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Salesforce Sales Engagement for Nonprofits
17Mar

Salesforce Sales Engagement for Nonprofits

Supercharge Your Nonprofit’s Donor Outreach with Salesforce Sales Engagement It’s time for the annual donor campaign. The fundraising team is juggling hundreds—if not thousands—of emails, phone calls, and follow-ups. The budget depends on surpassing last year’s donations, but with limited staff and time, reaching every potential donor feels impossible. The executive director asks, “How can we maximize donor engagement without increasing headcount—or at least focus our resources on the most likely givers?” Sound familiar? Every nonprofit faces the challenge of doing more with less. Fortunately, Salesforce offers a solution to keep your team organized, on task, and working smarter: Salesforce Sales Engagement. What Is Salesforce Sales Engagement? Salesforce Sales Engagement acts as a high-powered assistant for fundraising, membership, or program teams. This productivity hub, embedded within Salesforce, streamlines daily activities through automation, organization, and AI-powered insights. Key benefits include:✅ Cadences & Work Queues – Ensure no email, call, or task slips through the cracks.✅ Centralized Outreach – Keep all donor interactions in one place for seamless engagement.✅ AI-Driven Optimization – Analyze performance and refine strategies based on data. Previously known as High-Velocity Sales, Sales Engagement accelerates development cycles and scales outreach efforts effortlessly. By prioritizing critical tasks and automating others, your team can focus on building meaningful relationships and securing commitments faster. Engagement Cadences: Your Fundraising Playbook in Action Cadences serve as step-by-step roadmaps, guiding teams on how and when to engage with donors, members, or program participants. Whether you’re running a donor drive, promoting event registrations, or managing renewals, cadences ensure consistency and efficiency. Two Types of Cadences: 1️⃣ Standard Cadences – A structured sequence of touchpoints (emails, calls, LinkedIn messages) over time, such as a 30-day donor onboarding journey.2️⃣ Quick Cadences – A single, repeatable action, like automatically sending a thank-you email after a donation. With Cadence Builder, customizing workflows for different donor segments is fast and easy. Actions dynamically adjust based on engagement—so if a donor opens an email, they might receive a follow-up call; if they don’t, a reminder email is sent instead. Best of all, your team doesn’t have to track or remember each step—Sales Engagement assigns tasks automatically to individual work queues, ensuring nothing gets missed. Data-Driven Decision-Making with Built-In Analytics To improve outreach, you need to measure it. Sales Engagement provides powerful dashboards and reports to evaluate performance and optimize your approach. ✅ Track email open rates, call response rates, and donor engagement trends.✅ Identify successful messaging and refine underperforming campaigns.✅ Tie engagement metrics to fundraising goals to measure real impact. Unlike basic email tracking, Sales Engagement helps nonprofits connect data-driven insights with mission outcomes—empowering smarter decision-making without complex process changes. Already Using Salesforce Flows for Outreach? If your nonprofit relies on Salesforce Flow for outreach, you may wonder if Sales Engagement is necessary. The answer? Yes—if you want to do more with less effort. While flows are great for automation, Sales Engagement goes further with built-in call scripts, AI-powered task prioritization, and adaptable cadences. It offers a more intuitive, flexible approach to donor engagement, reducing manual work and boosting efficiency. Ready to Transform Your Fundraising Strategy? Salesforce Sales Engagement isn’t just for corporations—it’s a game-changer for nonprofits, helping teams increase donations, memberships, and event participation with less effort and greater impact. Are you ready to work smarter, engage better, and raise more? Let’s get started. Contact Tectonic 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 17, 2025in Data, Salesforce, Salesforce Flow0 Comments
Salesforce Energy and Utilities Cloud Explained
17Mar

Salesforce Energy and Utilities Cloud Explained

Salesforce Energy and Utilities Cloud is a specialized industry solution built on the Salesforce platform, designed to meet the unique needs of energy and utility companies. It helps these organizations manage customer relationships, streamline operations, and drive digital transformation in an increasingly complex and regulated industry. The cloud solution provides tools for customer engagement, field service management, and regulatory compliance, among other functionalities. Key Features of Salesforce Energy and Utilities Cloud: Benefits of Salesforce Energy and Utilities Cloud: Use Cases: Implementation Considerations: In summary, Salesforce Energy and Utilities Cloud is a comprehensive solution designed to help energy and utility companies enhance customer engagement, streamline operations, and achieve regulatory compliance. By leveraging advanced technologies and industry-specific functionalities, utilities can drive digital transformation and improve overall performance. 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 17, 2025in Data, Salesforce, Salesforce Einstein0 Comments
Financial Services Sector
14Mar

Future of Financial Services

The Future of Financial Services: AI Agents, Consumer Trust, and Digital Transformation Fewer than half of consumers are fully satisfied with the service they receive from banks, insurance providers, and wealth management advisors. This underscores the urgent need for financial service institutions (FSIs) to prioritize standout customer experiences—both human and digital—leveraging AI agents to enhance personalization, efficiency, and responsiveness. Why Customer Experience is Key Consumer loyalty has long been driven by competitive pricing, fees, and interest rates. However, with declining rates making promotional incentives less feasible, FSIs are refocusing on customer service as a key differentiator. AI-powered digital experiences provide an opportunity to exceed customer expectations, offering speed, convenience, and hyper-personalization at scale. A significant portion of consumers are willing to stay with an institution that offers an exceptional experience, even if it raises its rates or fees. For instance, 46% of consumers—and 55% of high earners in the U.S. (households making over $100,000 per year)—value experience over pricing alone. Digital self-service is a primary component of this enhanced experience, with many consumers preferring to complete tasks online rather than through traditional phone or in-branch interactions. Institutions like Credit Unions are already meeting this demand by deploying self-service tools that provide instant resolutions, 24/7. AI Agents: Transforming the FSI Landscape AI agents represent a major leap forward in customer service, automating interactions and resolving issues without human intervention. However, trust in these AI-driven systems remains a work in progress. Only 41% of wealth management clients report being fully satisfied with their institution’s speed and effectiveness, and satisfaction levels are even lower among banking and insurance customers. Despite some skepticism, AI adoption is accelerating. Half of consumers expect AI to significantly impact their financial relationships, a belief even more pronounced among Millennials and Gen Z. The percentage of customers anticipating AI-driven transaction speed improvements has risen from 46% in 2023 to 65% today. Yet, consumer education on AI’s capabilities remains a challenge. AI agents have the potential to act as financial advisors, enhancing financial literacy, optimizing savings, and even increasing earnings. Salesforce’s Agentforce aims to bridge this gap, offering digital financial assistants that can answer questions like, “Am I saving enough for retirement?” or “Can I afford this vacation?”—delivering expert insights instantly and at scale. Building Trust in AI-Powered Finance Despite AI’s promise, trust issues persist. While 54% of consumers express confidence in AI agents, only 10% fully trust them. This skepticism is fueled by concerns over data privacy, security, and transparency. Many consumers are wary of how FSIs handle their personal information and are seeking greater clarity on AI’s role in financial decision-making. A Salesforce study revealed that 73% of consumers want to know when they’re interacting with AI, highlighting the importance of transparency in AI implementation. “For AI to succeed in financial services, trust and compliance must be built into the foundation,” said Eran Agrios, SVP & GM of Financial Services at Salesforce. “FSIs need to ensure their AI strategies are not only effective but also worthy of customer confidence.” AI in Action: Case Studies in Financial Services Financial institutions leveraging Agentforce are already seeing tangible benefits: Integrating Agentforce with ERP for Maximum Impact To maximize the potential of AI agents, FSIs must integrate them seamlessly into their broader enterprise ecosystems. Best practices for integration include: The Next Two Years: Defining the Future of AI in Finance As AI continues to disrupt the financial sector, FSIs that embrace AI-first strategies will outperform competitors in efficiency, security, and customer experience. Here’s what the future holds: The Takeaway Financial institutions that invest in AI-driven experiences today will define the future of finance. By adopting transparent, compliant, and consumer-centric AI strategies, FSIs can build trust, drive efficiency, and deliver exceptional customer experiences that set them apart in an increasingly AI-powered world. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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March 14, 2025in Data, Enterprise, Mulesoft, Salesforce, Salesforce Data Cloud0 Comments
ViUniT: A Breakthrough AI Framework for Reliable Visual Unit Testing in AI
14Mar

ViUniT: A Breakthrough AI Framework for Reliable Visual Unit Testing in AI

Salesforce AI, in collaboration with the University of Pennsylvania, has introduced ViUniT (Visual Unit Testing)—a pioneering AI framework designed to improve the reliability of visual programs by automatically generating unit tests. By leveraging large language models (LLMs) and diffusion models, ViUniT enhances the logical correctness of visual reasoning systems, ensuring AI models produce accurate and justifiable results. The Challenge: Ensuring Logical Soundness in Visual Programs Visual programming has gained prominence in AI, particularly in computer vision, object detection, image captioning, and visual question answering (VQA). These systems excel at modularizing complex reasoning tasks, but their correctness remains a critical challenge. Unlike traditional text-based programming, where syntax errors and logic flaws can be easily debugged, visual programs often produce seemingly correct answers for incorrect reasons, making them unreliable. Recent studies highlight this issue: To address these challenges, systematic testing and verification frameworks are essential to ensure visual programs function as intended. Introducing ViUniT: A New Approach to Visual Program Reliability ViUniT is designed to systematically evaluate visual programs by generating unit tests in the form of image-answer pairs. Unlike conventional unit testing, which is primarily used for text-based applications, ViUniT focuses on: How ViUniT Works Key Applications of ViUniT ViUniT introduces four major innovations to improve model reliability: Performance & Key Findings ViUniT was extensively tested on three benchmark datasets: GQA, SugarCREPE, and Winoground, demonstrating significant improvements in model accuracy and reliability. 🔹 ViUniT improved model accuracy by 11.4% on average across datasets.🔹 Reduced logically flawed programs by 40%, ensuring models reason correctly.🔹 Enabled open-source 7B models to outperform GPT-4o-mini by 7.7%.🔹 ViUniT-based re-prompting improved performance by 7.5 percentage points compared to error-based re-prompting.🔹 Reinforcement learning strategies within ViUniT outperformed correctness-based reward strategies by 1.3%.🔹 Successfully identified unreliable programs, enhancing answer refusal strategies and reducing false confidence. Conclusion: A New Standard for Visual AI Testing ViUniT marks a significant step forward in AI-driven unit testing for visual programs, ensuring that AI models not only provide correct answers but also follow logically sound reasoning. By integrating LLMs, diffusion models, and reinforcement learning, this framework enhances trust, accuracy, and reliability in visual AI systems. As AI continues to evolve, ViUniT sets a new standard for validating and refining visual reasoning models, paving the way for more dependable AI-driven applications. 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 14, 2025in AI Tools, Artificial Intelligence, Data, Laws, Salesforce0 Comments
Salesforce Data Cloud
14Mar

Maximizing Salesforce Data Cloud

Maximizing Salesforce Data Cloud: Post-Implementation Strategies for Long-Term Success The Fastest-Growing Salesforce Product Salesforce Data Cloud is seeing explosive growth, with a 130% year-over-year increase in paid customers. In just one quarter, it processed an astonishing 2.3 quadrillion records—a 147% jump from the previous year. Businesses leveraging Data Cloud have seen a 165% boost in web engagement, with major brands like The Adecco Group, Aston Martin, and FedEx using it to strengthen customer relationships and drive growth. The Power of Data Cloud: Turning Information into Action What makes Salesforce Data Cloud so impactful is its ability to unify vast amounts of data, creating 360-degree customer profiles and transforming insights into action. But unlocking its full potential doesn’t stop at implementation—it requires ongoing optimization to keep your data clean, your systems efficient, and your AI models accurate. Post-Implementation Best Practices for Salesforce Data Cloud Once your Salesforce Data Cloud is up and running, the next step is ensuring long-term performance and business value. Here’s how to optimize and sustain your Data Cloud investment: 1. Maintain Data Integrity with Ongoing Quality Management 2. Optimize System Performance for Speed and Efficiency 3. Drive User Adoption with Tailored Training 4. Strengthen Data Governance and Compliance 5. Proactively Manage and Optimize Integrations 6. Refine Customer Segmentation for More Personalization 7. Keep AI and Predictive Models Up to Date 8. Measure ROI and Optimize for Business Impact 9. Foster a Data-Driven Culture Through Clear Communication 10. Stay Agile with Continuous Innovation and Community Engagement Conclusion: The Real Value of Data Cloud Begins After Implementation Salesforce Data Cloud is at the heart of next-gen customer engagement, but its true impact lies in how well you maintain and optimize it. Success depends on:✅ Involving key stakeholders in ongoing improvements✅ Enforcing strong data governance for security and accuracy✅ Continuously refining processes to adapt to changing business needs By committing to post-implementation optimization, your organization can stay agile, data-driven, and ahead of the competition—ensuring that Salesforce Data Cloud delivers maximum value now and in the future. 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 14, 2025in Data, Salesforce, Salesforce Data Cloud0 Comments
AI Agents
08Mar

AI Agents in Action: Real-World Applications

The true potential of AI agents lies in their practical use across industries. Let’s explore how different sectors are leveraging AI agents to solve real challenges. Software Development The shift from simple code completion to autonomous software development highlights AI’s expanding role in engineering. While GitHub Copilot introduced real-time coding assistance in 2021, today’s AI agents—like Devin—can manage end-to-end development, from setting up environments to deployment. Multi-agent frameworks, such as MetaGPT, showcase how specialized AI agents collaborate effectively: While AI agents lack human limitations, this shift raises fundamental questions about development practices shaped over decades. AI excels at tasks like prototyping and automated testing, but the true opportunity lies in rethinking software development itself—not just making existing processes faster. This transformation is already affecting hiring trends. Salesforce, for example, announced it will not hire new software engineers in 2025, citing a 30% productivity increase from AI-driven development. Meanwhile, Meta CEO Mark Zuckerberg predicts that by 2025, AI will reach the level of mid-level software engineers, capable of generating production-ready code. However, real-world tests highlight limitations. While Devin performs well on isolated tasks like API integrations, it struggles with complex development projects. In one evaluation, Devin successfully completed only 3 out of 20 full-stack tasks. In contrast, developer-driven workflows using tools like Cursor have proven more reliable, suggesting that AI agents are best used as collaborators rather than full replacements. Customer Service The evolution from basic chatbots to sophisticated AI service agents marks one of the most successful AI deployments to date. Research by Sierra shows that modern AI agents can handle complex tasks—such as flight rebookings and multi-step refunds—previously requiring multiple human agents, all while maintaining natural conversation flow. Key capabilities include: However, challenges remain, particularly in handling policy exceptions and emotionally sensitive situations. Many companies address this by limiting AI agents to approved knowledge sources and implementing clear escalation protocols. The most effective approach in production environments has been a hybrid model, where AI agents handle routine tasks and escalate complex cases to human staff. Sales & Marketing AI agents are now playing a critical role in structured sales and marketing workflows, such as lead qualification, meeting scheduling, and campaign analytics. These agents integrate seamlessly with CRM platforms and communication tools while adhering to business rules. For example, Salesforce’s Agentforce processes customer interactions, maintains conversation history, and escalates complex inquiries when necessary. 1. Sales Development 2. Marketing Operations Core capabilities: However, implementing AI in sales and marketing presents challenges: A hybrid approach—where AI manages routine tasks and data-driven decisions while humans focus on relationship-building and strategy—has proven most effective. Legal Services AI agents are also transforming the legal industry by processing complex documents and maintaining compliance across jurisdictions. Systems like Harvey can break down multi-month projects, such as S-1 filings, into structured workflows while ensuring regulatory compliance. Key capabilities: However, AI-assisted legal work faces significant challenges. Validation and liability remain critical concerns—AI-generated outputs require human review, and the legal responsibility for AI-assisted decisions is still unresolved. While AI excels at document processing and legal research, strategic decisions remain firmly in human hands. Final Thoughts Across industries, AI agents are proving their value in automation, efficiency, and data-driven decision-making. However, fully autonomous systems are not yet replacing human expertise—instead, the most successful implementations involve AI-human collaboration, where agents handle repetitive tasks while humans oversee complex decision-making. As AI technology continues to evolve, businesses must strike the right balance between automation, control, and human oversight to maximize its potential. 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 8, 2025in Data, Technology0 Comments
The Rise of AI Agents
07Mar

The Rise of AI Agents

The Rise of AI Agents: Salesforce’s Vision for a New Era of Business In just three months, more than 1,000 companies have deployed Salesforce AI agents, unlocking capabilities “they’ve never seen before” and setting the stage for game-changing business outcomes, according to CEO Marc Benioff. That’s a bold prediction—even for a visionary like Benioff, whose track record speaks for itself. But throughout our recent 25-minute conversation for the Cloud Wars CEO Outlook 2025 series, Benioff remained unwavering in his optimism about the AI-powered future. Agentic AI: The Force Driving Business Transformation According to Benioff, AI agents represent the next wave of business transformation, redefining how companies operate, innovate, and compete. “I’ve never been more excited about technology—this is an incredible moment in time,” Benioff said. He described AI agents as the bridge to a future where businesses engage with customers in ways previously thought possible only in science fiction. These AI-driven systems will help organizations operate at lower costs while improving customer relationships and key performance metrics. But Salesforce isn’t just selling this vision to customers—it’s living it. Benioff shared firsthand insights into how the company is leveraging AI to optimize its own operations, revealing lessons that could reshape how enterprises think about productivity and workforce planning. Digital Labor: A Multi-Trillion-Dollar Opportunity One of the most striking takeaways from our conversation was Salesforce’s approach to what Benioff calls “digital labor.” “For 25 years, Salesforce has helped businesses manage data. Now, we’re creating digital workers—AI agents that unlock entirely new ways to operate,” he said. This shift is already making an impact. Salesforce’s Agentforce AI now handles the bulk of the company’s customer support, transforming how its 9,000 service agents manage 36,000 weekly support inquiries: As a result, Salesforce is reallocating 2,000 support professionals to other roles—just one example of how AI is reshaping workforce dynamics. A Radical Rethink: No New Developers in 2025 Perhaps the most surprising revelation? Salesforce is pausing hiring for software engineers in 2025. Benioff explained that despite doubling its engineering team over the past five years, AI has driven a 30% increase in productivity. Rather than hiring more developers, Salesforce is leaning into AI-powered automation to accelerate software development. This shift raises fundamental questions about the future of work: Salesforce vs. Microsoft: Competing Visions for AI Agents AI agents are reshaping enterprise technology, but vendors have differing approaches. Benioff made it clear that Salesforce is taking a unique path—one he believes will ultimately lead the industry. Unlike Microsoft, which is deeply integrating AI within its core applications, Salesforce sees agents as an evolution of its CRM foundation, leveraging the vast 230-petabyte data ecosystem it manages for customers. “The businesses that are closest to their data will win,” Benioff said. “And we’re going to deliver capabilities that our customers have never seen before—ones that will thrill them out of their minds.” The Future: A Billion AI Agents As enterprises race to adopt AI, Benioff predicts an explosion in AI agent deployment. “In the next 12 months, we’ll see thousands of companies deploying up to a billion AI agents. And Salesforce will be the absolute leader in agentic technology for the enterprise,” he said. Benioff’s vision is clear: AI agents aren’t just an enhancement—they are the next frontier of business. And companies that embrace them will lead the way into a new era of efficiency, innovation, and growth. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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March 7, 2025in Agentic AI, Data, Enterprise, Salesforce, Technology0 Comments
07Mar

Cloud-Based Housing Repairs with Salesforce

Bernicia Leads the Way in Cloud-Based Housing Repairs with Salesforce Bernicia has become the first housing association in the UK to deliver end-to-end repairs services through Salesforce’s cloud-based, nonprofit solution—setting a new industry benchmark for streamlined, automated housing repairs. Transforming Repairs with Salesforce Field Services All electrical repairs at tenants’ homes are now managed through Salesforce Field Services, enhancing the customer experience with seamless, automated processes. By this summer, all responsive repairs will transition into the system, delivering key benefits such as: A Customer-Centric Digital Transformation In 2023, Bernicia reinforced its commitment to tenants by launching a multi-year cultural development program, supported by a £4 million investment in world-class technology. By listening to customer feedback and leveraging data-driven insights, Bernicia has aligned its new digital repairs service with tenant expectations and evolving habits. Andrea Malcolm, Deputy Chief Executive at Bernicia and project sponsor, stated: “The introduction of Field Services marks a major milestone in our journey to customer service excellence. The dedication and expertise of our team have been outstanding, creating an incredible momentum across the business. We’re excited to see the real difference this will make for both customers and colleagues.” Jude Comber, Account Executive at Salesforce Nonprofits, praised the project team, saying: “The level of skill and attention to detail in this project is outstanding. Bernicia’s customer-first approach is a model for how to successfully implement a digital transformation.” Strategic Collaboration with Alscient Achieving this milestone was made possible through Bernicia’s partnership with Alscient, a multi-cloud specialist. Their expertise in Salesforce integration and digital transformation played a key role in designing and implementing the Field Services solution. Salesforce: A Game-Changer for Housing Associations Salesforce offers housing associations a single, integrated platform to streamline operations, enhance tenant relationships, and eliminate inefficiencies caused by data silos. By embracing cloud-based, automated solutions, housing providers can transform service delivery and drive long-term tenant satisfaction. 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, Salesforce, 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
Transforming Fundraising for Nonprofits
05Mar

Salesforce Personalization for Fundraising

The Power of Personalization in Fundraising with Salesforce Successful fundraisers have long recognized that personalization in communicaation drives stronger donor relationships and inspires far greater generosity. However, achieving meaningful engagement at scale has traditionally been a time-intensive challenge. Salesforce, the world’s leading CRM, is transforming nonprofit fundraising by seamlessly integrating donor data with cutting-edge artificial intelligence. This powerful combination enables organizations to build deeper connections with donors through hyper-personalized interactions. How Salesforce is Revolutionizing Donor Engagement: Scalable Solutions for Every Nonprofit Salesforce is built to support organizations of all sizes, from small grassroots initiatives to large national institutions. As your objectives evolve, Salesforce’s flexible platform scales with you, ensuring you always have the right tools to achieve your fundraising goals. Now is the perfect time to leverage Salesforce’s power to enhance personalized giving. Getting Started with Salesforce Advancing Your Salesforce Strategy By leveraging Salesforce’s powerful tools and automation, nonprofits can enhance personalization, drive engagement, and build lasting donor relationships—all while streamlining operations and maximizing fundraising success. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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March 5, 2025in Artificial Intelligence, Data, Salesforce, Salesforce Personalization0 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
Data Data Data
01Mar

The Evolution of Data

Data’s Evolution: Once Oil Now Compute Power For years, data was dubbed the new oil, a valuable resource that could fuel innovation. However, with the rise of artificial intelligence (AI), compute power has taken center stage as the key driver of business success. Sequoia has not hesitated to outline AI’s transformative potential: “The fields that generative AI addresses — knowledge work and creative work — comprise billions of workers. If generative AI can make these workers at least 10% more efficient and/or creative, they become not only faster and more efficient but more capable than before. Therefore, generative AI has the potential to generate trillions of dollars of economic value.” — Sonya Huang, Pat Grady, Generative AI: A Creative New World While markets continue to assess the validity of this claim, the parallels to past technological revolutions—such as the internet and mobile phones—are undeniable. AI’s influence on knowledge work, particularly in data analytics, is poised to be profound, reshaping how organizations extract value from data. The Rise of Data Analytics and AI Integration The data analytics market is expanding at an unprecedented rate, with a projected CAGR of 27.3% through 2030. A decade ago, data science degrees were rare; professionals often transitioned from related analytical fields like physics, mathematics, accounting, and economics. However, the landscape has shifted dramatically. According to the National Center for Education Statistics, bachelor’s degrees in data science surged by 968% between 2020 and 2022, reflecting the growing demand for analytics expertise. Despite its rapid evolution, modern data analytics presents unique challenges. Unlike software engineering—where code is deterministic—data pipelines evolve based on ingestion processes, requiring a different approach to governance and tooling. AI’s introduction into this space offers a chance to accelerate insights, but only if organizations integrate it strategically into their data frameworks. Modernizing Data Practices: From ETL to ELTL Historically, organizations relied on extract-transform-load (ETL) processes for data management. However, inefficiencies led to the rise of extract-load-transform (ELT), empowering analysts to transform data within cloud-based environments. Developer tools like dbt further streamlined this process, enabling analysts to create data models without relying on centralized data architects. Yet, with increased speed came challenges—primarily, the proliferation of inconsistent data sources. This issue underscores the importance of a final load step (ELTL) that incorporates governance measures to ensure accuracy before presenting data to users. Without proper governance, discrepancies between dashboards can erode trust in analytics. Data Governance and the Role of the Semantic Layer To mitigate inconsistencies, organizations have embraced semantic layers—standardized frameworks that define key business metrics. dbt’s semantic layer and emerging solutions like SQLMesh help enforce governance, ensuring AI-powered analytics operate on reliable data. AI’s effectiveness hinges on a well-documented semantic layer, built on metadata that defines relationships between data objects. Many AI systems utilize retrieval-augmented generation (RAG), which retrieves relevant context before generating responses. However, for AI-driven analytics to succeed, organizations must implement safeguards such as primary key checks and join definitions, ensuring structured and accurate outputs. AI-Powered Precision Analytics The integration of AI into data analytics is driving a shift toward precision analytics—delivering exactly the right data transformation tailored to user needs. This approach mirrors the concept of precision medicine in healthcare, where treatments are customized for individuals. With AI, organizations can move beyond dashboards overloaded with filters and instead provide instant, context-aware insights. Data Objects: A New Paradigm Traditionally, analytics relied on dashboards, but AI enables a more flexible approach through “data objects.” A data object represents a distinct SQL query that answers a user’s prompt. These objects can take three primary forms: This shift allows users to generate and compare data objects dynamically, reducing reliance on static reports and fostering a more agile analytical environment. AI Data Analytics: The Next Frontier Organizations now have the opportunity to revolutionize data analytics through AI. Broadly, AI-driven analytics solutions fall into two categories: Text-to-SQL technology has made significant strides, with execution benchmarks like Spider achieving over 91% accuracy. However, new challenges such as Spider 2.0 highlight the complexity of multi-step analytical workflows. AI systems must incorporate rigorous governance mechanisms to ensure accuracy and reliability. Trust, Governance, and the Human Element Trust is paramount in AI-driven analytics. Without proper governance, AI models risk generating misleading insights, undermining confidence in data-driven decision-making. Organizations must establish clear metadata standards, enforce rigorous validation checks, and maintain a human-in-the-loop approach to AI oversight. An AI-powered data agent should function much like a skilled data analyst—asking clarifying questions, referencing well-documented schemas, and leveraging business glossaries to interpret queries accurately. When implemented correctly, AI-driven analytics can transform data accessibility, making insights available in seconds rather than weeks. The Future of AI-Driven Analytics AI is poised to revolutionize data analytics, offering real-time insights with unparalleled accuracy. However, success hinges on a strong foundation of governance, well-defined data models, and reliable metadata. Organizations that embrace AI with a strategic approach will unlock new efficiencies, reduce bottlenecks, and redefine how data powers decision-making. By integrating AI into analytics responsibly, businesses can move beyond dashboards and embrace true precision analytics—where every insight is timely, relevant, and trustworthy. 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 1, 2025in Artificial Intelligence, Data, Generative AI, Technology0 Comments

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