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Salesforce Einstein Discovery
23Mar

Salesforce Einstein Discovery

Unlock the Power of Historical Salesforce Data with Einstein Discovery Streamline Access to Historical Insights Salesforce Einstein Discovery (formerly Salesforce Discover) eliminates the complexity of manual data extraction, giving you instant access to complete historical Salesforce data—without maintaining pipelines or infrastructure. 🔹 Effortless Trend Analysis – Track changes across your entire org over time.🔹 Seamless Reporting – Accelerate operational insights with ready-to-use historical data.🔹 Cost Efficiency – Reduce overhead by retrieving trend data from backups instead of production. Why Use Historical Backup Data for Analytics? Most organizations struggle with incomplete or outdated SaaS data, making trend analysis slow and unreliable. With Einstein Discovery, you can:✅ Eliminate data gaps – Access every historical change in your Salesforce org.✅ Speed up decision-making – Feed clean, structured data directly to BI tools.✅ Cut infrastructure costs – Skip costly ETL processes and data warehouses. Einstein Discovery vs. Traditional Data Warehouses Traditional Approach Einstein Discovery Requires ETL pipelines & data warehouses No pipelines needed – backups auto-update Needs ongoing engineering maintenance Zero maintenance – always in sync with your org Limited historical visibility Full change history with minute-level accuracy 💡 Key Advantage: Einstein Discovery automates what used to take months of data engineering. How It Works Einstein Discovery leverages Salesforce Backup & Recover to:🔹 Track every field & record change in real time.🔹 Feed historical data directly to Tableau, Power BI, or other BI tools.🔹 Stay schema-aware – no manual adjustments needed. AI-Powered Predictive Analytics Beyond historical data, Einstein Discovery uses AI and machine learning to:🔮 Predict outcomes (e.g., sales forecasts, churn risk).📊 Surface hidden trends with automated insights.🛠 Suggest improvements (e.g., “Increase deal size by focusing on X”). Supported Use Cases: ✔ Regression (e.g., revenue forecasting)✔ Binary Classification (e.g., “Will this lead convert?”)✔ Multiclass Classification (e.g., “Which product will this customer buy?”) Deploy AI Insights Across Salesforce Once trained, models can be embedded in:📌 Lightning Pages📌 Experience Cloud📌 Tableau Dashboards📌 Salesforce Flows & Automation Get Started with Einstein Discovery 🔹 License Required: CRM Analytics Plus or Einstein Predictions.🔹 Data Prep: Pull from Salesforce or external sources.🔹 Bias Detection: Ensure ethical AI with built-in fairness checks. Transform raw data into actionable intelligence—without coding. Talk to your Salesforce rep to enable Einstein Discovery today! Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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March 23, 2025in Data, Salesforce, Salesforce Einstein, Salesforce Einstein Discovery, Salesforce Flow0 Comments
Salesforce Marketing Intelligence
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. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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March 18, 2025in Data, Google, Google Analytics, Marketing Intelligence, Salesforce0 Comments
advanced analytics
18Mar

Maximizing Sales Performance with Salesforce Sales Analytics

Salesforce, a leading CRM platform, provides powerful sales analytics tools that empower businesses to make data-driven decisions, boost productivity, and drive revenue growth. This guide highlights the importance of Salesforce Sales Analytics, its key features, and how to leverage them to optimize your sales team’s performance. Key Features of Salesforce Sales Analytics 1. Reports and Dashboards Salesforce’s reporting capabilities enable users to create custom dashboards and reports for real-time insights into lead conversion, sales performance, and other critical metrics. These visual tools help businesses track trends and make informed decisions effortlessly. 2. Einstein Analytics Powered by AI and machine learning, Einstein Analytics offers: 3. Sales Cloud Analytics Sales Cloud Analytics helps businesses: 4. Forecasting Tools Salesforce’s AI-powered forecasting tools provide accurate revenue projections by analyzing: How Different Teams Benefit from Sales Analytics ✅ Executives – Gain a high-level view of sales, service, and pipeline performance with real-time dashboards highlighting key business metrics. ✅ Sales Managers – Monitor team performance, track quota attainment, analyze pipeline changes, and optimize sales cycles to accelerate deal closures. ✅ Sales Representatives – Get insights into personal sales performance, pipeline activities, and quota attainment, allowing for quicker decision-making and identification of new business opportunities. ✅ Operations Teams – Analyze sales performance by customer, region, and source to optimize negotiation strategies and business development efforts. Setting Up the Salesforce Sales Analytics App 1. Launch Analytics Studio Navigate to Analytics Studio via the Sales Home page and click on the Apps button. 2. Search for Sales Analytics If the Sales Analytics App does not appear by default, use the search bar to locate it. 3. Access the Default Dashboard The default dashboard provides key metrics, including: 4. Customize Widgets Modify data representation by selecting the Edit button and customizing widgets to align with your business needs. 5. Adjust Goal Widgets Update goal widgets to match your sales targets and business objectives. 6. Explore Additional Dashboards Salesforce offers role-specific dashboards for Sales Managers, Executives, and other stakeholders to gain tailored insights. 7. Utilize the Lens Feature for Visualizations Leverage Lens to create object-specific visualizations, such as opportunities by time, stage, owner, and more. Conclusion Integrating Salesforce Sales Analytics with Tableau CRM creates a comprehensive Business Intelligence (BI) solution. However, businesses looking for a simpler or more cost-effective alternative may consider exporting Salesforce data into third-party analytics platforms for additional flexibility and ease of use. By leveraging Salesforce Sales Analytics, businesses can enhance forecasting, improve decision-making, and drive sales performance with real-time insights. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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March 18, 2025in Data0 Comments
Prioritize Data Quality
11Mar

Prioritize Data Quality

Prioritize Data Quality: Strengthening Governance for AI and Business Success 86% of analytics and IT leaders agree: AI’s effectiveness depends on the quality of its data inputs. High data quality brings organizations closer to data maturity and AI success—and it all starts with strong data governance. 🔹 92% of analytics and IT leaders say there’s never been a greater need for trustworthy data.📊 The State of Data and Analytics Report, 2023 Building a Strong Data Governance Strategy Data governance is more than compliance—it’s a structured approach to managing data quality, security, and usability. With the right governance in place, teams gain confidence in their data, leading to smarter decision-making and a culture of trust. Follow these six steps to lay the foundation for a successful governance strategy: 1. Align Governance Policies with Business Needs Meet with stakeholders to understand how data is used across teams. Ensure governance policies cover every critical workflow and use case, helping teams get the data they need—accurately and securely. 2. Define What ‘Data Quality’ Means for Your Organization Create a clear framework using these key data quality dimensions: ✅ Completeness: Are all necessary data fields populated?✅ Timeliness: Is data up to date and aligned with business goals?✅ Validity: Does data comply with governance rules and constraints?✅ Usage: How frequently is the data used for reporting and decision-making?✅ Accuracy: Does the data reflect reality, and is it sourced from trusted origins?✅ Consistency: Are data formatting and structure standardized across sources?✅ Reliability: Has data maintained quality and consistency over time? 3. Implement a Robust Quality Control Process Standardized processes—data entry validation, deduplication, cleansing, and archiving—are essential for governance. Leverage AI-powered tools like Tableau CRM Analytics to automate these tasks with built-in data profiling and enrichment features. 4. Schedule Regular Governance Reviews Your business evolves—your governance strategy should too. Establish a review cadence to assess policies, update processes, and address new data challenges. 5. Train Teams on Data Security and Compliance Education is key. Assign role-based security permissions, ensure regulatory compliance, and provide a clear process for reporting data issues (e.g., a dedicated Slack channel or help desk). 6. Define Success with Data Governance KPIs Tracking governance effectiveness is essential. Use these key metrics to measure impact: Metric Example of Smart KPI How to Track Data Quality Improve overall data quality by 4% per quarter. Assign values to frequency, error rates, and data usage. Data Usage Increase customer data-driven decision-making by 30% in 12 months. Measure employee logins, reports accessed, and data utilization. Time-to-Insight Reduce time from customer action → dashboard update to 10 minutes by next quarter. Track time-to-insight vs. benchmarks. Moving Up the Data Maturity Curve A well-governed data strategy leads to: 📈 Higher efficiency in decision-making🚀 More successful AI and analytics initiatives🏆 Competitive advantage through trustworthy data 🔍 “Ascending the data maturity curve unlocks new efficiencies and a competitive edge.”— Funke Bishi, Associate Director, Data and Business Analysis, RBC Capital Markets Take Action: Strengthen Your Data Governance ✅ Define what ‘quality data’ means for your business.✅ Align governance policies with team needs.✅ Use AI-powered tools like Tableau Data Prep for automated cleansing.✅ Train leaders on data best practices and compliance. 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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March 11, 2025in Data, Salesforce0 Comments
Aligning Strategy and Goals
07Mar

Aligning Strategy and Goals

Aligning Strategy and Goals: Bridging the Gap Between Data and Business Success Aligning data strategy with business goals is critical—but easier said than done. 41% of business leaders report that their data strategy is only partially or not at all aligned with their objectives. Here’s how to close the gap and make data a true driver of business success. 1. Define Your Business Goals Collaboration between business and IT stakeholders is essential. Start by identifying and prioritizing objectives that drive success, such as revenue growth, customer satisfaction, cost reduction, and market expansion. Business Goal How Data Supports It Revenue Growth Use analytics to identify high-value customers and optimize marketing strategies for higher conversions. Customer Satisfaction Leverage trusted customer data to personalize experiences and improve engagement. Cost Reduction Analyze operational data to streamline processes and improve efficiency. Market Expansion Use market and customer insights to identify new growth opportunities. 2. Determine Key Metrics Once goals are clear, define key performance indicators (KPIs) to measure progress. Business Goal Key Metric Revenue Growth Conversion Rate: Measures the percentage of leads converted into paying customers. Customer Satisfaction Retention Rate: Tracks the percentage of returning customers over time. Cost Reduction Operational Efficiency Ratio: Compares operational costs to revenue. Market Expansion Customer Acquisition Rate: Measures the rate of new customer growth. 3. Assess Resources and Budget Evaluate whether you have the systems, tools, and budget needed to support your goals. If customer personalization is a priority, you may need solutions like Data Cloud to unify and leverage customer insights. A strong CRM or data analytics platform may also be required to track specific KPIs. 4. Build a Data-Driven Culture Data maturity is not just about tools—it’s about people. Empower teams with the skills, training, and mindset to leverage data effectively. Change management initiatives and ongoing education will help integrate data into daily decision-making. See how F5 is building a data-driven culture with Tableau:“Data has been transforming our corporate culture right before our eyes. Every day, I wake up learning something new about data.”— Amie Bright, Former RVP of Enterprise Data Strategy and Insights, F5 5. Align Teams for Success Use this handy checklist to ensure alignment across your organization: ✅ Collaborate with business and IT teams to define and prioritize objectives.✅ Develop key data KPIs in partnership with internal stakeholders.✅ Survey team leaders to assess the tools, systems, and budgets needed.✅ Invest in training and change management to build a data-driven culture.✅ Join a data leadership community to gain insights and best practices. Want to accelerate your data strategy? Reach out to Tectonic to get started today. 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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March 7, 2025in Data, Enterprise, Salesforce Data Cloud, Technology0 Comments
Achieving AI Success Starts with Data Maturity
05Mar

Achieving AI Success Starts with Data Maturity

True AI success depends on data maturity. But what does that mean in practice? Organizations with high data maturity: The Path to Data Maturity Reaching data maturity requires a strategic commitment to: ✅ Develop a unified data strategy that aligns business and data teams toward common goals.✅ Implement strong data management and governance to ensure accuracy and trust.✅ Leverage advanced data solutions to transform raw data into actionable insights.✅ Prioritize security and compliance to protect data from breaches.✅ Foster a data-driven culture where every employee has the skills to analyze and act on insights. See How John Lewis & Partners Unlocks AI + Data-Driven Personalization “Investing in Salesforce has enabled us to make decisions faster and develop deeper relationships with our customers by providing a more personalized, convenient, and seamless customer experience.” — Libby Hickey, Tableau Product Manager, John Lewis & Partners Assess Your Data Maturity Ready to accelerate your data transformation? 📊 Take the free assessment to: Start your data maturity journey today. Contact Tectonic. 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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March 5, 2025in Data, Salesforce Data Cloud0 Comments
agetnforce for nonprofits
05Mar

TDX Announcements for Agentforce

Salesforce Expands Agentforce AI, Strengthening Its Lead in Agentic AI Salesforce’s latest updates to its agentic AI platform, Agentforce, are set to elevate its position in the competitive AI market, potentially outpacing enterprise application rivals and hyperscalers like AWS, Google, IBM, ServiceNow, and Microsoft. The updates, introduced under Agentforce 2dx, enhance orchestration, development, testing, and deployment capabilities. According to Arnal Dayaratna, vice president of research at IDC, these advancements could propel Salesforce ahead of its competition in a manner similar to OpenAI’s early dominance in large language models (LLMs). Agentforce API Expands Platform Extensibility A key enhancement in Agentforce 2dx is the Agentforce API, designed to improve extensibility and facilitate the seamless integration of agentic AI technologies into digital solutions. “Without an API, all AI agentic capabilities remain locked into the Agentforce platform,” explained Jason Andersen, principal analyst at Moor Insights & Strategy. “The API allows enterprises to build apps and agents with whatever they want.” Dion Hinchcliffe, CIO practice lead at The Futurum Group, sees this as a strategic move to drive adoption by removing usage constraints. While companies like Google and Microsoft have already introduced similar APIs, Salesforce differentiates itself by leveraging its deep CRM expertise, customer data, and business logic integration. “AI agents need contextual data to act effectively,” said Hinchcliffe. “While competitors will likely improve their integrations, Salesforce’s extensive background in business logic and automation will be difficult to match quickly.” Accelerating Enterprise Adoption with New Features Beyond the API, Agentforce 2dx includes enhancements like the Topic Center, MuleSoft integrations, Tableau Semantics, and Slack integrations, aimed at simplifying custom agent development, workflow integration, and deployment. Empowering Developers to Scale Agentic AI Salesforce is also focusing on developers with tools that provide greater control over agent creation, testing, and deployment. Key updates include: “Salesforce is encouraging hands-on experimentation, a strategy commonly used by cloud service providers,” said Cameron Marsh, senior analyst at Nucleus Research. Andersen sees this as a bold move in the SaaS market, positioning Salesforce as a direct competitor to Azure, AWS, and Google Cloud, which also offer developer-centric AI tools. Additionally, Salesforce introduced Testing Center, a low-code tool for enterprises to test agents before deployment. Scaling AI Agent Deployments with Confidence Hyoun Park, chief analyst at Amalgam Insights, emphasized the importance of these tools for scaling AI deployments. “One of the biggest challenges in agentic AI is simulating and testing interactions at scale,” Park noted. “With these capabilities, companies no longer need to manually test or build custom tools to manage AI agents.” Proven Market Traction Salesforce reports it has secured 5,000 deals with Agentforce, with customers like The Adecco Group, Engine, OpenTable, Oregon Humane Society, Precina, and Vivint already seeing immediate value. With Agentforce 2dx, Salesforce is reinforcing its leadership in agentic AI, giving enterprises more control, scalability, and integration capabilities to drive innovation in AI-powered automation. 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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March 5, 2025in Agentforce Platform, Agentic AI, AI Tools, Data, Enterprise, Google, Mulesoft, Salesforce0 Comments
AI Data Cloud and Integration
03Mar

It is Time to Implement Data Cloud

With Salesforce Data Cloud you can: With incomplete data your 360-degree customer view is limited and often leads to multiple sales reps working on the same lead. Slow access to the right leads at the right time leads to missed opportunties and delayed closings. If your team cannot trust the data due to siloes and inaccuracies, they avoid using it. It is Time to Implement Data Cloud. Unified Connect and harmonize data from all your Salesforce applications and external data systems. Then activate your data with insights and automation across every customer touchpoint. Powerful With Data Cloud and Agentforce, you can create the most intelligent agents possible, giving them access to the exact data they need to deliver any employee or customer experience. Secure Securely connect your data to any large language model (LLM) without sacrificing data governance and security thanks to the Einstein 1 trust layer. Open Data Cloud is fully open and extensible – bring your own data lake or model to reduce complexity and leverage what’s already been built. Plus, share out to popular destinations like Snowflake, Google Ads, or Meta Ads. Salesforce Data Cloud is the only hyperscale data engine native to Salesforce. It is more than a CDP. It goes beyond a data lake. You can do more with Data Cloud. Your Agentforce journey begins with Data Cloud. Agents need the right data to work. With Data Cloud, you can create the most intelligent agents possible, giving them access to the exact data they need to deliver any employee or customer experience. Use any data in your organization with Agentforce in a safe and secure manner thanks to the Einstein 1 Trust Layer. Datablazers are Salesforce community members who are passionate about driving business growth with data and AI powered by Data Cloud. Sign up to join a growing group of members to learn, connect, and grow with Data Cloud. Join today. The path to AI success begins and ends with quality data. Business, IT, and analytics decision makers with high data maturity were 2x more likely than low-maturity leaders to have the quality data needed to use AI effectively, according to our State of Data and Analytics report. “What’s data maturity?” you might wonder. Hang tight, we’ll explain in chapter 1 of this guide. Data-leading companies also experience: Your data strategy isn’t just important, it’s critical in getting you to the head of the market with new AI technology by your side. That’s why this Salesforce guide is based on recent industry findings and provides best practices to help your company get the most from your data. Tectonic will be sharing a focus on the 360 degree customer view with Salesforce Data Cloud in our insights. Stay tuned. It is Time to Implement Data Cloud 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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March 3, 2025in Data, Einstein 1 Platform, Einstein Insights, Google, Salesforce, Salesforce Data Cloud, Salesforce Implementation Services, Snowflake, Technology0 Comments
Salesforce Data Cloud
27Feb

Data Cloud March 2025 Release

Cross Cloud Updates for Data Cloud March 2025 Release Enhanced Marketing Cloud Integration Multi-Instance Event Routing Key Marketing Features: Expanded Data Sharing & Collaboration Real-Time Data Processing Event-Triggered Flows (Beta) Server-to-Server Connections Enterprise Tools Sandbox Migration External Data Connectivity Analytics & Security Key Details Feature Availability Editions Notes Multi-Instance Event Routing March 2025 Enterprise+ Action rules required 250-Object Data Shares March 2025 Enterprise+ AI/ML use cases Event-Triggered Flows March 2025 Enterprise+ Beta, add-on required This release delivers:✅ Precision marketing with cross-instance event routing✅ Scalable collaboration via expanded data sharing✅ Instant automation through real-time triggers Note: Beta features governed by Salesforce Beta Terms. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 27, 2025in Data, Enterprise, Google, Salesforce, Salesforce Data Cloud, Snowflake0 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

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February 26, 2025in Data, Salesforce, Salesforce Data Cloud0 Comments
salesforce end to end
24Feb

Salesforce and Google Announcement

Salesforce (NYSE:CRM) has entered into a deal with Google (NASDAQ:GOOGL) to offer its customer relations management software, Agentforce artificial intelligence assistants, and Data Cloud offerings through Google Cloud, the companies announced today. Google and Salesforce already have many of the same clients, and this new deal will allow for more product integration between Google Workspace and Salesforce’s customer relationship management and AI offerings. Salesforce already uses Amazon (AMZN) Web Services for much of its cloud computing. “Our mutual customers have asked us to be able to work more seamlessly across Salesforce and Google Cloud, and this expanded partnership will help them accelerate their AI transformations with agentic AI, state-of-the-art AI models, data analytics, and more,” said Thomas Kurian, CEO of Google Cloud. The deal is expected to total $2.5B over the next seven years, according to a report by Bloomberg. Salesforce and Google today announced a major expansion of their strategic partnership, delivering choice in the models and capabilities businesses use to build and deploy AI-powered agents. In today’s constantly evolving AI landscape, innovations like autonomous agents are emerging so quickly that businesses struggle to keep pace. This expanded partnership provides crucial flexibility, empowering customers to develop tailored AI solutions that meet their specific needs, rather than being locked into a single model provider. Google Cloud is at the forefront of enterprise AI innovation with millions of developers building with Google’s cutting-edge Gemini models and on Google Cloud’s AI-optimized infrastructure. This expanded partnership will empower Salesforce customers to build Agentforce agents using Gemini and to deploy Salesforce on Google Cloud. This is an expansion of the existing partnership that allows customers to use data from Data Cloud and Google BigQuery bi-directionally via zero-copy technology—further equipping customers with the data, AI, trust, and actions they need to bring autonomous agents into their businesses. Additionally, this integration empowers Agentforce agents with the ability to reference up-to-the-minute data, news, current events, and credible citations, substantially enhancing their contextual awareness and ability to deliver accurate, evidence-backed responses. For example, in supply chain management and logistics, an agent built with Agentforce could track shipments and monitor inventory levels in Salesforce Commerce Cloud and proactively identify potential disruptions using real-time data from Google Search, including weather conditions, port congestion, and geopolitical events. Availability is expected in the coming months. AI: Unlocking the Power of Choice and Flexibility with Gemini and Agentforce Businesses need the freedom to choose the best models for their needs rather than be locked into one vendor. In 2025, Google’s Gemini models will also be available for prompt building and reasoning directly within Agentforce. With Gemini and Agentforce, businesses will benefit from: For example, an insurance customer can submit a claim with photos of the damage and an audio voicemail from a witness. Agentforce, using Gemini, can then help the insurance provider deliver better customer experiences by processing all these inputs, assessing the claim’s validity, and even using text-to-speech to contact the customer with a resolution, streamlining the traditionally lengthy claims process. Availability is expected this year. Trust: Salesforce Platform deployed on Google Cloud Customers will be able to use Salesforce’s unified platform (Agentforce, Data Cloud, Customer 360) on Google Cloud’s highly secure, AI-optimized infrastructure, benefiting from features like dynamic grounding, zero data retention, and toxicity detection provided by the Einstein Trust Layer. Once Salesforce products are available on Google Cloud, customers will also have the ability to procure Salesforce offerings through the Google Cloud Marketplace, opening up new possibilities for global businesses to optimize their investments across Salesforce and Google Cloud and benefiting thousands of existing joint customers. Action: Enhanced Employee Productivity and Customer Service with AI-Powered Integrations Millions use Salesforce and Google Cloud daily. This partnership prioritizes choice and flexibility, enabling seamless cross-platform work. New and deeper connections between platforms like Salesforce Service Cloud and Google Cloud’s Customer Engagement Suite, as well as Slack and Google Workspace, will empower AI agents and service representatives with unified data access, streamlined workflows, and advanced AI capabilities, regardless of platform. Salesforce and Google Cloud are deeply integrating their customer service platforms—Salesforce Service Cloud and Google Cloud’s Customer Engagement Suite—to create a seamless and intelligent support experience. Expected later this year, this unified approach empowers AI agents in Service Cloud with: Salesforce and Google Cloud are also exploring deeper integrations between Slack and Google Workspace, boosting productivity and creating a more cohesive digital workspace for teams and organizations. The companies are currently exploring use cases such as: Expanding Partnership Capabilities and Integrations This partnership goes beyond core product integrations to deliver a more connected and intelligent data foundation for businesses. Expected availability throughout 2025: This landmark partnership between Salesforce and Google represents a strategic paradigm shift in enterprise AI deployment, emphasizing infrastructure innovation, AI capability enhancement, and enterprise value. The integration of Google Search grounding provides a unique competitive advantage, offering real-time, factual responses backed by the world’s most comprehensive search engine. The companies are committed to ongoing innovation and deeper collaboration to empower businesses with even more powerful solutions. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 24, 2025in Agentic AI, Artificial Intelligence, Data, Enterprise, Google, Salesforce, Salesforce Commerce Cloud, Salesforce Service Cloud, Technology0 Comments
Data Cloud and Genpact
14Feb

Unlock the Power of Your Data with Data Cloud

Seamlessly Connect, Unify, and Activate Your Data Data Cloud enables you to harness the full potential of your data—structured or unstructured—by integrating it across multiple sources. Key Capabilities: ✔ Connect All Data Sources – Ingest both batch and streaming data seamlessly.✔ Zero-Copy Data Federation – Access data without duplicating it.✔ Data Transformation & Governance – Standardize and secure your data.✔ Harmonize to a Common Data Model – Ensure consistency across datasets.✔ Identity Resolution – Unify data with advanced rulesets.✔ Advanced Analytics & Insights – Query, analyze, and extract business intelligence.✔ AI-Powered Predictions – Use AI to anticipate customer behavior.✔ Segmentation & Activation – Create targeted audience segments for personalized experiences.✔ Multi-Source Data Activation – Output data to multiple channels based on business needs.✔ Integration with Agentforce – Leverage data for AI-powered automation.✔ Continuous Optimization – Measure, refine, and enhance your data strategy. Designed for Every Role Data Cloud provides role-specific functionality, ensuring value across your organization. User Description Learn More Admins Enhance your admin skills with Data Cloud. Administer Data Cloud (Trailhead) Analysts Leverage Tableau to expand your analytics capabilities. Tableau Cloud Help Documentation Builders Develop applications using Data Cloud. ISVforce Guide Business Users Ingest data for diverse business needs. Salesforce Help Data Architects Map and model data effectively. Salesforce Architects Frameworks Developers Utilize APIs and SDKs to interact with Data Cloud. Data Cloud Developer Center Marketers Segment and activate audiences for cross-channel campaigns. Segmentation in Data Cloud (Trailhead) Partners Implement Data Cloud for customers. Partner Learning Camp Get Started with Data Cloud Customize Your Experience Data Cloud is built to scale, allowing you to tailor features to your business needs. While some features are included, others are available as add-ons or have adjustable limits. Work with your account executive to find the right solution. Available Editions: 📌 Data Cloud Starter – Get core Data Cloud functionality. 📌 Data Cloud + Tableau – Unlock powerful analytics with Tableau Enterprise. 📌 Marketing Use Cases – Leverage Segmentation and Activation for personalized marketing campaigns. 📌 Industry-Specific Solutions – Tailor Data Cloud for specialized needs. Better Together: Data & AI The best AI solutions are built on trusted, high-quality data. Data Cloud consolidates disparate data sources into unified customer and account profiles, fueling AI-driven automation and insights with Agentforce. Unlock the full potential of your data with Salesforce Data Cloud. Ready to get started? Learn more. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 14, 2025in Data, Enterprise, Salesforce, Salesforce Data Cloud
salesforce agentforce ai powered agentic agents
29Jan

Agentforce 2.0

Salesforce, the leading CRM provider, is set to launch Agentforce 2.0 in February 2025—an AI-powered toolset designed as a “digital labor platform for building a limitless workforce for the enterprise.” Agentforce 2.0 is a comprehensive AI system that enhances teams with autonomous AI agents embedded in everyday workflows. Among its key offerings are AI-driven agents for Sales Development and Sales Coaching, with pricing starting at $2 per conversation. With this release, Salesforce introduces a library of pre-built skills and workflow integrations, enabling rapid customization and seamless deployment within Slack. Marc Benioff, Chair and CEO of Salesforce, stated, “We’re seamlessly bringing together AI, data, apps, and automation with humans to reshape how work gets done. Agentforce 2.0 cements our position as the leader in digital labor solutions, allowing any company to build a limitless workforce that can truly transform their business.” Agentforce 2.0 includes pre-built AI skills across CRM, Slack, Tableau, and partner-developed integrations via the AppExchange. Customers can further extend Agentforce’s capabilities using MuleSoft, enabling low-code workflows that integrate with any system. The release also introduces an enhanced Agent Builder, which interprets natural language instructions—such as “Onboard New Product Managers”—to automatically generate new AI agents. These agents combine pre-made skills with custom logic built directly in Salesforce, offering unmatched flexibility and efficiency. Additionally, Agentforce 2.0 features Tableau Skills for advanced analytics and insights, further empowering businesses to harness AI-driven decision-making. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 29, 2025in Agentforce Platform, Data, Enterprise, Mulesoft, Salesforce
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