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25Mar

Salesforce’s Marketing Intelligence

Introducing Salesforce’s Marketing Intelligence: The Future of Marketing Analytics For the past dozen years, many marketers have been enamored with a powerful marketing analytics tool—Datorama, now known as Salesforce Marketing Cloud Intelligence (MCI). Regarded as one of the most seamless solutions for unifying data across multiple sources, MCI was built by marketers for marketers. It enables users to effortlessly combine data, generate reports, and build dashboards using plain language and pre-built data models. Whether for simple smart-lens dashboards or complex automated reporting triggered by specific events, MCI has been a game-changer. To the delight of marketers everywhere, Salesforce announced on March 18, 2025, a new evolution of the tool: Marketing Intelligence (MI). Built on the Salesforce Platform, MI takes the best of MCI and integrates it with Data Cloud’s unified architecture while introducing agentic AI features that deliver actionable, conversational insights. So, without further ado, let’s explore this exciting new tool. What Is Marketing Intelligence? Marketing Intelligence (MI) is a new Salesforce application designed to simplify marketing data management, deliver trustworthy insights, and maximize marketing ROI. Built on Data Cloud and deeply connected to the Salesforce ecosystem, MI is fully extensible—equipping marketers with everything they need to create powerful, meaningful dashboards with minimal effort. Data Cloud for Marketers, Made Easy One of the standout features of MCI has always been its AI-powered data mapping, which auto-populates based on past usage and logical predictions. Additionally, many APIs come with prebuilt models, reducing the need for manual configuration. These capabilities have helped marketers transition smoothly into data modeling and dashboarding without requiring deep technical expertise. Happily, MI retains and enhances these features. Users can upload a TotalConnect file (a flat file of their choice) or connect via API—with options like Google Ads available at launch and more integrations coming soon. Selecting a connection like Google Ads pulls in formatted data, ready for quick mapping, allowing users to build dashboards in just three clicks. Clean, Intuitive Dashboards MI’s dashboards are sleek, fast-loading, and prebuilt—yet fully customizable. A major upgrade over MCI is the inclusion of generative AI summaries, which analyze campaigns and highlight what’s working (and what isn’t). This feature represents the future of dashboarding: not just displaying data trends but explaining them in plain language and suggesting next steps. Marketers can even ask their AI agent to take action based on these insights, streamlining optimization like never before. This functionality is particularly valuable in large implementations where different users extract different insights from the same dashboard. Instead of manually interpreting data, marketers can now ask their AI agent for recommendations—saving time and reducing guesswork. Harmonized Data Across Channels The core goal of any marketing analytics tool—whether Data Cloud, MCI, or MI—is to unify cross-channel data into actionable insights. Beyond standardized API mapping, MI harmonizes fields across datasets and uses a semantic model to logically connect data (e.g., aligning campaign names across paid media, CRM, and other tools—even when naming conventions differ). For Existing MCI Users: What’s New? Many longtime MCI users may wonder: Can a new version really live up to the original? The answer? Absolutely. Here’s why: 1. Normalization, Simplified In MCI, joining messy and clean data often requires manual effort—using formulas or restructuring campaigns. MI changes that. With Einstein AI-powered normalization, users can automatically standardize data without manual adjustments, making cross-channel reporting smoother than ever. 2. Semantic Modeling Flexibility While MCI offers prebuilt data models, MI introduces semantic modeling, allowing users to define custom relationships across datasets. This means greater flexibility in structuring data, adding fields, and evolving models as business needs change—all while maintaining seamless integration with Salesforce objects. 3. ROI & Attribution, Supercharged The best MCI implementations tie cost/engagement data to real ROI. MI takes this further by integrating with Sales Cloud objects, enabling clearer ROI visualization. Additionally, attribution modeling is now more robust, with support for first- and last-touch attribution—helping marketers validate performance and optimize spend. For New Users: Why Choose MI? 1. Best-in-Class Data Harmonization MCI has long been the gold standard for unifying marketing data. Now, MI enhances this with Data Cloud integration, AI normalization, and three-click setup—making it the ultimate solution for marketers. 2. Smarter, Faster Visualizations While MCI offers strong visualization options, MI improves on two key pain points: 3. Unmatched Customization Want to dynamically rename campaigns, merge traffic sources, or filter data based on custom logic? MI makes it possible with pattern extraction, semantic-layer calculated fields, and Einstein normalization—giving marketers unprecedented control. A New Era for Marketing Analytics Marketing Intelligence launched on March 18, 2025 (requiring Data Cloud and MI licenses). Marketers eager to explore this next-generation tool should contact their Salesforce account executive. MI represents a leap forward in intelligent dashboarding, streamlining marketing data in ways MCI only hinted at. For data-driven marketers, the future is here—and it’s more powerful than ever. 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

March 25, 2025in Agentic AI, Data, Generative AI, Google, Marketing Intelligence, Salesforce, Salesforce Marketing Cloud0 Comments

18Mar

Salesforce Marketing Intelligence

Introducing Marketing IntelligenceYour AI-powered marketing analytics solution built on the Salesforce Platform to enhance campaign performance and eliminate wasted spend. OverviewAccessing, harmonizing, and analyzing marketing data remains a highly manual and time-intensive process. Many marketers spend up to a week each month collecting, cleansing, and modeling data for reporting and analysis. As a result, nearly 41% of marketers’ time is consumed by repetitive tasks, leading to delayed performance reporting—when it’s too late to make optimizations that reduce waste and enhance customer value. Marketing Intelligence, our native Salesforce marketing analytics solution, addresses these challenges. Leveraging Data Cloud, Agentforce, Einstein AI, and Tableau Next, it continuously integrates, harmonizes, and transforms third-party marketing performance data into actionable insights—enabling marketers to optimize campaign spend and performance effortlessly. How Marketing Intelligence WorksMarketing Intelligence empowers marketers to seamlessly manage, analyze, and act on performance data—ensuring data-driven decisions that maximize ROI with minimal manual effort. Manage Your Data Marketing Intelligence automates data management with prebuilt connectors, AI-powered enrichment, and a marketing-specific semantic data model. Marketers can connect and harmonize performance data in just three clicks. See a full demo Understand Your Data Marketing Intelligence accelerates insights with out-of-the-box dashboards, built-in attribution reporting, and Agentforce-powered campaign optimization. Act on Your Data Leverage Agentforce to autonomously optimize campaigns around your business goals, 24/7. “We see potential with the future of Marketing Intelligence to drive faster results and deeper analysis by utilizing AI and Agentforce to enhance the platform’s analytical capabilities.”— Spike Therrien, Performance Marketing Lead, Land O’Lakes What’s NextWe’re expanding our unified data and Agentforce capabilities to provide a holistic view of marketing performance across paid, owned, and earned media—directly within the app. Upcoming enhancements include: Stay ahead of the curve with Marketing Intelligence—your AI-powered marketing analytics solution designed to drive efficiency and maximize campaign impact. 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

March 18, 2025in Data, Google, Google Analytics, Marketing Intelligence, Salesforce0 Comments

10Mar

Predictive Analytics for Business Potential

Maximizing Business Potential with Predictive Analytics Every business generates vast amounts of data daily, yet not all leverage it effectively. Predictive analytics transforms raw data into actionable insights, enabling companies to forecast demand, reduce operational costs, and enhance customer engagement. Whether through AI-powered models, machine learning algorithms, or cloud-based analytics, predictive analytics is reshaping business strategies. Organizations that integrate predictive analytics into decision-making can anticipate challenges, seize new opportunities, and outperform competitors. This insight explores the significance of predictive analytics and how businesses can harness its power to gain a competitive edge. The Expanding Influence of Predictive Analytics Predictive analytics is revolutionizing industries, driving innovation, and transforming data into strategic advantages. Transforming Industries with Predictive Analytics Predictive analytics is now a cornerstone of modern industries, facilitating smarter decision-making through data-driven insights. By analyzing historical data, businesses can forecast trends, anticipate customer behaviors, and optimize operations. Sectors such as healthcare, retail, and finance are leveraging predictive tools to maintain competitiveness. For example: As industries adopt these solutions, predictive analytics continues to redefine efficiency and innovation. Key Trends in Predictive Analytics Adoption The widespread adoption of predictive analytics is fueled by advancements in AI, big data, and machine learning. Businesses are capitalizing on these trends to sharpen their competitive edge. Notable developments include: As predictive analytics tools become more sophisticated, they are becoming integral to business strategies, helping companies unlock untapped potential. Overcoming Implementation Challenges Despite its benefits, implementing predictive analytics poses challenges, such as data silos, integration complexities, and skill gaps. To address these issues, organizations should: By overcoming these barriers, businesses can fully harness predictive analytics to drive efficiency, innovation, and growth. Predictive Data Modeling for Smarter Decision-Making Predictive data modeling transforms raw data into strategic insights, improving forecasting and operational decision-making. Understanding Predictive Data Modeling Predictive data modeling employs statistical techniques and machine learning algorithms to analyze historical data and predict future trends. Its core components include: By applying these models, businesses can refine their strategies with data-backed insights, improving efficiency and competitiveness. The Role of Data Quality in Predictive Accuracy The effectiveness of predictive models depends on data quality. Inconsistent or outdated data can lead to unreliable predictions, affecting decision-making. Key steps to ensure high data quality include: High-quality data enhances predictive models, enabling businesses to make informed, confident decisions. Enhancing Forecasting with Predictive Data Modeling Predictive data modeling improves forecasting accuracy by analyzing historical trends and projecting future outcomes. Benefits include: Retailers optimize inventory, while manufacturers align production with demand fluctuations, demonstrating the strategic value of predictive modeling. Driving Business Growth with Predictive Analytics Why Businesses Should Adopt Predictive Analytics Now In today’s competitive landscape, predictive analytics is essential for staying ahead. By leveraging data, algorithms, and machine learning, businesses can anticipate risks and opportunities, optimizing strategies while reducing uncertainty. Retailers, for instance, use predictive insights to forecast seasonal demand spikes, ensuring optimal stock levels. As AI advances, predictive analytics is more accessible than ever, making now the ideal time for adoption. Enhancing Decision-Making and Efficiency Predictive analytics eliminates guesswork, empowering leaders with data-backed decisions. Benefits include: These advantages drive sustainable growth and competitive advantage across industries. Seamlessly Integrating Predictive Analytics into Business Workflows To maximize impact, predictive analytics must integrate into existing workflows. Steps for successful adoption include: By embedding predictive analytics into workflows, businesses enhance agility and decision-making capabilities. AI-Powered Predictive Analytics for Competitive Advantage Why AI Predictive Analytics is Transformative AI-powered predictive analytics delivers insights beyond traditional methods, processing vast datasets rapidly to identify complex patterns and trends. Applications include: With AI continuously learning and refining predictions, businesses gain a dynamic advantage. Enhancing Accuracy with AI AI refines predictions by analyzing diverse data sources, including text, images, and videos. Examples include: Advanced AI techniques, such as natural language processing and neural networks, ensure businesses derive actionable insights, driving smarter strategies and better results. Machine Learning’s Role in Predictive Analytics Machine learning (ML) is foundational to predictive analytics, continuously improving model accuracy. Examples include: By leveraging ML, businesses enhance their predictive capabilities, ensuring long-term competitive success. Enhancing Enterprise Solutions with Predictive Analytics Transforming SAP Systems with Predictive Analytics SAP systems integrated with predictive analytics unlock actionable insights from vast datasets. Benefits include: By embedding predictive capabilities, SAP users can optimize operations and drive proactive decision-making. Empowering Salesforce with Predictive Insights Salesforce predictive analytics enhances decision-making across marketing, sales, and customer service. Key capabilities include: With Salesforce Einstein, businesses can streamline operations, boost performance, and foster deeper customer engagement. Predictive analytics is a game-changer, reshaping industries, optimizing operations, and unlocking new growth opportunities. Businesses that embrace predictive analytics today will be well-positioned to navigate future challenges and lead in the data-driven economy. 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

March 10, 2025in Data, Enterprise, Salesforce, Salesforce Einstein0 Comments

05Mar

Salesforce Personalization for Fundraising

The Power of Personalization in Fundraising with Salesforce Successful fundraisers have long recognized that personalization in communicaation drives stronger donor relationships and inspires far greater generosity. However, achieving meaningful engagement at scale has traditionally been a time-intensive challenge. Salesforce, the world’s leading CRM, is transforming nonprofit fundraising by seamlessly integrating donor data with cutting-edge artificial intelligence. This powerful combination enables organizations to build deeper connections with donors through hyper-personalized interactions. How Salesforce is Revolutionizing Donor Engagement: Scalable Solutions for Every Nonprofit Salesforce is built to support organizations of all sizes, from small grassroots initiatives to large national institutions. As your objectives evolve, Salesforce’s flexible platform scales with you, ensuring you always have the right tools to achieve your fundraising goals. Now is the perfect time to leverage Salesforce’s power to enhance personalized giving. Getting Started with Salesforce Advancing Your Salesforce Strategy By leveraging Salesforce’s powerful tools and automation, nonprofits can enhance personalization, drive engagement, and build lasting donor relationships—all while streamlining operations and maximizing fundraising success. 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

March 5, 2025in Artificial Intelligence, Data, Salesforce, Salesforce Personalization0 Comments

27Feb

The Future of AI in Salesforce

The Future of AI in Salesforce: Smarter, Predictive, and Deeply Integrated Artificial Intelligence (AI) is revolutionizing the Salesforce ecosystem, reshaping customer interactions, automating workflows, and driving revenue growth. As we move into 2025 and beyond, AI within Salesforce will become even more intelligent, predictive, and seamlessly embedded across the platform. Let’s explore the key advancements defining the next era of AI in Salesforce. 1. Next-Gen Einstein AI: A Smarter CRM Assistant Salesforce Einstein continues to evolve, equipping businesses with powerful AI-driven capabilities: 2. AI-Powered Revenue Intelligence & Forecasting AI is transforming revenue intelligence, helping sales teams make data-driven decisions: 3. AI-Driven Sales & Service Automation AI-powered automation will streamline workflows and improve efficiency: 4. Hyper-Personalization with AI & Data Cloud Salesforce Data Cloud and AI will power personalized customer experiences at scale: 5. AI-Optimized Lead Generation & Marketing Automation AI will continue to enhance lead generation and marketing strategies: 6. AI & Low-Code/No-Code Innovation Salesforce is democratizing AI with accessible low-code and no-code tools: 7. Ethical AI & Governance: Building Trust in AI Salesforce remains committed to ethical, transparent, and bias-free AI: Conclusion As AI becomes deeply embedded in every Salesforce cloud, businesses will experience faster automation, smarter decision-making, and hyper-personalized customer engagement. From AI-powered sales forecasting to generative AI-driven content, the future of Salesforce AI is set to redefine CRM strategies in 2025 and beyond. 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

February 27, 2025in AI Tools, Artificial Intelligence, Data, Generative AI, Marketing Automation, Salesforce, Salesforce Data Cloud, Salesforce Einstein0 Comments

Data Cloud Billable Usage

Data Cloud Billable Usage Overview Usage of certain Data Cloud features impacts credit consumption. To track usage, access your Digital Wallet within your Salesforce org. For specific billing details, refer to your contract or contact your Account Executive. Important Notes ⚠️ Customer Data Platform (CDP) Licensing – If your Data Cloud org operates under a CDP license, refer to Customer Data Platform Billable Usage Calculations instead.⚠️ Sandbox Usage – Data Cloud sandbox consumption affects credits, with usage tracked separately on Data Cloud sandbox cards. Understanding Usage Calculations Credit consumption is based on the number of units used multiplied by the multiplier on the rate card for that usage type. Consumption is categorized as follows: 1. Data Service Usage Service usage is measured by records processed, queried, or analyzed. Billing Category Description Batch Data Pipeline Based on the volume of batch data processed via Data Cloud data streams. Batch Data Transforms Measured by the higher of rows read vs. rows written. Incremental transforms only count changed rows after the first run. Batch Profile Unification Based on source profiles processed by an identity resolution ruleset. After the first run, only new/modified profiles are counted. Batch Calculated Insights Based on the number of records in underlying objects used to generate Calculated Insights. Data Queries Based on records processed, which depends on query structure and total records in the queried objects. Unstructured Data Processed Measured by the amount of unstructured data (PDFs, audio/video files) processed. Streaming Data Pipeline Based on records ingested through real-time data streams (web, mobile, streaming ingestion API). Streaming Data Transforms Measured by the number of records processed in real-time transformations. Streaming Calculated Insights Usage is based on the number of records processed in streaming insights calculations. Streaming Actions (including lookups) Measured by the number of records processed in data lookups and enrichments. Inferences Based on predictive AI model usage, including one prediction, prescriptions, and top predictors. Applies to internal (Einstein AI) and external (BYOM) models. Data Share Rows Shared (Data Out) Based on the new/changed records processed for data sharing. Data Federation or Sharing Rows Accessed Based on records returned from external data sources. Only cross-region/cross-cloud queries consume credits. Sub-second Real-Time Events & API Based on profile events, engagement events, and API calls in real-time processing. Private Connect Data Processed Measured by GB of data transferred via private network routes. 🔹 Retired Billing Categories: Accelerated Data Queries and Real-Time Profile API (no longer billed after August 16, 2024). 2. Data Storage Allocation Storage usage applies to Data Cloud, Data Cloud for Marketing, and Data Cloud for Tableau. Billing Category Description Storage Beyond Allocation Measured by data storage exceeding your allocated limit. 3. Data Spaces Billing Category Description Data Spaces Usage is based on the number of data spaces beyond the default allocation. 4. Segmentation & Activation Usage applies to Data Cloud for Marketing customers and is based on records processed, queried, or activated. Billing Category Description Segmentation Based on the number of records processed for segmentation. Batch Activations Measured by records processed for batch activations. Activate DMO – Streaming Based on new/updated records in the Data Model Object (DMO) during an activation. If a data graph is used, the count is doubled. 5. Ad Audiences Service Usage Usage is calculated based on the number of ad audience targets created. Billing Category Description Ad Audiences Measured by the number of ad audience targets generated. 6. Data Cloud Real-Time Profile Real-time service usage is based on the number of records associated with real-time data graphs. Billing Category Description Sub-second Real-Time Profiles & Entities Based on the unique real-time data graph records appearing in the cache during the billing month. Each unique record is counted only once, even if it appears multiple times. 📌 Example: If a real-time data graph contains 10M cached records on day one, and 1M new records are added daily for 30 days, the total count would be 40M records. 7. Customer Data Platform (CDP) Billing Previously named Customer Data Platform orgs are billed based on contracted entitlements. Understanding these calculations can help optimize data management and cost efficiency. Track & Manage Your Usage 🔹 Digital Wallet – Monitor Data Cloud consumption across all categories.🔹 Feature & Usage Documentation – Review guidelines before activating features to optimize cost.🔹 Account Executive Consultation – Contact your AE to understand credit consumption and scalability options. 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

February 26, 2025in Data, Salesforce, Salesforce Data Cloud0 Comments

13Feb

How Agentforce Works

Salesforce Agentforce: Everything You Need to Know Salesforce Agentforce represents a paradigm shift from generative AI to agentic AI—a new class of AI capable of autonomous action. Since its launch at Dreamforce in September 2024, Agentforce has redefined the conversation around AI, customer service, and experience management. To meet skyrocketing demand, Salesforce announced plans to hire more than 1,000 employees shortly after the launch. What is Salesforce Agentforce? Agentforce is a next-generation platform layer within the Salesforce ecosystem. While its bots leverage generative AI capabilities, they differ significantly from platforms like ChatGPT or Google Gemini. Agentforce bots are designed not just to generate responses but to act autonomously within predefined organizational guardrails. Unlike traditional chatbots, which follow scripted patterns, Agentforce AI agents are trained on proprietary data, enabling flexible and contextually accurate responses. They also integrate with Salesforce’s Data Cloud, enhancing their capacity to access and utilize customer data effectively. Agentforce combines three core tools—Agent Builder, Model Builder, and Prompt Builder—allowing businesses to create customized bots using low-code tools. Key Features of Agentforce The platform offers ready-to-deploy AI agents tailored for various industries, including: Agentforce officially became available on October 25, 2024, with pricing starting at $2 per conversation, and volume discounts offered for enterprise customers. Salesforce also launched the Agentforce Partner Network, enabling third-party integrations and custom agent designs for expanded functionality. How Agentforce Works Salesforce designed Agentforce for users without deep technical expertise in AI. As CEO Marc Benioff said, “This is AI for the rest of us.” The platform is powered by the upgraded Atlas Reasoning Engine, a component of Salesforce Einstein AI, which mimics human reasoning and planning. Like self-driving cars, Agentforce interprets real-time data to adapt its actions and operates autonomously within its established parameters. Enhanced Atlas Reasoning Engine In December 2024, Salesforce enhanced the Atlas Reasoning Engine with retrieval-augmented generation (RAG) and advanced reasoning capabilities. These upgrades allow agents to: Seamless Integrations with Salesforce Tools Agentforce is deeply integrated with Salesforce’s ecosystem: Key Developments Agentforce Testing Center Launched in December 2024, the Testing Center allows businesses to test agents before deployment, ensuring they are accurate, fast, and aligned with organizational goals. Skill and Integration Library Salesforce introduced a pre-built library for CRM, Slack, Tableau, and MuleSoft integrations, simplifying agent customization. Examples include: Industry-Specific Expansion Agentforce for Retail Announced at the NRF conference in January 2025, this solution offers pre-built skills tailored to retail, such as: Additionally, Salesforce unveiled Retail Cloud with Modern POS, unifying online and offline inventory data. Notable Agentforce Customers Looking Ahead Marc Benioff calls Agentforce “the third wave of AI”, advancing beyond copilots into a new era of autonomous, low-hallucination intelligent agents. With its robust capabilities, Agentforce is positioned to transform how businesses interact with customers, automate workflows, and drive success. 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

February 13, 2025in Agentforce Platform, Agentic AI, Data, Enterprise, Generative AI, Google, Mulesoft, Salesforce, Salesforce Einstein0 Comments

22Jan

Agentforce Versus Einstein

Salesforce offers a variety of tools and platforms to help businesses manage customer relationships, automate processes, and leverage AI for better decision-making. Two of its prominent offerings in the customer service and AI space are Service Cloud (Agent Console) and Einstein AI. Here’s a comparison of Agent Console (part of Service Cloud) and Einstein: 1. Salesforce Agent Console (Service Cloud) The Agent Console is a core component of Salesforce’s Service Cloud, which is designed to help customer service agents manage cases, interactions, and customer data efficiently. Key Features: Use Case: The Agent Console is ideal for customer service teams that need a centralized platform to manage customer interactions and resolve issues quickly. 2. Salesforce Einstein Einstein is Salesforce’s AI platform that integrates artificial intelligence across Salesforce products, including Service Cloud, Sales Cloud, Marketing Cloud, and more. It provides predictive analytics, automation, and personalized recommendations. Key Features: Use Case: Einstein is ideal for organizations looking to leverage AI to enhance customer service, improve decision-making, and automate routine tasks. Agent Console vs. Einstein: Key Differences Feature/Aspect Agent Console (Service Cloud) Einstein AI Purpose Centralized platform for managing customer service operations. AI-powered insights, automation, and personalization. Core Functionality Case management, omnichannel support, and agent productivity tools. Predictive analytics, chatbots, and AI-driven recommendations. Automation Workflow automation for case management and task routing. AI bots and automated responses for customer inquiries. Insights Basic reporting and analytics for agent performance. Advanced predictive analytics and AI-driven insights. Integration Part of Service Cloud, focused on customer service. Integrated across Salesforce products (Sales, Service, Marketing, etc.). User Interaction Primarily used by customer service agents. Used by agents, managers, and customers (via bots). How They Work Together The Agent Console and Einstein are not mutually exclusive; they complement each other. For example: Which One Should You Use? In many cases, businesses use both together to create a seamless, AI-enhanced customer service 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

January 22, 2025in Artificial Intelligence, Data, Einstein Insights, Salesforce, Salesforce Einstein

AI evolves with tools like Agentforce and Atlas

13Jan

Agentforce Powered Marketing

Maximize Team Productivity and Customer Engagement with Agentforce and AI-Powered Marketing Tools Transform your marketing operations with Agentforce, an advanced AI-powered suite seamlessly integrated into your platform. From building end-to-end campaigns to personalizing touchpoints in real time, Agentforce empowers your team to optimize performance with actionable AI insights. Here’s how: Revolutionize Campaign Management with Agentforce Agent-Driven Campaign Briefs Streamline campaign creation with Agentforce, which uses structured and unstructured data from Data Cloud to create tailored campaign briefs. Define your target segments and key messages effortlessly with the support of AI. AI-Powered Content Creation Leverage Agentforce to generate on-brand content at scale, including email subject lines, body copy, and SMS messages. Every piece of content aligns with your brand guidelines and campaign goals, ensuring consistency and relevance across audiences. Unified SMS Conversations Turn static promotions into dynamic, two-way conversations with Agentforce Unified SMS. Automatically connect customers to AI agents for tasks like appointment scheduling and offer redemption, delivering seamless customer experiences. Supercharge Insights and Actions with Data Cloud Agent-Driven AI Segmentation Create target audience segments in minutes using natural language prompts. With Agentforce and Data Cloud working in harmony, agents translate prompts into precise segment attributes—no technical expertise or SQL required. Integrate or Build Custom AI Models Develop predictive AI models with clicks, not code, or bring in existing models via direct integrations with tools like Amazon SageMaker, Google Vertex AI, or Databricks. Use these models to generate actionable predictions, such as purchase propensity or churn likelihood. Secure, Harmonized Data Foundation Keep your data safe on the Einstein Trust Layer while enabling agents to analyze harmonized, structured, and unstructured data in Data Cloud. This ensures informed decision-making without compromising security. Automate Intelligent Journeys with Marketing Cloud Engagement Journey Optimization Automate personalized campaign variations with predictive AI. Optimize engagement by tailoring content, timing, channels, and frequency dynamically across customer journeys. Generative AI for Content Creation Solve the content bottleneck with generative AI tools that instantly create on-brand copy and visuals grounded in first-party data, campaign insights, and brand guidelines—all while safeguarding trust. Real-Time Messaging Insights Stay proactive with Einstein Messaging Insights, which flags engagement anomalies like sudden drops in click-through rates. These real-time insights enable quick resolutions, preventing performance surprises. Unified WhatsApp Conversations Transform WhatsApp into a dynamic two-way engagement channel. Use a single WhatsApp number to connect marketing and service teams while enabling AI-driven self-service actions like appointment booking and offer redemptions. Scale Lead Generation and Account-Based Marketing Agent-Driven Campaign Creation Accelerate campaign planning with Agentforce, which handles everything from briefs to audience segmentation, content, and journey creation. Ground campaigns in real-time customer data for accurate targeting, all with marketer oversight for approvals. AI Lead and Account Scoring Boost alignment between marketing and sales with Einstein AI Scoring, which identifies top leads and prospects automatically. Improve ABM strategies with automated account rankings based on historical and behavioral data, driving higher conversions. Full-Funnel Attribution Gain end-to-end visibility with AI-powered multi-touch attribution. Use models like Einstein Attribution to measure the impact of each channel, event, or team activity on your pipeline, boosting ROI and campaign efficiency. Personalization on Auto-Pilot with AI Objective-Based AI Recommendations Set business objectives and let AI optimize product and content recommendations to achieve those goals. AI-Automated Offers Combine real-time customer behavior data with AI-driven insights to personalize offers across touchpoints. This results in higher satisfaction and conversion rates tailored to each individual customer. Real-Time Affinity Profiling Use AI to uncover customer affinities, preferences, and intent in real time. Deliver hyper-personalized messaging and offers across your website, app, and other channels for maximum engagement. Optimize Spend, Planning, and Performance with Marketing Cloud Intelligence AI-Powered Data Integration Say goodbye to spreadsheets and manual data maintenance. Automate data unification, KPI standardization, and cross-channel analytics with AI-powered connectors, saving time and boosting campaign effectiveness. AI Campaign Performance Insights Get interactive visualizations and AI-generated insights to adjust campaign spend and offers mid-flight. Use these insights to optimize ROI and maximize in-the-moment opportunities. Predictive Budgeting and Planning Allocate budgets more effectively with predictive AI. Real-time alerts help prevent overages or underspending, ensuring your marketing dollars are used efficiently for maximum return. With Agentforce and AI marketing tools, your team can focus on what matters most—building stronger customer relationships and driving measurable results. 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

January 13, 2025in AI Tools, Data, Generative AI, Google

03Jan

How Agentforce Augments Marketing Cloud

Key Features of Salesforce Agentforce for Marketing and Marketers AI-Powered Assistance: Agentforce leverages AI to automate and optimize marketing tasks, allowing your team to focus on strategic initiatives. From generating campaign plans to analyzing metrics, Agentforce acts as your trusted assistant working around the clock with nary a coffee break. Omnichannel Support: Engage with customers across multiple platforms, including email, social media, and messaging apps like WhatsApp. Agentforce ensures a consistent and personalized experience at every touchpoint. Recognizing your prospect and customer throughout every interaction. Real-Time Analytics and Reporting: Gain in-depth insights into your marketing performance with real-time analytics. Agentforce helps you track key metrics and make data-driven decisions to improve your campaigns. Integration with Salesforce CRM: Seamlessly connect Agentforce with your existing Salesforce CRM to leverage customer data and create more targeted and effective marketing strategies. Proactive Customer Engagement: Agentforce enables personalized, two-way conversations with customers, helping you build deeper relationships and reduce churn through proactive retention strategies. Added Value of Integrating Agentforce with Salesforce Marketing Cloud The integration of Agentforce with the Salesforce Marketing Cloud platform, whether you choose the Growth or Advanced edition, brings several benefits: Enhanced Personalization: With the power of AI and unified customer profiles, you can deliver highly personalized content and offers across every customer interaction. Scalability and Efficiency: The Growth edition supports companies looking to scale their marketing efforts with powerful data tools and content management features. The Advanced edition offers additional tools for deeper insights and more sophisticated customer engagement strategies. Seamless Campaign Management: Both editions provide tools to create, deploy, and adapt campaigns faster, with Agentforce helping to surface insights, define strategy, and generate content. Improved Customer Journeys: Use intelligent reprioritization and real-time interaction management to enhance customer journeys and drive better engagement. Elevating Customer Experience with AI-Powered Marketing Offering a great product or service is important—but have you considered how your customers feel when they engage with your brand? Beyond features and pricing, the real differentiator is the experience you create. How the customer experiences your company can be more impactful than how they experience your product or service. Salesforce research reveals that 80% of customers value their experience with a company as much as the products or services themselves. It’s not just about what you have to offer; it’s about how you make people feel at every interaction. Because in today’s competitive marketplace, customers don’t just buy products—they invest in experiences. In the go-to-market space, Salesforce Agentforce is redefining the Marketing Cloud experience by making customer interactions more intelligent, personalized, and human-like than ever before—all powered by AI. Imagine a marketing strategy where every interaction—every click, every purchase—delivers actionable insights instead of guesswork. This is the future of AI-driven marketing. In fact, recent research found that nearly half (46%) of financial services firms leveraging AI report enhanced customer experiences. With AI-driven automation, conversational intelligence, and predictive analytics, Agentforce helps businesses engage customers at the right time, in the right way, and on the right platform—building deeper, more meaningful relationships. Salesforce’s Ongoing Relationship with Data Since pioneering cloud-based CRM in 1999, Salesforce has been relentless in its pursuit of data-driven experiences. Over time, its capabilities have expanded far beyond traditional CRM, culminating in the Salesforce Data Cloud—a unified data platform that consolidates insights across Sales, Service, Commerce, and Marketing. Data, especially the data we use for ongoing marketing, lives in various platforms like email, advertising tools, social media, analytics, CRMs, and perhaps even spreadsheets. And it is completely unstructured. What began as a Data Management Platform has evolved into a real-time decision-making engine. By integrating Agentforce AI, Data Cloud moves beyond just storing information—it enables businesses to act on real-time insights with automation and intelligence that move deals closer to the goalpost. Meet Agentforce: Humanizing AI in Marketing Cloud At the heart of AI-driven marketing transformation is quality data—which is why Einstein AI is built on Salesforce Data Cloud. “AI is only as good as the data that powers it, and Salesforce is where thousands of companies across industries manage their sales, service, marketing, commerce, and IT data,” says Jayesh Govindarajan, Salesforce SVP of AI & Machine Learning. “That’s an advantage for Salesforce customers because they can use their existing data to create and deliver AI-generated content at scale, seamlessly within their current workflows.” With Agentforce, businesses go beyond access to data—they gain an AI partner that understands how to foster authentic customer connections. How AI is Humanizing the Marketing Experience Instead of generic messaging, Agentforce crafts and delivers hyper-personalized content, offers, and recommendations—at scale. The Future of AI-Driven Marketing is Here With Agentforce, Salesforce Data Cloud, and Einstein GPT, businesses can move beyond static campaigns and embrace dynamic, AI-driven experiences that feel authentic, intuitive, and deeply personal. The next era of marketing isn’t just about automation—it’s about delivering humanized AI experiences that drive lasting customer relationships. The evolution of Einstein, GPT, AI, and Data on top of a powerful marketing platform is the future of AI-driven marketing. 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

January 3, 2025in Agentforce Platform, Data, Salesforce, Salesforce Data Cloud, Salesforce Marketing Cloud

1 Billion Enterprise AI Agents

Inside Salesforce’s Ambition to Deploy 1 Billion Enterprise AI Agents Salesforce is making a bold play in the enterprise AI space with its recently launched Agentforce platform. Introduced at the annual Dreamforce conference, Agentforce is positioned to revolutionize sales, marketing, commerce, and operations with autonomous AI agents, marking a significant evolution from Salesforce’s previous Einstein AI platform. What Makes Agentforce Different? Agentforce operates as more than just a chatbot platform. It uses real-time data and user-defined business rules to proactively manage tasks, aiming to boost efficiency and enhance customer satisfaction. Built on Salesforce’s Data Cloud, the platform simplifies deployment while maintaining powerful customization capabilities: “Salesforce takes care of 80% of the foundational work, leaving customers to focus on the 20% that truly differentiates their business,” explains Adam Forrest, SVP of Marketing at Salesforce. Forrest highlights how Agentforce enables businesses to build custom agents tailored to specific needs by incorporating their own rules and data sources. This user-centric approach empowers admins, developers, and technology teams to deploy AI without extensive technical resources. Early Adoption Across Industries Major brands have already adopted Agentforce for diverse use cases: These real-world applications illustrate Agentforce’s potential to transform workflows in industries ranging from retail to hospitality and education. AI Agents in Marketing: The New Frontier Salesforce emphasizes that Agentforce isn’t just for operations; it’s poised to redefine marketing. AI agents can automate lead qualification, optimize outreach strategies, and enhance personalization. For example, in account-based marketing, agents can analyze customer data to identify high-value opportunities, craft tailored strategies, and recommend optimal engagement times based on user behavior. “AI agents streamline lead qualification by evaluating intent signals and scoring leads, allowing sales teams to focus on high-priority prospects,” says Jonathan Franchell, CEO of B2B marketing agency Ironpaper. Once campaigns are launched, Agentforce monitors performance in real time, offering suggestions to improve ROI and resource allocation. By integrating seamlessly with CRM platforms, the tool also facilitates better collaboration between marketing and sales teams. Beyond B2C applications, AI agents in B2B contexts can evaluate customer-specific needs and provide tailored product or service recommendations, further enhancing client relationships. Enabling Creativity Through Automation By automating repetitive tasks, Agentforce aims to free marketers to focus on strategy and creativity. Dan Gardner, co-founder of Code and Theory, describes this vision: “Agentic AI eliminates friction and dissolves silos in data, organizational structures, and customer touchpoints. The result? Smarter insights, efficient distribution, and more time for creatives to do what they do best: creating.” Competitive Landscape and Challenges Despite its promise, Salesforce faces stiff competition. Microsoft—backed by its integration with OpenAI’s ChatGPT—has unveiled AI tools like Copilot, and other players such as Google, ServiceNow, and HubSpot are advancing their own AI platforms. Salesforce CEO Marc Benioff has not shied away from the rivalry. On the Masters of Scale podcast, he criticized Microsoft for overpromising on products like Copilot, asserting that Salesforce delivers tangible value: “Our tools show users exactly what is possible, what is real, and how easy it is to derive huge value from AI.” Salesforce must also demonstrate Agentforce’s scalability across diverse industries to capture a significant share of the enterprise AI market. A Transformative Vision for the Future Agentforce represents Salesforce’s commitment to bringing AI-powered automation to the forefront of enterprise operations. With its focus on seamless deployment, powerful customization, and real-time capabilities, the platform aims to reshape how businesses interact with customers and optimize internal processes. By targeting diverse use cases and emphasizing accessibility for both technical and non-technical users, Salesforce is betting on Agentforce to drive adoption at scale—and position itself as a leader in the increasingly competitive AI market. 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

December 27, 2024in Agentforce Platform, AI Tools, Data, Enterprise, Google, Salesforce, Technology

07Dec

Ushering in the Era of AI-Driven Workforces

Agentforce: Ushering in the Era of AI-Driven Workforces “Agentforce is redefining what’s possible in business and beyond, ushering in a new era of AI abundance and limitless workforces that augment every employee, build deeper customer relationships, and drive unprecedented growth and profitability.”— Marc Benioff, Salesforce CEO Key Features and Takeaways Out-of-the-Box AI Agents Agentforce introduces pre-built, customizable agents that are deployable with low-code or no-code tools, working tirelessly across any channel. Its first generally available solution, the Agentforce Service Agent, surpasses traditional chatbots by handling a diverse range of tasks—from simple inquiries to complex scenarios. Key capabilities include: Seamless Integration with Salesforce Platform Agentforce eliminates the complexity of building AI solutions from scratch. Unlike other platforms that demand intricate data integration and custom automation, Agentforce is fully embedded within the Salesforce ecosystem. With Agentforce, businesses can: Always-On Automation Agentforce operates independently of human intervention. Agents can be triggered by changes in data, predefined business rules, or pre-built automations, ensuring uninterrupted workflows. This blend of autonomous operation and human collaboration creates a symbiotic relationship between people and AI, enhancing productivity and customer satisfaction. A Competitive Edge in the AI Space Salesforce emphasizes that Agentforce goes beyond chatbots and copilots, setting a new benchmark for enterprise AI. In a strategic swipe at competitors, Marc Benioff likened rival offerings—like Microsoft’s Dynamics 365 AI agents—to “Clippy 2.0,” critiquing their inaccuracies and risks of corporate data leaks. By contrast, Agentforce builds on Salesforce’s proven Einstein AI platform, ensuring reliability, scalability, and secure integration. Redefining Customer Success Agentforce isn’t just about automation—it’s about driving outcomes. By enabling businesses to automate complex processes, deepen customer relationships, and scale operations, it paves the way for limitless growth in the age of AI. Ready to transform your workforce? With Agentforce, the future of AI-driven business is already here. 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

December 7, 2024in Agentforce Platform, Data, Enterprise, Mulesoft, Salesforce

Microsoft Copilot as “Repackaged ChatGPT”

Salesforce CEO Marc Benioff Criticizes Microsoft Copilot as “Repackaged ChatGPT” Salesforce CEO Marc Benioff took aim at Microsoft’s Copilot AI offerings during Salesforce’s latest quarterly earnings call, dismissing them as a rebranding of OpenAI’s generative AI technology. “In many ways, it’s just repackaged ChatGPT,” Benioff asserted. He contrasted this with Salesforce’s platform, emphasizing its unique ability to operate an entire business. “You won’t find that capability on Microsoft’s website,” he added. Benioff highlighted Agentforce, Salesforce’s autonomous AI agent product, as a transformative force for both Salesforce and its customers. The tool, available on Salesforce’s support portal, is projected to manage up to half of the company’s annual support case volume. The portal currently handles over 60 million sessions and 2 million support cases annually. Agentforce Adoption and Partner Involvement Salesforce COO Brian Millham outlined the significant role of partners in driving Agentforce adoption. During the quarter, global partners were involved in 75% of Agentforce deals, including nine of Salesforce’s top 10 wins. More than 80,000 system integrators have completed Agentforce training, and numerous independent software vendors (ISVs) and technology partners are developing and selling AI agents. Millham pointed to Accenture as a notable example, leveraging Agentforce to enhance sales operations for its 52,000 global sellers. “Our partners are becoming agent-first enterprises themselves,” Millham said. Since its general availability on October 24, Agentforce has already secured 200 deals, with thousands more in the pipeline. Benioff described the tool as part of a broader shift toward digital labor, claiming, “Salesforce is now the largest supplier of digital labor.” Expanding Use Cases and Market Impact Agentforce, powered by Salesforce’s extensive data repository of 740,000 documents and 200–300 petabytes of information, supports diverse use cases, including resolving customer issues, qualifying leads, closing deals, and optimizing marketing campaigns. Salesforce has committed to hiring 1,000–2,000 additional salespeople to expand Agentforce adoption further. Benioff positioned Salesforce as the leading enterprise AI provider, citing its 2 trillion weekly transactions through its Einstein AI product. He claimed Salesforce’s unified codebase provides a competitive edge, unlike rival systems that run disparate applications, potentially limiting AI effectiveness. “This is a bold leap into the future of work,” Benioff said, “where AI agents collaborate with humans to revolutionize customer interactions.” AI Growth Across Salesforce Products AI-driven growth extended beyond Agentforce to other Salesforce products: Millham noted that AI-related $1 million+ deals more than tripled year over year. Financial Highlights For Q3 FY2024, Salesforce reported: Looking ahead, Salesforce expects Q4 revenue between $9.9 billion and $10.1 billion, representing 7%–9% year-over-year growth. The company raised its full fiscal year revenue guidance to .8– billion, an 8%–9% increase. Industry and Product Insights Salesforce’s growth was driven by its core clouds and subscription services, with health, life sciences, manufacturing, and automotive industries performing particularly well. However, retail and consumer goods saw slower growth. While subscription revenue for MuleSoft and Tableau decelerated, Salesforce’s broader portfolio continued to deliver robust performance. Benioff concluded by emphasizing the transformative potential of Salesforce’s AI ecosystem: “This is the next evolution of Salesforce—an intelligent, scalable technology that’s no longer tied to workforce growth.” 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

December 3, 2024in Data, Enterprise, Generative AI, Mulesoft, Salesforce, Technology

19Nov

How Does Salesforce Use AI

With all the buzz in the news about AI, it may feel like AI is everywhere. In fact, as of 2023, over 80% of global companies report adopting AI to enhance their business operations. This means if your company isn’t yet leveraging AI to strengthen customer relationships, you risk falling behind. The good news is that Salesforce CRM already comes with a suite of AI tools ready for use. In this insight, we’ll explore how combining quality data, AI, and Salesforce can help you build more meaningful, lasting relationships with your customers. How Does Salesforce Use AI? Salesforce offers various built-in functionalities to create customizable, predictive, and generative AI experiences tailored to your business needs. One standout tool is Agentforce, which enables the creation of autonomous AI agents. If you have numerous routine tasks but limited staff, Agentforce could be the solution. For instance, if you lack an in-house customer support agent, Agentforce can build an AI service agent to handle incoming cases, responding intuitively in real-time. Not enough sales reps? No problem—create an AI sales agent to manage records, interact with leads, answer questions, and schedule meetings. Another significant AI feature is generative AI in Salesforce. According to KPMG, 77% of executives believe generative AI will have a more profound societal impact in the next three to five years than any other emerging technology. So, how can it improve your business? Salesforce’s in-house LLM, xGen, helps you generate human-like text and create original visual content from existing data or user input. This capability can enhance user experiences by automating the generation of dynamic and personalized imagery for applications. Generative AI also transforms how users interact with and consume data. Complex datasets can now be converted into easily understandable formats—visualizations, charts, or graphs—generated from natural language prompts. These insights make data accessible, enabling users to share knowledge and drive informed decisions. How Can You Use AI to Improve Customer Relationships? AI is reshaping business models, workflows, and customer engagement. By harnessing quality data, AI, and Salesforce, you can enhance how you connect with customers. Here are key ways to leverage this combination for a smarter customer strategy: Challenges You May Encounter on Your AI Journey Adopting AI in Salesforce, especially Einstein AI, offers many benefits, but it also comes with challenges. Here are some factors to consider for a successful rollout: Importance of Data Quality When Using AI Analytics Data quality is essential for AI accuracy and reliability. Poor data can skew predictions and erode user trust. Key factors that contribute to high data quality include: AI can also enhance data quality by automating data validation and cleansing. Machine learning algorithms can detect and address anomalies, duplicate records, and incomplete datasets, improving the reliability of your data over time. The Future of CRM: AI-Driven Customer Engagement and Business Growth Integrating AI into Salesforce is revolutionizing CRM by enabling businesses to engage with customers more intelligently. From automating routine tasks to enhancing decision-making and delivering personalized communication, AI-driven innovations are empowering businesses to build stronger relationships with customers. As AI continues to evolve, those who embrace it will gain a competitive edge and drive long-term growth. The future of CRM is here—and it’s smarter, faster, and more customer-focused than ever. 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

November 19, 2024in AI Tools, Data, Generative AI, Salesforce, Technology

18Nov

Redefining Autonomous AI for the Enterprise

Salesforce Agentforce: Redefining Autonomous AI for the Enterprise Salesforce has unveiled Agentforce, a groundbreaking addition to its platform that enables businesses to create and deploy autonomous AI agents capable of performing tasks across any business function. Unlike traditional chatbots or copilots, Agentforce leverages advanced reasoning capabilities to independently resolve customer cases, qualify sales leads, optimize marketing campaigns, and more. By automating actions triggered by data changes, business rules, pre-built automations, or API signals, Agentforce empowers companies like OpenTable, Saks, and Wiley to scale their workforce and enhance customer experiences. “Agentforce is redefining what’s possible in business and beyond,” said Marc Benioff, Chair and CEO of Salesforce. “This technology is ushering in an era of AI abundance and limitless workforces, augmenting employees, building deeper customer relationships, and driving unprecedented growth and profitability.” Built on a Metadata-Driven Architecture Agentforce builds on Salesforce’s metadata-driven platform, ensuring rapid deployment and customization without extensive manual effort. “Agentforce taps into the trusted Salesforce platform, seamlessly integrating enterprise data, workflows, and AI models to deliver actionable intelligence,” said Srini Tallapragada, President and Chief Engineering Officer at Salesforce. Addressing Market Inefficiencies Salesforce research identified significant inefficiencies Agentforce is designed to address: Marc Benioff emphasized, “The agent revolution is as transformative as the cloud, social, and mobile revolutions, setting a new standard for operational efficiency.” Rapid Adoption and Industry Use Cases At Dreamforce 2024, customers created over 10,000 autonomous agents in three days, with adoption accelerating to 20,000 agents globally through Salesforce World Tour events. The platform’s natural language interface enables business users—not just IT teams—to build and customize agents. Industry Applications: Ecosystem and Partner Support The launch is bolstered by partnerships with global systems integrators, including Accenture, Deloitte, IBM, PwC, and Slalom. These collaborations have accelerated emerging technology rollouts by 31%, according to Salesforce. Additionally, the new Agentblazer Community provides a hub for knowledge sharing and integrations via the Salesforce AppExchange. Pricing and Future Development Agentforce is now generally available, with pricing starting at $2 per conversation, including volume discounts. Customers can explore the platform through the Salesforce Foundations trial, offering 1,000 conversation credits for free. Future development plans focus on enabling multi-agent scenarios for complex workflows and expanding autonomous capabilities across business processes. “This is just the first chapter,” said Clara Shih, CEO of Salesforce AI. “The innovation we’ll see from this technology will transform businesses in ways we’ve only begun to imagine.” What This Means for Businesses Agentforce represents Salesforce’s most ambitious platform expansion since Einstein AI’s debut in 2016. Its consumption-based pricing model aligns with Salesforce’s broader shift toward pay-as-you-use services, mirroring strategies with Data Cloud and Einstein GPT. For enterprises, the platform offers a low-risk trial to assess its potential for driving operational improvements. The challenge will be transitioning from pilot projects to large-scale deployments while maintaining the claimed accuracy and efficiency advantages. With over 20,000 agents created and a robust partner ecosystem, Salesforce is well-positioned to lead the autonomous AI revolution. However, the ultimate success of Agentforce will depend on its ability to consistently deliver measurable business value beyond the initial wave of adoption. 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

November 18, 2024in Agentforce Platform, Data, Enterprise, Mulesoft, Salesforce Foundations, Technology

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