PHI Archives - gettectonic.com

14Mar

Marketing Cloud Growth Edition

Salesforce has unveiled the Marketing Cloud Growth Edition, (Marketing Cloud Engagement) offering a glimpse into the future of marketing applications aligned with the core Salesforce platform. This edition marks the first iteration of Marketing Cloud on the ‘core’ Salesforce platform, known as Einstein 1 Platform. Built on Data Cloud, it introduces new builders powered by Salesforce CMS, a data model tapping into Salesforce objects, and a suite of data management capabilities through Data Cloud and Einstein’s generative AI tools. It’s crucial to understand that while this edition brings new functionality, Salesforce remains committed to innovating existing Marketing Cloud products as well. Marketing Cloud Growth Edition targets B2B SMB organizations, offering lead capture, cross-channel journeys, engagement scoring, and reporting capabilities. Built on Einstein 1 Built on Einstein 1, Marketing Cloud Growth Edition leverages Data Cloud’s technology to enhance marketing products with AI-powered features. This move signifies Salesforce’s focus on integrating powerful new technologies into the Marketing Cloud tech stack. Two years ago, Salesforce made the decision to rename a number of their Marketing Cloud offerings. Marketing Cloud’s most popular modules for messaging and journeys go by Marketing Cloud Engagement. Has it really been two years? The architecture of Marketing Cloud Growth Edition represents a significant shift, with key components like the email and form builders built on Salesforce CMS. These builders offer guided setup processes and seamless integration with Flow, Salesforce’s automation engine. Marketers will benefit from simplified workflows and advanced personalization options. Marketing Cloud Account Engagement (formerly Pardot), caters to more B2B use cases. So which product is Marketing Cloud Growth Edition really: Marketing Cloud Engagement or Marketing Cloud Account Engagement? Being targeted at B2B, SMB (small-medium) organizations, you may be asking if this is the beginning of the end for Account Engagement. In short, this is not only a new edition, it’s a whole new world…Marketing Cloud ‘On Core’ (Einstein 1). Marketing Cloud Growth Edition and Einstein AI Einstein AI plays a pivotal role in Marketing Cloud Growth Edition, providing features like Send Time Optimization and Co-Create for campaign brief and message generation. Additionally, robust analytics capabilities built on Data Cloud offer insights into marketing performance. Announced at Dreamforce ‘23 as a better re-engineered core platform with the inherent ability to handle generative AI with speed and agility. Support of Salesforce Data Cloud for their marketing platforms has been a focus and now it is a reality. Pricing for Marketing Cloud Growth Edition starts at $18,000 per org per year, with additional options for email sends, unified profiles, segmentation credits, and SMS sends. With Marketing Cloud Growth Edition, you will gain the following: 180k email sends /org/year (add on email sends at an additional cost). 10k unified profiles, unified via Data Cloud. 10k activation and segmentation credits, to use with Data Cloud. The rollout of Marketing Cloud Growth Edition begins in North America, with plans for availability in Europe/Middle East (EMEA) in the second half of 2024. Learning resources and guided setup will be available to help customers get started with the new edition. While Marketing Cloud Growth Edition represents a significant step forward, it’s important to note that it’s not the end of Marketing Cloud or Account Engagement products. Salesforce continues to invest in innovation and development, with future plans to migrate more Marketing Cloud functionality onto the core platform. Great Changes with Marketing Cloud Growth Edition This includes lead capture, sending leads on journeys with email and SMS, automating notifications to sales and service teams, engagement scoring, and reporting for engagement on assets (such as emails, SMS, landing pages and forms). A new type of scoring that combines what we have known as scoring (behavioral) and grading (demographic). With the advent of advanced personalization, sending a large volume of customers through personalized cross-channel journeys, and reporting on these results. The email builder is built on top of Salesforce CMS, a shared service across other parts of the platform, so you have a single repository for assets. Let the tools do what they each excel at. CMS do what it does best, and allow Flow to do what it does best. Tectonic suspects Account Engagement (formerly Pardot) customers will start to see some of this reimagined building experience in the first half of 2024. Salesforce platform users have long known Flow to be Salesforce’s automation engine, bringing incredible power to non-coder that they historically didn’t have. Flow will power the automation behind Marketing Cloud Growth Edition too – including email sending. On The Core Platform As a result of being on the Einstein 1 (‘core’) platform, any AI-powered features marketers choose to use will be accessible and more powerful. Einstein Send Time Optimization is included, which will advise the most optimal time to send an email, based on the best performing emails for that audience in the past. Also, you’ll find Einstein Co-Create for campaign brief and message generation, and likely more that we’ve yet to encounter. When it comes to reporting on marketing on the Salesforce platform, you have many options. B2B Marketing Analytics (B2BMA) is an add-on to Account Engagement, where customers gain access to a pre-built CRM Analytics app that contains dashboards for use cases such as pipeline, engagement, account-based marketing, and other. Will there be access to something similar? For Marketing Cloud Growth Edition, at the time of launch there will instead be a set of reports and dashboards, built on Data Cloud. Details are currently yet to be released by Salesforce. Tectonic will alert you as soon as we hear. Easy Guided Set-ups You may have already gone through the new-style guided setup with other Salesforce modules. You will know that Salesforce has cut down the number of clicks required. Everyone on the Salesforce side involved with the project has been through the setup multiple times, which can be launched in minutes. Overall, Marketing Cloud Growth Edition promises to empower marketers with advanced capabilities and insights, setting the stage for continued evolution and growth in the marketing automation landscape. Marketers like us

March 14, 2024in Salesforce Marketing Cloud

Workflow Rules & Process Builder End of Support

07Mar

Workflow Rules And Process Builder End of Support

Publish Date: Mar 5, 2024 Description Salesforce will no longer be supporting Workflow Rules and Process Builder on December 31, 2025, and we recommend that you migrate your automation to Flow Builder by that time. Workflow Rules & Process Builder End of Support You’re also probably wondering why we’re retiring Workflow Rules and Process Builder. Salesforce wants to focus development on a modern, extensible, low-code automation solution in Flow Builder, which led us to retire the previous features. What does this change mean for me? If you have active Workflow Rules or Process Builder processes running after 2025, they will no longer receive customer support or bug fixes. What action can I take? We recommend implementing a plan to migrate any active rules or processes to Flow Builder before the deadline. Depending on the complexity of your org, this migration may take a significant amount of time and testing, so we recommend starting now. To assist in the migration process, we have a Migrate to Flow tool and extensive support resources available. What happens if I don’t take action? After December 31, 2025, Workflow Rules and Process Builder may continue to function and execute existing automation, but customer support will not be available, and bugs will not be fixed. How do I identify affected users? You can identify whether you have active workflow rules by going to Setup | Process Automation | Workflow Rules and sorting the Active column for checkmarks. You can identify whether you have active Process Builder processes by going to Setup | Process Automation | Process Builder and sorting the Status column for Active. If you have more questions, open a case with support via Salesforce Help. To view all current and past retirements, see Salesforce Product & Feature Retirements. To read about the Salesforce approach to retirements, read our Product & Feature Retirement Philosophy. 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

March 7, 2024in Salesforce

02Mar

Einstein Copilot Studio Explained

Einstein Copilot Studio Explained: Crafting and Personalizing a Reliable AI Assistant Enterprises aiming to personalize Einstein Copilot can leverage the newly introduced Einstein Copilot Studio. This platform enables the construction and customization of AI assistants, incorporating pertinent prompts, skills, and AI models tailored for specific sales, service, marketing, commerce, and IT tasks. Beyond the confines of Salesforce applications, companies can seamlessly integrate Einstein Copilot into consumer-facing channels. This extension enhances customer interactions by embedding AI assistants into websites for real-time chat capabilities or integrating with popular messaging platforms such as Slack, WhatsApp, or SMS. Einstein Copilot Studio comprises the following key components: Just as Microsoft has introduced its own Copilot solutions, powered by generative AI, Salesforce is tapping into the power of LLMs to empower sales, marketing, and customer service professionals. Building on Salesforce’s existing range of Einstein AI features, the company announced “Einstein 1” this year – the next generation of the Salesforce platform. Einstein 1 is a comprehensive suite of tools that empowers users to bring AI into their everyday workflows. The Einstein Copilot (Salesforce Copilot) solution is at the core of this solution, alongside the new Copilot studio and the Einstein Trust Layer. Contact Tectonic today to explore the value of Einstein Copilot Studio for your company., Like2 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

March 2, 2024in Einstein 1 Platform

01Mar

Optimism Among Marketers

In anticipation of challenging market conditions, numerous companies are tightening their financial reins, prompting marketers to carefully allocate strategic investments within finite budgets and resources. The task is further complicated by disruptions stemming from inflation and supply chain issues. Global marketing budgets predominantly allocate significant portions to advertising, as teams strive to enhance awareness in a landscape where customers are faced with abundant choices. And yet, Optimism Among Marketers remains. Optimism Among Marketers In response to a fluctuating job market, marketing organizations are directing investments towards their personnel to attract and retain employees. A notable 71% of marketers express that retaining employees has become more challenging compared to a year ago. B2B marketing entities are earmarking an average of 15% of their budget for account-based marketing (ABM), underscoring the growing emphasis on personalized messaging and engagement extending from B2C to B2B strategies. Marketers have undergone a transformation in their work dynamics, with enduring changes. Liberated from geographical and time constraints, many marketers are achieving success by exploring new customer segments, prioritizing digital-first experiences, and organizing virtual and hybrid events. The shift towards distributed marketing teams has spurred investments in collaboration technology, with 70% viewing such investments as permanent. Similarly, 70% of marketers who invested in process/workflow automation consider it a long-term strategic shift, highlighting the importance of enhancing productivity and efficiency. 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

March 1, 2024in Distributed Marketing, Marketing Automation

29Feb

Sales Cloud Innovation Driven by UX Design Principles

Driving Sales Cloud Innovation Through UX Design Principles: Sales Cloud Innovation Driven by UX Design Principles Enhancing user experiences and driving innovation within Sales Cloud relies on the fundamental principles of UX design. The core philosophy revolves around understanding users’ needs and ensuring simplicity as the default, allowing for increased trust and success. Here’s how three foundational UX design principles guide the product design team at Salesforce: UX Design in Action: The principles of meeting users where they’re at, maintaining low walls and high ceilings, and favoring simplicity are integral to Sales Cloud’s UX design philosophy. By adhering to these principles, Sales Cloud strives to build confidence among users, fostering a collaborative approach to developing innovative and user-friendly products. Sales Cloud administrators need to operate with the same thought process. Tectonic is proud to introduce our Sales Cloud Implementation Solutions. Content updated May 2024. 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

February 29, 2024in Salesforce Implementation Services, Salesforce Sales Cloud

22Feb

How Good is Our Data?

Generative AI promises to significantly reshape how you manage your customer relationships, but it requires data that is accurate, updated, accessible, and complete. Why is this important? You may do something differently this quarter than you did last quarter, based on the latest data. But if your data is outdated or incorrect, that’s what the AI will use. Generative AI focuses on creating new and original content, chat responses, designs, synthetic content or even deepfakes. It’s particularly valuable in creative fields and for novel problem-solving, as it can autonomously generate many types of new outputs. Generative Artificial Intelligence models often present inaccurate information as though it were correct. This is often caused by limited information in the system, biases in training data, and issues with the algorithm. These are commonly called ‘hallucinations‘ and they present a huge problem. When training your models for generative AI, you should first ensure high information excellence from top to bottom. To get your information house in order, remove duplicates, outliers, errors, and other things that can negatively affect how you make decisions. Then connect your data sources — marketing, sales, service, commerce – into a single record, updated in real time, so the AI can make the best recommendations. McKinsey recently wrote, “Companies that have not yet found ways to harmonize and provide ready access to their information will be unable to unlock much of generative AI’s potentially transformative power.” Why is data important in generative AI? Aside from the cost factor, poor information quality can introduce unnecessary and harmful noise into the generative AI systems and models, leading to misleading answers, nonsensical output, or overall lower efficacy. What is high-quality data for AI? High-quality information is essential for AI systems to deliver meaningful results. Data quality possesses several key attributes: Accuracy: High-quality information is free from errors and inaccuracies. Inaccurate information can mislead AI models and produce unreliable outputs. Is AI 100 percent accurate? Because AI will still rely on your data for decision making and accuracy depends on the quality of your information. AI machines must be well-programmed to make sure the machine is making decisions based on the correct, available information. Also, privacy and security of the data are paramount. AI machines need to access information that is encrypted and secure. Understand that Generative AI is most effective at creating new data based on existing patterns and examples, with a focus on text and image data. Generative AI is most suitable for generating new data based on existing patterns and examples. It doesn’t actually think for itself. Yet. Known Limitations Of Generative AI Large language models (LLMs) are prone to “hallucinations” – generating fictitious information, presented as factual or accurate. This can include citations, publications, biographical information, and other information commonly used in research and academic papers. 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

February 22, 2024in Generative AI, Salesforce Einstein

21Feb

Vertex AI

Exploring Google Vertex AI Conversation — Dialogflow CX with Generative AI, Data Stores, and Generators Vertex AI Conversation, built on Dialogflow and Vertex AI, introduces generative conversational features that utilize large language models (LLMs) for natural language understanding, crafting responses, and managing conversation flow. These advancements streamline agent design and enhance the quality of interactions. With Vertex AI Conversation, you can employ a state machine approach to develop sophisticated, generative AI-powered agents for dynamic conversation design and automation. In this insight, we’ll delve into the cutting-edge Dialogflow CX Generative AI technology, focusing on Data Stores and Generators. Data Stores: The Library of Information for Conversations Imagine Data Stores as an extensive library. When a question is asked, the virtual assistant acts as a librarian, locating relevant information. Dialogflow CX’s Data Store feature makes it easy to create conversations around stored information from various sources: For data preparation guidance, visit Google’s official documentation. Generators: LLM-Enhanced Dynamic Responses Dialogflow CX also enables Generators to use an LLM directly in Dialogflow CX without webhooks. Generators can perform tasks like summarization, parameter extraction, and data manipulation. Sourced from Vertex AI, they create real-time responses based on your prompts. For example, a Generator can be customized to summarize lengthy answers—an invaluable feature for simplifying conversations in chat or voice applications. You can find common Generator configurations in Google Cloud Platform (GCP) documentation. Creating a Chat Application with Vertex AI To start building, go to the Search and Conversation page in Google Cloud, agree to the terms, activate the API, and select “Chat.” Setting Up Your Agent After naming your agent and configuring data sources, like a Cloud Storage bucket with PDF documents, you’ll see your new chat app under Search & Conversation | Apps. Navigate to Dialogflow CX, where you can use your data store by setting up parameters for the agent and configuring responses. Once your agent is ready, you can test it in the Agent simulator. Adding a Generator for Summarization Using the Generator feature, you can further refine responses. Set parameters to target the Generator’s summarization feature, and link it to a specific page for summarized responses. This improves chat flow, providing concise answers for faster interactions. Integrating with Discord If you want to deploy your agent on platforms like Discord, follow Google’s integration guide for Dialogflow and adjust your code as needed. With the integration, responses will include hyperlinks for easy reference. Conclusion Vertex AI Conversation, with Dialogflow CX, enables powerful, human-like chat experiences by combining LLMs, Data Stores, and Generators. Ready to build your own dynamic conversational experiences? Now is the perfect time to experiment with this technology and see where it can take you. 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

February 21, 2024in Data, Generative AI, Google, Technology

20Feb

Salesforce Pro Suite

Revolutionizing CRM: Introducing Salesforce Pro Suite In today’s dynamic business technology landscape, Salesforce has established itself as a leader in customer relationship management (CRM) solutions. The launch of Salesforce Pro Suite marks a significant milestone in their mission to empower businesses with cutting-edge tools designed to optimize operations, enhance customer engagement, and drive growth. This article explores the features, benefits, and potential of Salesforce Pro Suite, showcasing why it stands out as a transformative solution for businesses of all sizes. What is Salesforce Pro Suite? Salesforce Pro Suite is a comprehensive collection of integrated tools and services designed to augment the capabilities of Salesforce’s CRM platform. Tailored for modern businesses—from startups to large enterprises—it incorporates advanced functionalities such as artificial intelligence (AI), automation, and data analytics to boost productivity, foster collaboration, and facilitate informed decision-making. Unlock growth and deepen customer relationships with Pro Suite—the all-in-one CRM suite with marketing, sales, service, and commerce tools that scale with your business. Get the flexibility to automate tasks and customize your CRM to fit your specific needs with Pro Suite. Key Features of Salesforce Pro Suite Benefits of Salesforce Pro Suite Use Cases of Salesforce Pro Suite What Can You Do with Pro Suite? Conclusion Salesforce Pro Suite represents a significant advancement in CRM technology, offering a comprehensive suite of tools that cater to the diverse needs of modern businesses. By harnessing AI, automation, and advanced analytics, Pro Suite empowers organizations to optimize operations, enhance customer engagement, and make informed, data-driven decisions. Whether you’re a small startup or a large enterprise, Salesforce Pro Suite provides the scalability, flexibility, and security required to thrive in today’s competitive 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

February 20, 2024in Artificial Intelligence, Data, Enterprise, Salesforce, Technology

Generative AI Prompts with Retrieval Augmented Generation

11Feb

Generative AI Cheat Sheets

Wanted to utilize this insight to share a link to some incredible AI cheat sheets compiled by Medium. Generative AI Cheat Sheets. Top 8 Cheat Sheets on AI Whether you need assistance building a Powerpoint Presentation, AI for enterprise, machine learning, podcast enhancement tools, large language models, efficient ChatGPT prompts, efficient use of emojis, journeys, or more. This list is pretty inclusive. Tectonic would like to share one additional tool we have been using internally. Fireflies. Firflies helps teams transcribe, summarize, search, and analyze voice conversations. When ChatGPT made its debut in late 2022, it sparked global recognition of the transformative capabilities of artificial intelligence (AI). This groundbreaking chatbot represents one of the most significant advancements in AI history. Unlike traditional AI systems that analyze or categorize existing data, generative AI has the remarkable ability to create entirely new content, spanning text, images, audio, synthetic data, and more. This innovation is poised to revolutionize human creativity and productivity across industries, including business, science, and society as a whole. From ChatGPT to DALL-E, the latest wave of generative AI applications has emerged from foundation models, sophisticated machine learning systems trained on massive datasets encompassing text, images, audio, or a combination of these data types. Recent advancements now enable companies to develop specialized models for image and language generation based on these foundation models, most of which are large language models (LLMs) trained on natural language. The power of these models lies not only in their scale but also in their adaptability to diverse tasks without the need for task-specific training. Techniques like zero-shot learning and in-context learning allow models to make predictions and generate responses even in domains they haven’t been explicitly trained on. As a result, companies can leverage these models to address a wide range of challenges, from customer service automation to product design. The introduction of pre-trained foundation models with unprecedented adaptability is expected to have profound implications. According to Accenture’s 2023 Technology Vision report, 97% of global executives believe that foundation models will revolutionize how and where AI is applied, enabling seamless connections across different data types. To thrive in this evolving landscape, businesses must leverage the full potential of generative AI. To expedite implementation, organizations can readily access foundation models through APIs. However, customization and fine-tuning are necessary to tailor these models to specific use cases and maximize their effectiveness. By harnessing generative AI, companies can enhance efficiency, drive innovation, and gain a competitive edge in the market. As generative AI continues to evolve, its impact will only multiply. Companies will increasingly rely on these technologies to streamline workflows, optimize processes, and unlock new opportunities for growth and innovation. With the global AI market projected to reach nearly trillion by 2030, the future holds immense potential for companies to leverage generative AI in solving complex problems and driving transformative change. Generative AI encompasses various machine learning techniques, including transformer models, generative adversarial networks (GANs), and variational autoencoders (VAEs). These technologies underpin a wide range of applications, from natural language processing to image generation, enabling businesses to approach tasks in innovative ways. While generative AI presents unprecedented opportunities, it also raises ethical and security concerns. It is essential for companies to adopt responsible AI practices and ensure the safe and ethical use of these technologies. By embracing generative AI and investing in the necessary infrastructure and talent, businesses can unlock its full potential and drive sustainable growth in the digital era. 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

February 11, 2024in Generative AI, Salesforce

11Feb

Considerations When Implementing PHI

Consumers today express heightened concerns about their data privacy, with 92% of Americans showing apprehension about online privacy. This apprehension extends beyond worries about the security of mobile phones, email, and browsers, particularly in the healthcare sector, where providers face increased scrutiny in safeguarding patients’ Protected Health Information (PHI). PHI is a prime target for cybercriminals due to its sensitivity, but securing it at scale poses significant challenges. Considerations When Implementing PHI. What is PHI and how is it protected? With certain exceptions, the Privacy Rule protects a subset of individually identifiable health information, known as protected health information or PHI, that is held or maintained by covered entities or their business associates acting for the covered entity. HIPAA mandates stringent rules for the protection of healthcare information qualifying as PHI, imposing severe financial and criminal penalties for non-compliance. The HIPAA Privacy Rule specifically oversees PHI, encompassing health or personal information that can identify an individual, including historical, present, or future data related to mental or physical health. Entities handling PHI must adhere to strict requirements for transmitting, storing, and disposing of this data, as patients inherently possess legal rights to the privacy and security of their PHI. Compliance is vital for the protection of PHI, not only to fulfill regulatory obligations but also to mitigate the substantial risks posed by cybercriminals who target this valuable information. The allure for cybercriminals lies in the lucrative market for healthcare data, with records selling for hundreds to thousands of dollars per record on the black market. Given the potential for compromising millions of patient records in a single breach, attackers stand to gain significant sums. In contrast, other personal identifiers like Social Security numbers and credit card information fetch considerably lower prices. What are some of the barriers to implementing HIPAA guidelines in health care organizations? The three main aspects of HIPAA that continue to be a challenge for organizations are privacy, security and breach notification. Ensuring compliance involves both technical and procedural considerations, and practices must implement updated training programs, access controls, secure data disposal methods, encryption measures, and regular security assessments. Compliance extends beyond internal practices, requiring thorough scrutiny of third-party vendors’ adherence to PHI protection regulations. In the broader context of system compliance with PHI regulations, including HIPAA, specific software requirements play a pivotal role. These requirements, such as data encryption, access controls, audit logs, data integrity measures, and breach notification capabilities, collectively ensure the confidentiality, integrity, and availability of PHI. Compliance necessitates an organizational commitment to privacy and security considerations, encompassing technical safeguards, administrative policies, and physical security measures. Various businesses, including hospitals, insurance providers, pharmacies, and psychologists, handle PHI, making its protection challenging yet imperative to adhere to HIPAA standards. Maintain documents containing PHI in locked cabinets or locked rooms when the documents are not in use and after working hours. Establish physical and/or procedural controls (e.g., key or combination access, access authorization levels) that limit access to only those persons who have a need for the information. What’s your responsibility in protecting PHI? This includes implementing HIPAA-required administrative , physical , and technical safeguards with regard to any person, process, application, service, or system used to collect, process, manage, analyze, or store PHI. Like1 Related Posts 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 CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more Salesforce Data Studio Data Studio Overview Salesforce Data Studio is Salesforce’s premier solution for audience discovery, data acquisition, and data provisioning, offering access Read more

February 11, 2024in Salesforce Data Cloud, Salesforce Health and Life Sciences Solutions

07Feb

Healthcare Cloud Marketplace

Healthcare Cloud Computing Market: A Comprehensive Overview and Future Outlook Vantage Market Research Report: Insights into Healthcare Cloud Computing by 2030 WASHINGTON, D.C., February 6, 2024 /EINPresswire.com/ — The global Healthcare Cloud Marketplace was valued at USD 38.25 billion in 2022 and is projected to grow at a compound annual growth rate (CAGR) of 18.2% from 2023 to 2030, reaching approximately USD 145.86 billion by 2030, according to Vantage Market Research. This technology allows healthcare organizations to utilize cloud-based services for data storage, management, and analysis, providing numerous benefits such as cost efficiency, scalability, flexibility, security, and interoperability. It enhances healthcare delivery by enabling seamless data access and sharing across various locations, devices, and networks. Additionally, cloud computing supports the integration of advanced technologies like artificial intelligence, big data analytics, telehealth, and mobile health, driving progress in disease diagnosis, treatment, and prevention. Market Dynamics The market’s growth is fueled by several key factors, including the increasing demand for healthcare IT solutions, the rising prevalence of chronic diseases, the widespread adoption of electronic health records (EHRs), and evolving payment models and regulatory frameworks. The exponential increase in healthcare data, encompassing patient records, imaging scans, and research findings, necessitates scalable storage and analysis solutions. Cloud computing meets this need by providing flexible and scalable infrastructure, accommodating data growth without overburdening IT systems. The rise of telehealth and remote patient monitoring further boosts the demand for secure, cloud-based platforms that facilitate efficient data exchange. However, stringent data privacy regulations like HIPAA and GDPR require robust security measures, compelling healthcare organizations to seek cloud providers that offer strong compliance and access controls. This need for a balance between agility and security shapes the healthcare cloud computing market’s future trajectory. Leading Companies in the Global Healthcare Cloud Computing Market Market Segmentation By Product: By Deployment: By Component: By Pricing Model: By Service Model: Key Trends and Opportunities The healthcare cloud computing market is witnessing significant trends, including the adoption of hybrid and multi-cloud models, which combine the benefits of both public and private clouds. The integration of artificial intelligence (AI) and machine learning (ML) into cloud-based healthcare applications is opening new avenues for personalized medicine, clinical decision support, and drug discovery. Moreover, blockchain technology is emerging as a solution to enhance data security and patient privacy, addressing critical industry concerns. Key Findings: Opportunities: Healthcare Cloud Marketplace The healthcare cloud computing market is poised for robust growth, driven by the increasing demand for scalable and secure data management solutions. As healthcare organizations navigate challenges related to data privacy and security, robust cloud solutions and supportive government policies will be essential in unlocking the full potential of cloud computing in healthcare. 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

February 7, 2024in Salesforce

07Feb

AI Adoption Not Even Across the Board

Reflecting on AI’s potential and its challenges, McElheran calls for a balanced approach: “To fully harness AI’s benefits, we need a realistic, evidence-based approach that accounts for both the advantages and the societal costs associated with adoption.”

February 7, 2024in Data, Technology

07Jan

AI’s Impact on the Workforce

According to McKinsey, generative AI has the potential to contribute between $2.6 trillion and $4.4 trillion in value to the global economy across various industries, spanning banking, retail, high tech, healthcare, and life sciences. Its impact is expected to reach diverse professions, including customer operations, marketing and sales, software engineering, and research and development. The influence of AI on the workforce is significant. A report by Goldman Sachs suggests that AI could replace the equivalent of 300 million full-time jobs, affecting a quarter of work tasks in the US and Europe. However, it also brings forth new job opportunities and a productivity boom. Despite concerns about job displacement, AI is anticipated to generate numerous new opportunities. Roles like prompt engineer and AI product manager are emerging, with a Salesforce-sponsored IDC white paper predicting a surge in demand for positions such as data architects, AI ethicists, and AI solutions architects over the next 12 months. The report also forecasts the creation of 11.6 million new jobs within the Salesforce ecosystem alone over the next six years. Recent advancements in generative AI, exemplified by products like ChatGPT with 100 million monthly active users in two months, have reignited discussions about automation’s impact on jobs. While the extent of disruption remains unknown, developers, users, and policymakers should consider its effects on workers. To address challenges and opportunities, Majority Leader Chuck Schumer has launched a SAFE Innovation Framework, emphasizing worker security. The Biden administration is developing a National AI Strategy to address economic and job impacts. For individuals in the workforce, there’s an opportunity to cultivate existing skills and acquire new ones through platforms like Salesforce’s Trailhead, Coursera, and LinkedIn. AI’s impact on jobs involves eliminating repetitive tasks, allowing individuals to focus on more strategic and creative aspects of their roles. In fields like sales, customer service, marketing, healthcare, finance, and graphic design, AI will transform roles and create new opportunities. Chris Poole, AI Technical Consulting Lead in Salesforce’s global AI practice, envisions AI becoming ingrained in every aspect of our lives, contributing to fascinating evolution across various fields. The scale of AI adoption’s impact on workers, especially with generative AI tools, remains uncertain. Potential effects include replacing, complementing, or freeing workers for more productive tasks, or creating new jobs. A Goldman Sachs estimate suggests that about two-thirds of current jobs are exposed to some degree of AI automation, with generative AI potentially substituting up to one-fourth of current work. McKinsey Global Institute estimates that 29.5 percent of all hours worked could be automated by 2030. Regarding job impact, professional occupations associated with clerical work in finance, law, and business management are most exposed to AI. However, AI is also concurrently creating many new jobs. 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

January 7, 2024in AI Tools, Data, Generative AI, Google, Salesforce, Salesforce Einstein

23Dec

2024 AI and Machine Learning Trends

In 2023, the AI landscape experienced transformative changes following the debut of ChatGPT in November 2022, a landmark event for artificial intelligence. 2024 AI and Machine Learning Trends ahead, AI is set to dramatically alter global business practices and drive significant advancements across various sectors. Organizations are shifting their focus from experimental initiatives to real-time applications, reflecting a more mature understanding of AI’s capabilities while still being intrigued by generative AI technologies. Key AI and Machine Learning Trends for 2024 Here are the top trends shaping the AI and machine learning landscape for 2024: 1. Agentic AIAgentic AI is evolving from reactive to proactive systems. Unlike traditional AI that primarily responds to user inputs, these advanced AI agents demonstrate autonomy, proactivity, and the ability to independently set and pursue goals. 2. Open-Source AIOpen-source AI is democratizing access to sophisticated AI models and tools by offering free, publicly accessible alternatives to proprietary solutions. This trend has seen significant growth, with notable competitors like Mistral AI’s Mixtral models and Meta’s Llama 2 making strides in 2023. 3. Multimodal AIMultimodal AI integrates various types of inputs—such as text, images, and audio—mimicking human sensory capabilities. Models like GPT-4 from OpenAI showcase this ability, enhancing applications in fields like healthcare by improving diagnostic precision. 4. Customized Enterprise Generative AI ModelsThere is a rising interest in bespoke generative AI models tailored to specific business needs. While broad tools like ChatGPT remain widely used, niche-specific models are increasingly popular for their efficiency in addressing specialized requirements. 5. Retrieval-Augmented Generation (RAG)RAG combines text generation with information retrieval to boost the accuracy and relevance of AI-generated content. By reducing model size and leveraging external data sources, RAG is well-suited for business applications that require up-to-date factual information. 6. Shadow AIShadow AI, which refers to user-friendly AI tools used without formal IT approval, is gaining traction among employees seeking quick solutions or exploring new technologies. While it fosters innovation, it also raises concerns about data privacy and security. Looking Ahead to 2024 These trends highlight AI and machine learning’s expanding role across industries in 2024. Organizations must adapt to these advancements to remain competitive, balancing innovation with strong governance frameworks to ensure security and compliance. Staying informed about these developments will be crucial for leveraging AI’s transformative potential in the coming year. 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

December 23, 2023in Generative AI

22Dec

Marketing Cloud Growth and Advanced Editions

While Growth Edition is tailored to small businesses looking to get started with robust marketing automation, Advanced Edition caters to companies that need more sophisticated tools to scale personalization efforts, improve customer engagement, and streamline workflows. It offers additional features, including real-time journey testing, predictive AI for customer scoring, and advanced SMS capabilities, allowing businesses to enhance every touchpoint with their customers.

December 22, 2023in Data, Enterprise, Marketing Automation, Salesforce, Salesforce Data Cloud, Salesforce Implementation Services, Salesforce Marketing Automation, Salesforce Marketing Cloud, Technology

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