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Reshaping the Automotive Industry With Salesforce

Changing customer expectations are reshaping the automotive industry, compelling dealerships to reevaluate their approach to business. With only 1% of buyers fully satisfied with their vehicle purchase experience, dealerships face a significant barrier to fostering loyalty. This dissatisfaction jeopardizes long-term profitability, as customers may turn elsewhere for future service or vehicle needs. Delivering exceptional customer experiences has become more critical than ever. However, rising operational costs present the challenge of achieving more with fewer resources — and doing so quickly. To drive sustainable growth, dealerships must prioritize relationship-building alongside achieving sales goals. Central to this effort is creating personalized digital touchpoints, especially for millennial and Gen Z shoppers, who now dominate the market. These younger consumers seek seamless, consistent experiences — from online browsing to in-person showroom visits. Turning them into lifelong customers requires a unified view of customer data, encompassing their digital shopping habits, service requests, and communications across all platforms. Fortunately, new tools can help dealerships meet these changing demands while reducing costs and improving productivity. To succeed, however, dealerships must adopt a mindset shift, moving beyond transactional practices to focus on customer-centric strategies. Digital Storefronts Are Falling Short Research reveals that fewer than 20% of original equipment manufacturers (OEMs) and retailers consider their digital storefronts engaging and mobile-friendly. For more insights into the industry’s challenges and opportunities, check out the “Trends in Automotive” report, based on feedback from 500 industry leaders. Beyond 30-Day Sales Goals: Building Lasting Relationships Dealerships have long operated in 30-day cycles, dictated by monthly sales goals from OEMs. However, successful dealerships now balance these targets with efforts to nurture long-term relationships. This involves more than sporadic emails about promotions or tune-ups. Instead, it’s about providing consistent, valuable interactions that address customer needs year-round. For example, keeping customers informed with personalized communications—such as alerts about service offers or recommendations for vehicle upgrades—can enhance their overall experience and build trust. Four Steps to Build Customer Loyalty The Path to Loyalty: A 360-Degree Customer View Sustaining long-term profitability hinges on extending customer loyalty beyond individual car sales. With Americans now keeping vehicles for an average of 12 years, dealerships must create enduring relationships across the vehicle’s lifecycle. Salesforce Automotive Cloud empowers dealerships with a 360-degree view of customer data, enabling teams to deliver personalized, seamless experiences. This unified approach helps sales teams close deals faster and service teams provide tailored consultations, ultimately fostering loyalty. Salesforce Sales and Service Cloud provide the same 360-degree view with powerful sales and service tools, including automated agents. The goal? To ensure customers think of your dealership first—whether for service, upgrades, or their next vehicle purchase. By placing the customer at the center of your business and leveraging advanced technology, dealerships can adapt to the evolving landscape and thrive 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 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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September 22, 2023in Agentforce Platform, Artificial Intelligence, Data, Salesforce, Salesforce Automotive Cloud, Technology
Communicating With Machines
20Sep

Communicating With Machines

For as long as machines have existed, humans have struggled to communicate effectively with them. The rise of large language models (LLMs) has transformed this dynamic, making “prompting” the bridge between our intentions and AI’s actions. By providing pre-trained models with clear instructions and context, we can ensure they understand and respond correctly. As UX practitioners, we now play a key role in facilitating this interaction, helping humans and machines truly connect. The UX discipline was born alongside graphical user interfaces (GUIs), offering a way for the average person to interact with computers without needing to write code. We introduced familiar concepts like desktops, trash cans, and save icons to align with users’ mental models, while complex code ran behind the scenes. Now, with the power of AI and the transformer architecture, a new form of interaction has emerged—natural language communication. This shift has changed the design landscape, moving us from pure graphical interfaces to an era where text-based interactions dominate. As designers, we must reconsider where our focus should lie in this evolving environment. A Mental Shift In the era of command-based design, we focused on breaking down complex user problems, mapping out customer journeys, and creating deterministic flows. Now, with AI at the forefront, our challenge is to provide models with the right context for optimal output and refine the responses through iteration. Shifting Complexity to the Edges Successful communication, whether with a person or a machine, hinges on context. Just as you would clearly explain your needs to a salesperson to get the right product, AI models also need clear instructions. Expecting users to input all the necessary information in their prompts won’t lead to widespread adoption of these models. Here, UX practitioners play a critical role. We can design user experiences that integrate context—some visible to users, others hidden—shaping how AI interacts with them. This ensures that users can seamlessly communicate with machines without the burden of detailed, manual prompts. The Craft of Prompting As designers, our role in crafting prompts falls into three main areas: Even if your team isn’t building custom models, there’s still plenty of work to be done. You can help select pre-trained models that align with user goals and design a seamless experience around them. Understanding the Context Window A key concept for UX designers to understand is the “context window“—the information a model can process to generate an output. Think of it as the amount of memory the model retains during a conversation. Companies can use this to include hidden prompts, helping guide AI responses to align with brand values and user intent. Context windows are measured in tokens, not time, so even if you return to a conversation weeks later, the model remembers previous interactions, provided they fit within the token limit. With innovations like Gemini’s 2-million-token context window, AI models are moving toward infinite memory, which will bring new design challenges for UX practitioners. How to Approach Prompting Prompting is an iterative process where you craft an instruction, test it with the model, and refine it based on the results. Some effective techniques include: Depending on the scenario, you’ll either use direct, simple prompts (for user-facing interactions) or broader, more structured system prompts (for behind-the-scenes guidance). Get Organized As prompting becomes more common, teams need a unified approach to avoid conflicting instructions. Proper documentation on system prompting is crucial, especially in larger teams. This helps prevent errors and hallucinations in model responses. Prompt experimentation may reveal limitations in AI models, and there are several ways to address these: Looking Ahead The UX landscape is evolving rapidly. Many organizations, particularly smaller ones, have yet to realize the importance of UX in AI prompting. Others may not allocate enough resources, underestimating the complexity and importance of UX in shaping AI interactions. As John Culkin said, “We shape our tools, and thereafter, our tools shape us.” The responsibility of integrating UX into AI development goes beyond just individual organizations—it’s shaping the future of human-computer interaction. This is a pivotal moment for UX, and how we adapt will define the next generation of design. Content updated October 2024. 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 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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September 20, 2023in Data
Successful Salesforce Implementation
17Sep

Successful Salesforce Implementation

Unlocking the Potential of Salesforce: A Guide to Corporate Success Are you ready to explore the world of Successful Salesforce Implementation? In this Tectonic insight, we’ll explore how to leverage Salesforce to its fullest potential for your corporate success. Whether you’re a small startup or a large corporation, keep reading for practical advice and real-world insights to make Salesforce implementation work for you! What is Salesforce? Salesforce acts as a digital headquarters for organizations, organizing all client information, such as names, purchases, and contact methods. It’s also an Internet application that helps organizations manage customer relationships more effectively by sorting customer details, tracking sales leads, and automating tasks to ease customer interactions. Salesforce is cloudbased, so it is accessible from anywhere. Why Implement Salesforce Now? Implementing Salesforce offers numerous benefits for organizations across various industries: Overall, Salesforce improves how organizations manage customer relationships and utilize data for growth, but effective implementation requires thoughtful planning and customization. Types of Salesforce Implementation Sales Cloud Implementation Sales Cloud is Salesforce’s CRM platform designed to manage sales, leads, and customer interactions. Service Cloud Implementation Service Cloud helps companies provide excellent customer service and support. Marketing Cloud Implementation Marketing Cloud Engagement simplifies marketing efforts, helping businesses connect with customers across various channels. Each type of Salesforce implementation offers unique benefits and challenges, depending on the organization’s needs and goals. CRM Implementation Considerations Implementing a CRM system is a significant move for any business. Here are important things to remember: Step-by-Step Guide to Implement Salesforce Successfully Benefits of a Successful Salesforce Implementation Conclusion Implementing Salesforce is more than adding a powerful CRM system; it’s a journey to greater efficiency, productivity, and customer satisfaction. By thoughtfully planning and customizing Salesforce, organizations can enhance operations, deepen customer relationships, and drive sustainable growth. Embrace the possibilities of Salesforce implementation to chart a course for lasting success and innovation in the modern business landscape. 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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September 17, 2023in Salesforce Development Services, Salesforce Implementation Services
Crucial Role of Data and Integration in AI at Dreamforce
13Sep

The Crucial Role of Data and Integration in AI at Dreamforce

Understanding The Crucial Role of Data and Integration in AI at Dreamforce At this year’s Dreamforce, AI is the star of the show, but two essential supporting actors are data and integration. Enterprises are increasingly recognizing the importance of unifying their diverse data sources for effective analysis and swift action, and the race to harness AI makes this integration even more critical. Integration is key not only for merging data but also for automating end-to-end processes, enabling organizations to move faster and deliver better outcomes to customers. Crucial Role of Data and Integration in AI at Dreamforce. It’s no surprise that MuleSoft, acquired by Salesforce five years ago, is now a major contributor to Salesforce’s growth. Brian Millham, President and COO at Salesforce, highlighted this during the company’s recent Q2 earnings call: “In Q2, nearly half of our greater than $1 million deals included MuleSoft. As customers integrate data from all sources to drive efficiency, growth, and insights, MuleSoft has become mission-critical and was included in half of our top 10 deals.” Breaking Down Silos Param Kahlon, EVP and General Manager for Automation and Integration at Salesforce, recently discussed the investments customers are making in data and integration. He emphasized the importance of breaking down operational silos: “We are in the business of breaking silos across systems to ensure that data can travel seamlessly through multiple systems and people for processes like order-to-cash or procure-to-pay. Our technology connects these dots.” The surge in AI interest has increased the urgency to act, as Kahlon explained: “Creating data repositories for AI algorithms requires real-time data across silos, driving significant demand for our integration solutions.” Consolidating Data Enterprises have long struggled with data consolidation due to monolithic application stacks with separate data stores. This has been a challenge even within Salesforce’s own products. Last year, Salesforce introduced a Customer Data Platform (CDP) called Data Cloud, which includes a real-time data layer named Genie. Kahlon elaborated on its significance: “Data Cloud’s strength lies in its understanding and storage of Salesforce metadata. This native integration allows for real-time actions within Salesforce, enhancing the ability to aggregate, reason over, and act on data.” For example, when a customer contacts a bank, Data Cloud can compile their ATM usage, website interactions, and recent support cases, providing the agent with a comprehensive view to better assist the customer. Leveraging Metadata for AI Salesforce’s metadata layer, which has been fine-tuned over two decades, gives it a distinct advantage. Kahlon noted: “This metadata-based architecture allows us to create meaningful AI algorithms that are natively consumed within Salesforce, enabling visualization and action based on real-time data.” This is crucial for training the underlying Large Language Model (LLM) accurately, ensuring generated content is contextually grounded and trustworthy. Kahlon emphasized: “The trust layer is essential. We need to ensure no hallucination or toxicity in the LLM’s responses, and that communications align with our company’s values.” Real-Time Data and API Management Data Cloud’s ability to connect to other data sources like Snowflake without duplicating data is a significant benefit. Kahlon commented: “Duplicating data is not desirable. Customers need real-time access to the actual source of truth.” On the integration front, APIs have simplified connecting applications and data sources. However, managing API sprawl is crucial. Kahlon explained: “Standardizing API use and publishing them in a centralized portal is essential for reusability and consistency. Low-code platforms and connectors are becoming increasingly relevant, enabling business users to access data without relying on IT.” Automation and AI The demand for automation is growing, and low-code tools are vital. Instead of integration experts being overwhelmed, organizations should establish Centers for Excellence to focus on creating reusable connectors and automations. Kahlon added: “Companies need low-code tools to involve more business users in the transformation journey without slowing down due to legacy applications.” In the future, AI may further ease the workload on integration specialists. MuleSoft recently introduced an API Experience Hub to make APIs discoverable, and AI might eventually help monitor execution logs and manage APIs more effectively. Kahlon concluded: “AI could help developers find and use APIs efficiently, enhancing security and governance while simplifying access to data across the organization.” 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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September 13, 2023in Mulesoft, Salesforce, Salesforce Einstein, Snowflake
salesforce marketing cloud interaction studio
03Aug

Marketing Cloud and Einstein

AI has emerged as an effective solution to tackle the challenges arising from the sheer volume and rapidity of data in the marketing landscape. This article delves into some cutting-edge functionalities presented by Einstein within the Salesforce Marketing Cloud, showcasing how these features empower marketers to enhance performance and streamline their workflows. Einstein for Marketing Cloud uses Salesforce’s AI to help you best evaluate and implement your marketing activities. Use valuable insights on audiences, send time, engagement frequency, and your content to best target your customers. Deliver information to your customers when they need it and how they need it. Einstein in Marketing Cloud offers a range of opportunities for you to analyze, automate, and optimize your content. Use the apps throughout Marketing Cloud platforms to gain insight and better target your audiences. Salesforce Einstein for Marketing Cloud In the dynamic realm of marketing and sales, the pursuit of refining strategies is perpetual. Einstein Social Insights Within the Marketing Cloud’s Social Studio feature, marketers can publish content, engage in conversations, and analyze social data. Einstein augments this platform, introducing AI-powered capabilities: These advanced features empower marketers to optimize social strategy, fostering brand loyalty. For instance: Einstein Vision for Social With over 3 billion images uploaded to social platforms daily, Einstein Vision for Social equips marketers to analyze and derive insights from images. Marketers can train Social Studio to recognize images related to their brand, including products, logos, scenes, and food. This enriched data allows for a deeper understanding of brand followers, facilitating engagement and measurement of marketing efforts. Lookalikes Einstein lookalikes leverage lookalike modeling, identifying common traits among current customers to target new customers with similar characteristics. This tool streamlines the process, allowing marketers to create rich audiences and segments for modeling purposes using first, second, and third-party data in Audience Studio. Einstein Journey Insights In today’s consumer-centric world, Einstein Journey Insights helps marketers comprehend customer journeys by tracking interactions across touchpoints like web browsing and email. Advanced attribution modeling enhances engagements and event sequences, leading to specific goals such as purchases or product reviews. Interactive reports and visualizations enable marketers to optimize campaigns by comparing planned journeys with organic consumer journeys. Einstein Content Tagging Personalized and engaging messages demand an organized library of content. Einstein Content Tagging and image recognition technology automatically add and update content tags and metadata, helping marketers manage their assets efficiently. Smart Orchestration Einstein Send Time Optimization determines the best time to send an email or push notification. Einstein Engagement Frequency evaluates your contacts and identifies the optimal number of email messages or push notifications to send. Marketing Cloud Intelligence As marketing budgets increase, the need for ROI and superior customer experiences rises. Marketing Cloud Intelligence delivers AI-generated insights through automated regression modeling and statistical analysis. Einstein Marketing Insights sifts through data to identify high and low performers, enabling marketers to make informed decisions swiftly and optimize strategies for better results. The Einstein features in Salesforce Marketing Cloud present myriad opportunities for marketers to optimize their performance and work more efficiently. By harnessing these AI-powered capabilities, marketers can make informed decisions rapidly, fostering better brand engagement and higher ROIs. Tectonic is ready to assist you in deploying Einstein for Marketing Cloud. Contact us today. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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August 3, 2023in Data, Einstein Insights, Marketing Automation, Salesforce, Salesforce Einstein, Salesforce Marketing Cloud, Technology
The Evolution of Salesforce Data Cloud
21Jul

The Evolution of Salesforce Data Cloud

The Evolution of Salesforce Data Cloud Salesforce’s journey to Data Cloud started with its acquisition of Krux in 2016, which was later rebranded as Salesforce DMP. This transformation gained momentum in 2019 when Salesforce introduced its customer data platform (CDP), incorporating Salesforce DMP. Subsequent acquisitions of Datorama, MuleSoft, Tableau, and Evergage (now Interaction Studio) enriched Salesforce CDP’s functionality, creating today’s robust Data Cloud. Understanding Customer Data Platforms (CDPs) A customer data platform (CDP) aggregates customer data from multiple channels to create a unified customer profile, enabling deeper insights and real-time personalization. A CDP serves as a centralized customer data repository, merging isolated databases from marketing, service, and ecommerce to enable easy access to customer insights. Salesforce’s “State of Marketing” report highlights the impact of CDPs, noting that 78% of high-performing businesses use CDPs, compared to 58% of underperformers. This analysis explores the evolution of CDPs and their role in transforming customer relationship management (CRM) and the broader tech ecosystem, turning customer data into real-time interactions. Key Functions of a Customer Data Platform (CDP) CDPs perform four main functions: data collection, data harmonization, data activation, and data insights. Origins of Customer Data Platforms (CDPs) CDPs evolved as the latest advancement in customer data management, driven by the need for a unified marketing data repository. Unlike earlier tools that were often limited to specific channels, CDPs enable real-time data synchronization and cross-platform engagement. Advances in AI, automation, and machine learning have made this level of segmentation and personalization attainable. The Future of Customer Data Platforms (CDPs) The next generation of CDPs, like Salesforce’s Data Cloud, supports real-time engagement across all organizational functions—sales, service, marketing, and commerce. Data Cloud continuously harmonizes and updates customer data, integrating seamlessly with Salesforce products to process over 100 billion records daily. With Data Cloud, organizations gain: Benefits of a Customer Data Platform (CDP) CDPs provide comprehensive insights into customer interactions, supporting personalization and cross-selling. Beyond segmentation, they serve as user-friendly platforms for audience analysis and data segmentation, simplifying day-to-day data management. Data Cloud allows organizations to transform customer data into personalized, seamless experiences across every customer touchpoint. Leading brands like Ford and L’Oréal utilize Data Cloud to deliver connected, real-time interactions that enhance customer engagement. The Need for Customer Data Platforms (CDPs) CDPs address critical data management challenges by unifying disjointed data sources, resolving customer identities, and enabling seamless segmentation. These capabilities empower companies to maximize the potential of their customer data. CDP vs. CRM CDPs are an evolution of traditional CRM, focusing on real-time, highly personalized interactions. While CRMs store known customer data, CDPs like Data Cloud enable real-time engagement, making it the world’s first real-time CRM by powering Salesforce’s Customer 360. Selecting the Right CDP When choosing a CDP, the focus often falls into two areas: insights and engagement. An insights-oriented CDP prioritizes data integration and management, while an engagement-focused CDP leverages data for real-time personalization. Data Cloud combines both, integrating real-time CDP capabilities to deliver unmatched insights and engagement across digital platforms. Content updated October 2024. 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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July 21, 2023in Data, Mulesoft, Salesforce, Salesforce Data Cloud
Salesforce BI
15Jul

Salesforce Analytics Acronyms

Here is a helpful list of analytics acronyms you may encounter when discussing Salesforce. Salesforce Analytics Acronyms Acronym Meaning Definition AWS Amazon Web Services AWS offers “reliable, scalable, and inexpensive cloud computing services…the world’s most comprehensive and broadly adopted cloud, offering over 200 fully featured services from data centers globally.” (source)Multiple Salesforce products use AWS; however, it’s prominent in the analytics arena, where organizations rely on AWS to:”Extract, prepare, and analyze Salesforce.com data using Amazon AppFlow, AWS Glue DataBrew, and Amazon Athena.” (source) BYOAI Bring Your Own AI ‘Bring your own AI (model)’ is Salesforce’s way to meet their customers where they’re at. With Data Cloud, Salesforce not only supports Einstein (their own LLM), but also other ones like Sagemaker, Vertex AI, etc. BYOM Bring Your Own Model ‘Bring your own AI (model)’ is Salesforce’s way to meet their customers where they’re at. With Data Cloud, Salesforce not only supports Einstein (their own LLM), but also other ones like Sagemaker, Vertex AI, etc. CRMA CRM Analytics This is the analytics/business intelligence (BI) solution on the Salesforce platform, integrating Salesforce data with external data and provides the ability to analyze large datasets while performing predictive analytics. (Previously known as Wave/Einstein Analytics/Tableau CRM). EA Einstein Analytics The former name for CRM Analytics (also formerly Tableau CRM). You may still come across EA in outdated documentation. GPT Generative Pre-trained Transformer GPT is a technology concept, although it’s often mistaken for a product name (with the rise of the wildly popular ChatGPT). LLM Large Language Model An AI model that has been trained using lots of data. Salesforce has their own LLM that outperformed expectations during testing. Salesforce’s LLM leverages Data Cloud, or can be plugged into a different data lake. Organizations can also opt to their own LLM alongside their Salesforce data. NBA Einstein Next Best Action An AI-driven Salesforce product that makes recommendations to users when they are working with records in Salesforce. It appears within a Lightning component that’s typically placed on the record page sidebar. The user can choose to Accept or Reject the recommendation. NLP Natural Language Processing “Artificial intelligence that focuses on how computers can understand, interpret, and generate human language. NLP allows customers to interact with systems using normal human language rather than complex commands.” (source) SAQL Structured Query Language “Use SAQL to access data in Tableau CRM dataset. Tableau CRM uses SAQL behind the scenes in lenses, dashboards, and explorer to gather data for visualizations.” (source) TCRM Tableau CRM Tableau CRM is a self-service data visualization and business intelligence (BI) platform that integrates Salesforce data with external data. Formerly known as Einstein Analytics, and now CRM Analytics, this product boasts some of the most powerful data analysis capabilities in the market. XMD Extended Metadata “Enables you to customize the formatting of dataset fields and their values in Analytics dashboards and lenses.” (source) 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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July 15, 2023in Salesforce
Salesforce Marketing Cloud Journey Builder
13Jul

Journey Builder Explained

In B2C marketing, the focus on Journey Builder within the Marketing Cloud framework is essential to take customers on journeys with personalized interactions depending on where they are at in the buying cycle. This tool empowers marketers to craft intricate marketing journeys that deliver personalized experiences to customers. Operating within Marketing Cloud, the journey tool orchestrates comprehensive customer journeys, facilitating interactions across multiple platforms such as email, mobile, advertising, and websites. It stands as a foundational element of Marketing Cloud, primarily tailored for B2C initiatives. Salesforce Journey Builder facilitates a deeper understanding of customers by triggering actions based on their unique behaviors and ensuring consistent messaging across channels. As consumers navigate seamlessly between platforms and devices, brands must offer personalized and seamless journeys to maximize customer lifetime value. To achieve this, marketers must address key questions: Answering these questions requires a comprehensive view of the customer journey, with actions aligned to evolving customer expectations. With Salesforce Marketing Cloud Journey Builder, marketers can attain a unified view of all customer interactions, optimizing end-to-end journeys. Journey Builder provides visibility into consumer interactions across marketing channels, including email, mobile, social ads, and more. By connecting these interactions, marketers gain insights for improved message crafting, campaign design, and automation, fostering seamless customer experiences and fostering loyalty. Interactions a customer may have with the brand throughout their journey include clicking on an ad, opening an email, making a purchase, conversing with customer support, and more. Journey Builder, as an event-driven tool, initiates conversations based on customer history, preferences, and real-time behavior, supporting visual mapping of simple or complex journeys. However, Journey Builder operates within Marketing Cloud and utilizes content and audiences from Email Studio, Mobile Studio, Advertising Studio, Content Builder, and Audience Builder. It leverages event-driven triggers to react to customer actions, such as downloading an app or leaving a shopping cart abandoned, thus enabling timely and relevant responses. Key features of Journey Builder include a user-friendly drag-and-drop interface, entry and filter criteria for swift actions, and powerful add-ons for enhanced functionality. Ultimately, Salesforce Journey Builder facilitates a seamless customer experience by guiding journeys, ensuring consistent messaging, adapting to evolving needs, and maintaining brand consistency across channels. 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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July 13, 2023in Data, Google, Salesforce, Salesforce Marketing Cloud
Salesforce JSON
28Jun

Salesforce JSON

Today we are diving into JSON (JavaScript Object Notation) and exploring why it’s a crucial concept for you to understand. JSON is a data representation format widely used across the internet for APIs, configuration files, and various applications JSON Class Contains methods for serializing Apex objects into JSON format and deserializing JSON content that was serialized using the serialize method in this class. Usage Use the methods in the System.JSON class to perform round-trip JSON serialization and deserialization of Apex objects. Roundtrip Serialization and Deserialization Use the JSON class methods to perform roundtrip serialization and deserialization of your JSON content. These methods enable you to serialize objects into JSON-formatted strings and to deserialize JSON strings back into objects. What does JSON serialize do in Salesforce? JSON. serialize() accepts both Apex collections and objects, in any combination that’s convertible to legal JSON. String jsonString = JSON. What is the difference between JSON parse and JSON deserialize? The parser converts the JSON data into a data structure that can be easily processed by the programming language. On the other hand, JSON Deserialization is the process of converting JSON data into an object in a programming language. What is the difference between JSON and XML in Salesforce? JSON supports numbers, objects, strings, and Boolean arrays. XML supports all JSON data types and additional types like Boolean, dates, images, and namespaces. JSON has smaller file sizes and faster data transmission. XML tag structure is more complex to write and read and results in bulky files. Which is more secure XML or JSON? Generally speaking, JSON is more suitable for simple and small data, more readable and maintainable for web developers, faster and more efficient for web applications or APIs, supports native data types but lacks a standard schema language, and is more compatible with web technologies but less secure than XML. What is Salesforce JSON heap size limit? Salesforce enforces an Apex Heap Size Limit of 6MB for synchronous transactions and 12MB for asynchronous transactions. How to store JSON data in Salesforce object? If you need to store the actual JSON payload in Salesforce for audit purposes, Tectonic would recommend just using a Long Text Area field to store JSON content. You wouldn’t have any performance impacts when interacting with records, and if required you could add this to the layout of the child object storing this data. 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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June 28, 2023in Salesforce
web content accessibility guidelines
27Jun

Web Content Accessibility Guidelines

WCAG and ADA compliance While compliance with the Americans with Disabilities Act (ADA) and WCAG conformance have become almost synonymous over the years, it’s important to understand the distinction. Since WCAG itself is not a law, but a set of accessibility standards, there is no such thing as “compliance” with WCAG. However, WCAG was designed to help website owners achieve the level of accessibility that is required by laws like the ADA. It can be helpful to think of accessibility laws such as the ADA as the end destination—i.e., web accessibility for all—while WCAG maps out how to get there. Web content accessibility guidelines follow. Republished from www.w3.org Web Content Accessibility Guidelines Web Content Accessibility Guidelines (WCAG) 2.1 covers a wide range of recommendations for making Web content more accessible. Following these guidelines will make content more accessible to a wider range of people with disabilities, including accommodations for blindness and low vision, deafness and hearing loss, limited movement, speech disabilities, photosensitivity, and combinations of these, and some accommodation for learning disabilities and cognitive limitations; but will not address every user need for people with these disabilities. These guidelines address accessibility of web content on desktops, laptops, tablets, and mobile devices. Following these guidelines will also often make Web content more usable to users in general. WCAG 2.1 success criteria are written as testable statements that are not technology-specific. Guidance about satisfying the success criteria in specific technologies, as well as general information about interpreting the success criteria, is provided in separate documents. See Web Content Accessibility Guidelines (WCAG) Overview for an introduction and links to WCAG technical and educational material. WCAG 2.1 extends Web Content Accessibility Guidelines 2.0 [WCAG20], which was published as a W3C Recommendation December 2008. Content that conforms to WCAG 2.1 also conforms to WCAG 2.0. The WG intends that for policies requiring conformance to WCAG 2.0, WCAG 2.1 can provide an alternate means of conformance. The publication of WCAG 2.1 does not deprecate or supersede WCAG 2.0. While WCAG 2.0 remains a W3C Recommendation, the W3C advises the use of WCAG 2.1 to maximize future applicability of accessibility efforts. The W3C also encourages use of the most current version of WCAG when developing or updating Web accessibility policies. Status of This Document This section describes the status of this document at the time of its publication. A list of current W3C publications and the latest revision of this technical report can be found in the W3C technical reports index at https://www.w3.org/TR/. This is a Recommendation of WCAG 2.1 by the Accessibility Guidelines Working Group. This incorporates errata and are described in the change log. At some point additional changes might be incorporated into an Edited or Amended Recommendation. To comment, file an issue in the W3C WCAG GitHub repository. Although the proposed Success Criteria in this document reference issues tracking discussion, the Working Group requests that public comments be filed as new issues, one issue per discrete comment. It is free to create a GitHub account to file issues. If filing issues in GitHub is not feasible, send email to [email protected] (comment archive). This document was published by the Accessibility Guidelines Working Group as a Recommendation using the Recommendation track. W3C recommends the wide deployment of this specification as a standard for the Web. A W3C Recommendation is a specification that, after extensive consensus-building, is endorsed by W3C and its Members, and has commitments from Working Group members to royalty-free licensing for implementations. This document was produced by a group operating under the 1 August 2017 W3C Patent Policy. W3C maintains a public list of any patent disclosures made in connection with the deliverables of the group; that page also includes instructions for disclosing a patent. An individual who has actual knowledge of a patent which the individual believes contains Essential Claim(s) must disclose the information in accordance with section 6 of the W3C Patent Policy. This document is governed by the 12 June 2023 W3C Process Document. Requirements for WCAG 2.1 Introduction This section is non-normative. Background on WCAG 2 Web Content Accessibility Guidelines (WCAG) 2.1 defines how to make Web content more accessible to people with disabilities. Accessibility involves a wide range of disabilities, including visual, auditory, physical, speech, cognitive, language, learning, and neurological disabilities. Although these guidelines cover a wide range of issues, they are not able to address the needs of people with all types, degrees, and combinations of disability. These guidelines also make Web content more usable by older individuals with changing abilities due to aging and often improve usability for users in general. WCAG 2.1 is developed through the W3C process in cooperation with individuals and organizations around the world, with a goal of providing a shared standard for Web content accessibility that meets the needs of individuals, organizations, and governments internationally. WCAG 2.1 builds on WCAG 2.0 [WCAG20], which in turn built on WCAG 1.0 [WAI-WEBCONTENT] and is designed to apply broadly to different Web technologies now and in the future, and to be testable with a combination of automated testing and human evaluation. For an introduction to WCAG, see the Web Content Accessibility Guidelines (WCAG) Overview. Significant challenges were encountered in defining additional criteria to address cognitive, language, and learning disabilities, including a short timeline for development as well as challenges in reaching consensus on testability, implementability, and international considerations of proposals. Work will carry on in this area in future versions of WCAG. We encourage authors to refer to our supplemental guidance on improving inclusion for people with disabilities, including learning and cognitive disabilities, people with low-vision, and more. Web accessibility depends not only on accessible content but also on accessible Web browsers and other user agents. Authoring tools also have an important role in Web accessibility. For an overview of how these components of Web development and interaction work together, see: Where this document refers to WCAG 2 it is intended to mean any and all versions of WCAG that start with 2. WCAG

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June 27, 2023in Salesforce Sales Cloud
Salesforce
16Jun

Codescan Salesforce

Codescan Salesforce by AutoRABIT is a static code analysis solution that provides visibility into code health from the first line written through final deployment into production. Reliable code analysis directly on the AutoRABIT DevSecOps platform drives Salesforce development quality, speed, and security. The quick code scan tool is free of charge at this time. Code Scanning Definition Code scanning is the process of examining code to identify bugs, errors, and security flaws. Any issues found are displayed, enabling you to address them quickly and enhance the security of your application. What is the CodeScan tool for Salesforce? CodeScan Shield is the leading end-to-end static code analysis solution for code security and quality. Lightning ready and exclusively for the Salesforce platform, CodeScan increases productivity, quality, and security for all Salesforce DevOps teams. What does static code analysis do? Static analysis is a method of debugging that is done by automatically examining the source code without having to execute the program. This provides developers with an understanding of their code base and helps ensure that it is compliant, safe, and secure. The most comprehensive code analysis tool supporting SF languages and metadata. Track and control your SF code quality with CodeScan. Robust Analysis for High-Quality Code and Intuitive Governance Total visibility over the health of your environment reduces costs and increases time to market. 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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June 16, 2023in Salesforce
Salesforce Einstein and Einstein Automate
10Jun

AI Fundamentals

The concept of Artificial Intelligence (AI) has long been a fascination for storytellers and sci-fi enthusiasts. However, for a considerable period, most individuals didn’t give AI much serious consideration, perceiving it as a distant futuristic sci-fi possibility. Nevertheless, researchers and computer scientists have been actively working to transform the dream of AI into a tangible reality, leading some to insist that we have already entered the Age of AI. The AI Fundamentals explained. While the extent of AI’s integration into our daily lives remains uncertain, it is evident that meaningful conversations about AI require a shared vocabulary and a solid foundation of core concepts. Presently, asking ten people to define artificial intelligence is likely to yield ten different answers. This insight attempts to establish a common understanding by exploring AI’s current capabilities and digging into the methodologies employed by computer scientists in creating remarkable AI systems. AI Fundamentals Defining AI proves challenging due to distorted perceptions influenced by science fiction narratives portraying AI as a potentially malevolent force. Additionally, our tendency to benchmark AI against human intelligence contributes to this challenge. And I don’t want AI to be able to write a blog post as well as me! Acknowledging the vast spectrum of intelligence in the animal kingdom, as well as the diversity in human intelligence, prompts a need to view artificial intelligence through a similar lens. As humans we may think we are a lot smarter than a bird. But I don’t know how to fly, do you? AI Capabilities Recognizing specific AI capabilities tailored to distinct tasks is crucial, dispelling the notion of a universally proficient AI, known as general AI, which remains a distant goal. AI currently exists in specialized forms, each excelling at particular jobs. Key AI capabilities fall into several categories: It’s safe to say, artificial intelligence encompasses computer abilities associated with human intuition, inference, and reasoning. Presently, AI skills are highly specialized, covering categories like numeric predictions and language processing. The evolving landscape of AI offers a glimpse into the transformative potential of this technology, emphasizing its current application in specific domains. 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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June 10, 2023in Salesforce, Salesforce Einstein, Salesforce Financial Services Solutions, Salesforce Health and Life Sciences Solutions
Salesforce Sales Cloud
07Jun

Salesforce Sales Cloud GPT

What is Salesforce Sales Cloud GPT? Salesforce’s Einstein GPT is a robust AI tool that seamlessly integrates both public and private AI models with CRM data. This unique synergy allows users to articulate natural-language queries directly within the Salesforce CRM environment, resulting in continuously adapted AI-generated content tailored to evolving customer information and requirements. Salesforce Sales Cloud GPT The suite encompasses a suite of powerful Artificial Intelligence (AI) products, including the Einstein service, the workplace-messaging app Slack, and the data analysis software Tableau. Notably, it unveils a compelling array of natural language tools slated for release in 2023, such as Sales GPT for personalized emails, Service GPT for service messages and chatbots, and Marketing GPT for refined audience targeting. Furthermore, the AI Cloud is meticulously crafted to host extensive language models from various providers such as AWS, Anthropic, and Cohere. Salesforce’s commitment to AI startups is further underscored by a substantial $500 million injection into its venture capital fund. Impact on Sales Cloud with AI and EinsteinGPT: Sales Cloud undergoes a transformative impact through AI, notably EinsteinGPT. Anchored in principles of Trust, Security, and Privacy, Salesforce introduces the Einstein Trust Layer within its AI Cloud offering to assuage privacy concerns. This layer ensures adaptability and transparency while upholding stringent standards for data privacy, security, and compliance. EinsteinGPT for Sales Cloud emerges as a game-changing innovation, serving as a personalized assistant within Salesforce CRM to streamline sales processes. Leveraging Generative AI, it transcends mere data analysis by generating novel content, ideas, and approaches. Key features encompass Einstein GPT, Einstein Conversation Insights, and Einstein Relationship Insights. Industries Experience Tangible Impact: Salesforce’s substantial investments in AI are reshaping the landscape of sales and customer engagement. As EinsteinGPT becomes an integral part of the platform, the anticipation of new and innovative use cases signals a significant leap forward in AI accessibility. Tectonic is please to announce our Sales Cloud Implementation Solutions. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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June 7, 2023in Salesforce Einstein, Salesforce Financial Services Solutions, Salesforce Manufacturing Automotive Energy, Salesforce Public Sector Solutions, Salesforce Sales Cloud
06Jun

Race to AI for CX

AI emerges as a transformative force revolutionizing the customer experience (CX) landscape in the dynamic world of global e-commerce. Its ability to handle extensive data and facilitate large-scale automation empowers brands to offer tailored and seamless CX journeys, fostering customer loyalty and satisfaction. The great race to AI for CX is upon us. In the era of rapid technological advancements, organizations worldwide are in a race to integrate AI-driven capabilities across their operations. The widespread adoption of AI is fueled by its recognition not just as a technological advancement but as a strategic imperative. Businesses invest in AI to enhance operational productivity, reduce costs, elevate customer experiences, and maintain competitiveness. AI’s impact on customer experience extends to substantial improvements in Customer Relationship Management (CRM) systems. Automation of tasks like data entry, lead scoring, and follow-up reminders, coupled with intelligent insights such as predicting high-converting leads, empowers sales teams to optimize their efforts. Considering the pivotal role customers play for every business, CRM has become a launchpad for AI-led transformations throughout enterprises. Businesses swiftly integrate AI-powered experiences into sales, marketing, service, and e-commerce use cases. However, for AI investments to meet expectations, they must be built on robust data practices and trust. Data readiness, reflecting an organization’s preparedness to access and use quality data across its business, is crucial for successful AI outcomes. Ensuring trust in AI, free from data-security concerns or incorrect outcomes, is equally essential. Many companies, lacking mature data practices for advanced AI capabilities like generative AI (genAI), express significant trust concerns; nevertheless, the imperative to progress prompts continued AI investments. The deployment of AI-powered chatbots enables customer service teams to deliver convenient, 24/7 support. These chatbots, exemplified by Zendesk bots, operate round the clock, offering real-time assistance even when support agents are offline. Generative AI-powered conversational bots enhance customer self-service, reduce resolution times, and improve satisfaction by maintaining case-specific tonality and context in real time. Personalized marketing, beyond being a trend, has become a cornerstone strategy for businesses aiming to establish profound connections with their audiences. Crafting messages that resonate personally not only captures attention but also cultivates conversations and fosters lasting brand loyalty. In a digital age where user experience can make or break a brand, strategic partnerships become crucial. The race to AI for CX is on and you can’t afford to be left behind. Enhancing digital user experiences often requires collaboration with specialized partners. Regpack, a versatile payment and registration solution, exemplifies this approach by collaborating with Webeo, specialists in B2B website personalization. This partnership resulted in a 565% increase in site conversion, a 302% rise in average time spent on the site, and a significant 30% drop in bounce rates. Webeo’s personalization software enabled Regpack to identify and adapt to the diverse needs of its clientele through advanced behavioral personalization techniques. Race to AI for CX AI’s impact on marketing extends beyond being an add-on tool, serving as a fundamental game-changer for crafting bespoke customer experiences. AI seamlessly bridges the digital and physical realms, particularly in ecommerce and retail sectors, dynamically adapting products and content based on consumer behavior. AI-driven technologies interpret vast data points, allowing brands to offer hyper-personalized interactions. Real-time data analysis and pattern recognition capabilities make AI a powerful tool for creating engaging and emotionally resonant personalized experiences. In essence, AI architects a new era in marketing, where experiences are not merely personalized but dynamically respond to evolving consumer desires and expectations. Leveraging AI, brands can create narratives that consumers feel intrinsically part of, fostering profound connections. For instance, Calian IT & Cyber Solutions employs personalized marketing tactics to understand and address the unique challenges and needs of each business they serve, fostering strong, long-term relationships with clients. The key takeaway for marketers is clear – the era of generic messaging is fading. A more nuanced, data-driven, and empathetic approach is emerging. Brands that embrace this shift, continuously innovate, and create experiences that customers feel a part of will thrive. As technology advances and consumer expectations evolve, mastering the art of personalization becomes crucial to redefine the marketing landscape. Key Strategies for Exceptional Customer Experience with AI: AI and Customer Experience (CX): AI impacts the entire customer journey, from predictive and prescriptive analytics to sentiment analysis, journey mapping assistance, orchestration, dynamic pricing, virtual try-ons, and augmented reality, providing an interactive and engaging shopping experience. AI and Employee Experience (EX): Efficiencies introduced by AI in employee tasks directly benefit customers. When repetitive tasks are automated, employees gain time for critical and value-added tasks, leading to increased productivity, reduced workload, fewer errors, and improved job satisfaction. Delivering Exceptional Customer Experience with AI: As customer expectations evolve, AI offers a scalable approach for brands to exceed expectations, resulting in memorable customer experiences shaped by clear communication, seamless journeys, and engaging personalized interactions. The transformative potential of AI for CX success is evident in its ability to reshape the marketing landscape. 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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June 6, 2023in Salesforce Einstein

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