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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 Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Agentforce Testing Tool

Agentforce Testing Tool

Salesforce Unveils Agentforce Testing Center: A Breakthrough in AI Agent Lifecycle Management Salesforce, the global leader in AI-powered CRM solutions, has announced the Agentforce Testing Center, a first-of-its-kind platform for managing the lifecycle of autonomous AI agents. This innovative solution enables organizations to test AI agents at scale, leveraging synthetic data in secure environments, while ensuring accurate performance and robust monitoring. Designed to meet the unique demands of deploying intelligent AI agents, the Agentforce Testing Center introduces new tools to test, prototype, and optimize AI agents without disrupting live production systems. Core Features of the Agentforce Testing Center Why It Matters Autonomous AI agents represent a paradigm shift in enterprise software, capable of reasoning, retrieving data, and acting on behalf of users. However, ensuring their reliability and trustworthiness requires a robust testing framework that eliminates risks to live systems. The Agentforce Testing Center addresses these challenges by combining: “Agentforce is helping businesses create a limitless workforce,” said Adam Evans, EVP and GM for Salesforce AI Platform. “To deliver this value quickly, CIOs need advanced tools for testing and monitoring autonomous systems. Agentforce Testing Center provides the necessary framework for secure, repeatable deployment.” Customer and Analyst Perspectives Shree Reddy, CIO, PenFed:“With nearly 3 million members, PenFed is dedicated to providing personalized, efficient service. Using Data Cloud Sandboxes, we’re able to test and refine AI agents, ensuring they deliver fast, accurate support that aligns with our members’ financial goals.” Keith Kirkpatrick, Research Director, The Futurum Group:“To instill trust in AI, businesses must rigorously test autonomous agents. Salesforce’s Testing Center enables confidence by simulating hundreds of interaction scenarios, helping organizations deploy AI agents securely and effectively.” Availability A Competitive Edge in AI Lifecycle Management Salesforce’s Agentforce Testing Center sets a new industry standard for testing and deploying AI agents at scale. By providing a secure, scalable, and transparent solution, Salesforce enables businesses to embrace an “agent-first” approach with confidence. As enterprises continue adopting AI, tools like the Agentforce Testing Center will play a critical role in accelerating innovation while maintaining trust and reliability. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce adds Testing Center to Agentforce for AI agents

Salesforce adds Testing Center to Agentforce for AI agents

Salesforce Unveils Agentforce Testing Center to Streamline AI Agent Lifecycle Management Salesforce has introduced the Agentforce Testing Center, a suite of tools designed to help enterprises test, deploy, and monitor autonomous AI agents in a secure and controlled environment. These innovations aim to support businesses adopting agentic AI, a transformative approach that enables intelligent systems to reason, act, and execute tasks on behalf of employees and customers. Agentforce Testing Center: A New Paradigm for AI Agent Deployment The Agentforce Testing Center offers several key capabilities to help businesses confidently deploy AI agents without risking disruptions to live production systems: Supporting a Limitless Workforce Adam Evans, EVP and GM for Salesforce AI Platform, emphasized the importance of these tools in accelerating the adoption of AI agents: “Agentforce is helping businesses create a limitless workforce. To deliver this value fast, CIOs need new tools for testing and monitoring agentic systems. Salesforce is meeting the moment with Agentforce Testing Center, enabling companies to roll out trusted AI agents with no-code tools for testing, deploying, and monitoring in a secure, repeatable way.” From Testing to Deployment Once testing is complete, enterprises can seamlessly deploy their AI agents to production using Salesforce’s proprietary tools such as Change Sets, DevOps Center, and the Salesforce CLI. Additionally, the Digital Wallet feature offers transparent usage monitoring, allowing teams to track consumption and optimize resources throughout the AI development lifecycle. Customer and Analyst Perspectives Shree Reddy, CIO of PenFed, praised the potential of Agentforce and Data Cloud Sandboxes: “By enabling rigorous pre-deployment testing, we can deliver faster, more accurate support and recommendations to our members, aligning with our commitment to financial well-being.” Keith Kirkpatrick, Research Director at The Futurum Group, highlighted the broader implications: “Salesforce is instilling confidence in AI adoption by testing hundreds of variations of agent interactions in parallel. These enhancements make it easier for businesses to pressure-test autonomous systems and ensure reliability.” Availability With these tools, Salesforce solidifies its leadership in the agentic AI space, empowering enterprises to adopt AI systems with confidence and transform their operations at scale. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Conversational Commerce Explained

Conversational Commerce Explained

Conversational Commerce is a modern approach to customer engagement and sales that leverages chat-based interfaces (like messaging apps, chatbots, and voice assistants) to facilitate seamless, personalized, and real-time interactions between businesses and customers. It combines the power of conversational AI with e-commerce to create a more natural and interactive shopping experience. 1. What is Conversational Commerce? Conversational commerce allows customers to interact with brands through text or voice conversations instead of traditional methods like browsing websites or using apps. It enables businesses to engage with customers in a more personalized, immediate, and convenient way, often using tools like: 2. How Does Conversational Commerce Work? Conversational commerce uses Artificial Intelligence (AI), Natural Language Processing (NLP), and machine learning to understand and respond to customer queries. Here’s how it typically works: 3. Key Features of Conversational Commerce a) Personalization b) Real-Time Interaction c) Omnichannel Support d) Automation e) Seamless Transactions 4. Benefits of Conversational Commerce a) Improved Customer Experience b) Higher Engagement c) Increased Sales d) Cost Efficiency e) 24/7 Availability 5. Examples of Conversational Commerce a) Chatbots b) Voice Assistants c) Social Media Messaging d) In-App Messaging 6. Technologies Powering Conversational Commerce a) Artificial Intelligence (AI) b) Natural Language Processing (NLP) c) Machine Learning d) APIs and Integrations 7. The Future of Conversational Commerce 8. Challenges of Conversational Commerce In summary, conversational commerce is transforming the way businesses interact with customers by making shopping more conversational, personalized, and convenient. It’s a key trend in the future of e-commerce and customer engagement! Content updated February 2025. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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