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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 Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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salesforce service assistant

Salesforce Service Assistant

Salesforce Service Assistant is an AI-powered tool that helps service representatives resolve cases faster. It’s available on Service Cloud and is designed to save time for agents. How it works Benefits Helps agents resolve cases faster, Saves time for service representatives, Grounded in the organization’s knowledge base and data, and Adheres to company policies. Additional information Alongside agent guidance, the Service Assistant provides two other notable features. The first enables agents to create conversation summaries with “just a click” after using the solution to complete a case. The second allows agents to request that the assistant auto-crafts a new knowledge article when its guidance proved insufficient, based on how they resolved the query. Thanks to this second feature, the Service Assistant may get better with time, aiding agent proficiency, customer satisfaction, and – ultimately – average handling time (AHT). However, despite this capability, Salesforce has pledged to advance the solution further. Indeed, during a recent webinar, Kevin Qi, Associate Product Manager at Salesforce, teased what will come in June. Pointing to Service Cloud’s Summer ‘25 release wave, Qi said: The next phase of Service Assistant involves actionable plans. So, not only will it help guide the service rep, but it’ll also take actions to automate various steps, so it can look up orders, check eligibilities, and more to help speed up the efficiency of tackling that case. Beyond the summer, Salesforce plans to have the Assistant blend modalities, guiding customer conversations across channels to further streamline the interaction. “The Service Assistant will become even more adaptive, support more channels, including messaging and voice, being able to adapt to changes in case context,” concluded Qi. The Latest AI Solutions on Service Cloud Alongside the Service Assistant, Salesforce has released several other AI and Agentforce capabilities, embedded across Service Cloud. Qi picked out the “Freeform Instructions in Service Email Assistant” feature for special reference. “If the agent doesn’t have a template already made for a particular instance, they can type – in natural language – the sort of email they’d want to generate and have Agentforce create that email in the flow of work,” he said. That capability may prove highly beneficial in helping agents piece their thoughts together when resolving a tricky case. After all, they can note some key points – in natural language – and the feature will create a coherent customer response. Alongside this comes a solution to quickly summarize case activity for wrap-up in beta. Yet, most new features focus on improving the knowledge that feeds into AI solutions, like the Service Assistant. For starters, there’s a flow orchestrator in beta that helps contact center leaders build a process for approving new knowledge articles and updates. Additionally, there’s an “Update Knowledge Content with AI” feature. This ingests prompts and – as it says on the tin – updates the tone, style, and length of particular knowledge articles. Last comes the “Knowledge Sync to Data Cloud” tool that pulls contact center knowledge into the Salesforce customer data platform (CDP). Not only does this democratize service insights, but it also supports contact centers in grounding the Service Assistant and other AI agents. Both of these final knowledge capabilities are now generally available. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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My Service Journey is Here

Salesforce Service Assistant Now Generally Available

Salesforce Service Assistant Now Generally Available in Service Cloud Salesforce has officially launched Service Assistant in Service Cloud, bringing AI-powered agent guidance to customer service teams. The assistant creates step-by-step action plans to help agents resolve queries efficiently by analyzing intent, case history, and customer context. Previously known as Salesforce Service Planner, the solution entered a pilot phase in October 2024 and is now live just four months later. Enhancing Accuracy with Data Cloud Integration To maximize accuracy, Salesforce recommends integrating Service Assistant with Data Cloud and the contact center knowledge base. This connection enables the assistant to access critical business processes and customer history across service, sales, marketing, and more. Key Features of Service Assistant Beyond real-time agent guidance, Service Assistant introduces two standout capabilities: This continuous learning cycle improves agent proficiency, enhances customer satisfaction, and reduces Average Handling Time (AHT). What’s Next for Service Assistant? Despite these capabilities, Salesforce plans to further enhance Service Assistant. In a recent webinar, Kevin Qi, Associate Product Manager at Salesforce, revealed upcoming enhancements in the Summer ’25 release (June 2025): “The next phase of Service Assistant involves actionable plans. It will not only guide service reps but also automate steps like looking up orders and checking eligibility to speed up case resolution.” Beyond summer, Salesforce aims to make Service Assistant more adaptive, supporting additional channels such as messaging and voice while dynamically adjusting to case context changes. Expanding AI & Agentforce Capabilities in Service Cloud Alongside Service Assistant, Salesforce has introduced several AI and Agentforce capabilities across Service Cloud. Highlighted features include: What’s Coming in the Summer ’25 Release? One of the most anticipated features in June 2025 is Agentforce: Service Actions in Slack. Salesforce already enables case swarming in Slack, allowing agents to collaborate with external teams. Now, this guidance will be automatically recorded in the case summary and converted into knowledge articles for future reference. Other upcoming knowledge management features include: Custom AI with Agentforce Beyond prebuilt AI solutions, Agentforce enables brands to create AI-powered workflows tailored to their needs. Service teams can: By integrating Agentforce with Data Cloud, businesses can connect cross-platform workflows and automate enterprise-wide operations. Content updated March 2025. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Open Activities vs. Activity History

Understanding Activity Management in Salesforce: Open Activities vs. Activity History Core Concepts of Activity Tracking Salesforce provides two specialized read-only components for tracking interactions with records: These components appear as related lists on record pages and provide a comprehensive view of all interactions with contacts associated with the record. Key Characteristics of Activity Objects Read-Only Nature Special Considerations Functional Capabilities What Users Can Do ✔ View activities through standard and custom record pages✔ Create new tasks/events via the Activity tab or timeline✔ Edit existing activities through the UI interface✔ Track completion status of all interactions System Limitations ✖ No direct SOQL queries against OpenActivity/ActivityHistory objects✖ No API operations (insert/update/delete) on these objects✖ No workflow/process builder automation on the read-only objects Practical Implementation Guide Viewing Activities Managing Activities Technical Architecture These read-only objects serve as: Alternative Approaches for Developers While direct SOQL access isn’t available, developers can: Best Practices for Activity Management These read-only activity components provide essential tracking capabilities while maintaining system integrity through their protected design. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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The Hidden Risks of Over-Reliance on AI

The Hidden Risks of Over-Reliance on AI

Are Marketers Trusting AI Too Much? How to Avoid Losing Your Strategic Edge AI tools have revolutionized how marketers approach research, content creation, and decision-making. However, an overreliance on these tools could undermine critical thinking and strategic planning, leaving marketers vulnerable in a fast-evolving landscape. Here’s how to balance the power of automation with human insight. The Rise of AI in Search and Marketing In late December, SEO consultancy Previsible shared a striking report: Google’s search dominance has plateaued and is now being challenged by AI-assisted search tools. These tools, such as ChatGPT, Claude, and Google’s own AI-enhanced search, are growing in popularity due to their ability to deliver contextually relevant and personalized results. Unlike traditional search, which relies on keyword matching, AI-driven search processes intent and context. This shift is reshaping how users find information and make decisions. How AI Is Changing User Behavior The increasing sophistication of AI tools brings both opportunities and risks. Users often trust AI-generated outputs without question, assuming they’re accurate and complete. Traditional search, by contrast, forces users to critically analyze and filter multiple sources. This blind trust in AI mirrors the concept of “System 1 thinking,” as described by Nobel Prize-winning psychologist Daniel Kahneman in Thinking, Fast and Slow. As AI models like ChatGPT operate primarily as “System 1 thinkers,” users risk adopting a similar approach, bypassing critical analysis in favor of convenience. The Hidden Risks of Over-Reliance on AI Younger marketers may be especially at risk of falling into this trap. Many are using AI tools like ChatGPT to summarize information or generate ideas, often without questioning the accuracy of the outputs. For B2B marketers, the allure of AI lies in its speed and perceived accuracy. However, this reliance on automation could lead to a generation of marketers who lack the ability—or inclination—to think strategically. The danger is clear: unchecked dependence on AI tools could foster a “groupthink” mentality, where creativity and critical thinking are sidelined. Without intervention, marketing departments risk becoming overly reliant on tools that were designed to enhance human efforts, not replace them. How Marketing Leaders Can Address This Threat To counter this trend, marketing leaders must actively promote the development of strategic skills. Here’s how: In a world increasingly driven by AI, marketers who can blend automation with strategic thinking will be best positioned for success. Using AI to Enhance, Not Replace, Strategic Thinking AI should empower marketers to make better decisions—not serve as the sole decision-maker. As one professor aptly put it, “Use AI to become a better student, not to be the student.” The key is balance. By combining the intuitive capabilities of AI with the deliberate, analytical approach of System 2 thinking, marketers can leverage technology without sacrificing creativity or strategy. In short, AI is a tool—not a replacement for human ingenuity. Those who recognize this distinction will thrive in an increasingly automated world. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Potential of GenAI in Healthcare

5 Key Use Cases for Generative AI in Healthcare Documentation

Generative AI (GenAI) holds significant promise for improving healthcare documentation, but clear regulations and standards are needed to maximize benefits while minimizing risks. Healthcare documentation encompasses medical histories, clinical notes, diagnostic results, treatment plans, prescriptions, and billing records. Studies show that clinicians spend more time on documentation than patient care—a major contributor to burnout. GenAI can help by automating electronic health record (EHR) data entry and drafting medical notes for clinician review. According to a February 2025 American Medical Association (AMA) survey, early GenAI adoption in healthcare focuses on administrative tasks that enhance documentation quality and efficiency. For example, Microsoft’s Dax Copilot saves clinicians five minutes per patient encounter, while Oracle Health Clinical AI Agent reduces documentation time by nearly 30%. Here are five key ways GenAI improves healthcare documentation: 1. Streamline Workflows GenAI reduces administrative burdens by automating documentation tasks, allowing clinicians to focus more on patient care. Key applications include: A JAMA Network Open (2024) study found AI-generated draft replies to patient messages reduced provider workload and emotional exhaustion, suggesting strong potential for workflow efficiency. 2. Improve Data Accuracy GenAI enhances documentation precision by identifying missing or inconsistent data. Applications include: By minimizing manual entry, GenAI helps prevent errors that lead to billing delays or compliance issues. 3. Optimize Medical Data Approximately 80% of healthcare data is unstructured (e.g., physician notes, scanned documents). GenAI transforms this into structured, usable formats by: This optimization improves interoperability and speeds up decision-making. 4. Reduce Clinician Burnout Physician burnout is often linked to excessive documentation. GenAI alleviates stress by: A UC San Diego (2024) study found that AI-assisted documentation helps clinicians engage more with patients, improving satisfaction and outcomes. 5. Enhance Patient Engagement GenAI improves patient interactions by: By reducing screen time during visits, GenAI helps clinicians build stronger patient relationships. Best Practices for GenAI in Healthcare Documentation To ensure safe and effective AI adoption:✔ Start with pilot programs – Test AI tools in controlled settings.✔ Train clinicians on AI review – Ensure staff can validate AI-generated content.✔ Notify patients about AI use – Maintain transparency in documentation.✔ Secure patient data – Encrypt and de-identify protected health information (PHI).✔ Maintain audit logs – Track AI-generated documentation for accuracy and compliance. Challenges & Future Outlook GenAI faces hurdles in data privacy, regulatory compliance, and liability. Until formal standards emerge, frameworks like the WHO’s AI Ethics Guidelines and Coalition for Health AI (CHAI) Assurance Standards can help guide responsible use. As multimodal AI models advance, GenAI will better adapt to clinician workflows. However, strong governance is essential to balance innovation with patient safety. Conclusion GenAI is transforming healthcare documentation by reducing burnout, improving accuracy, and enhancing patient engagement. By implementing best practices and robust governance, healthcare organizations can harness AI’s potential while mitigating risks. Content updated April 2025. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Financial Services Sector

Fundingo Outshines Mortgage Automator

Why Fundingo Outshines Mortgage Automator: A Salesforce-Based Perspective Introduction In the dynamic world of loan servicing and mortgage management, businesses face increasing demands for flexibility, efficiency, and scalability. While Mortgage Automator is a well-known provider, many users encounter significant challenges, including inflexible loan structures and cumbersome reporting processes. Fundingo, a Salesforce-native solution, addresses these issues head-on with a modern, adaptable, and user-friendly approach to loan management. Pain Points of Mortgage Automator Despite its established presence, Mortgage Automator comes with notable limitations: Fundingo’s Competitive Edge Fundingo offers a suite of advantages designed for modern lending institutions, making it the superior choice: Head-to-Head Comparison Feature Fundingo Mortgage Automator Flexibility High – Supports diverse loan products Limited – Rigid loan structures Reporting Automated and user-friendly Complex and manual processes Integrations Seamless with Salesforce ecosystem Poor integration capabilities Scalability Cost-effective, built-in scalability Expensive add-ons hinder growth Security & Compliance SOC 1 certified Basic security measures Summary Fundingo emerges as the ideal solution for modern loan servicing and mortgage management. By addressing the common challenges associated with Mortgage Automator—rigid loan structures, manual processes, and costly add-ons—Fundingo provides a flexible, scalable, and secure alternative. Its Salesforce-native design, built-in CRM, mobile accessibility, exceptional uptime, and robust security measures make it the best competitor in the market, empowering financial institutions to deliver exceptional service while optimizing operational efficiency. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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salesforce agentforce ai powered agentic agents

AI for Membership Sites

AI for Membership Sites: How Artificial Intelligence is Driving New Revenue for Member-Only Platforms Membership sites are entering a transformative era where “AI is the New UI.” Two recent developments illustrate this trend and underscore how artificial intelligence is redefining user interaction and unlocking new revenue streams. The first insight comes from Dr. John Sviokla’s Forbes article, “AI Is The New UI: 3 Steps Business Leaders Must Take Now”. Sviokla emphasizes a fundamental shift: “For decades, we’ve interacted with technology through screens, buttons, and menus. But a fundamental shift is underway — artificial intelligence is becoming the new user interface.” The second example involves a large members-only association in the airline industry. This organization has implemented custom AI chatbots within its member portal to address a growing challenge: members no longer have time to sift through lengthy PDFs or dense slide decks. Instead, they crave fast, ChatGPT-style access to information—and they’re willing to pay for it. A Paradigm Shift in User Interfaces Historically, intuitive gestures and responsive designs revolutionized how people interacted with technology. Today, AI is driving the next evolution, moving interfaces from static designs to dynamic, user-centric experiences. Dr. Sviokla notes: “This transformation isn’t just about chatbots; it’s about AI becoming the primary means through which we interact with systems, data, and machines. For business leaders, this shift represents both an opportunity and an imperative to reimagine how their organizations engage with customers and operate internally.” AI-powered interfaces offer users immediate, conversational, and personalized access to information, bypassing the traditional maze of links and menus. For membership sites, this evolution is particularly significant, as it transforms how members interact with content and services. The “ChatGPT Effect” on Membership Sites The rise of ChatGPT has shifted consumer expectations for digital interactions. Websites are now adopting chatbots and virtual assistants that provide tailored experiences. For membership sites, this technology enables: For example, organizations are deploying AI assistants on their websites to handle various functions, such as sales inquiries, product support, and pricing guidance. These tools enhance member satisfaction and provide opportunities for new revenue streams. AI as a Revenue Generator Membership sites leveraging AI are seeing measurable financial benefits. Consider a crypto token regulation platform that integrated custom AI chatbots. These tools allow members to interact with proprietary data in real time, transforming static content into a dynamic, accessible resource. This shift has significantly increased the platform’s value proposition, attracting and retaining members willing to pay a premium for enhanced access. Starting Small: A Scalable Approach to AI Implementing AI doesn’t require a complete system overhaul. Membership sites can begin with a simple, custom chatbot built using existing content, such as publicly available documents or FAQs. By monitoring member interactions and gathering feedback, organizations can gradually expand their AI capabilities. The key is to focus on enhancing the member experience. Missteps often occur when organizations adopt overly complex solutions that fail to address real user needs. A phased approach ensures AI integration adds value and aligns with member expectations. The Future of AI in Membership Sites The potential for AI in membership sites extends far beyond chatbots. Future applications include: For example, the Martin Trust Center for MIT Entrepreneurship recently launched an AI-powered tool specifically designed to serve its members. These types of innovations highlight how AI can enhance the member experience while driving operational and financial success. Reimagining Member Engagement Membership sites that embrace AI as a foundational component of their user experience are positioning themselves for long-term success. By focusing on solving real problems and delivering meaningful interactions, organizations can strengthen member relationships and drive sustainable growth. For membership sites, the question is no longer whether to adopt AI but how quickly they can integrate it. AI represents an opportunity—and an imperative—to transform the way members interact with content, data, and services. The sites that act now will set the standard for the future of member-driven platforms. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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Agentforce for Retail

Agentforce for Retail

Salesforce Introduces Agentforce for Retail: A Sector-Specific Skills Library for AI Innovation Salesforce has unveiled Agentforce for Retail, an industry-specific skills library designed to empower retailers to develop AI agents tailored to their unique business needs. This release provides tools for retailers to enhance customer service, assist store associates, and engage customers in innovative ways. For example, AI agents can now automate and streamline processes like order management, guided shopping, and appointment scheduling. While Salesforce had previously launched 100 preconfigured, industry-specific AI agents for the core Agentforce platform, this new retail-focused release represents a shift toward providing specialized tools that enable retailers to build AI agents with greater precision and flexibility. Driving Seamless, Unified Retail Experiences Nitin Mangtani, SVP & GM of Retail at Salesforce, described the vision behind Agentforce for Retail: “Salesforce is helping retailers deliver seamless, unified shopping experiences across both the physical and digital realms of retail, driving productivity advancements and business growth across their entire enterprise.” This move aligns with Salesforce’s broader commitment to delivering sector-specific AI innovations, expanding the Agentforce offering into targeted solutions that meet the distinct demands of industries like retail. Agentforce for Retail: Core Capabilities Commerce Skills for Order Management These skills empower retailers to offer self-service order support, helping reduce costs while boosting customer loyalty. Customers can: Commerce Skills for Guided Shopping Using natural language, customers can receive personalized product recommendations based on behavior, inventory, and operational data. They can also: Field Service Skills for Appointment Scheduling Service representatives can use AI-powered tools to streamline the scheduling of deliveries, installations, or consultations. Real-time availability updates improve efficiency and enhance customer satisfaction. Marketing Skills for Loyalty Promotion Creation Marketers can use conversational prompts informed by shopper data, point-of-sale (POS) insights, and segmentation to design loyalty campaigns. These tools also assist in creating personalized email content and subject lines to drive higher engagement. Retail Cloud with Modern POS: A Complementary Innovation In addition to Agentforce for Retail, Salesforce announced the Retail Cloud with Modern POS, a cloud-based point-of-sale solution designed to unify online and offline shopping experiences. Key features include: The POS system also incorporates AI capabilities such as: Shoppers benefit from flexible fulfillment options, including buy-online-pickup-in-store (BOPIS) and omni-exchanges. Each cart item can have unique fulfillment methods, optimizing supply chain costs while enhancing convenience. Mangtani noted, “Together, AI-fueled digital labor and a modern POS can unlock a new scale of operational capacity for retailers.” The Evolution of Agentforce: A Platform for Digital Labor In late 2024, Salesforce launched Agentforce 2.0, branding it as “The Digital Labor Platform.” This expanded version introduced enhanced capabilities aimed at helping businesses streamline operations and adopt AI-driven automation on a larger scale. Agentforce for Retail builds on this foundation, offering retailers the tools to reimagine customer engagement, boost efficiency, and drive business growth. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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HIPAA

Salesforce HIPAA Compliance

Compliance plays a critical role in managing sensitive information, especially under regulations like the Health Insurance Portability and Accountability Act (HIPAA). Salesforce HIPAA Compliance. Enacted in 1996, HIPAA establishes national standards for safeguarding sensitive health information. Organizations and individuals who store, manage, or transmit healthcare data are subject to these regulations, which prioritize the confidentiality, integrity, and availability of patient information. While Salesforce provides tools to support HIPAA compliance, the responsibility for ensuring compliance ultimately lies with the data-processing organization or individual—not solely the platform itself. This insight explores Salesforce’s role in HIPAA compliance, key features for safeguarding electronic Protected Health Information (ePHI), and best practices for adhering to regulatory requirements. Understanding HIPAA Salesforce’s flexibility as a CRM platform allows it to serve industries that require HIPAA compliance, particularly healthcare and life sciences. At its core, HIPAA protects Protected Health Information (PHI)—any patient-identifiable information in medical records. PHI extends beyond traditional medical data to include names, addresses, birth dates, Social Security numbers, and more. When PHI is managed or transmitted electronically, it’s classified as electronic Protected Health Information (ePHI), which is subject to additional safeguards. Entities Covered by HIPAA HIPAA applies to several types of entities: While Salesforce is classified as a Business Associate, organizations using the platform remain responsible for adhering to HIPAA’s security requirements. Salesforce and the Business Associate Agreement (BAA) As a Business Associate, Salesforce must enter into a Business Associate Agreement (BAA) with healthcare organizations and other Covered Entities to define responsibilities and security measures for handling ePHI. The BAA outlines the Salesforce features and services eligible for HIPAA compliance. Notably: Without a signed BAA, organizations face significant penalties for HIPAA violations, even in the absence of a data breach. HIPAA-Compliant Salesforce Solutions Salesforce offers various solutions and features to support HIPAA compliance. These are categorized into platform security measures and specific compliant services: Key Security Features HIPAA-Compliant Services It’s important to note that not all Salesforce features are HIPAA-compliant, and proper configuration is critical to ensure compliance. Restrictions and Challenges While Salesforce offers robust security tools, some limitations and risks exist: Additionally, some Salesforce services, like certain social or mobile features in Health Cloud, are not compliant by default and require explicit mention in the BAA to be used with ePHI. Best Practices for HIPAA Compliance To maximize HIPAA compliance with Salesforce, organizations should: HIPAA Compliance Checklist Here’s a concise checklist to guide your HIPAA compliance efforts: Leveraging Third-Party Tools Solutions like GRAX can enhance HIPAA compliance in Salesforce by adding capabilities such as data backup, archiving, and recovery. GRAX’s security features include: However, integrating third-party solutions requires careful vetting to avoid compliance risks. Salesforce HIPAA Compliance Salesforce is a powerful tool for healthcare organizations, but achieving HIPAA compliance requires understanding its capabilities and limitations. A well-configured Salesforce environment, combined with diligent user management and third-party tools, can help organizations meet regulatory requirements while safeguarding patient data. By embracing best practices and staying informed about shared responsibilities, organizations can ensure HIPAA compliance, avoid penalties, and build trust with patients and stakeholders. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Native Salesforce App to Simplify Event Management

Native Salesforce App to Simplify Event Management

Why a Native Salesforce App Changes Everything Streamlined Event Operations Blackthorn.io’s platform eliminates the need for external integrations by operating entirely within Salesforce. This means event data—registrations, payments, and attendee interactions—is instantly accessible and linked to existing CRM records in real-time. Case in Point: USC Marshall School of Business Facing inefficiencies in manual data entry and registration processes, USC Marshall School adopted Blackthorn.io’s solution. They leveraged branded event pages, automated attendee check-ins, and simplified scaling for admissions events. The Salesforce-native architecture streamlined data analysis, ensuring a single source of truth and improving follow-ups with prospective students. Harnessing Salesforce Data for Personalization Blackthorn.io’s platform empowers organizations to personalize event experiences using CRM data. For example: Traditional event tech systems only pull basic fields into Salesforce. In contrast, Blackthorn.io leverages all standard and custom Salesforce fields, enabling planners to design deeply personalized event experiences. Addressing Integration Challenges Event planners often face inefficiencies caused by integrating third-party platforms with Salesforce, such as data flow disruptions, duplicate management, and delays. Blackthorn.io removes these obstacles by unifying event data with CRM data. This seamless approach enables real-time management of everything from registration to post-event follow-ups, cutting hours of manual work. 🔔🔔  Follow us on LinkedIn  🔔🔔 Applications Across Industries Corporate Events Higher Education Healthcare Nonprofits Associations AI and Automation: Redefining Event Planning Leverage Salesforce AI Blackthorn.io taps into Salesforce’s AI capabilities to deliver advanced insights, such as correlating event attendance with conversion likelihood. This reduces planning time and enhances decision-making. AgentForce AI AgentForce from SalesforceLaunching in 2025, Blackthorn.io’s upcoming AgentForce-based AI will analyze multiple data sources for insights beyond traditional reporting. It will answer questions like, “Which events are most effective for donor acquisition?” Scaling with Personalization Key Features Clients Love The Blackthorn Advantage By operating natively within Salesforce, Blackthorn.io simplifies event management while empowering organizations to deliver personalized, data-driven experiences. Its unified approach to event data eliminates inefficiencies, scales effortlessly, and opens up new opportunities for meaningful engagement across industries. Ready to transform your event management? Discover the power of Blackthorn.io with Tectonic and start planning smarter today. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Agentforce for Retail

Agentforce for Retail

Salesforce Introduces Agentforce for Retail and Retail Cloud with Modern POS Just ahead of the National Retail Federation (NRF) conference in New York, Salesforce has announced Agentforce for Retail and Retail Cloud with Modern POS, further expanding its AI-driven capabilities into the retail sector. This launch underscores Salesforce’s commitment to leveraging agentic AI to enhance productivity and streamline retail operations. Saks Fifth Avenue and SharkNinja: Early Adopters Retail giants like Saks Fifth Avenue and SharkNinja are among the first to test Agentforce for Retail, showcasing its potential to redefine customer engagement and operational efficiency in the industry. Agentforce for Retail Agentforce for Retail equips businesses with a library of pre-built AI agent skills tailored specifically for retail use cases, delivering what Salesforce calls “digital labor.” These skills are designed to simplify routine tasks, freeing up human employees to focus on higher-value activities. New Pre-Built Skills These tools aim to help retailers deploy AI agents efficiently, improving customer satisfaction and operational scalability. Retail Cloud with Modern POS Retail Cloud with Modern POS consolidates online and offline inventory data into a single, unified platform, empowering retailers with modern tools for seamless customer experiences. Key Features Retail Cloud integrates seamlessly with Commerce Cloud, Service Cloud, and Order Management, ensuring a cohesive ecosystem for retailers. Why This Matters This dual announcement highlights Salesforce’s strategy to embed Agentforce as a foundational capability across its multi-cloud architecture, while also tailoring solutions for specific industries like retail. “Together, AI-fueled digital labor and a modern POS can unlock a new scale of operational capacity for retailers,” said Nitin Mangtani, Salesforce SVP and GM of Retail, in a press release. With Agentforce for Retail, Salesforce empowers brands to embrace AI-driven automation while modernizing their point-of-sale systems, enabling a seamless blend of personalized customer engagement and operational excellence. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Statement Accuracy Prediction based on Language Model Activations

Statement Accuracy Prediction based on Language Model Activations

When users first began interacting with ChatGPT, they noticed an intriguing behavior: the model would often reverse its stance when told it was wrong. This raised concerns about the reliability of its outputs. How can users trust a system that appears to contradict itself? Recent research has revealed that large language models (LLMs) not only generate inaccurate information (often referred to as “hallucinations”) but are also aware of their inaccuracies. Despite this awareness, these models proceed to present their responses confidently. Unveiling LLM Awareness of Hallucinations Researchers discovered this phenomenon by analyzing the internal mechanisms of LLMs. Whenever an LLM generates a response, it transforms the input query into a numerical representation and performs a series of computations before producing the output. At intermediate stages, these numerical representations are called “activations.” These activations contain significantly more information than what is reflected in the final output. By scrutinizing these activations, researchers can identify whether the LLM “knows” its response is inaccurate. A technique called SAPLMA (Statement Accuracy Prediction based on Language Model Activations) has been developed to explore this capability. SAPLMA examines the internal activations of LLMs to predict whether their outputs are truthful or not. Why Do Hallucinations Occur? LLMs function as next-word prediction models. Each word is selected based on its likelihood given the preceding words. For example, starting with “I ate,” the model might predict the next words as follows: The issue arises when earlier predictions constrain subsequent outputs. Once the model commits to a word, it cannot go back to revise its earlier choice. For instance: In another case: This mechanism reveals how the constraints of next-word prediction can lead to hallucinations, even when the model “knows” it is generating an incorrect response. Detecting Inaccuracies with SAPLMA To investigate whether an LLM recognizes its own inaccuracies, researchers developed the SAPLMA method. Here’s how it works: The classifier itself is a simple neural network with three dense layers, culminating in a binary output that predicts the truthfulness of the statement. Results and Insights The SAPLMA method achieved an accuracy of 60–80%, depending on the topic. While this is a promising result, it is not perfect and has notable limitations. For example: However, if LLMs can learn to detect inaccuracies during the generation process, they could potentially refine their outputs in real time, reducing hallucinations and improving reliability. The Future of Error Mitigation in LLMs The SAPLMA method represents a step forward in understanding and mitigating LLM errors. Accurate classification of inaccuracies could pave the way for models that can self-correct and produce more reliable outputs. While the current limitations are significant, ongoing research into these methods could lead to substantial improvements in LLM performance. By combining techniques like SAPLMA with advancements in LLM architecture, researchers aim to build models that are not only aware of their errors but capable of addressing them dynamically, enhancing both the accuracy and trustworthiness of AI systems. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Salesforce Spring ’25 Release

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 Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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