Generative AI Archives - gettectonic.com - Page 20
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

Read More
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 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 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

Read More
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

Read More
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 Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
March 3, 2024in 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

Read More
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. Like1 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 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 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

Read More
February 28, 2024in Generative AI, 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 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 Consent Management Analytics and Data Quality Understanding Data Analytics Consent and Consent Management Why Consent Management is Crucial Consent Management Analytics and Data Quality. With laws Read more

Read More
February 22, 2024in Generative AI, Salesforce Einstein
Exploring Google Vertex AI
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

Read More
February 21, 2024in Data, Generative AI, Google, Technology
Conversational Commerce
20Feb

Conversational Commerce

“Hey Siri, find the top-rated red saddle pads.” This simple command exemplifies how conversational commerce is revolutionizing the digital shopping experience. While Siri and Alexa are training us to talk to our technology, traditional chatbots teach us to ask our technology in natural language to do something. Now, customers can utilize chatbots, messaging apps, and voice assistants to explore products and complete purchases online. This experiential shopping shift enables businesses to engage with consumers in a natural manner, seamlessly integrating into their everyday routines. With conversational AI, shopping feels akin to conversing with a friend. Thanks to advancements in generative AI, the process is becoming increasingly personalized, intuitive, and hassle-free. Here’s an overview of conversational commerce: What is conversational commerce? Conversational shopping tools involve enhancing sales through direct communication with customers. It encompasses automated conversation flows as well as interactions between sales and service representatives and customers via text or social media messaging. Ultimately, conversational commerce aims to establish meaningful, personalized connections with customers, combining the convenience of digital communication with the warmth of human language to drive sales and foster loyalty. Different Types of Conversational Commerce: The Role of AI in Conversational Commerce: AI plays a primary role in evolving conversational commerce by understanding consumer intent and guiding them through the purchasing process. Natural language processing (NLP) enables chatbots to comprehend inquiries and provide relevant responses, while machine learning analyzes customer data to offer personalized recommendations and streamline the purchase journey. Conversational Commerce and Social Commerce: Conversational commerce intersects with social commerce, capitalizing on platforms like Instagram and TikTok to build authentic connections with customers and facilitate seamless transactions embedded in their social interactions. Benefits of Conversational Commerce: Common Pitfalls and Solutions: By leveraging conversational commerce effectively, businesses can create seamless, personalized interactions that drive sales and foster long-term customer relationships. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

Read More
February 20, 2024in Generative AI, Salesforce Development Services, Salesforce Sales Cloud
steps to embrace ai
19Feb

Steps to Embrace AI

The world is evolving rapidly, with AI playing a transformative role. Despite concerns about AI’s impact on jobs, it has the potential to empower and simplify our lives. Rather than replacing humans, AI can automate routine tasks, allowing individuals to focus on more creative and value-added work. The future lies in human-AI collaboration, requiring us to prepare for a shift in roles and responsibilities.

Read More
February 19, 2024in Generative AI, Salesforce Einstein
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 $2 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

Read More
February 11, 2024in Generative AI, Salesforce
Salesforce prompt builder
10Feb

Create Test and Refine Prompt Templates With Prompt Builder

Salesforce has introduced Prompt Builder, a revolutionary tool powered by generative AI, designed to enhance business tasks by seamlessly integrating prompts into workflows. This article delves into the core AI concepts underlying Prompt Builder, offering insights into creating, managing, testing, and refining prompt templates for optimal performance. Before digging into the intricacies of this new innovation, let’s first explore what generative AI means for administrators. Create Test and Refine Prompt Templates With Prompt Builder. Understanding Key Terms: Key Features of Prompt Builder: Utilizing Prompt Templates: Testing and Refining Prompt Templates: Deploying Prompts: Designing Effective Prompt Templates: Embracing Generative AI with Prompt Builder: As Prompt Builder prepares for its general availability in Spring ’24, businesses can anticipate a paradigm shift in how they harness AI to propel their operations forward. Whether seasoned Salesforce Admins or newcomers to AI integration, Prompt Builder offers a gateway to unlocking the myriad possibilities of generative AI within Salesforce. Create Test and Refine Prompt Templates With Prompt Builder. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
February 10, 2024in Generative AI, Salesforce, Salesforce Einstein
Generative AI Terms Do I Need to Understand
09Feb

What Generative AI Terms Do I Need to Understand to Participate in AI Conversations?

You don’t need to be a software engineer, a data scientist, or a geek to understand gen AI or speak with authority about it with technical people. But business leaders should be able to think about AI holistically. Including benefits and risks, where it fits into the company’s culture, and mission. As well as what type of governance and infrastructure it requires.  What Generative AI Terms Do I Need to Understand to participate in the conversation? Business leaders can’t help lead AI programs to success if they can’t engage with the tech teams.    We’ve put together a list of the most essential AI terms that will help everyone in your company — no matter their technical background – understand the power of generative AI. Each term is defined based on how it impacts both your customers and your team, a crucial element in understanding the power of AI.  Gen AI technologies (and adoption) are growing extraordinarily fast. As it informs more business decisions and transforms your relationships with customers, leaders at all levels must understand its potential, its use cases, and its risks. How do you do that? Start by asking the right questions about AI.   Salesforce’s most recent survey on generative AI use among the general population within the U.S., UK, Australia and India found the public is split between users and non-users. Within each country, the online populations surveyed reported the below usage (note: cultural bias may impact results): Like1 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 Sales Cloud Einstein Forecasting Salesforce, the global leader in CRM, recently unveiled the next generation of Sales Cloud Einstein, Sales Cloud Einstein Forecasting, incorporating Read more

Read More
February 9, 2024in Generative AI, Salesforce Einstein
Generative AI Glossary
27Jan

Key Questions to Ask About Generative AI Before Diving into the Gene Pool

As generative AI plays an increasingly significant role in shaping business decisions and reshaping customer relationships, leaders must grasp the potential.  This means use cases, and risks associated with AI. The good, the bad, and the ugly.  Questions to Ask About Generative AI gene pool. The journey begins with asking pertinent questions. Are you feeling overwhelmed by generative AI yet? The multitude of questions that businesses need to address regarding AI—covering technology, skills, privacy, data, and organizational requirements, among others—can be seemingly endless. Knowing where to start and identifying the most crucial AI-related questions before jumping into implementation can be challenging.  But it is totally worth the time. “Many organizations are venturing into AI for the first time. They are transitioning from predictive AI, machine learning, or deep learning to explore the next generation of AI for elevating productivity.” Marc Benioff, CEO of Salesforce While the demand and potential of AI are substantial, so are the associated risks. To assist in navigating this landscape, here’s a snapshot: Employee View: Exec Summary: Your Next Move: By Tectonic’s Marketing Consultant, Shannan Hearne 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 Sales Cloud Einstein Forecasting Salesforce, the global leader in CRM, recently unveiled the next generation of Sales Cloud Einstein, Sales Cloud Einstein Forecasting, incorporating Read more

Read More
January 27, 2024in Generative AI, Salesforce Einstein

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

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