intensive, and requires constant updates to remain accurate. An LLM trained on static data quickly becomes outdated, much like a GPS that fails after the first detour. Instead, companies are turning to out-of-the-box AI solutions that integrate seamlessly with their existing systems. These tools offer the flexibility to scale quickly and adapt in real time, enabling businesses to stay competitive without the heavy lift of building from scratch. Scaling AI for the Future Many organizations remain stuck in pilot phases with AI due to data quality issues and a limited understanding of use cases. Companies like Wiley and OpenTable, however, have cracked the code: integrating prebuilt AI systems with robust data flows, automation, and workflows. By embracing agentic AI, forward-thinking organizations are creating digital labor forces that unlock new efficiencies, enhance customer experiences, and position themselves for long-term success. The trillion-dollar AI opportunity awaits—will you lead or trail behind? Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 2, 2025in Agentforce Platform, Agentic AI, Data, Generative AI, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Flow
AI is revolutionizing BI by transforming it from a retrospective tool into a proactive, real-time decision-making engine.
30Dec

AI in Business Intelligence

AI in Business Intelligence: Applications, Benefits, and Challenges AI is rapidly transforming business intelligence (BI) by enhancing analytics capabilities and streamlining processes. This shift is reshaping how organizations leverage data for decision-making. Here’s an in-depth look at how AI complements BI, its advantages, and the challenges it introduces. The Evolution of Business Intelligence with AI BI has traditionally focused on aggregating historical and current data to provide insights into business operations—a process known as descriptive analytics. However, many decision-makers seek more: insights into future trends (predictive analytics) and actionable recommendations (prescriptive analytics). AI bridges this gap. With advanced tools like natural language processing (NLP) and machine learning (ML), AI enables businesses to move beyond static dashboards to dynamic, real-time insights. It also simplifies complex analytics, making data more accessible to business users and fostering more informed, proactive decision-making. Key Benefits of AI in Business Intelligence AI brings significant benefits to BI, including: Real-World Applications of AI in BI AI’s integration into BI goes beyond internal efficiency, delivering external value by enhancing customer experiences and driving business growth. Notable applications include: Challenges of AI in Business Intelligence Despite its potential, integrating AI into BI comes with challenges: Best Practices for AI-Driven BI To successfully integrate AI with BI, organizations should: Future Trends in AI and BI AI is expected to augment rather than replace BI, enhancing its capabilities while keeping human expertise central. Emerging trends include: Conclusion AI is revolutionizing BI by transforming it from a retrospective tool into a proactive, real-time decision-making engine. While challenges remain, thoughtful implementation and adherence to best practices can help organizations unlock AI’s full potential in BI. By integrating AI into existing BI workflows, businesses can drive innovation, improve decision-making, and create more agile and data-driven operations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 30, 2024in AI Tools, Data, Generative AI
Sales Email Prompt Template
28Dec

Sales Email Prompt Template

Salesforce Guide: Creating a Sales Email Prompt Template Want to create personalized, targeted sales emails efficiently? By leveraging Salesforce’s LLM capabilities, you can design a Sales Email Prompt Template that uses customer insights and relationship history to generate high-quality emails at scale. Reusable for different products and audiences, these templates save time and simplify workflows. Here’s how to set it up: 1. Enable Einstein Setup 2. Enable Einstein for Sales 3. Create a Sales Email Prompt Template 4. Draft and Ground the Prompt in the Template Workspace 🔔🔔  Follow us on LinkedIn  🔔🔔 Example Prompt: plaintextCopy codeYou are a {!$Input:Sender.Title} and your name is {!$Input:Sender.Name} from {!$Input:Sender.CompanyName}. Your prospect is {!$Input:Recipient.Name}, a {!$Input:Recipient.Title}. They are based in {!$Input:Recipient.MailingCity}. In the email, invite the prospect to attend the event “Floating on Clouds: Ontario Kickoff” on September 18. This event is for customers of Cloud Kicks, new and old, to network and preview upcoming products. Keep the email within 70 words, explain the benefits of attending, and mention that you’d be happy to chat further at the event or online if needed. 5. Preview the Template 6. Save and Activate the Prompt 7. Send Emails Using the Prompt 8. Adjust and Finalize the Email By following these steps, you can seamlessly create and use dynamic sales email templates to elevate your outreach efforts. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 28, 2024in Agentforce Platform, Generative AI
Integrate Digital Delivery and Human Connection
21Dec

Types of Salesforce Integration

Types of Salesforce Integration: A Comprehensive Guide As a leading CRM platform, Salesforce is often required to integrate with other systems to deliver a seamless experience and ensure efficient business operations. Whether it’s syncing data, automating workflows, or enabling real-time communication, Salesforce provides robust integration methods tailored to various needs. In this guide, we’ll explore the different types of Salesforce integrations, their practical applications, and how to choose the right approach for your business. Why Integrate Salesforce? Integrating Salesforce with other systems empowers businesses to: Types of Salesforce Integration 1. Data Integration Ensures data consistency between Salesforce and external systems, enabling seamless synchronization. 2. Process Integration Links workflows across systems, ensuring actions in one system trigger automated processes in another. 3. User Interface (UI) Integration Combines multiple applications into a single interface for a unified user experience. 4. Application Integration Connects Salesforce with external apps for real-time data exchange and functional synchronization. 5. Real-Time Integration Facilitates instant synchronization of data and events between Salesforce and external systems. 6. Batch Integration Processes large data volumes in chunks, typically during off-peak hours. 7. Hybrid Integration Combines multiple integration types, such as real-time and batch, to handle complex requirements. Tools for Salesforce Integration Native Salesforce Tools: Third-Party Tools: Best Practices for Salesforce Integration Conclusion Salesforce integration is essential for streamlining operations and unlocking business potential. With options like data, process, and real-time integration, Salesforce offers the flexibility to meet diverse needs. By adopting the right integration approach and adhering to best practices, businesses can create a unified, efficient ecosystem, enhancing operations and improving customer experience. Whether integrating with ERP systems, marketing tools, or support platforms, Salesforce provides the tools to make integration seamless and impactful. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 21, 2024in Data, Enterprise, Marketing Automation, Mulesoft, Salesforce, Salesforce Flow
AI Sales Agents Explained
20Dec

AI Sales Agents Explained

If you were to ask a sales rep why they chose a job in sales, they’d probably tell you something like, “I love helping to people. I’m ambitious and goal-oriented, and no two days are ever the same.” The reality, however, is that a lot of time in sales isn’t spent selling. Recent data suggests that sales reps dedicate only 28% of their time to actual selling, with the rest swallowed up by administrative tasks and non-revenue-generating work. To ease this burden, sales teams are turning to AI sales agents, enabling them to focus more on building relationships and closing deals. Below, we explore the different types of AI sales agents and how businesses are using them to increase productivity, efficiency, and revenue. What is an AI sales agent? AI sales agents are autonomous applications that analyze and learn from sales and customer data to perform tasks with little or no human intervention. These agents can manage a wide range of activities, from top-of-funnel tasks like nurturing leads via email outreach, answering questions, booking meetings, and generating quotes to more integrated sales support like buyer roleplays and coaching. Unlike simple workflow automation, AI agents are capable of learning, enabling them to improve efficiency and act independently based on data and analysis. They often plug directly into existing CRMs, with pre-built capabilities or customizable configurations for specific business needs. Types of AI sales agents There are two primary types of AI sales agents: The ability to autonomously analyze data, create action plans, and execute them sets modern AI sales agents apart from traditional sales tools and bots. Key features of AI sales agents Benefits of AI sales agents Future trends for AI sales agents In the early days, AI in sales served primarily as a co-pilot — summarizing insights and assisting with tasks like forecasting. It often required significant human input and created siloed data challenges. Today, AI agents autonomously augment human teams, empowering them to focus on high-value tasks like building relationships. In the near future, AI sales agents are expected to handle increasingly complex workflows and multi-step processes across diverse channels. Potential advancements include: These developments promise to unlock new possibilities for efficiency, personalization, and customization in sales teams. AI sales agents pushing teams into a new era According to recent data, sales leaders are focusing on improving sales enablement, targeting new markets, and adopting new tools and technologies to drive growth. Challenges like scaling personalized interactions and hitting quotas are top of mind. AI sales agents directly address these needs, transforming sales organizations by enabling teams to offload repetitive work to autonomous systems while maintaining quality and personalization. Who uses AI sales agents? AI sales agents are used by sales teams to manage tasks such as lead qualification, follow-ups, meeting scheduling, and coaching. By handling repetitive activities, these agents free up reps to focus on relationship-building and closing deals, ultimately driving better outcomes for both teams and customers. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 20, 2024in Agentforce Platform, Data
AI Agents and Consumer Trust
13Dec

AI Agents Next AI Evolution

AI agents are being hailed as the next big leap in artificial intelligence, but there’s no universally accepted definition of what they are—or what they should do. Even within the tech community, there’s debate about what constitutes an AI agent. At its core, an AI agent can be described as software powered by artificial intelligence that performs tasks once handled by human roles, such as customer service agents, HR representatives, or IT help desk staff. However, their potential spans much further. These agents don’t just answer questions—they take action, often working across multiple systems. For example, Perplexity recently launched an AI agent to assist with holiday shopping, while Google introduced Project Mariner, an agent that helps users book flights, find recipes, and shop for household items. While the idea seems straightforward, it’s muddied by inconsistent definitions. For Google, AI agents are task-based assistants tailored to specific roles, like coding help for developers or troubleshooting issues for IT professionals. In contrast, Asana views agents as digital co-workers that take on assigned tasks, and Sierra—a startup led by former Salesforce co-CEO Bret Taylor—envisions agents as sophisticated customer experience tools that surpass traditional chatbots by tackling complex problems. This lack of consensus adds to the uncertainty around what AI agents can truly achieve. Rudina Seseri, founder and managing partner at Glasswing Ventures, explains this ambiguity stems from the technology’s infancy. She describes AI agents as intelligent systems capable of perceiving their environment, reasoning, making decisions, and taking actions to achieve specific goals autonomously. These agents rely on a mix of AI technologies, including natural language processing, machine learning, and computer vision, to operate in dynamic environments. Optimists, like Box CEO Aaron Levie, believe AI agents will improve rapidly as advancements in GPU performance, model efficiency, and AI frameworks create a self-reinforcing cycle of innovation. However, skeptics like MIT robotics pioneer Rodney Brooks caution against overestimating progress, noting that solving real-world problems—especially those involving legacy systems with limited API access—can be far more challenging than anticipated. David Cushman of HFS Research likens current AI agents to assistants rather than fully autonomous entities, with their capabilities limited to helping users complete specific tasks within pre-defined boundaries. True autonomy, where AI agents handle contingencies and perform at scale without human oversight, remains a distant goal. Jon Turow, a partner at Madrona Ventures, emphasizes the need for dedicated infrastructure to support the development of AI agents. He envisions a tech stack that allows developers to focus on product differentiation while leaving scalability and reliability to the platform. This infrastructure would likely involve multiple specialized models working together under a routing layer, rather than relying on a single large language model (LLM). Fred Havemeyer of Macquarie US Equity Research agrees, noting that the most effective AI agents will combine various models to handle complex tasks. He imagines a future where agents act like autonomous supervisors, delegating tasks and reasoning through multi-step processes to achieve abstract goals. While this vision is compelling, the current state of AI agents suggests we’re still in a transitional phase. The progress so far is promising, but several breakthroughs are needed before agents can operate as envisioned—truly autonomous, multi-functional, and capable of seamless collaboration across diverse systems. This story, originally published on July 13, 2024, has been updated to reflect new developments from Perplexity and Google. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 13, 2024in Artificial Intelligence, Google, Salesforce, Technology

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