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Choose Salesforce for SMS

Choose Salesforce for SMS

Why Integrating SMS with Salesforce Transforms Business Communication Effective communication is crucial in today’s fast-paced business environment. A company’s success often hinges on its ability to interact seamlessly with customers—whether through personalized service, timely updates, or the latest product offerings. Choose Salesforce for SMS. Today’s customers demand a seamless, omnichannel experience that goes beyond traditional communication methods like flyers and emails. They expect real-time, two-way interactions, which is where Salesforce SMS apps come into play. These apps, which integrate smoothly with existing CRM systems, are transforming how businesses engage with their customers. 5 Reasons to Integrate SMS with Salesforce Integrating SMS with Salesforce offers numerous benefits, primarily enhancing customer-facing efficiency and effectiveness. Here are five key advantages: SMS for Salesforce enables businesses to provide immediate customer support. For instance, logistics companies can use SMS to notify customers about delivery statuses or appointment updates in real time. SMS boasts an impressive open rate—over 95% within the first three minutes—making it a highly effective medium for increasing marketing engagement compared to email. You can even couple Salesforce SMS with tools like geofencing to send notifications via SMS when they are in the store. Integrating SMS with Salesforce allows for streamlined automation of processes such as order updates and appointment reminders. This reduces the need for manual intervention, boosts productivity, and frees up resources for more strategic tasks. Automated texts can be scheduled based on customer behavior or sales stages, optimizing workflows and enhancing efficiency. With a response rate of approximately 45%, SMS is highly effective for engaging customers. It facilitates prompt replies due to its immediate nature. Sales and marketing teams can leverage SMS for direct interactions, while retailers can use it to distribute discount codes and drive quick responses. Additionally, SMS is ideal for important notifications, enhancing customer service. By integrating SMS with Salesforce, businesses can tailor their messages to address specific customer needs and preferences. This personalization fosters stronger customer relationships and improves conversion rates. For example, a travel agency can send personalized vacation recommendations, while financial advisors can provide client-specific updates and advice. Salesforce’s integration with SMS allows for robust tracking and analysis of customer interactions and campaign effectiveness. Marketing teams can refine their strategies by reviewing metrics such as open rates, click-through rates, and conversion rates from SMS campaigns. Additionally, customer support teams can evaluate response times and resolution rates to improve service efficiency. How to Implement SMS in Salesforce To send and receive texts via Salesforce, you have several options: Salesforce offers two primary SMS solutions: Mobile Studio and Digital Engagement. For more tailored functionality, you can use Salesforce API or another API provider to develop a custom texting solution. While this offers greater flexibility and avoids extra costs, it involves significant development time and expense. Opting for a Salesforce-native SMS app from the Salesforce AppExchange can be advantageous. These apps, designed specifically for SMS within Salesforce, often offer: These native apps also come with dedicated customer support, making them a cost-effective and efficient choice. Best Practices for SMS Communication While SMS boasts high engagement rates, it’s essential to follow best practices to maintain a positive customer experience: Ensure compliance with data privacy regulations like GDPR and CCPA by securing clear consent from customers before sending SMS. Automate re-opt-in processes to maintain compliance. Send messages during the recipient’s regular business hours to avoid disturbing them at inconvenient times. Stay in touch with your audience regularly but avoid overwhelming them with excessive messages. Provide valuable content to keep engagement high. Use the same number for messaging to help customers recognize your communications and build trust. Respond promptly and courteously to customer replies. Provide clear, detailed responses to inquiries. Acknowledge and reward outstanding customer actions with thoughtful messages or gestures, such as donations to their favorite charities. Even a thank you for your purchase message can contain a surprise such as a coupon or a notification that a free gift is included with their order. Use SMS to highlight important announcements, events, or opportunities, tapping into the fear of missing out to drive engagement. SMS is the perfect omnichannel tool to incorporate into all your Salesforce journeys. Balance promotional content with conversational engagement to avoid appearing pushy and to keep the communication enjoyable for customers. People are much happier to get news they can use rather than advertisements. Encourage further engagement by including clear, actionable steps in your SMS messages, such as signing up for a free trial or using a discount code. A call to action must be designed with smaller screen views in mind. Include an easy way for recipients to unsubscribe from future messages to comply with legal requirements and respect customer preferences. By integrating SMS with Salesforce and adhering to these best practices, businesses can enhance their communication strategies, foster better customer relationships, and drive greater engagement. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Introducing Marketing Cloud Advanced

Introducing Marketing Cloud Advanced

Salesforce has unveiled a series of innovations in its Marketing Cloud, (Introducing Marketing Cloud Advanced) designed to empower businesses with AI-driven tools and enhanced data capabilities to elevate customer engagement. These new features aim to deepen customer relationships, improve team productivity, and boost operational efficiency. Introducing Marketing Cloud Advanced One of the standout innovations is Marketing Cloud Advanced, an upcoming edition that integrates advanced automation and AI. This edition is designed to connect marketing journeys with sales, service, and commerce workflows, offering a more personalized experience across multiple customer touchpoints. Additionally, the introduction of Agentforce for Marketing will bring generative and predictive AI into the marketing realm, helping marketers create comprehensive, end-to-end campaign experiences. Steve Hammond, Executive Vice President and General Manager of Marketing Cloud at Salesforce, commented: “Today’s most successful marketers engage customers on their terms and act as value multipliers across the entire customer experience—whether helping sales or service have more personalized conversations or re-engaging inactive customers. Built on Data Cloud, Marketing Cloud is the only solution that unifies data across every department and moment in the customer lifecycle, powered by Agentforce Agents and automation, driving growth, loyalty, and optimizing ROI.” Agentforce for Marketing introduces several capabilities that streamline marketing processes. Marketers can now plan, launch, and optimize campaigns with ease. Agentforce allows marketers to set campaign goals and brand guidelines, after which the AI generates campaign briefs, identifies target audience segments, and drafts initial emails and landing pages. The system continuously monitors performance and provides data-driven optimization suggestions based on key performance indicators (KPIs). A key addition is Einstein Marketing Intelligence (EMI), which helps marketers manage and optimize cross-channel campaign performance. EMI automates the process of data preparation, enrichment, harmonization, and visualization, enabling marketers to measure campaign effectiveness and make informed decisions to improve return on investment. Furthermore, Salesforce introduced Einstein Personalization, an AI-powered decision engine that delivers tailored customer experiences. This tool allows sales, service, and commerce teams to engage customers in real time based on live interactions and data. Using Flow’s A/B split testing feature, marketers can select dynamic email content for different audience segments and track performance to adjust strategies effectively. Sarah Lukins, General Manager of Digital at Fisher & Paykel Appliances, praised the new functionality: “Salesforce enables us to seamlessly access all of our marketing, commerce, service, sales, and external data in one place and leverage AI for more targeted audience engagement. We can now deliver more relevant and consistent personalized experiences across email, ads, web, social, and service engagements.” The Marketing Cloud Advanced Edition will roll out to customers in North America, Europe, and Latin America, while Agentforce Personalization is expected to become generally available by next summer. Additional releases include expanded Einstein multi-language support and unified SMS conversation capabilities. These innovations are part of Salesforce’s ongoing efforts to equip marketers with unified and actionable data, enhancing the performance of marketing teams and fostering deeper integration across organizations. Through AI and automation, Salesforce is helping businesses deliver more personalized, connected, and seamless customer experiences. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce to Acquire Zoomin

Salesforce to Acquire Zoomin

Salesforce to Acquire Zoomin: Enhancing AI Capabilities with Unstructured Data Salesforce, the world’s leading AI CRM, has signed a definitive agreement to acquire Zoomin, a top data management provider specializing in unstructured data. This acquisition is a pivotal move that will strengthen Salesforce’s Data Cloud, empowering AI agents with more personalized, context-aware capabilities. With Zoomin’s technology, Salesforce’s Agentforce platform will gain new intelligence, allowing customers to build AI that delivers real-time, data-driven responses tailored to individual needs. The acquisition is expected to close in the fourth quarter of Salesforce’s fiscal year 2025, subject to customary closing conditions. “Proprietary unstructured data is powerful fuel our customers can use for AI agents and customer experiences,” said Rahul Auradkar, EVP & GM of Unified Data Services & Einstein at Salesforce. “Zoomin’s proven expertise and technology will accelerate Data Cloud’s innovation and enable our customers to get better value from Agentforce. This transaction underscores our commitment to help customers harness the value of all their data, offering contextual AI experiences backed by enterprise-leading trust controls.” Strategic Value of the Acquisition With the integration of Zoomin’s technology, Salesforce can unlock new use cases for customers across various touchpoints. For example, Service Cloud users will be able to automate service interactions by leveraging enterprise knowledge, enhancing the efficiency of Agentforce for service representatives. This integration will lead to faster issue resolution, increased customer satisfaction, and reduced operational costs. Zoomin’s ability to consolidate unstructured data from multiple sources will empower service teams with a comprehensive understanding of their customers, turning distributed knowledge into actionable insights. Zoomin’s CEO, Gal Oron, echoed this sentiment: “We’re both humbled and excited to join forces with Salesforce. As organizations accelerate their enterprise AI transformation, our joint mission is to support them and ensure AI doesn’t hit the data wall. As part of the #1 AI CRM, we’ll enable customers to leverage their existing enterprise data in ways they never thought possible.” A Long-Standing Partnership Zoomin has been a Salesforce AppExchange partner since 2018 and became a part of the Salesforce Ventures portfolio in 2019. Through this partnership, hundreds of Salesforce customers already use Zoomin’s unified knowledge platform to deliver intuitive customer experiences. This acquisition builds on that foundation, with Zoomin set to enhance Salesforce’s AI-driven platforms by making enterprise knowledge more accessible and usable for AI agents. Despite the significance of this acquisition, Salesforce noted that it would not result in any changes to its financial guidance provided in August 2024, and no further financial details will be disclosed. This move is part of Salesforce’s broader strategy to push deeper into AI-powered customer experiences, enabling customers to utilize the full potential of their data for more intelligent, personalized interactions across all channels. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Unique Form Links With Jotform

Unique Form Links With Jotform

Create Unique Form Links with Jotform Once you’ve set up Salesforce Prefill, you can generate unique form links for your customers, automatically populating forms with their specific data. This helps minimize errors and ensures the data collected is accurate and consistent. Steps to Create and Send Personalized Links Each recipient will receive an email with a link to their prefilled form. If you prefer to distribute the links manually, you can download them using the Download option at the top. Unique Form Links With Jotform for Salesforce are an easy solution for your Salesforce org. Need assistance implementing Jotform? 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Agentforce - AI's New Role in Sales and Service

Agentforce – AI’s New Role in Sales and Service

From Science Fiction to Reality: AI’s Game-Changing Role in Service and Sales AI for service and sales has reached a critical tipping point, driving rapid innovation. At Dreamforce in San Francisco, hosted by Salesforce we explored how Salesforce clients are leveraging CRM, Data Cloud, and AI to extract real business value from their Salesforce investments. In previous years, AI features branded under “Einstein” had been met with skepticism. These features, such as lead scoring, next-best-action suggestions for service agents, and cross-sell/upsell recommendations, often required substantial quality data in the CRM and knowledge base to be effective. However, customer data was frequently unreliable, with duplicate records and missing information, and the Salesforce knowledge base was underused. Building self-service capabilities with chatbots was also challenging, requiring accurate predictions of customer queries and well-structured decision trees. This year’s Dreamforce revealed a transformative shift. The advancements in AI, especially for customer service and sales, have become exceptionally powerful. Companies now need to take notice of Salesforce’s capabilities, which have expanded significantly. Agentforce – AI’s New Role in Sales and Service Some standout Salesforce features include: At Dreamforce, we participated in a workshop where they built an AI agent capable of responding to customer cases using product sheets and company knowledge within 90 minutes. This experience demonstrated how accessible AI solutions have become, no longer requiring developers or LLM experts to set up. The key challenge lies in mapping external data sources to a unified data model in Data Cloud, but once achieved, the potential for customer service and sales is immense. How AI and Data Integrate to Transform Service and Sales Businesses can harness the following integrated components to build a comprehensive solution: Real-World Success and AI Implementation OpenTable shared a successful example of building an AI agent for its app in just two months, using a small team of four. This was a marked improvement from the company’s previous chatbot projects, highlighting the efficiency of the latest AI tools. Most CEOs of large enterprises are exploring AI strategies, whether by developing their own LLMs or using pre-existing models. However, many of these efforts are siloed, and engineering costs are high, leading to clunky transitions between AI and human agents. Tectonic is well-positioned to help our clients quickly deploy AI-powered solutions that integrate seamlessly with their existing CRM and ERP systems. By leveraging AI agents to streamline customer interactions, enhance sales opportunities, and provide smooth handoffs to human agents, businesses can significantly improve customer experiences and drive growth. Tectonic is ready to help businesses achieve similar success with AI-driven innovation. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Oracle Advertising Sundown

Oracle Advertising Sundown

Oracle Shifts Focus to B2B CX, Introduces New Fusion Cloud Features Despite winding down its online advertising products, Oracle is doubling down on its investment in customer experience (CX) technology, particularly in enabling B2B buying and supporting subscription and consumption models. During the Oracle CloudWorld conference on Wednesday, the company unveiled new capabilities for its Fusion Cloud Customer Experience and Unity Customer Data Platform. These enhancements empower Oracle CX users to analyze customer profiles to assemble B2B buying teams, leverage generative AI tools like native analytics, and utilize industry-specific accelerators to speed up the adoption of customer data tools. Key features include the ability to create self-service sites for individual accounts, enabling customers to review and summarize contracts using generative AI, receive quotes, and renew subscriptions. Other features enhance “assisted buying experiences,” blending self-service and human interaction, while tools like account onboarding and AI-powered email drafting simplify full-service sales processes. Subscription models, though still in their early stages for B2B, offer a streamlined alternative to traditional procurement processes. As Liz Miller, an analyst at Constellation Research, noted, subscription-based buying is easier and quicker, avoiding the lengthy procurement cycles many B2B buyers are familiar with. “The pain of traditional B2B buying is still fresh in everyone’s mind,” she said. Oracle Advertising Shuts Down Oracle’s advertising product support will end on September 30, as confirmed by CEO Safra Catz during the company’s June earnings call. The Oracle Advertising Data Management Platform (DMP), built from its BlueKai acquisition, is being retired, following in the footsteps of Salesforce, which discontinued its Audience Studio in 2021. Despite Oracle winding down its ad platform, this move shouldn’t be seen as a shift away from customer experience. Oracle founder Larry Ellison remains deeply involved in shaping the company’s CX strategy, with a focus on marketing tools and Apex low-code platforms, said Rob Pinkerton, Oracle’s senior vice president. Oracle’s modernized CX suite, built on the Fusion Cloud platform, has evolved significantly in recent years, though questions remain about whether it’s too late to regain market share. “Oracle as a CX platform has fallen off the radar for many buyers,” said Miller, adding that customers are no longer debating between Oracle, Microsoft, and Salesforce in the CX space. New Industry-Specific Tools for CX Oracle has also expanded its CX platform with industry-specific tools designed to accelerate the adoption of its customer data platform (CDP) across sectors such as high tech, manufacturing, professional services, telecommunications, utilities, financial services, travel, and retail. According to Rebecca Wettemann, CEO of research firm Valoir, Oracle’s Fusion platform has matured significantly and now supports the complexity of modern customer needs. Wettemann highlighted how common components like customer interaction summaries can be adapted for multiple industries, delivering faster results than traditional applications. Oracle’s Clinical Digital Assistant is one such example of this approach, illustrating the platform’s versatility and AI-driven enhancements. With these developments, Oracle continues to refine its CX offerings to better meet the unique demands of B2B customers, providing tools that streamline operations and enhance customer experiences across various industries. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Key Sales Statistics and Trends

Sales Statistics and Trends

Key Sales Statistics and Trends Sales professionals often face a rapidly evolving industry, with constant changes to navigate. The key to successfully maneuvering through these shifts is a deep understanding of sales data and trends. Here’s a detailed look at the current state of sales, highlighting both opportunities and challenges. Key Sales Statistics and Trends. Revenue Growth Trends Sales Challenges AI and Data Insights Enablement and Training Employee Experience For more insights and detailed statistics, download the full State of Sales Report from Salesforce. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Open AI Update

Open AI Update

OpenAI has established itself as a leading force in the generative AI space, with its ChatGPT being one of the most widely recognized AI tools. Powered by the GPT series of large language models (LLMs), as of September 2024, ChatGPT primarily uses GPT-4o and GPT-3.5. This insight provides an Open AI Update. In August and September 2024, rumors circulated about a new model from OpenAI, codenamed “Strawberry.” Initially, it was unclear if this model would be a successor to GPT-4o or something entirely different. On September 12, 2024, the mystery was resolved with the official launch of OpenAI’s o1 models, including o1-preview and o1-mini. What is OpenAI o1? OpenAI o1 is a new family of LLMs optimized for advanced reasoning tasks. Unlike earlier models, o1 is designed to improve problem-solving by reasoning through queries rather than just generating quick responses. This deeper processing aims to produce more accurate answers to complex questions, particularly in fields like STEM (science, technology, engineering, and mathematics). The o1 models, currently available in preview form, are intended to provide a new type of LLM experience beyond what GPT-4o offers. Like all OpenAI LLMs, the o1 series is built on transformer architecture and can be used for tasks such as content summarization, new content generation, question answering, and writing code. Key Features of OpenAI o1 The standout feature of the o1 models is their ability to engage in multistep reasoning. By adopting a “chain-of-thought” approach, o1 models break down complex problems and reason through them iteratively. This makes them particularly adept at handling intricate queries that require a more thoughtful response. The initial September 2024 launch included two models: Use Cases for OpenAI o1 The o1 models can perform many of the same functions as GPT-4o, such as answering questions, summarizing content, and generating text. However, they are particularly suited for tasks that benefit from enhanced reasoning, including: Availability and Access The o1-preview and o1-mini models are available to users of ChatGPT Plus and Team as of September 12, 2024. OpenAI plans to extend access to ChatGPT Enterprise and Education users starting September 19, 2024. While free ChatGPT users do not have access to these models at launch, OpenAI intends to introduce o1-mini to free users in the future. Developers can also access the models through OpenAI’s API, and third-party platforms such as Microsoft Azure AI Studio and GitHub Models offer integration. Limitations of OpenAI o1 As preview models, o1 comes with certain limitations: Enhancing Safety with OpenAI o1 To ensure safety, OpenAI released a System Card that outlines how the o1 models were evaluated for risks like cybersecurity threats, persuasion, and model autonomy. The o1 models improve safety through: GPT-4o vs. OpenAI o1 Here’s a quick comparison between GPT-4o and OpenAI’s new o1 models: Feature GPT-4o o1 Models Release Date May 13, 2024 Sept. 12, 2024 Model Variants Single model Two variants: o1-preview and o1-mini Reasoning Capabilities Good Enhanced, especially for STEM fields Mathematics Olympiad Score 13% 83% Context Window 128K tokens 128K tokens Speed Faster Slower due to in-depth reasoning Cost (per million tokens) Input: $5; Output: $15 o1-preview: $15 input, $60 output; o1-mini: $3 input, $12 output Safety and Alignment Standard Enhanced safety, better jailbreak resistance OpenAI’s o1 models bring a new level of reasoning and accuracy, making them a promising advancement in generative AI. 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 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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Dreamforce 24 Insights

Dreamforce 24 Insights

Three Key Insights You Might Have Missed from Dreamforce ’24 In today’s digital-driven world, interconnected systems are commonplace and essential, making platform integration and unified operations critical. As AI becomes more central, technologies like Salesforce Agentforce AI are drawing increased attention. At Dreamforce ’24, automation and AI were the event’s stars, particularly Salesforce’s plans for Agentforce AI. Dreamforce 24 Insights. Here are three key insights from Dreamforce ’24 that you might have missed: 1. Salesforce’s Automation Plans Could Reshape Its Future Salesforce has a solid reputation for business automation, but now, with agentic systems entering the picture, the company is looking at a transformative opportunity. John Furrier of theCUBE noted during Dreamforce, “Salesforce is positioned to use generative AI to simplify complexity and reduce the steps required to get things done.” As Salesforce integrates generative AI, the emphasis on securing and utilizing data becomes paramount. Christophe Bertrand of theCUBE pointed out that many organizations are not fully utilizing their data. The introduction of Agentforce AI, which aims to leverage this untapped potential, could bring automation to new heights and fundamentally transform how businesses operate. 2. Salesforce Agentforce AI Aims to Integrate Seamlessly Into Business Workflows A major focus of Dreamforce was Salesforce’s new AI offering—Agentforce. According to Muralidhar Krishnaprasad, Salesforce’s CTO, this represents the next stage of AI for the company. While earlier efforts focused on predictive AI (Einstein) and generative AI copilots, Agentforce moves toward more autonomous AI agents. “Our platform will be one of the most comprehensive for agent development,” Krishnaprasad explained. He highlighted that Agentforce will allow businesses to deploy AI agents across various functions—advertising, sales, service, and analytics—creating a seamless AI-driven ecosystem within the Salesforce platform. David Schmaier, president and CPO of Salesforce, added that Agentforce will transform customer interactions by integrating AI agents with Salesforce Data Cloud to deliver more personalized and efficient experiences. 3. Strategic Partnerships Are Streamlining Business and Enhancing Customer Solutions At Dreamforce, partnerships played a key role in Salesforce’s strategy for the future. A collaboration between Salesforce and AWS is streamlining procurement for joint customers through AWS Marketplace. This partnership allows companies to optimize their spend management and simplify the purchasing process for Salesforce products. IBM is also leveraging Agentforce to drive new outcomes through watsonx Orchestrate, as Nick Otto, IBM’s head of global strategic partnerships, explained. Automation and orchestration have been focal points for both IBM and Salesforce. Another partnership with Canva showcased AI-driven data autofill capabilities that integrate with Salesforce CRM. This allows sales teams to create personalized presentations at scale, automating workflows and increasing efficiency, as noted by Canva’s Chief Customer Officer, Rob Giglio. These insights from Dreamforce ’24 highlight the growing importance of AI, automation, and strategic partnerships in shaping the future of business operations with Salesforce at the forefront. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce Success Story

Case Study: Salesforce Advanced Forcasting and Streamline Operations Yields Big Change and Bigger Results

Case Study: Salesforce Advanced Forcsting and Streamline Operations Yields Big Change and Bigger Results

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Next Gen Commerce Cloud

Next Gen Commerce Cloud

Salesforce has launched the next generation of Commerce Cloud, delivering a unified platform that connects B2C, DTC, and B2B commerce, along with Order Management, Payments, and more, to drive seamless customer experiences and revenue growth. With these innovations, businesses can scale across digital and physical channels while leveraging trusted AI and enterprise-wide data for smarter operations. Next Gen Commerce Cloud. Key features include Autonomous Agentforce Agents, which enhance commerce for merchants, buyers, and shoppers by automating tasks such as product recommendations and order tracking. Companies like MillerKnoll have seen success by using Commerce Cloud’s innovations to scale their workforce and drive revenue across multiple channels. New Agentforce Agents for Commerce — Merchant, Buyer, and Personal Shopper — autonomously manage tasks and improve the customer journey. They handle tasks without human intervention, such as product recommendations or order lookups, drawing insights from rich data sources like customer interactions, inventory, orders, and reviews. By tapping into unified data, these agents augment employees, offering tailored experiences and increasing efficiency, while strictly adhering to privacy and security standards. Salesforce’s Commerce Cloud now natively integrates every part of the commerce journey, helping businesses break down data silos and offer consistent, personalized interactions. As Michael Affronti, SVP and GM of Commerce Cloud, highlights: “Unified commerce is the future, breaking down silos to deliver seamless experiences across all channels.” Key new features and functionalities include: With these advancements, Commerce Cloud empowers businesses to create seamless, AI-powered experiences that drive customer loyalty, operational efficiency, and revenue growth across every touchpoint. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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How to Achieve AI Democratization

How to Achieve AI Democratization

AI democratization empowers non-experts by placing AI tools in the hands of everyday users, enabling them to harness the technology’s potential without requiring specialized technical skills. Today, IT leaders are increasingly focused on expanding AI’s benefits across the enterprise. The growing number of AI-based tools is making this more achievable. In some respects, democratization extends the concept of low- and no-code development—allowing non-developers to create software—into the realm of AI. However, it’s also about ensuring data is accessible and fostering data literacy throughout the organization. This doesn’t mean every employee needs to write machine learning scripts. Instead, it means business professionals should understand AI’s potential, identify relevant use cases, and apply insights to drive business outcomes. Achieving AI democratization is feasible, thanks to decentralized governance models and the emergence of AI-focused services. However, as with any new technology, democratization brings both benefits and challenges. How to Achieve AI Democratization AI is no longer reserved for experts. Tools like Google Colab and Microsoft’s Azure OpenAI Service have simplified AI development, enabling more employees to participate by writing and sharing code for various projects. To maximize the impact, enterprises must train business users on the basics of AI and how it can enhance their daily work. According to Arpit Mehra, Practice Director at Everest Group, decentralized governance models can help organizations build strategies for data and technology learning. Key strategies include: Arun Chandrasekaran, VP and Analyst at Gartner, also advises companies to focus on intelligent applications in areas such as customer engagement and talent acquisition, which can provide specialized training. Benefits and Challenges of AI Democratization AI democratization can significantly expand an organization’s capabilities. By placing AI in the hands of more employees, businesses reduce barriers to adoption, cut costs, and create highly accurate AI models. “Making AI more accessible broadens the scope of what businesses can achieve,” said Michael Shehab, PwC U.S. Technology and Innovation Leader. AI democratization also helps companies address IT talent shortages by upskilling employees and enabling them to integrate AI into their workflows. This approach improves productivity, allowing businesses to more easily spot trends and patterns within large data sets. However, challenges also arise. If AI is implemented without proper oversight, the technology is susceptible to bias. Poor training could lead to decision-making based on inaccurate or skewed data. Business leaders must ensure they understand who is using AI tools and establish standards for responsible use. Without careful testing, AI applications can automate mistakes that go unnoticed but may cause significant issues. Ed Murphy, SVP and Head of Data Science at 1010data, emphasizes the importance of testing to prevent these errors. To mitigate risks, organizations should invest in upskilling and reskilling employees. A well-defined training plan will enable nontechnical teams to participate in AI adoption and deployment effectively. Mehra from Everest Group also suggests exploring MLOps technologies to simplify AI development and streamline processes. Ultimately, AI democratization will benefit businesses that recognize AI’s potential beyond a small group of experts. While the benefits are clear, organizations must remain vigilant about the risks to ensure successful AI integration and reap the rewards of their efforts. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Tableau Einstein is Here

Tableau Einstein is Here

Tableau Einstein marks a new chapter for Tableau, transforming the analytics experience by moving beyond traditional reports and dashboards to deliver insights directly within the flow of a user’s work. This new AI-powered analytics platform blends existing Tableau and Salesforce capabilities with innovative features designed to revolutionize how users engage with data. The platform is built around four key areas: autonomous insight delivery through AI, AI-assisted development of a semantic layer, real-time data access, and a marketplace for data and AI products, allowing customers to personalize their Tableau experience. Some features, like Tableau Pulse and Tableau Agent, which provide autonomous insights, are already available. Additional tools, such as Tableau Semantics and a marketplace for AI products, are expected to launch in 2025. Access to Tableau Einstein is provided through a Tableau+ subscription, though pricing details remain private. Since being acquired by Salesforce in 2019, Tableau has shifted its focus toward AI, following the trend of many analytics vendors. In February, Tableau introduced Tableau Pulse, a generative AI-powered tool that delivers insights in natural language. In July, it also rolled out Tableau Agent, an AI assistant to help users prepare and analyze data. With AI at its core, Tableau Einstein reflects deeper integration between Tableau and Salesforce. David Menninger, an analyst at Ventana Research, commented that these new capabilities represent a meaningful step toward true integration between the two platforms. Donald Farmer, founder of TreeHive Strategy, agrees, highlighting that while the robustness of Tableau Einstein’s AI capabilities compared to its competitors remains to be seen, the platform offers more than just incremental add-ons. “It’s an impressive release,” he remarked. A Paradigm Shift in Analytics A significant aspect of Tableau Einstein is its agentic nature, where AI-powered agents deliver insights autonomously, without user prompts. Traditionally, users queried data and analyzed reports to derive insights. Tableau Einstein changes this model by proactively providing insights within the workflow, eliminating the need for users to formulate specific queries. The concept of autonomous insights, represented by tools like Tableau Pulse and Agentforce for Tableau, allows businesses to build autonomous agents that deliver actionable data. This aligns with the broader trend in analytics, where the market is shifting toward agentic AI and away from dashboard reliance. Menninger noted, “The market is moving toward agentic AI and analytics, where agents, not dashboards, drive decisions. Agents can act on data rather than waiting for users to interpret it.” Farmer echoed this sentiment, stating that the integration of AI within Tableau is intuitive and seamless, offering a significantly improved analytics experience. He specifically pointed out Tableau Pulse’s elegant design and the integration of Agentforce AI, which feels deeply integrated rather than a superficial add-on. Core Features and Capabilities One of the most anticipated features of Tableau Einstein is Tableau Semantics, a semantic layer designed to enhance AI models by enabling organizations to define and structure their data consistently. Expected to be generally available by February 2025, Tableau Semantics will allow enterprises to manage metrics, data dimensions, and relationships across datasets with the help of AI. Pre-built metrics for Salesforce data will also be available, along with AI-driven tools to simplify semantic layer management. Tableau is not the first to offer a semantic layer—vendors like MicroStrategy and Looker have similar features—but the infusion of AI sets Tableau’s approach apart. According to Tableau’s chief product officer, Southard Jones, AI makes Tableau’s semantic layer more agile and user-friendly compared to older, labor-intensive systems. Real-time data integration is another key component of Tableau Einstein, made possible through Salesforce’s Data Cloud. This integration enables Tableau users to securely access and combine structured and unstructured data from hundreds of sources without manual intervention. Unstructured data, such as text and images, is critical for comprehensive AI training, and Data Cloud allows enterprises to use it alongside structured data efficiently. Additionally, Tableau Einstein will feature a marketplace launching in mid-2025, which will allow users to build a composable infrastructure. Through APIs, users will be able to personalize their Tableau environment, share AI assets, and collaborate across departments more effectively. Looking Forward As Tableau continues to build on its AI-driven platform, Menninger and Farmer agree that the vendor’s move toward agentic AI is a smart evolution. While Tableau’s current capabilities are competitive, Menninger noted that the platform doesn’t necessarily set Tableau apart from competitors like Qlik, MicroStrategy, or Microsoft Fabric. However, the tight integration with Salesforce and the focus on agentic AI may provide Tableau with a short-term advantage in the fast-changing analytics landscape. Farmer added that Tableau Einstein’s autonomous insight generation feels like a significant leap forward for the platform. “Tableau has done great work in creating an agentic experience that feels, for the first time, like the real deal,” he said. Looking ahead, Tableau’s roadmap includes a continued focus on agentic AI, with the goal of providing each user with their own personal analyst. “It’s not just about productivity,” said Jones. “It’s about changing the value of what can be delivered.” Menninger concluded that Tableau’s shift away from dashboards is a reflection of where business intelligence is headed. “Dashboards, like data warehouses, don’t solve problems on their own. What matters is what you do with the information,” he said. “Tableau’s push toward agentic analytics and collaborative decision-making is the right move for its users and the market as a whole.” 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Wordle Today

Most people are familiar with Wordle by now. It’s that simple yet addictive game where players try to guess a five-letter word within six attempts. Introducing WordMap: Guess the Word of the Day A few weeks ago, while using semantic search in a Retrieval-Augmented Generation (RAG) system (for those curious about RAG, there’s more information in a previous insight), an idea emerged. What if there were a game like Wordle, but instead of guessing a word based on its letter positions, players guessed the word of the day by how close their guesses were in meaning? Players would input various words, and the game would score each one based on its semantic similarity to the target word, evaluating how related the guesses are in terms of meaning or context. The goal would be to guess the word in as few tries as possible, though without a limit on the number of attempts. This concept led to the creation of ☀️ WordMap! To develop the game, it was necessary to embed both the user’s input word and the word of the day, then calculate how semantically similar they were. The game would normalize the score between 0 and 100, displaying it in a clean, intuitive user interface. Diagram of the Workflow The Embedding ChallengeRAGs are frequently used for searching relevant data based on an input. The challenge in this case was dealing with individual words instead of full paragraphs, making the context limited. There are two types of embeddings: word-level and sentence-level. While word-level embeddings might seem like the logical choice, sentence-level embeddings were chosen for simplicity. Word-Level Embeddings Word-level embeddings represent individual words as vectors in a vector space, with the premise that words with similar meanings tend to appear in similar contexts. Key Features However, word embeddings treat words in isolation, which is a limitation. For instance, the word “bank” could refer to either a financial institution or the side of a river, depending on the context. Sentence-Level Embeddings Sentence embeddings represent entire sentences (or paragraphs) as vectors, capturing the meaning by considering the order and relationships between words. Key Features The downside is that sentence embeddings require more computational resources, and longer sentences may lose some granularity. Why Sentence Embeddings Were Chosen The answer lies in simplicity. Most embedding models readily available today are sentence-based, such as OpenAI’s text-embedding-3-large. While Word2Vec could have been an option, it would have required loading a large pre-trained model. Moreover, models like Word2Vec need vast amounts of training data to be precise. Using sentence embeddings isn’t entirely inaccurate, but it does come with certain limitations. Challenges and SolutionsOne limitation was accuracy, as the model wasn’t specifically trained to embed single words. To improve precision, the input word was paired with its dictionary definition, although this method has its own drawbacks, especially when a word has multiple meanings. Another challenge was that semantic similarity scores were relatively low. For instance, semantically close guesses often didn’t exceed a cosine similarity score of 0.45. To avoid discouraging users, the scores were normalized to provide more realistic feedback. The Final Result 🎉The game is available at WordMap, and it’s ready for players to enjoy! 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Is Agentforce Different?

Is Agentforce Different?

The Salesforce hype machine is in full swing, with product announcements like Chatter, Einstein GPT, and Data Cloud, all positioned as revolutionary tools that promise to transform how we work. Is Agentforce Different? However, it’s often difficult to separate fact from fiction in the world of Salesforce. The cloud giant thrives on staying ahead of technological advancements, which means reinventing itself every year with new releases and updates. You could even say three times per year with the major releases. Why Enterprises Need Multiple Salesforce Orgs Over the past decade, Salesforce product launches have been hit or miss—primarily miss. Offerings like IoT Cloud, Work.com, and NFT Cloud have faded into obscurity. This contrasts sharply with Salesforce’s earlier successes, such as Service Cloud, the AppExchange, Force.com, Salesforce Lightning, and Chatter, which defined its first decade in business. One notable exception is Data Cloud. This product has seen significant success and now serves as the cornerstone of Salesforce’s future AI and data strategy. With Salesforce’s growth slowing quarter over quarter, the company must find new avenues to generate substantial revenue. Artificial Intelligence seems to be their best shot at reclaiming a leadership position in the next technological wave. Is Agentforce Different? While Salesforce has been an AI leader for over a decade, the hype surrounding last year’s Dreamforce announcements didn’t deliver the growth the company was hoping for. The Einstein Copilot Studio—comprising Copilot, Prompt Builder, and Model Builder—hasn’t fully lived up to expectations. This can be attributed to a lack of AI readiness among enterprises, the relatively basic capabilities of large language models (LLMs), and the absence of fully developed use cases. In Salesforce’s keynote, it was revealed that over 82 billion flows are launched weekly, compared to just 122,000 prompts executed. While Flow has been around for years, this stat highlights that the use of AI-powered prompts is still far from mainstream—less than one prompt per Salesforce customer per week, on average. When ChatGPT launched at the end of 2022, many predicted the dawn of a new AI era, expecting a swift and dramatic transformation of the workplace. Two years later, it’s clear that AI’s impact has yet to fully materialize, especially when it comes to influencing global productivity and GDP. However, Salesforce’s latest release feels different. While AI Agents may seem new to many, this concept has been discussed in AI circles for decades. Marc Benioff’s recent statements during Dreamforce reflect a shift in strategy, including a direct critique of Microsoft’s Copilot product, signaling the intensifying AI competition. This year’s marketing strategy around Agentforce feels like it could be the transformative shift we’ve been waiting for. While tools like Salesforce Copilot will continue to evolve, agents capable of handling service cases, answering customer questions, and booking sales meetings instantly promise immediate ROI for organizations. Is the Future of Salesforce in the Hands of Agents? Despite the excitement, many questions remain. Are Salesforce customers ready for agents? Can organizations implement this technology effectively? Is Agentforce a real breakthrough or just another overhyped concept? Agentforce may not be vaporware. Reports suggest that its development was influenced by Salesforce’s acquisition of Airkit.AI, a platform that claims to resolve 90% of customer queries. Salesforce has even set up dedicated launchpads at Dreamforce to help customers start building their own agents. Yet concerns remain, especially regarding Salesforce’s complexity, technical debt, and platform sprawl. These issues, highlighted in this year’s Salesforce developer report, cannot be overlooked. Still, it’s hard to ignore Salesforce’s strategic genius. The platform has matured to the point where it offers nearly every functionality an organization could need, though at times the components feel a bit disconnected. For instance: Salesforce is even hinting at usage-based pricing, with a potential $2 charge per conversation—an innovation that could reshape their pricing model. Will Agents Be Salesforce’s Key to Future Growth? With so many unknowns, only time will tell if agents will be the breakthrough Salesforce needs to regain the momentum of its first two decades. Regardless, agents appear to be central to the future of AI. Leading organizations like Copado are also launching their own agents, signaling that this trend will define the next phase of AI innovation. In today’s macroeconomic environment, where companies are overstretched and workforce demands are high, AI’s ability to streamline operations and improve customer service has never been more critical. Whoever cracks customer service AI first could lead the charge in the inevitable AI spending boom. We’re all waiting to see if Salesforce has truly cracked the AI code. But one thing is certain: the race to dominate AI in customer service has begun. And Salsesforce may be at the forefront. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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