Engagement Archives - gettectonic.com - Page 7
Marketing Cloud Website Activity Collection
09Oct

Marketing Cloud Website Activity Collection

Leveraging Website Activity Data in Salesforce Marketing Cloud Understanding how users interact with your website is essential for delivering personalized customer experiences. Salesforce Marketing Cloud (SFMC) offers robust tools to capture website activity and transform this data into actionable insights, enhancing your marketing strategies. This guide walks you through the process of collecting website activity data in SFMC. Marketing Cloud Website Activity Collection Before diving into the setup process, it’s important to understand the benefits of collecting website activity data: Now, let’s explore how to set up website activity tracking in Salesforce Marketing Cloud. Set Up Marketing Cloud Website Activity Collection Step 1: Install Salesforce Marketing Cloud Tracking Code To begin collecting website activity, install the Salesforce Marketing Cloud tracking code on your website. Known as the “Web Collect” code, this script captures visitor behavior data and sends it to SFMC. Step 2: Configure Data Extensions After installing the tracking code, set up data extensions in SFMC to store the website activity data you collect. Step 3: Set Up Behavioral Triggers To maximize the value of your data, set up behavioral triggers in SFMC. These triggers can automatically send personalized communications based on specific website actions. Step 4: Leverage Advertising Studio for Retargeting To further enhance your marketing efforts, use Advertising Studio to create retargeting campaigns based on website activity data. Step 5: Monitor and Optimize After setting up website activity tracking, regularly monitor the performance of your campaigns and the quality of your collected data. Final Thoughts Collecting website activity data in Salesforce Marketing Cloud enables you to understand customer behavior better and deliver more personalized experiences. By following these steps—installing the tracking code, configuring data extensions, setting up behavioral triggers, and leveraging retargeting—you can effectively harness website activity data to elevate your marketing efforts. Start implementing these strategies today to unlock the full potential of Salesforce Marketing Cloud and drive deeper engagement and conversions. 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

Read More
October 9, 2024in Analytics Builder, Data, Google, Salesforce, Salesforce Marketing Cloud
09Oct

Enterprise AI

Enterprise AI: Revolutionizing Business Operations for a Competitive Edge Enterprise AI refers to the suite of advanced artificial intelligence technologies—such as machine learning, natural language processing (NLP), robotics, and computer vision—that organizations use to transform operations, enhance efficiency, and gain a competitive advantage. These technologies demand high-quality data, skilled expertise, and adaptability to rapid advancements. Businesses increasingly adopt enterprise AI because of its ability to automate critical processes, reduce costs, optimize operations, and enable data-driven decision-making. According to McKinsey’s 2024 report, 72% of organizations now integrate AI into their operations, a significant increase from 50% just six years ago. However, implementing AI presents challenges, such as employee mistrust, data biases, lack of explainability, and managing AI’s fast evolution. Successful adoption requires aligning AI initiatives with organizational goals, fostering data trust, and building internal expertise. This guide provides a strategic roadmap for embracing enterprise AI, covering foundational concepts, advanced use cases, and ways to navigate common pitfalls. Why AI Matters in the Enterprise Enterprise AI is a transformative force, similar to how the internet revolutionized global businesses. By integrating AI into their operations, organizations can achieve: AI-driven applications are reshaping industries by enabling hyper-personalized customer experiences, optimizing supply chains, and automating repetitive tasks to free employees for higher-value contributions. The rapid pace of AI innovation requires leaders to consistently re-evaluate its alignment with their strategies while maintaining effective data management and staying informed on evolving tools and regulations. AI’s Transformational Impact on Business AI’s potential is as groundbreaking as electrification in the 20th century. Its immediate influence lies in automating tasks and augmenting human workflows. For example: Generative AI tools like ChatGPT and Copilot further accelerate adoption by automating creative and intellectual tasks. Key Benefits of Enterprise AI Challenges of Enterprise AI Despite its benefits, AI adoption comes with hurdles: Ethical concerns, such as workforce displacement and societal impacts, also demand proactive strategies. AI and Big Data: A Symbiotic Relationship AI thrives on large, high-quality datasets, while big data analytics leverage AI to extract deeper insights. The rise of cloud computing amplifies this synergy, enabling scalable, cost-effective AI deployments. Evolving AI Use Cases AI continues to redefine industries, turning complex tasks into routine operations: Future AI Trends to Watch Building the Future with Responsible AI As AI advances, organizations must prioritize responsible AI practices, balancing innovation with ethical considerations. Developing robust frameworks for transparency and governance is essential to maintaining trust and fostering sustainable growth. AI’s future offers vast opportunities for businesses willing to adapt and innovate. By aligning AI initiatives with strategic goals and investing in robust ecosystems, enterprises can unlock new efficiencies, drive innovation, and lead in their 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

Read More
October 9, 2024in AI Tools, Artificial Intelligence, Data, Enterprise, Generative AI
Marketing Cloud and Commerce Cloud Innovations
09Oct

Marketing Cloud and Commerce Cloud Innovations

What Our Dreamforce Marketing Cloud and Commerce Cloud Innovations Mean for You This year’s Dreamforce was nothing short of amazing. It was exciting to reconnect with fellow Trailblazers, exchange brilliant ideas, and showcase the innovations we’ve been crafting at Salesforce. A recurring theme throughout the event was how businesses can leverage data and AI to forge deeper customer-driven relationships by bringing internal teams closer together. These innovations are designed to transform not only how companies engage with customers but also how their teams work together. Marketing Cloud and Commerce Cloud Innovations. Seamless integration between Marketing, Commerce, Sales, and Service teams is crucial for creating unified customer experiences. Often, customers feel as though they are interacting with separate departments rather than one cohesive company—this is largely due to disconnected technology and processes. But thanks to Salesforce’s advancements in unified data, AI, and automation, those days are numbered. Now, departments can collaborate more effectively, delivering hyper-personalized, frictionless experiences across the entire customer lifecycle. Let’s explore the latest Marketing Cloud and Commerce Cloud innovations announced at Dreamforce 2024 and how they can benefit your business. What You’ll Learn Salesforce Marketing Cloud Innovations These four innovations in Marketing Cloud are built on the Salesforce Platform and powered by Data Cloud, offering marketers a seamless view of customer data across the business. This foundation makes it easier to deliver unified customer experiences, improve handoffs between teams, and measure success more effectively. 1. Agentforce Embedded in Marketing Workflows Agentforce for Marketing combines generative and predictive AI to create an end-to-end campaign experience that marketers can launch and optimize with ease. Here’s how it helps: Example: A marketer looking to prevent customer churn can launch a re-engagement campaign. Agentforce will identify the right audience, craft personalized messages, and optimize delivery based on customer behavior. 2. Empowering Small and Medium Businesses The new Marketing Cloud Advanced Edition brings enhanced AI and automation capabilities to SMBs, enabling them to scale personalization and improve productivity: 3. Automating Data Preparation and Analytics with Einstein Marketing Intelligence (EMI) EMI uses AI and Data Cloud to automate the ingestion, transformation, and analysis of marketing data: 4. Einstein Personalization for 1:1 Experiences Einstein Personalization uses AI to recommend products, content, or services based on individual customer preferences: Example: A service agent could offer a discount on a product a customer was recently viewing, creating a seamless, personalized experience. Salesforce Commerce Cloud Innovations As businesses scale and handle increasing amounts of data, managing complex commerce systems can be a challenge. The new Commerce Cloud updates simplify these complexities by extending unified commerce capabilities across the organization. 1. Simplifying Cross-Functional Commerce Tasks By unifying data from across the business, Commerce Cloud enables better cross-functional collaboration: 2. AI-Powered Commerce Agents with Agentforce Commerce Cloud introduces three AI-powered agents to streamline business processes: 3. Streamlining Checkout for a Faster, Easier Experience With new express payment options like Link by Stripe and Amazon Pay, Commerce Cloud Checkout speeds up transactions and improves conversion rates by 14%. Plus, Buy with Prime integration allows shoppers to use their Amazon Prime accounts for a faster checkout experience, complete with trusted delivery and hassle-free returns. The Future of Unified Commerce Salesforce Commerce Cloud offers a unified platform that brings together sales, service, and marketing, providing a 360-degree view of the entire customer journey. This unified commerce approach enables businesses to deliver seamless B2B and B2C experiences, all powered by a single platform. By integrating enterprise-wide data, trusted AI, and automated workflows, Salesforce helps businesses scale personalized, intelligent experiences across every touchpoint. Every interaction becomes an opportunity for growth, setting the standard for success in today’s customer-driven world. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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

Read More
October 9, 2024in Data, Enterprise, Salesforce, Salesforce Commerce Cloud, Salesforce Marketing Cloud, Technology
Data Cloud Model
08Oct

Data Cloud Model

While many Salesforce products like Sales Cloud, Service Cloud, Education Cloud, Health Cloud, and various industry clouds are built on a common ‘core’ platform that shares the same datastore (an Oracle relational database), Salesforce Data Cloud operates on (Data Cloud Model) a distinct architecture and technology stack. This insight explores the data models and related concepts that underpin the platform. Data Cloud Architecture and Storage Starting with the storage layer, Salesforce Data Cloud integrates multiple services: This combination enables Data Cloud to provide a petabyte-scale data store, overcoming the scalability and performance constraints of traditional relational databases. The physical architecture of Data Cloud is represented as a set of data objects, which form the foundation for how data is ingested, harmonized, and activated within the platform. Key Data Cloud Objects Data Source A Data Source is the initial data layer in Data Cloud, representing an external platform or system from which your data originates. Data Sources can include: Data Stream A Data Stream is an entity extracted from a Data Source, such as ‘Orders’ from Commerce Cloud, ‘Contacts’ from Sales Cloud, or ‘Subscribers’ from Marketing Cloud. Once a Data Source is connected to Data Cloud, Data Streams provide access to these entities and require assignment to a category: Profile, Engagement, or Other. A single Data Source can contain multiple Data Streams. Data Source Object (DSO) Data Streams are ingested into Data Source Objects (DSOs), which serve as temporary staging stores containing data in its raw, native format (e.g., CSV files). Minor transformations can be applied to fields during data ingestion. Data Lake Object (DLO) The next step in the data flow is the Data Lake Object (DLO). DLOs are typed, schema-based, materialized views that reside in the data lake (Amazon S3) and are generally stored as Apache Parquet files. This format, along with Apache Iceberg’s abstraction layer, supports efficient data storage and retrieval. DLOs are the first objects available for inspection and preparation of data, including field mapping and additional transformations. Data Model Object (DMO) Unlike DSOs and DLOs, which use a physical data store, Data Model Objects (DMOs) provide a virtual, non-materialized view into the data lake. Queries against a DMO return results based on the current data snapshot in DLOs, without storing them. DMOs can aggregate attributes from different Data Streams, Calculated Insights, and other sources. DMOs inherit their category from the first DLO mapped to them, and only DLOs with the same category can be mapped to the DMO. Like Salesforce objects, DMOs offer a canonical data model with pre-defined attributes (standard objects), and you can also create custom DMOs (custom objects). DMOs can have one-to-one or many-to-one relationships with other DMOs. Currently, there are 89 standard DMOs in Data Cloud, and this number is growing to support more use cases. DMOs are organized into various subject areas, including: Data Spaces Data Spaces offer logical partitions, allowing data to be segregated between different brands, regions, or departments, without the need for multiple Data Cloud instances. They also align with a Software Development Lifecycle (SDLC), enabling you to stage and test Data Objects in separate environments without affecting production data. Data Sources, Data Streams, and DLOs can be shared across Data Spaces, while DMOs and other platform features are isolated based on user permissions. Final Thoughts With the drop in storage costs and advancements in technology, companies now have vast datasets at their disposal. Every customer interaction, whether it’s a purchase, an email open, or a web page view, can be captured and stored. When properly organized, this data allows businesses to understand customers better, predict their needs, personalize interactions, and much more. However, one of Salesforce’s challenges is that its original platform, built over 20 years ago, was designed for a different era and struggles with handling voluminous, “big” data. Salesforce Data Cloud addresses these limitations with a modern architecture that overcomes the constraints of relational databases. Data Cloud is poised to become the backbone of the Salesforce platform, supporting the data needs of customers and products for the next two decades. If you’re interested in learning how to implement and integrate Salesforce Data Cloud in your organization, following best practices, reach out 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

Read More
October 8, 2024in Data, Google, Salesforce, Salesforce Data Cloud, Snowflake, Technology, Unified Knowledge
Coveo and Salesforce Data Cloud
07Oct

Coveo and Salesforce Data Cloud

Coveo Integrates with Salesforce Data Cloud for Enhanced Data Access Coveo has officially integrated with Salesforce Data Cloud, providing companies with improved access to a broad range of data across the Salesforce ecosystem. This integration enhances the capabilities of Salesforce’s Service Cloud, Commerce Cloud, and Experience Cloud by offering secure access to a wide array of enterprise data sources and engagement data from Coveo-powered search experiences. By leveraging Coveo’s advanced indexing and security features, the integration enables enterprises to seamlessly inject external content into Salesforce experiences through Data Cloud. It also delivers comprehensive analytics across both platforms, allowing businesses to track interactions and touchpoints more effectively. “Coveo has worked closely with Salesforce on a global scale for over a decade,” said Laurent Simoneau, president and CTO of Coveo. “The integration of Coveo with Salesforce creates a powerful synergy, particularly beneficial for large enterprises with complex content ecosystems. Coveo’s robust indexing and relevance capabilities, combined with Salesforce Data Cloud, provide secure access to external data sources, boosting performance and delivering added value across all Salesforce Clouds. This integration sets a new standard for unifying enterprise data and elevating the customer experience.” Kishan Chetan, executive vice president and general manager of Service Cloud at Salesforce, emphasized the impact on service interactions: “Providing precise answers during service interactions is crucial for reducing service costs and improving customer satisfaction, especially for large enterprises managing vast amounts of content and diverse customer bases. Coveo’s ability to connect to extensive content sources and enhance relevance is a key enabler for enterprises with complex search needs in Service Cloud.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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

Read More
October 7, 2024in Salesforce Data Cloud
Salesforce Agentforce Integration
07Oct

Salesforce Agentforce Integration

The rise of AI-powered solutions is transforming customer service, support, and automation. For organizations such as nonprofits, national associations, and large enterprises, delivering seamless customer experiences has become crucial. Salesforce’s Agentforce, a next-generation conversational AI tool, plays a vital role in this transformation. Designed to elevate customer support and interaction, Agentforce provides an intelligent and scalable solution for integrating AI chatbots into content management systems (CMS) like WordPress, Drupal, and HubSpot. Salesforce Agentforce Integration. In this detailed feature review, we will dive into the extensive capabilities of Salesforce Agentforce, analyzing its role as a conversational tool, its technical requirements, and the benefits it provides for nonprofits, national associations, and businesses. We’ll also compare its applications across various CMS platforms like Drupal, WordPress, and HubSpot, exploring its potential as a powerful AI assistant for website automation and customer interaction. Salesforce Agentforce: A Technical Perspective Salesforce Agentforce is an advanced AI-driven conversational assistant that seamlessly integrates into the Salesforce environment. By tapping into Salesforce CRM’s vast data resources, Agentforce serves as an intelligent interface, automating everything from initial customer inquiries to more personalized interactions. Utilizing natural language processing (NLP) and machine learning, it continually refines responses and scales interactions, making it an indispensable tool for organizations aiming to enhance customer service workflows. Agentforce integrates smoothly with Salesforce Service Cloud, automating both live chat support and chatbot responses. Additionally, it can connect with third-party platforms, including popular CMS solutions like WordPress, Drupal, and HubSpot, allowing organizations to centralize customer service operations in one interface. Core Features and Technical Architecture of Agentforce Natural Language Understanding (NLU) and Processing (NLP) Agentforce’s NLP capabilities are its backbone, allowing it to understand complex human language and respond contextually. This empowers it to manage initial inquiries as well as more sophisticated support requests. Agentforce’s NLU also enables it to work across different languages, dialects, and industry-specific terminology, making it particularly valuable for global organizations and national associations serving diverse audiences. Machine Learning for Continuous Improvement Agentforce’s machine learning feature enhances its ability to improve accuracy and understanding over time. Each interaction helps the chatbot evolve, making it more effective at delivering relevant, real-time responses. This model integrates directly with Salesforce’s data infrastructure, giving Agentforce access to historical data and interactions to offer highly personalized, context-aware answers. Deep Integration with Salesforce CRM As a Salesforce-native tool, Agentforce can harness CRM data in ways other AI tools cannot. By accessing customer histories, purchase data, and previous interactions, it creates personalized experiences that build customer trust. Nonprofits and associations can use this data to improve donor or member interactions, offering targeted support and outreach. Agentforce can also be tailored to retrieve specific datasets, such as an individual’s support history or ongoing service case updates. Cross-Platform Flexibility and API Integration Agentforce offers flexible APIs that enable integration with third-party systems, including CMS platforms like WordPress, Drupal, and HubSpot. This flexibility ensures that AI-powered chatbots can be deployed on organizational websites, providing a seamless experience for customers, donors, and members alike. Whether it’s a nonprofit using Drupal or a business on WordPress, Agentforce acts as the central hub for support and engagement, offering fluid interactions on top of your CMS. HubSpot users can further leverage Agentforce’s marketing features to align lead generation with personalized, chat-based interactions. Use Cases for Agentforce in Nonprofits, National Associations, and Businesses Nonprofit Organizations For nonprofits managing donor, volunteer, and beneficiary relationships, Agentforce offers scalable, automated support: National Associations National associations can use Agentforce to handle high volumes of inquiries from members and professionals: Businesses For service-based enterprises, Agentforce is essential for customer service: Salesforce Agentforce and CMS Integration: WordPress, Drupal, and HubSpot WordPress and Salesforce Agentforce Integration For WordPress users, Agentforce offers customizable chatbot widgets that enhance customer engagement, handle ecommerce inquiries, and integrate with WooCommerce for product support. Drupal and Agentforce Integration Drupal’s modular architecture allows Agentforce to automate membership management, provide multilingual support, and distribute content for nonprofits and associations. HubSpot and Agentforce Integration HubSpot users benefit from Agentforce’s ability to automate lead nurturing, sales and marketing workflows, and customer support, all while keeping HubSpot and Salesforce CRM data synchronized. Tectonic and Salesforce Agentforce Integration At Tectonic, we understand that adopting AI-powered solutions like Salesforce Agentforce is only the first step toward delivering exceptional customer experiences. We specialize in crafting, training, and implementing tailored AI chatbot solutions that enhance engagement, streamline processes, and drive growth, all while seamlessly integrating with your current website or mobile app. As a full-service digital strategy firm, Tectonic excels in integrating advanced tools like Salesforce Agentforce into platforms like WordPress, Drupal, and HubSpot, ensuring your automation strategies are executed with precision. From custom chatbot implementations to comprehensive digital strategy services, our team is dedicated to optimizing your website for engagement and lead generation. 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

Read More
October 7, 2024in Agentforce Platform, AI Tools, Data, Enterprise, Salesforce, Salesforce Service Cloud
AI All Grown Up
07Oct

AI All Grown Up

If you thought Salesforce had fully embraced AI, think again. The company has much more in store. AI All Grown Up and Salesforce is the educator! Alongside the announcement of the new Agentforce platform, Salesforce has teased plans to offer free premium instructor-led courses and AI certifications throughout 2025, reflecting a bold commitment to fostering AI skills and expertise. We’ve talked quite a bit over the last year about the need for AI education, and lo and behold here comes Salesforce to the rescue! AI All Grown Up Ah, they grow up so fast. Once just a baby cradeled in our arms with endless possibilities and potential. It was just like a year or so ago we heard of ChatGPT. Prior to that most people’s main exposure to artificial intelligence was their smart phones, which today we realize weren’t reall that smart. Generative, predictive and agentic AI have barreled down the pipeline increasing our vocabulary, and understanding, of what artificial intelligence can do. From generative content to sounds and images, AI continued to amaze us. Then predictive AI did our calculations faster than we could have imagined. Then agentic AI did nearly everything imaginable. AI All Grown Up. Like a very proud mentor of the process, I want to talk about Salesforce’s major contribution. Addressing the AI Skills Gap: Salesforce’s $50 Million Investment As the veritable plethora of AI tools rapidly expands, Salesforce is taking proactive steps to address the growing AI skills gap by investing $50 million into workforce upskilling initiatives. The company aims to ensure that businesses and individuals are prepared to utilize their new wave of AI tools effectively. While the full details have yet to be released, Salesforce has revealed that its premium AI courses and certifications will be made available for free via Trailhead by the end of 2025. This could mean certifications such as AI Associate and AI Specialist, which currently cost $75 and $200 respectively, may soon be offered at no cost. Gratis. Free, Salesforce has also mentioned “premium instructor-led training,” sparking speculation that AI-focused, instructor-led Trailhead Academy courses could become accessible to everyone in the Salesforce ecosystem. Expanding AI Education with Global AI Centers Salesforce’s AI upskilling push is part of a broader initiative to establish “AI Centers” across the globe. Following the opening of its first center in London in June, Salesforce is planning to launch additional AI hubs in cities like Chicago, Tokyo, Sydney, and even a pop-up center in San Francisco. These centers will host in-person premium courses and serve as gathering spaces for industry experts, partners, and customers. This initiative benefits not only the Salesforce ecosystem by increasing AI knowledge where expertise is scarce, but also aligns with Salesforce’s strategy of bringing AI-driven solutions to market through new products like Copilot Studio, Data Cloud, and the newly launched Agentforce platform. Agentforce: Salesforce’s Third Wave of AI On August 28, 2024, Salesforce introduced Agentforce, a suite of autonomous AI agents that marks a significant leap in how businesses engage with customers. Described as the “Third Wave of AI,” Agentforce goes beyond traditional chatbots, providing intelligent agents capable of driving customer success with minimal human intervention. What is Agentforce? Agentforce is a comprehensive platform designed for organizations to build, customize, and deploy autonomous AI agents across various business functions, such as customer service, sales, marketing, and commerce. These agents operate independently, accessing data, crafting action plans, and executing tasks without needing constant human oversight. It is like Artificial Intelligence just graduated highschool and is off to a world of new adventures and growth opportunities at college or university! Key Features of Agentforce: The Technology Behind Agentforce At the core of Agentforce is the Atlas Reasoning Engine, a system designed to mimic human reasoning. Here’s how it works: Customization Tools: Agent Builder Agentforce provides tools like Agent Builder, a low-code platform for customizing out-of-the-box agents or creating new ones for specific business needs. With this tool, users can: The Agentforce Partner Network Salesforce’s partner ecosystem plays a key role in Agentforce’s versatility, with contributions from companies like AWS, Google, IBM, and Workday. Together, they’ve developed over 20 agent actions available through the Salesforce AppExchange. As proud parents we watch our Artificial Intelligence child venture into the world making friends along the way. Learning social skills. Benefits and Impact of Agentforce Early Adopters and Success Stories Several companies are already benefiting from Agentforce: Availability and Pricing of Salesforce’s AI All Grown Up Agentforce for Service and Sales will be generally available on October 25, 2024, with some components of the Atlas Reasoning Engine launching in February 2025. Pricing starts at $2 per conversation, with volume discounts available. The Future of AI and Work Salesforce’s ambitious vision is to empower one billion AI agents with Agentforce by the end of 2025. This reflects their belief that the future of work will involve a hybrid workforce, where humans and AI agents collaborate to drive customer success. AI All Grown Up and We Couldn’t Be Prouder Our amazing AI child has graduated college and ventured out into the workforce. Agentforce vs. Einstein Bots: What’s the Difference? Conclusion Agentforce represents a major leap forward in AI-powered customer engagement. By providing autonomous, intelligent agents capable of managing complex tasks, Salesforce is positioning itself at the forefront of AI innovation. As businesses continue to explore ways to improve efficiency and customer satisfaction, Agentforce could redefine how organizations interact with customers and streamline their operations. If this is the Third Wave of AI, what will the fourth wave bring? Written by Tectonic’s Solutions Architect, Shannan Hearne 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

Read More
October 7, 2024in Agentforce Platform, AI Tools, Data, Google, Mulesoft, Salesforce, Technology
Generative AI and Patient Engagement
07Oct

Generative AI and Patient Engagement

The healthcare industry is undergoing a significant digital transformation, with generative AI and chatbots playing a prominent role in various patient engagement applications. Technologies such as online symptom checkers, appointment scheduling, patient navigation tools, medical search engines, and patient portal messaging are prime examples of how AI is enhancing patient-facing interactions. These advancements aim to alleviate staff workload while improving the overall patient experience, according to industry experts. However, even these patient-centric applications face challenges, such as the risk of generating medical misinformation or biased outcomes. As healthcare professionals explore the potential of generative AI and chatbots, they must also implement safeguards to prevent the spread of false information and mitigate disparities in care. Online Symptom Checkers Online symptom checkers allow patients to input their symptoms and receive a list of potential diagnoses, helping them decide the appropriate level of care, whether it’s urgent care or self-care at home. These tools hold promise for improving patient experiences and operational efficiency, reducing unnecessary healthcare visits. For healthcare providers, they help triage patients, ensuring those who need critical care receive it. However, the effectiveness of online symptom checkers is mixed. A 2022 literature review revealed that diagnostic accuracy ranged between 19% and 37.9%, while triage accuracy was higher, between 48.9% and 90%. Patient reception to these tools has been lukewarm as well, with some expressing dissatisfaction with the COVID-19 symptom checkers during the pandemic, mainly when the tools did not emulate human interaction. Moreover, studies have indicated that these tools might exacerbate health inequities, as users tend to be younger, female, and more digitally literate. To mitigate this, developers must ensure that chatbots can communicate in multiple languages, replicate human interactions, and escalate to human providers when needed. Self-Scheduling and Patient Navigation Generative AI and conversational AI have shown promise in addressing lower-level patient inquiries, such as appointment scheduling and navigation, reducing the strain on healthcare staff. AI-driven scheduling systems help fill gaps in navigation by assisting patients with appointment bookings and answering logistical questions, like parking or directions. A December 2023 review noted that AI-optimized patient scheduling reduces provider time burdens and improves patient satisfaction. However, barriers such as health equity, access to broadband, and patient trust must be addressed to ensure effective implementation. While organizations need to ensure these systems are accessible to all, AI is a valuable tool for managing routine patient requests, freeing staff to focus on more complex issues. Online Medical Research AI tools like ChatGPT are expanding on the “Dr. Google” phenomenon, offering patients a way to search for medical information. Despite initial concerns from clinicians about online medical searches, recent studies show that generative AI tools can provide accurate and understandable information. For instance, ChatGPT accurately answered breast cancer screening questions 88% of the time in one 2023 study and offered adequate colonoscopy preparation information in another. However, patients remain cautious about AI-generated medical advice. A 2023 survey revealed that nearly half of respondents were concerned about potential misinformation, and many were unsure about the sources AI tools use. Addressing these concerns by validating source material and providing supplementary educational resources will be crucial for building patient trust. Patient Portal Messaging and Provider Communication Generative AI is also finding its place in patient portal messaging, where it can generate responses to patient inquiries, helping to alleviate clinician burnout. In a 2024 study, AI-generated responses within a patient portal were often indistinguishable from those written by clinicians, requiring human editing in only 58% of cases. While chatbot-generated messages have been found to be more empathetic than those written by overworked providers, it’s important to ensure AI-generated responses are always reviewed by healthcare professionals to catch any potential errors. In addition to patient engagement, generative AI is being used in clinical decision support and ambient documentation, showcasing its potential to improve healthcare efficiency. However, developers and healthcare organizations must remain vigilant about preventing algorithmic bias and other AI-related risks. 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

Read More
October 7, 2024in AI Tools, Generative AI, Google, Google Analytics, Salesforce Development Services, Salesforce Health and Life Sciences Solutions, Salesforce Implementation Services, Salesforce Optimization, Technology
Natural Language Processing Explained
06Oct

Natural Language Processing Explained

What is Natural Language Processing (NLP)? Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that enables computers to interpret, analyze, and generate human language. By leveraging machine learning, computational linguistics, and deep learning, NLP helps machines understand written and spoken words, making communication between humans and computers more seamless. I apologize folks. I am feeling like the unicorn who missed the Ark. Tectonic has been providing you with tons of great material on artificial intelligence, but we left out a basic building block. Without further ado, Natural Language Processing Explained. Like a lot of components of AI, we often are using it without knowing we are using it. NLP is widely used in everyday applications such as: How Does NLP Work? Natural Language Processing combines several techniques, including computational linguistics, machine learning, and deep learning. It works by breaking down language into smaller components, analyzing these components, and then drawing conclusions based on patterns. If you have ever read a first grader’s reading primer it is the same thing. Learn a little three letter word. Recognize the meaning of the word. Understand it in the greater context of the sentence. Key NLP preprocessing steps include: Why Is NLP Important? NLP plays a vital role in automating and improving human-computer interactions by enabling systems to interpret, process, and respond to vast amounts of textual and spoken data. By automating tasks like sentiment analysis, content classification, and question answering, NLP boosts efficiency and accuracy across industries. For example: Key Use Cases of NLP in Business NLP Tasks NLP enables machines to handle various language tasks, including: Approaches to NLP Future of NLP NLP is becoming more integral in daily life as technology improves. From customer service chatbots to medical record summarization, NLP continues to evolve, but challenges remain, including improving coherence and reducing biases in machine-generated text. Essentially, NLP transforms the way machines and humans interact, making technology more intuitive and accessible across a range of industries. By Tectonic Solutions Architect – Shannan Hearne 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

Read More
October 6, 2024in Artificial Intelligence, Data, Google, Technology
Promising Patient Engagement Use Cases for GenAI and Chatbots
06Oct

Promising Patient Engagement Use Cases for GenAI and Chatbots

Promising Patient Engagement Use Cases for GenAI and Chatbots Generative AI (GenAI) is showing great potential in enhancing patient engagement by easing the burden on healthcare staff and clinicians while streamlining the overall patient experience. As healthcare undergoes its digital transformation, various patient engagement applications for GenAI and chatbots are emerging as promising tools. Let’s look at Promising Patient Engagement Use Cases for GenAI and Chatbots. Key applications of GenAI and patient-facing chatbots include online symptom checkers, appointment scheduling, patient navigation, medical search engines, and even patient portal messaging. These technologies aim to alleviate staff workloads while improving the patient journey, according to some experts. However, patient-facing AI applications are not without challenges, such as the risk of generating medical misinformation or exacerbating healthcare disparities through biased algorithms. As healthcare professionals explore the potential of GenAI and chatbots for patient engagement, they must also ensure safeguards are in place to prevent the spread of inaccuracies and avoid creating health inequities. Online Symptom Checkers Online symptom checkers allow healthcare organizations to assess patients’ medical concerns without requiring an in-person visit. Patients can input their symptoms, and the AI-powered chatbot will generate a list of possible diagnoses, helping them decide whether to seek urgent care, visit the emergency department, or manage symptoms at home. These tools promise to improve both patient experience and operational efficiency by directing patients to the right care setting, thus reducing unnecessary visits. For healthcare providers, symptom checkers can help triage patients and ensure high-acuity areas are available for those needing critical care. Despite their potential, studies show mixed results regarding the diagnostic accuracy of online symptom checkers. A 2022 literature review found that diagnostic accuracy for these tools ranged from 19% to 37.9%. However, triage accuracy—referring patients to the correct care setting—was better, ranging between 48.9% and 90%. Patient reception to symptom checkers has also been varied. For example, during the COVID-19 pandemic, symptom checkers were designed to help patients assess whether their symptoms were virus-related. While patients appreciated the tools, they preferred chatbots that displayed human-like qualities and competence. Tools perceived as similar in quality to human interactions were favored. Furthermore, some studies indicate that online symptom checkers could deepen health inequities, as users tend to be younger, female, and more digitally literate. To mitigate this, AI developers must create chatbots that can communicate in multiple languages, mimic human interaction, and easily escalate issues to human professionals when needed. Self-Scheduling and Patient Navigation GenAI and conversational AI are proving valuable in addressing routine patient queries, like appointment scheduling and patient navigation, tasks that typically fall on healthcare staff. With a strained medical workforce, using AI for lower-level inquiries allows clinicians to focus on more complex tasks. AI-enhanced appointment scheduling systems, for example, not only help patients book visits but also answer logistical questions like parking directions or department locations within a clinic. A December 2023 literature review highlighted that AI-optimized scheduling could reduce provider workload, increase patient satisfaction, and make healthcare more patient-centered. However, key considerations for AI integration include ensuring health equity, broadband access, and patient trust. While AI can manage routine requests, healthcare organizations need to ensure their tools are accessible and functional for diverse populations. Online Medical Research GenAI tools like ChatGPT are contributing to the “Dr. Google” phenomenon, where patients search online for medical information before seeing a healthcare provider. While some clinicians have been cautious about these tools, research suggests they can effectively provide accurate medical information. For instance, an April 2023 study showed that ChatGPT answered 88% of breast cancer screening questions correctly. Another study in May 2023 demonstrated that the tool could adequately educate patients on colonoscopy preparation. In both cases, the information was presented in an easy-to-understand format, essential for improving health literacy. However, GenAI is not without flaws. Patients express concern about the reliability of AI-generated information, with a 2023 Wolters Kluwer survey showing that 49% of respondents worry about false information from GenAI. Additionally, many are uneasy about the unknown sources and validation processes behind the information. To build patient trust, AI developers must ensure the accuracy of their source material and provide supplementary authoritative resources like patient education materials. Patient Portal Messaging and Provider Communication Generative AI has also found use in patient portal messaging, where it can draft responses on behalf of healthcare providers. This feature has the potential to reduce clinician burnout by handling routine inquiries. A study conducted at Mass General Brigham in April 2024 revealed that a large language model embedded in a secure messaging tool could generate acceptable responses to patient questions. In 58% of cases, chatbot-generated messages required human editing. Promising Patient Engagement Use Cases for GenAI and Chatbots Interestingly, other research has found that AI-generated responses in patient portals are often more empathetic than those written by overworked healthcare providers. Nevertheless, AI responses should always be reviewed by a clinician to ensure accuracy before being sent to patients. Generative AI is also making strides in clinical decision support and ambient documentation, further boosting healthcare efficiency. However, as healthcare organizations adopt these technologies, they must address concerns around algorithmic bias and ensure patient safety remains a top priority. 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

Read More
October 6, 2024in Agentforce Platform, AI Tools, Generative AI, Google, Laws, Life Sciences Cloud, Salesforce Development Services, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud
Discharge Planning
03Oct

Discharge Planning

Discharge planning is crucial for smoothly transitioning patients from hospital care to the next stage of their recovery. This process requires collaboration among patients, caregivers, and providers to create a personalized plan that ensures continuity of care after hospitalization. Effective discharge planning must consider the patient’s care needs, preferences, and concerns. When done well, it helps prevent readmissions and alleviates strain on both patients and hospitals. However, balancing clinical judgment with patient data can challenge care teams already burdened with heavy workloads. Jean Halpin, COO at Grant Medical Center, shared how the organization has integrated AI tools to predict discharge dates and automate parts of the discharge planning process, helping to streamline patient care. Challenges of Effective Discharge Planning Halpin emphasized that a streamlined discharge process is essential for reducing wait times and improving patient engagement. Yet, various factors influence how quickly patients are discharged, particularly in emergency rooms where delays can affect overall patient flow. “Most of the wait time we experience as patients boils down to a lengthy discharge process that isn’t effectively moving patients,” Halpin explained. “It’s a domino effect. Someone waiting in the ER for a bed is delayed because another patient hasn’t been discharged when they should have been.” To address these inefficiencies, Grant Medical Center implemented the Qventus Inpatient Solution. This tool integrates with electronic health records (EHRs) to analyze patient data—such as clinical notes, history, and labs—and provides recommendations on discharge timing. These insights have helped reduce ER wait times and improved patient flow. Integrating AI into Clinical Workflows Adopting AI in healthcare comes with integration challenges, particularly ensuring that tools enhance, rather than hinder, clinicians’ workflows. Halpin noted that the Qventus tool minimizes disruptions by seamlessly pulling EHR data to generate an estimated discharge date, allowing care teams to focus on patient care without extra administrative burdens. “As a patient’s health changes, the [discharge] date can fluctuate, but AI uses its data to predict the most accurate day based on similar cases,” Halpin explained. “The care teams can then review the date and determine whether they agree, without having to sift through records to develop their own recommendation.” Halpin also highlighted the value of AI in reducing the administrative load. Tasks like coordinating discharges to rehab facilities, ordering tests, and prescribing medication consume significant time, and automating these functions allows care teams to focus more on direct patient care. Embracing AI to Alleviate Healthcare Worker Burdens For healthcare systems adopting AI, accurately assessing its impact is critical. At Grant Medical Center, leadership is measuring success by evaluating employee satisfaction, patient outcomes, and administrative improvements—such as time and cost savings. “By improving our patient flow, we reduced unnecessary stays by nearly 1,400 days. Patients are happy to go home on time, and our care teams can focus on working at the top of their license,” said Halpin. Despite the benefits, Halpin stressed that implementing AI requires thoughtful onboarding to ensure staff are comfortable with the new tools. Training and support are key to making the transition seamless and enabling teams to see how AI can enhance their workflows. “Health system leaders should embrace advancements that help alleviate burdens for workers,” she said. “Once teams understand the tool, they can prioritize patient care while AI handles the time-consuming admin tasks.” Halpin concluded that embracing AI in discharge planning not only improves operational efficiency but also empowers healthcare teams to deliver better, more focused care. 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

Read More
October 3, 2024in AI Tools, Data, Salesforce Einstein, Salesforce Health and Life Sciences Solutions, Salesforce Optimization, Technology
Salesforce and the Customer-Centric Dealership
03Oct

Salesforce and the Customer-Centric Dealership

Building Blocks for a Customer-Centric Dealership For a dealership to thrive, it must be truly customer-centric. As a Salesforce Implementation Partner, we at Tectonic know the key to success lies in prioritizing customer needs at every step. Growth, profitability, and market expansion come from consistently putting customers at the center of your strategies. Tectonic can help you implement Salesforce and the Customer-Centric Dealership. Customers as the Ultimate Scorekeepers Your customers are the true measure of your dealership’s success. Their evaluations extend far beyond pricing—they assess every touchpoint, from your website’s ease of use to the cleanliness of your parking lot, from your voicemail system to post-sale follow-ups. Each interaction shapes their perception. A single negative encounter, such as a poor experience with a parts associate, may not drive them away, but it certainly won’t motivate them to return. Creating positive, seamless interactions is crucial. Optimizing Customer-Centric Processes Are your processes truly serving your customers? Are they complimenting your dealership’s efficiency? Take something as routine as monthly statements. While they may be straightforward for your team, have you considered your customers’ perspectives? They may not even want a statement, or they might need quicker, more accessible responses to their inquiries. As customer expectations rise due to experiences with brands like Amazon and Starbucks, your dealership must ensure its processes meet or exceed those standards. A Customer portal like Salesforce Experience Cloud can put resources at your customers’ fingertips with the click of a button. Treating Customer Data as a Strategic Asset Customer data is one of your dealership’s most valuable assets. Yet, many dealerships struggle to fully utilize this resource. Are you effectively visualizing and leveraging your customer data? This data, gathered over years of operation, can drive strategic decision-making. To maximize its potential, it’s crucial to have a dedicated role—perhaps a Chief Data Officer—focused on managing, updating, and safeguarding this information. A well-managed data strategy unlocks insights that fuel customer-centric improvements. Letting Data Shape Your Processes With Salesforce, you can use customer data to quickly identify inefficiencies and enhance processes. Streamlined operations lead to happier customers and a more engaged team. For instance, if your manufacturer can deliver most parts within 24 hours, why maintain an overstocked inventory? By analyzing your inventory data, Salesforce can help you identify which parts are essential and which are surplus, allowing you to optimize stock levels and ensure smoother operations. Aligning your inventory with actual demand ensures your dealership functions efficiently, keeping both your customers and staff satisfied. Expert Guidance in Leveraging Salesforce for Growth Adopting a customer-centric approach and utilizing Salesforce to analyze and act on your data can transform your dealership. As your Salesforce Implementation Partner, we’re here to help you integrate these solutions to meet and exceed customer expectations while driving growth and profitability. Together, we can build a dealership that not only competes but thrives in today’s competitive market. With the future of AI, the connected car, and more; there has never been a betrter time to add Salesforce to your customer-centric tool box. Reach out to schedule an introductory call and start your journey toward a more customer-centric 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

Read More
October 3, 2024in Data, Google, Salesforce, Salesforce Experience Cloud

Challenges of EHR Implementation in Healthcare

Challenges of EHR Implementation and How to Overcome Them Implementing an electronic health record (EHR) system is a monumental task, with complexities that require careful planning and execution. Common challenges—such as resistance to change, data migration hurdles, cost overruns, cybersecurity risks, and patient engagement issues—can impede progress. However, understanding these obstacles and applying targeted strategies can pave the way for a smooth transition. 1. Resistance to Change The adoption of a new EHR system affects nearly every workflow in a healthcare organization, often sparking resistance among staff. Fear of change and attachment to familiar processes can hinder implementation. Solution: 2. Data Migration Issues Accurate migration of patient health records is critical, yet transitioning data between systems often presents technical and logistical challenges. Solution: 3. Cost Overruns EHR implementation costs can quickly escalate, extending beyond software and hardware expenses to include consulting fees, training, and operational adjustments. Solution: 4. Heightened Cybersecurity Risks Transitioning sensitive patient data between EHR systems increases vulnerability to breaches, ransomware, and other cybersecurity threats. Solution: 5. Patient Engagement Challenges Patients are often overlooked during EHR transitions, leading to confusion about changes in medication requests, appointment scheduling, and other interactions. Solution: Conclusion EHR implementation is undoubtedly challenging, but with proactive strategies, healthcare organizations can navigate these complexities effectively. By addressing resistance to change, ensuring seamless data migration, managing costs, bolstering cybersecurity, and engaging patients, organizations can achieve a successful EHR transition that enhances workflows, safeguards data, and improves patient outcomes. 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

Read More
October 3, 2024in Data, Life Sciences Cloud, Salesforce, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud

Subscribe to our mailing list. Join our mail list to receive our newsletter

We'll keep you up to date with our latest news, insights, free resources, and much more.
Don't worry, we won't spam you.
gettectonic.com