Generative AI Archives - gettectonic.com - Page 21
Salesforce Einstein
25Mar

Use AI to Prep for Meetings

Sales is fundamentally a relationship-oriented endeavor, where representatives invest substantial time delving into lead interests, needs, and behaviors to fortify connections. What if you could Using AI to prep for meetings? Imagine a tool that assumes this responsibility, endowing you with the ability to swiftly acquaint yourself with pertinent information. Here’s what AI can accomplish: it undertakes the arduous research, analyzing both public and CRM data to succinctly encapsulate vital prospect details essential for pre-meeting preparation. If you have specific queries, just pose a question, and AI promptly provides a powered response. Consider this scenario: A sales representative steps in for a colleague on leave, aiming to catch up on major accounts. They leverage Einstein in Sales Cloud, filtering deals with a revenue exceeding $100,000. Many of these deals boast extensive historical data, a formidable amount to sift through. Einstein streamlines the process by presenting deal summaries encompassing crucial information such as involved parties, recent activities, potential risks, and recommended next steps. How to use AI to prep for meetings Einstein goes a step further, flagging an email from a customer with pricing queries awaiting a response. The rep seeks guidance: “What key information should I know about this customer before addressing the email?” Einstein synthesizes the deal in plain language, offering key account details and insights from past meetings to seamlessly resume the conversation. In other words, Einstein answers the reps question – in seconds. Sales Summaries for Sales Cloud becomes the go-to solution for instant meeting preparation, enabling sellers to navigate meetings with agility. Elevate your selling velocity with integrated AI directly in your CRM. Provide each seller with an AI assistant to turbocharge sales across the cycle, automating tasks, expediting decisions, and steering sellers towards swift closures. Einstein 1 allows effortless customization and integration of AI into various workspaces. Here are some key functionalities: 1. Call Summaries & Exploration: Bid farewell to tedious note-flipping. Ask Einstein to synthesize critical call information swiftly, generating concise summaries or identifying pivotal takeaways and customer sentiment from sales calls. 2. Prospect and Account Research: Streamline research on prospects and accounts. Summarize CRM records to gauge deal viability, competitor involvement, and more. Fetch real-time data updates from the news, and direct Einstein to update lead or opportunity records effortlessly. 3. Call Insights: Identify crucial moments from sales conversations. Instantly recognize objections, pricing attitudes, and questions asked without sifting through entire calls. Accelerate deal progression with conversation insights related to opportunities. 4. Relationship Graphs: Discern relationship networks effortlessly. Grasp prospect and customer networks for each deal, with automatic population of contacts and relevant details to fortify relationships with decision-makers. 5. Relationship Insights: Unearth new relationship insights with support from external data. Gain vital context from diverse sources across the web, seamlessly integrated into your CRM, and automatically update existing records with newfound information. Generative AI for Sales: Generative AI employs straightforward prompts to craft copy (e.g., prospecting emails) and provide recommendations (e.g., suggestions for quick-win deals). It analyzes existing sales and customer data to assist in drafting emails and determining messages or resources that would propel a sales conversation forward. Integration into a CRM, the hub of sales and customer data, is the likely destination for these capabilities. And while we’re at it – Real-Time Improvement of Sales Presentations: Crafting compelling presentations demands significant time and effort. Generative AI, activated through text-based prompts in presentation tools, facilitates the creation of customized decks and pitches within minutes. Early versions of real-time coaching are emerging, where AI-based guidance, embedded in video conferencing tools, evaluates live presentations to ensure they address the prospect’s pain points effectively. This advanced system, triggered by specific keywords, can recommend prospect-specific information, transforming your presentation into a tailored and impactful experience. Like Related Posts Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Public Sector Salesforce Solutions Public Sector Solutions revolutionize public service delivery through flexible and secure e-government tools supporting both service providers and constituents. Designing Read more

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March 25, 2024in Einstein Insights, Generative AI, Salesforce Einstein
Learning AI
21Mar

The New Age of Compliance with AI

How can small businesses ensure compliance? Business in the New Age of Compliance with AI can be challenging. While larger corporations often allocate resources for extensive research and development to maintain compliance, smaller businesses may lack the means to conduct thorough due diligence. In such cases, it becomes crucial for them to pose the right questions to vendors and technology partners within their ecosystem. Even as Salesforce takes strides in creating trustworthy generative AI solutions for its customers, these customers also engage with other vendors and processors. It is imperative for them to remain vigilant about potential risks and not rely solely on trust. Salesforce and Tectonic suggest that smaller companies should inquire about: For smaller companies, depending on the due diligence of third-party service providers becomes essential. Evaluating privacy protocols, security procedures, identification of potential harms, and safeguarding measures are critical aspects that demand close attention. In this New Age of Compliance with AI everyone is responsible. Choosing an AI savvy Salesforce partner like Tectonic protects you and your company. The Einstein Trust Layer is your insurance that you are doing artificial intelligence right. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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March 21, 2024in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Einstein
LLMs Beyond Generative AI
16Mar

LLMs Beyond Generative AI

Beyond Text Generation: The Versatile Capabilities of Large Language Models While large language models (LLMs) and generative AI have dominated the conversation over the past year, the spotlight has largely been on their text generation capabilities. There’s no denying the value of LLMs in generating answers to questions. However, focusing solely on this use case overlooks other valuable applications. This insight will explore several primary uses of LLMs, ensuring you recognize their broader potential beyond just generative purposes. Creation and Generation This is the most publicized use case for LLMs today. Applications like ChatGPT can answer questions with detailed responses, and tools like DALL-E generate images based on user prompts. Similar generators exist for code, video, and 3D virtual worlds. Interestingly, these generators share fundamental algorithmic approaches despite producing different content types—text, images, videos. Since they all process prompts, they require training to understand and decompose these prompts to guide the generation process, necessitating the use of LLMs. However, generating new content is just one aspect of what LLMs can achieve. Summarization LLMs excel at summarizing information. For instance, if you have a list of papers on your to-read list, an LLM can summarize their key themes, common points, and differences. This provides a clear baseline, helping you focus on essential aspects as you read. Summarizing content with AI tends to have a lower error risk compared to generating new content because the LLM works within the boundaries of the provided information. While it might occasionally miss a pattern or emphasize the wrong details, it’s unlikely to produce completely incorrect summaries. Translation Often underrated, translation might be one of the most impactful uses of LLMs. For example, LLMs can translate old code from obsolete languages into modern ones. An LLM generates a draft translation, which, although imperfect, can be refined by a programmer who understands the goal of the code even with limited knowledge of the original language. Human language translation also stands to benefit significantly. Soon, we’ll be able to communicate in our preferred languages, with LLMs instantly translating our words into the listener’s language. This will eliminate the need for a common language and help preserve uncommon languages by removing the communication barriers associated with them. Interpretation and Extraction LLMs are also adept at interpreting statements and triggering subsequent actions. Image generators use this approach, as do tools that handle analytical queries. For instance, asking “Please summarize this year’s sales by region and subtotal by product” allows an LLM to interpret the request, extract key parameters, and pass them to a query generator for the answer. Companies like Quaeris, which I advise, focus on this capability. Additionally, LLMs can handle tasks like sentiment analysis and customer service inquiries. They can ingest inquiries and extract relevant details, such as the product in question, the issue raised, and the requested action, to route the inquiry to the appropriate person more effectively. LLMs Beyond Generative AI The examples discussed are not exhaustive but represent some common and powerful uses of LLMs. They highlight that LLMs offer far more than just text generation. Exploring these other applications can provide significant benefits for you and your organization. Originally posted in the Analytics Matters newsletter on LinkedIn. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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March 16, 2024in Generative AI, Salesforce Einstein
What is Einstein Used for in Salesforce?
14Mar

What is Einstein Used for in Salesforce?

Salesforce Einstein is an AI-powered platform that can be used in various ways to enhance customer experiences and streamline business operations: SalesSalesforce Einstein can help sales teams better understand customers, improve conversion rates, and close deals more quickly. For instance, it can generate sales call summaries, draft emails using customer data, and provide real-time predictions. Customer ServiceEinstein helps customer service agents resolve cases faster and provide customers with relevant information during interactions. MarketingSalesforce Einstein enables marketers to create personalized experiences and send the right content to the right customer at the right time. ITSalesforce empowers IT teams to embed intelligence across the business and create smarter apps for customers and employees. CommerceSalesforce assists retailers by recommending the best products to each customer. Salesforce also includes features to protect data privacy and security, such as the Tectonic GPT Trust Layer, which provides AI bias detection, data security, and regulatory compliance. Salesforce Einstein is the first all-inclusive AI for CRM. It’s an integrated set of AI technologies that makes the Customer Success Platform smarter and brings AI to Salesforce users everywhere. Salesforce is the only comprehensive AI for CRM. It is: Tectonic and Salesforce allow businesses to become AI-first, providing the ability to anticipate customer needs, improve service efficiency, and enable smarter, data-driven decision-making. Sales teams can anticipate next opportunities and exceed customer needs,Service teams can proactively resolve issues before they occur,Marketing teams can create predictive journeys and personalize experiences like never before,IT teams can embed intelligence everywhere and create smarter apps. AI that works for your business.Drive business productivity and personalization with predictive AI, generative AI, and agents across the Customer 360 platform. Create and deploy assistive AI experiences natively in Salesforce, allowing your customers and employees to converse directly with Agentforce to solve issues faster and work smarter. Empower service reps, agents, marketers, and others with AI tools safely grounded in your customer data to make every customer experience more impactful. What is Salesforce Einstein?As of 2024, this groundbreaking AI-based product remains a leader in the CRM industry since its release in 2016. It combines a range of AI technologies, including advanced machine learning, natural language processing (NLP), predictive analytics, and image recognition, enabling businesses to improve productivity and sustain growth. Salesforce AI BenefitsThe most significant benefits of AI are the time and efficiency gains it offers to business processes. By automating tasks, employees can focus on more strategic work. Additionally, automating repetitive tasks reduces errors and enhances operational efficiency. Saleesforce provides robust reporting features that generate valuable insights to support decision-making, helping businesses understand customer needs and identify opportunities. From a customer perspective, Salesforce ensures more meaningful and personalized experiences through advanced NLP capabilities and machine learning to better understand customer behavior. Salesforce AI FeaturesSalesforce is a feature-rich platform that leverages AI’s capabilities in Natural Language Processing, Machine Learning, and image processing. Some of the key features include: Salesforce PricingCosts depend on the required features and the size of the business. Pricing starts at $50 per user per month, with potential increases based on the specific capabilities needed. Salesforce Tectonic ChallengesAlthough Salesforce Tectonic offers numerous benefits, companies may face challenges during integration, such as aligning it with existing systems and ensuring proper training for employees to maximize its use. How to Prepare for Salesforce Tectonic IntegrationUsing an implementation partner like Tectonic can help ensure seamless integration. A partner will assess your current Salesforce setup, recommend the right features, and guide you through the integration process. ConclusionSalesforce is a cutting-edge platform that empowers businesses to transform operations with comprehensive AI capabilities. It provides tailored solutions for sales, service, marketing, and commerce teams, enabling better customer interactions, data-driven decision-making, and increased productivity. With the right implementation partner like Tectonic, businesses can seamlessly integrate and leverage Tectonic to stay ahead in a competitive landscape. Content updated November 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

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March 14, 2024in AI Tools, Data, Generative AI, Salesforce, Salesforce Einstein
FigJam AI
13Mar

FigJam AI

Recently Edward Chechique explained FigJam AI, an AI flowchart generator. Below is a summary of this article originally published at uxdesign.cc Over the past three years, the author has extensively researched and tested how product designers can use generative AI technology to improve efficiency and accuracy in their design workflows. Although this journey is still in its early stages, designers must integrate AI into their design processes today. This integration will enable them to work more efficiently and with greater precision. Common AI tools on the market include ChatGPT, Gemini, and Midjourney, showcasing key features of artificial intelligence technology. Additionally, many new tools are launched daily. Apart from the new AI tools, there are tools not originally AI-based, like Figma and Miro. These tools have started to add AI capabilities, enhancing their utility. This article aims to show how designers can use FigJam AI, an efficient AI flowchart maker, to create flowcharts. In the words of designers: “Stop moving rectangles and invest in creativity.” This encapsulates the author’s goal. What is FigJam AI? FigJam AI is an AI tool that Figma added to FigJam. It helps cluster information, generate design thinking workshops, organize information, summarize information, and more. For a more detailed look at this AI feature, check out the author’s article about FigJam AI. Step-by-Step Introduction to Figjam AI for Better Design Collaboration Enhancing Design Team Workflows with Figjam AI The Importance of Detailed Prompts When teaching students how to use AI, the author emphasizes the importance of providing the AI with exact instructions. Without this, the desired results may not be achieved. This highlights a significant difference from traditional work processes. Often, traditional methods don’t start with a clear end solution but involve experimenting, adjusting designs, and refining the vision over time. In contrast, AI requires precise instructions from the beginning. The examples provided illustrate this point. During the process, small changes in the prompt can significantly affect the results, demonstrating the importance of clear and specific instructions. Generate Flowcharts from Text The author conducted several tests with FigJam AI to illustrate the process. Starting with simple prompts and gradually moving to more sophisticated approaches, here are three key tests: Test 1: Happy Flow The author began with a simple flowchart for buying a T-shirt in an online store to see if the AI could generate a complete flow from it. Prompt: Act like a product designer and create a Flow chart for the process of buying a T-shirt in an e-commerce store: Create only this flow. Do not add anything else. Result: The AI created exactly what was asked, making the creation process more efficient by eliminating the need to manually adjust “rectangles,” streamlining the diagram creation. Test 2: Flow with One Error The second test aimed to see if the AI could add a condition to the flow for cases where something does not work correctly. Prompt: Act like a product designer and create a Flow chart for the process of buying a T-shirt in an e-commerce store: Take into account the error case: Promo Code does not work. Create only this flow. Do not add anything else. Result: The AI accomplished the task exactly as requested and added the error case to the flowchart creation. Test 3: Flowchart with Three Errors The next step was to see if the AI could handle three error cases. Prompt: Act like a product designer and create a Flow chart for the process of buying a T-shirt in an e-commerce store: Take into account these error cases: Create only this flow. Do not add anything else. Result: The AI added all error cases but with issues: To address these issues, the author revised the prompt: Revised Prompt: Act like a product designer and create a Flow chart for the process of buying a T-shirt in an e-commerce store: Create only this flow. Do not add anything else. Result: The AI added all error cases correctly, creating a more legible and easy-to-understand flow. Key Insights from the Tests: To Summarize: This insight demonstrated how to use FigJam AI as an AI flowchart tool. The author shared three tests: a happy path flowchart, a flowchart with one error case, and a more complex flowchart with three error cases. After refining the prompts, the desired results were achieved. Key insights from the process were also discussed. Like Related Posts Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust 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’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more

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March 13, 2024in Generative AI
Customized Conversational AI Assistant
11Mar

Customized Conversational AI Assistant

Create and Customize a Conversational AI Assistant for CRM Einstein Copilot is your all-in-one CRM AI assistant, seamlessly integrated into every Salesforce application. It empowers teams to accelerate tasks with intelligent actions, deploy conversational AI with built-in trust, and easily scale a unified copilot across your organization. Customized Conversational AI Assistant. Einstein 1 Studio Customize and Enhance AI for CRM:Einstein 1 Studio allows you to tailor Einstein Copilot to your specific business needs. Configure actions, prompts, and models to create a personalized AI experience. Users can interact with the AI using natural language, making task execution more intuitive and efficient. Copilot Builder Expand Einstein Copilot with Advanced Features:Enhance Einstein Copilot by integrating actions with familiar Salesforce platform features like Flows, Apex code, and Mulesoft APIs. Convert workflows into copilot actions and test these interactions within a user-friendly interface, enabling you to monitor and refine your copilot’s performance. Prompt Builder Accelerate Employee Task Completion:Design prompt templates that quickly summarize and generate content, helping employees complete tasks faster. Create prompts that draw from CRM data, Data Cloud, and external sources to make every business task more relevant. Develop prompts once and deploy them across Einstein Copilot, Lightning pages, and flows. Model Builder Integrate and Manage AI Models:Incorporate your predictive AI models and large language models (LLMs) within Salesforce through the Einstein Trust Layer. Utilize no-code ML models in Data Cloud, and manage all your AI models from a centralized control platform, ensuring seamless operation and integration. Deploy Trustworthy AI Leverage Generative AI with Built-In Safeguards:Einstein Copilot is designed to ensure the privacy and security of your data, while improving result accuracy and promoting responsible AI use across your organization. Built directly into the Salesforce Platform, the Einstein Trust Layer offers top-tier features and safeguards to ensure your AI deployments are trustworthy. “The combination of AI, data, and CRM allows us to help busy parents solve the ‘what’s for dinner’ dilemma with personalized recipe recommendations their family will love.”— Heather Conneran, Director, Brand Experience Platforms, General Mills Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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March 11, 2024in Data, Generative AI, Mulesoft, Salesforce
Service and Generative AI
08Mar

Service and Generative AI

Customer service organizations are currently grappling with formidable challenges, as service agents contend with unprecedented case volumes and customers increasingly express frustration over extended wait times. Agents often find themselves managing multiple customer issues simultaneously, awaiting data from legacy systems to load, leading to inefficiencies. Service and Generative AI together are a solution to better serve your customers. The closure of a case does not mark the end of the challenge, as case notes may go missing, and subsequent agents may unknowingly address similar issues from scratch. With nearly half of customers citing poor service experiences as a primary reason for switching brands, companies are under immense pressure to find more effective solutions. Recent excitement surrounds ChatGPT, an artificial intelligence (AI) model by OpenAI. Models like GPT, Anthropic, and Bard, constructed on large language models, hold the potential to revolutionize customer service. Combined with Salesforce’s established AI expertise, generative AI models are poised to transform customer service operations, enhancing efficiency, fostering empathetic responses, and expediting case resolutions. Here’s a glimpse into how generative AI could reshape service operations: Automated Personalized Responses: Integrating generative AI with Einstein for Service and Customer 360 allows companies to automatically generate personalized responses, enabling agents to promptly communicate with customers. AI training across all case notes facilitates the creation of knowledge articles, significantly reducing the time to produce knowledge and enabling easier updates. Field Service Enhancements: Generative AI will benefit frontline service teams with automated reports, assist new employees and contractors in onboarding and ongoing learning, and empower customers to troubleshoot common issues with knowledge base articles. Super-powered Chatbots: Layering generative AI on Einstein capabilities automates the creation of intelligent, personalized chatbot responses, enhancing the understanding and anticipation of customer issues. This approach improves first-time resolution rates and allows organizations to drive continuous improvement through sentiment analysis and pattern identification.  Conversational bots that are powered by generative AI can power customer self-service and improve customer satisfaction — by ensuring case-specific tonality and context in real time. Auto-generate Knowledge Articles: Generative AI will draft knowledge articles based not only on case notes but also on Slack conversations, messaging history, and data across Customer 360, accelerating agent case resolution and increasing support cases in self-service experiences. Fast-track Case Swarming: Generative AI identifies past cases similar to ongoing complex issues, recommends experts within the organization to address the problem, and suggests resolutions and customer communications. This streamlines case swarming processes, making them more efficient and, in some cases, automating aspects of the process. Customer Service and Generative AI While generative AI presents tremendous opportunities, human oversight is essential due to the potential for biased or harmful outputs. Salesforce has published guidelines for trusted generative AI development, emphasizing ethical considerations. As we enter this new era of AI, guided by Salesforce’s commitment to ethical product development, organizations can leverage generative AI to boost productivity, accelerate case resolution, and enhance customer relationships with greater personalization and relevance. 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 Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust 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’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more

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March 8, 2024in Generative AI, Salesforce Service Cloud
Data Management and Data Maturity
07Mar

Data Management and Data Maturity

Data Management and Data Maturity: Generative AI Raises Concerns About Data Ethics and Equity Harnessing the capabilities of generative AI is contingent on having comprehensive, unified, and accurate data, as indicated by more than half of IT leaders. However, several obstacles hinder progress. A recent survey unveils that a majority of IT leaders lack a unified data strategy, impeding the seamless integration of generative AI into their existing technology stack. Beyond technical challenges, generative AI also brings to the forefront serious ethical considerations. Key findings from the survey reveal: AI Illuminates Data Management While generative AI garners attention, more established AI applications, such as predictive analytics and chatbots, have long been advantageous for organizations. Technical leaders leveraging AI report significantly faster decision-making and operations. The benefits extend beyond speed, with analytics and IT leaders highlighting more time to address strategic challenges rather than being immersed in mundane tasks. Customers also reap the rewards, with technical leaders noting substantial improvements in customer satisfaction due to AI. Given the pivotal role of quality data in AI outcomes, it is unsurprising that nearly nine out of ten analytics and IT leaders consider new developments in AI to prioritize data management. Realized Benefits of AI Adoption Analytics and IT leaders cite several top benefits realized from AI adoption: Data Maturity Signals AI Preparedness Data maturity emerges as a foundational element for successful AI adoption, with high-maturity organizations boasting superior infrastructure, strategy, and alignment compared to their low-data-maturity counterparts. The disparities are particularly evident in terms of data quality, with high-maturity respondents being twice as likely as low-maturity respondents to possess the high-quality data required for effective AI utilization. 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

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March 7, 2024in Generative AI, Salesforce Data Cloud, Salesforce Einstein
AI and the Role of Healthcare CIOs
07Mar

AI and the Role of Healthcare CIOs

Healthcare leaders see significant potential in data analytics and AI technology to transform the industry over the next five years, according to a new market research report from Arcadia and The Harris Poll. AI and the Role of Healthcare CIOs The report, titled “The Healthcare CIO’s Role in the Age of AI,” examines AI’s impact on the healthcare sector and how decision-makers are preparing to leverage the technology. Notably, 96% of healthcare leaders surveyed believe that adopting AI effectively will provide a competitive edge both now and in the future. While only a third see AI as essential today, 73% expect it to become critical within five years. How Health Systems Are Using AI Around 63% of respondents revealed that their organizations use AI to analyze large patient data sets to identify trends and guide population health management efforts. Another 58% are using AI to analyze individual patient data to identify opportunities for improving health outcomes. Close to half of the leaders indicated that AI is being used to optimize electronic health records (EHR) management and analysis. These trends align with the findings of the recent “Top of Mind for Top Health Systems” survey, conducted by the University of Pittsburgh Medical Center’s Center for Connected Medicine (CCM) in collaboration with KLAS, which identified AI as the most exciting emerging technology in healthcare with transformative potential for both administration and care delivery. The excitement surrounding healthcare AI largely stems from its ability to break down data silos and tap into the wealth of clinical data that healthcare organizations already collect. “Healthcare leaders are thoughtfully preparing to harness the full value of AI in care delivery reform,” said Aneesh Chopra, Arcadia’s chief strategy officer. “As safe, secure data sharing scales, technology leaders prioritize data platforms that organize fragmented patient records into clinically relevant insights at every stage of the patient journey.” A quest for a 360 degree patient view abounds. Using AI to Support Strategic Priorities The Arcadia survey emphasized the importance of using analytics to improve patient care, with 83% of leaders believing that harnessing data will help healthcare organizations remain competitive and resilient while overcoming digital transformation and financial challenges. Eighty-four percent of respondents cited technology as a current priority, with 44% focusing on an enterprise-wide approach to data analytics, 41% prioritizing AI-driven decision-making, and 32% working to simplify technical ecosystems. These efforts are viewed as crucial to advancing other strategic goals, with 40% of leaders prioritizing the patient experience, 35% aiming to improve outcomes, and 29% focusing on patient engagement. Although healthcare leaders view AI adoption positively for strategic advancements, hurdles remain. While 96% of respondents are confident in adopting AI, many feel pressured to move quickly. When asked about the sources of this pressure, 82% cited data and analytics teams, 78% pointed to IT and tech teams, and 73% mentioned executives. However, successfully implementing AI requires talent and resources that some organizations lack. About 40% of leaders identified a lack of talent as a significant barrier to AI adoption, signaling the need for IT and analytics teams to acquire new skill sets. Seventy-one percent of IT leaders reported a growing demand for data-driven decision-making skills, while two-thirds pointed to a rising need for expertise in data analysis, machine learning, and systems integration. Additionally, nearly 60% mentioned the need for roles that focus on training and support for healthcare staff. The Evolving Role of CIOs CIOs and other healthcare leaders are seeing their roles evolve as AI and data become more integrated into healthcare operations. Eighty-seven percent of respondents see themselves as strategy influencers, actively involved in setting and executing AI strategies, while only 13% view themselves as purely focused on implementation. Despite these evolving roles, many CIOs feel constrained by daily operations. Fifty-eight percent reported being primarily focused on tactical execution rather than developing long-term AI strategies, although they believe they should spend 75% of their time on strategic planning to be most effective. Part of these strategies will likely focus on improving communication and workforce readiness. Three out of four leaders cited a lack of effective communication between IT teams and clinical staff as a barrier to leveraging new technologies, and two out of five noted that clinical staff are not fully equipped to make the best use of data analytics. “CIOs and their teams are setting the stage for an AI-powered revolution in patient care and healthcare operations,” said Michael Meucci, Arcadia’s president and CEO. “Our findings highlight a strong consensus that a solid data foundation is necessary to realize the future of AI in healthcare. At the same time, the human workforce, with evolving talent and skills, will shape the real-world impact of AI in healthcare.“ Content updated August 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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March 7, 2024in Generative AI, Salesforce Development Services, Salesforce Health and Life Sciences Solutions
demand generation web use cases for personalization
03Mar

Demand Generation Web Use Cases for Personalization

Utilize effective personalization techniques adopted by businesses in online campaigns to stimulate demand generation. The term “demand generation” has somewhat faded from the marketing lexicon due to the emphasis on analytics, AI, and metrics for lead conversion. However, where does personalization fit into the broader scope of demand generation? Demand generation web use cases for personalization. Personalization plays a pivotal role in various aspects of demand generation: In lead nurturing, personalization is equally vital: Moreover, personalization is instrumental in lead acquisition efforts by delivering relevant experiences to all of your prospects. To effectively implement personalization, real-time insights into individual behaviors and interactions are essential. A comprehensive personalization solution should unify data from various channels and systems, enabling seamless cross-channel personalization. This includes “stitching” together anonymous and known user profiles, integrating data with complementary systems like CRMs and marketing platforms, and facilitating real-time omni-channel personalization. The key to successful personalization lies in understanding and addressing each individual’s unique needs and preferences. By adopting a customer-centric approach and setting clear objectives aligned with business goals, organizations can leverage personalization to enhance customer experiences, boost conversion rates, and drive measurable business growth. To execute a successful personalization strategy, organizations must: By following these steps and continuously optimizing personalization efforts, organizations can build stronger customer relationships, drive business growth, and maximize marketing ROI. Website personalization serves as the starting point for many companies embarking on their personalization journey. This entails ensuring that returning visitors encounter pages tailored to their previous experiences or recent purchases. It can also involve presenting new customers with product recommendations based on their current browsing session. The return on this initial investment can be substantial, with many companies witnessing a significant increase in conversion rates, sometimes by as much as 50% or more. For instance, a site converting 2% of visitors might see that figure rise to 3%, a dream scenario for digital marketers. Moreover, this boost in conversion rates can have far-reaching effects across marketing programs, leading to a reduction in overall customer acquisition costs. Tectonic now offers Personalization Implementation Solutions. The next stage in personalization maturity involves integrating a customer’s web and email experiences. This seamless connection between two major channels for customer engagement brings organizations closer to achieving an omni-channel personalization experience. Timely and relevant follow-up messages after a customer’s website visit or purchase can deepen relationships and enhance lifetime value without significant additional marketing expenditure. Finally, the ultimate goal is to extend personalization across all channels, ensuring consistent and tailored experiences wherever customers interact with your brand. However, achieving this can be challenging due to fragmented customer data across multiple channels, teams, and systems. An effective personalization solution should consolidate and synthesize this cross-channel information by maintaining unified customer profiles and enabling real-time omni-channel personalization. Testing is a crucial aspect of successful personalization efforts, allowing organizations to optimize campaigns and maximize engagement, conversions, and revenue. A robust personalization solution should facilitate A/B testing, measuring lift over control, evaluating impacts against specific goals, and filtering results by segment. Effective website personalization lays the foundation for broader personalization efforts across channels. By seamlessly integrating web and email experiences and extending personalization to all touchpoints, organizations can deliver tailored experiences that drive engagement, loyalty, and ultimately, business growth. By Tectonic’s Salesforce Marketing Platform 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

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March 3, 2024in Data, Einstein Insights, Generative AI, Salesforce, Salesforce Einstein, Salesforce Marketing Cloud, Salesforce Optimization, Salesforce Sales Cloud
AI Training Options
29Feb

AI Training Options

As AI adoption accelerates, AI certifications and courses have proliferated, providing deeper knowledge of this rapidly evolving technology. AI Training Options. Numerous AI certifications cover the basics, so we’ve narrowed the field to 10 of the most diverse and comprehensive programs. AI Training Options Artificial intelligence is poised to become the key technology that drives business transformation and gives companies a competitive edge. According to a recent forecast by the International Data Corporation, global spending on AI—including AI-enabled applications, infrastructure, and related services—will more than double to $632 billion by 2028, growing at a compound annual rate of 29% between 2024 and 2028. AI helps businesses boost productivity by automating processes such as robotics and autonomous vehicles, while also supporting existing workforces with technologies like assisted and augmented intelligence. Companies are integrating AI across various sectors, including finance, healthcare, retail, smart home devices, fraud detection, and security surveillance. Why AI certifications are important: 10 of the best AI certifications and courses: Each certification offers unique benefits, whether you’re a beginner or an experienced professional aiming to stay ahead in AI-driven industries. Content updated September 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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February 29, 2024in Artificial Intelligence, Data, Generative AI, Google, Technology
Personalization With Customized AI-Driven Journeys
28Feb

Personalization With Customized AI-Driven Journeys

AI-Enabled Triggers for Guiding Customer Journeys – Personalization With Customized AI-Driven Journeys Initiate timely and relevant customer experiences that seamlessly lead individuals through their purchasing journey. Employ AI-powered decision-making to identify the most suitable next steps for customers, offering personalized suggestions based on real-time behavior, historical data, and business-specific datasets such as pricing and inventory. Deliver predefined experiences, such as browsing or cart abandonment journeys, while utilizing real-time interactions to determine the optimal content, channel, or offer for each customer. Efficiently extract insights by harnessing behavioral data and advanced analytics to visualize cross-channel customer journeys for both individuals and segments, identifying and resolving key friction points. Elevate customer acquisition, loyalty, and lifetime value by crafting personalized, omni-channel journeys that align with both customer desires and business objectives. Enable trigger-based customer journeys that facilitate immediate responses to customer actions, whether in the physical realm, such as entering a store and connecting to Wi-Fi, or in the virtual space, like visiting a shopping website. The Role of AI in Elevating the Customer Journey AI significantly contributes to heightened customer satisfaction, ultimately leading to improved retention. Address customer pain points in their preferred language and provide solutions tailored to their needs based on purchasing history and previous interactions with customer service. AI’s Influence Across Customer Journey Stages At each stage of the customer journey, AI transforms experiences by delivering personalized interactions from awareness to post-purchase. This transformation is made possible through automation, predictive analytics, and intelligent virtual agents. Transformative Impact of Generative AI on Customer Journeys Generative AI, exemplified by advanced language models like GPT-4, has the potential to revolutionize customer journeys. These models automate communication and content creation, dynamically adjusting tone and style to match customer preferences. For instance, Grammarly’s tone detector adapts communication based on the recipient’s profile and interaction history. Continuous Iteration and AI in Customer Journey Mapping In the era of digitization, AI-driven personalization surpasses traditional customer journey mapping based on a few personas. Organizations must harness AI and machine learning to create personalized journeys that enhance user experiences. The iterative improvement process involves collecting comprehensive data, utilizing AI for analysis and insights, implementing changes, and evaluating results through key performance indicators. Netflix: An AI Success Story Netflix serves as a prime example of AI success, continuously analyzing user behavior and preferences to refine content recommendation algorithms. This approach enhances personalization, leading to increased customer engagement and satisfaction. Integrating Generative AI into Existing Systems To fully capitalize on generative AI, integration into existing systems and processes is crucial. This may entail developing APIs to connect AI tools with customer relationship management (CRM) systems and content management systems. Testing and Continuous Enhancement Implementing AI-driven personalization necessitates a robust testing and evaluation process. Clearly defined key performance indicators and analytics capabilities are essential for measuring effectiveness and making continuous improvements. 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

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February 28, 2024in AI Tools, Data, Generative AI, Salesforce, Salesforce Marketing Cloud, Salesforce Personalization
How Good is Our Data
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

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February 22, 2024in Generative AI, Salesforce Einstein

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