, Author at gettectonic.com - Page 9
01Nov

Agentforce Campaigns

Revolutionizing Content Marketing with Agentforce: AI-Powered Marketing Agents Content creation and distribution have long been challenging for marketers. According to new research from the Content Marketing Institute, 54% of B2B marketers lack the resources to produce quality content at scale. A similar issue plagues the B2C sector, where marketers often struggle to make their efforts repeatable, consistent, or scalable due to the relentless demand for content. On top of this, they must manage resources effectively to deliver efficient, successful campaigns that engage customers and outshine competitors. What’s the solution to these challenges? Marketing agents powered by data and AI, which can create, manage, and optimize campaigns seamlessly. At this year’s Dreamforce, Salesforce unveiled Agentforce, a suite of tools to design and customize AI-powered agents across the Customer 360 platform. A key component of this launch is Agentforce Campaigns, a tool already generating buzz among customers eager to harness its potential. According to Salesforce’s 9th State of Marketing report, 71% of marketers plan to use generative and predictive AI within the next 18 months. In this insight, we’ll explore how marketing agents like those in Agentforce can transform your customer engagement strategies while boosting your team’s productivity and cohesion. What Are Marketing Agents? If you’re new to AI in marketing, it’s important to understand the concept of marketing agents and how they can reshape your approach to campaign execution. Marketing agents are part of a broader family of AI virtual assistants designed to collaborate with humans. These tools leverage data to build and execute plans, analyze tasks, and make decisions. In marketing, they handle activities such as content creation, campaign optimization, and results analysis. Salesforce has developed AI agents to serve as partners within the customer experience. They take on time-consuming, repetitive tasks, freeing marketers to focus on high-value activities. For example, instead of spending hours sourcing and analyzing data, marketers can act on insights immediately. Similarly, rather than crafting endless variations of content, they can devote time to strategic personalization and targeting. The real shift lies in changing your mindset from, “How can these agents help me improve efficiency?” to, “How can these agents help me radically enhance the customer experience?” How Agentforce Campaigns Simplify Marketing Let’s explore some of the groundbreaking features of Agentforce Campaigns and how they streamline campaign creation, execution, and optimization. 1. Intelligent Recommendations That Lead to Action Salesforce’s AI engine, Einstein, already tracks your data and goals, offering contextual recommendations. Agentforce Campaigns elevates this capability by turning static suggestions into actionable steps. For example, it might recommend adjusting your audience, refining an existing campaign, or launching a new one you hadn’t considered. 2. Instant Campaign Briefs Agentforce Campaigns enables you to generate campaign briefs in seconds. By using simple language prompts, you can create a comprehensive brief aligned with your organization’s goals and marketing guidelines. The brief is embedded in Salesforce, making it easy to refine and share with stakeholders for approval. 3. Contextual Content Creation Once your brief is approved, marketing agents can generate content tailored to your brand. From subject lines to body copy and calls to action, Agentforce Campaigns creates branded emails and landing pages within pre-configured templates. Marketers can refine this content using natural language prompts to ensure it aligns with their campaign strategy and tone. 4. Data-Driven Audience Segmentation Agentforce Campaigns simplifies audience segmentation by translating natural language prompts into segment attributes. You don’t need to be a data scientist or SQL expert to create precise target audiences. 5. Personalized Journey Activation Marketing agents can automatically build multi-channel, personalized journey flows based on your campaign brief. Using natural language prompts, you can configure and activate draft journeys with ease. 6. Effortless Content Variations Agentforce Campaigns allows marketers to generate multiple content variations in seconds. This capability enables personalized messaging for different audience segments, such as high-value customers, new prospects, or long-time brand advocates. 7. Expanding Audience Segmentation With AI handling segmentation, marketers can explore nuanced audiences that were previously inaccessible due to limited resources. For instance, you can create churn segments based on engagement scores, location, or purchase history using simple prompts. 8. Building a Culture of Testing and Learning Time constraints often limit testing in marketing campaigns. Agentforce Campaigns automates journey flows, making it easier to embed testing and continuous learning into every campaign. Reimagining Marketing with AI Agentforce Campaigns isn’t just about efficiency—it’s about rethinking how marketing can deliver exceptional customer experiences. By leveraging AI-powered agents, marketers can overcome resource constraints, enhance personalization, and unlock new opportunities for growth. Now is the time to embrace this transformation. With Agentforce, you can move beyond “business as usual” and start building campaigns that resonate with your audience like never before. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

Read More
November 1, 2024in Agentforce Platform, Data, Salesforce
Sales Incentives That Work
31Oct

Sales Incentives That Work

Sales Incentives That Actually Work Spooktacular Sales incentives to kick off your Halloween. Sales Incentives That Work are an essential tool to encourage and reward desired behaviors within a sales team. They serve as a motivational driver, helping teams achieve their goals while reinforcing the company’s objectives. Incentivizing a team goes beyond merely showing up for work—it involves sparking enthusiasm and a genuine drive to exceed expectations. With the right incentive program, companies can energize their teams, ensuring they come to work motivated and ready to achieve results. Below is a guide on different types of sales incentives, their impact on performance, and best practices for creating an effective incentive program. What Are Sales Incentives? Sales incentives are rewards offered to sales representatives in addition to their base pay for exceptional performance, typically when they meet or exceed sales targets. While monetary rewards such as bonuses are common, sales incentives can take many forms, all aimed at motivating the sales force toward specific goals. Types of Sales Incentives There are five main categories of sales incentives, each tailored to motivate different roles and sales activities: How Sales Incentives Motivate a Team Sales incentives work by reinforcing the behaviors a company wants its team to prioritize. For highly competitive reps, the prospect of a reward adds an extra layer of motivation. For others who may not be as driven by competition, incentives provide tangible goals to strive toward. Moreover, well-structured incentive programs can enhance job satisfaction, decrease turnover, and ensure top performers stay motivated. 10 Effective Sales Incentives While monetary rewards are often the most straightforward incentive, incorporating a mix of creative rewards can enhance a company’s incentive program. Some ideas include: Best Practices for Implementing Sales Incentives A well-designed sales incentive program ensures both clarity and motivation. Some best practices for implementation include: Measuring the Impact of Sales Incentives To gauge the success of a sales incentive program, companies should track key performance indicators (KPIs) like overall sales, new and returning customer numbers, program costs versus ROI, employee turnover, and employee satisfaction. Monitoring these metrics ensures that the program aligns with both sales goals and employee satisfaction. Tectonic’s Final Thoughts Sales incentives are an effective way to drive performance and boost morale. By designing a simple, clear, and motivating incentive program, companies can align their sales goals with individual motivation, ensuring both business success and employee satisfaction. If you need assistance utilizing sales incentives and your Salesforce platform, contact Tectonic today. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

Read More
October 31, 2024in Data, Salesforce, Salesforce Sales Cloud
Salesforce Maps Winter 25
28Oct

Salesforce Maps Winter 25

The Salesforce Maps Winter 25 release will be available in production environments between October 29 – 31. Auto-Enablement of the new Maps experience in October To enhance your experience in Salesforce Maps on desktop, the new features currently available in all environments will be auto-enabled in the Winter ’25 release. The Enhanced User Experience setting in the admin configuration settings will remain and can be manually disabled until the Spring ‘25 release. Get Release Ready-Salesforce Maps Winter 25 To ensure a smooth transition, please take the following actions prior to the production release. What This Change Brings See Spring ’25 Updates Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

Read More
October 28, 2024in Data
AI FOMO
26Oct

AI FOMO

Enterprise interest in artificial intelligence has surged in the past two years, with boardroom discussions centered on how to capitalize on AI advancements before competitors do. Generative AI has been a particular focus for executives since the launch of ChatGPT in November 2022, followed by other major product releases like Amazon’s Bedrock, Google’s Gemini, Meta’s Llama, and a host of SaaS tools incorporating the technology. However, the initial rush driven by fear of missing out (FOMO) is beginning to fade. Business and tech leaders are now shifting their attention from experimentation to more practical concerns: How can AI generate revenue? This question will grow in importance as pilot AI projects move into production, raising expectations for financial returns. Using AI to Increase Revenue AI’s potential to drive revenue will be a critical factor in determining how quickly organizations adopt the technology and how willing they are to invest further. Here are 10 ways businesses can harness AI to boost revenue: 1. Boost Sales AI-powered virtual assistants and chatbots can help increase sales. For example, Ikea’s generative AI tool assists customers in designing their living spaces while shopping for furniture. Similarly, jewelry insurance company BriteCo launched a GenAI chatbot that reduced chat abandonment rates, leading to more successful customer interactions and potentially higher sales. A TechTarget survey revealed that AI-powered customer-facing tools like chatbots are among the top investments for IT leaders. 2. Reduce Customer Churn AI helps businesses retain clients, reducing revenue loss and improving customer lifetime value. By analyzing historical data, AI can profile customer attributes and identify accounts at risk of leaving. AI can then assist in personalizing customer experiences, decreasing churn and fostering loyalty. 3. Enhance Recommendation Engines AI algorithms can analyze customer data to offer personalized product recommendations. This drives cross-selling and upselling opportunities, boosting revenue. For instance, Meta’s AI-powered recommendation engine has increased user engagement across its platforms, attracting more advertisers. 4. Accelerate Marketing Strategies While marketing doesn’t directly generate revenue, it fuels the sales pipeline. Generative AI can quickly produce personalized content, such as newsletters and ads, tailored to customer interests. Gartner predicts that by 2025, 30% of outbound marketing messages will be AI-generated, up from less than 2% in 2022. 5. Detect Fraud AI is instrumental in detecting fraudulent activities, helping businesses preserve revenue. Financial firms like Capital One use machine learning to detect anomalies and prevent credit card fraud, while e-commerce companies leverage AI to flag fraudulent orders. 6. Reinvent Business Processes AI can transform entire business processes, unlocking new revenue streams. For example, Accenture’s 2024 report highlighted an insurance company that expects a 10% revenue boost after retooling its underwriting workflow with AI. In healthcare, AI could streamline revenue cycle management, speeding up reimbursement processes. 7. Develop New Products and Services AI accelerates product development, particularly in industries like pharmaceuticals, where it assists in drug discovery. AI tools also speed up the delivery of digital products, as seen with companies like Ally Financial and ServiceNow, which have reduced software development times by 20% or more. 8. Provide Predictive Maintenance AI-driven predictive maintenance helps prevent costly equipment downtime in industries like manufacturing and fleet management. By identifying equipment on the brink of failure, AI allows companies to schedule repairs and avoid revenue loss from operational disruptions. 9. Improve Forecasting AI’s predictive capabilities enhance planning and forecasting. By analyzing historical and real-time data, AI can predict product demand and customer behavior, enabling businesses to optimize inventory levels and ensure product availability for ready-to-buy customers. 10. Optimize Pricing AI can dynamically adjust prices based on factors like demand shifts and competitor pricing. Reinforcement learning algorithms allow businesses to optimize pricing in real time, ensuring they maximize revenue even as market conditions change. Keeping ROI in Focus While AI offers numerous ways to generate new revenue streams, it also introduces costs in development, infrastructure, and operations—some of which may not be immediately apparent. For instance, research from McKinsey & Company shows that GenAI models account for only 15% of a project’s total cost, with additional expenses related to change management and data preparation often overlooked. To make the most of AI, organizations should prioritize use cases with a clear return on investment (ROI) and postpone those that don’t justify the expense. A focus on ROI ensures that AI deployments align with business goals and contribute to sustainable revenue growth. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

Read More
October 26, 2024in Generative AI
$15 Million to AI Training for U.S. Government Workforce
24Oct

$15 Million to AI Training for U.S. Government Workforce

Google.org Commits $15 Million to AI Training for U.S. Government Workforce Google.org has announced $15 million in grants to support the development of AI skills in the U.S. government workforce, aiming to promote responsible AI use across federal, state, and local levels. These grants, part of Google.org’s broader $75 million AI Opportunity Fund, include $10 million to the Partnership for Public Service and $5 million to InnovateUS. The $10 million grant to the Partnership for Public Service will fund the establishment of the Center for Federal AI, a new hub focused on building AI expertise within the federal government. Set to open in spring 2025, the center will provide a federal AI leadership program, internships, and other initiatives designed to cultivate AI talent in the public sector. InnovateUS will use the $5 million grant to expand AI education for state and local government employees, aiming to train 100,000 workers through specialized courses, workshops, and coaching sessions. “AI is today’s electricity—a transformative technology fundamental to the public sector and society,” said Max Stier, president and CEO of the Partnership for Public Service. “Google.org’s generous support allows us to expand our programming and launch the new Center for Federal AI, empowering agencies to harness AI to better serve the public.” These grants clearly underscore Google.org’s commitment to equipping government agencies with the tools and talent necessary to navigate the evolving AI landscape responsibly. With these tools in place, Tectonic looks forward to assist you in becoming an ai-driven public sector service. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

Read More
October 24, 2024in Google, Technology
Scope of Generative AI
24Oct

Scope of Generative AI

Generative AI has far more to offer your site than simply mimicking a conversational ChatGPT-like experience or providing features like generating cover letters on resume sites. Let’s explore how you can integrate Generative AI with your product in diverse and innovative ways! There are three key perspectives to consider when integrating Generative AI with your features: system scope, spatial relationship, and functional relationship. Each perspective offers a different lens for exploring integration pathways and can spark valuable conversations about melding AI with your product ecosystem. These categories aren’t mutually exclusive; instead, they overlap and provide flexible ways of envisioning AI’s role. 1. System Scope — The Reach of Generative AI in Your System System scope refers to the breadth of integration within your system. By viewing integration from this angle, you can assess the role AI plays in managing your platform’s overall functionality. While these categories may overlap, they are useful in facilitating strategic conversations. 2. Spatial Relationships — Where AI Interacts with Features Spatial relationships describe where AI features sit in relation to your platform’s functionality: 3. Functional Relationships — How AI Interacts with Features Functional relationships determine how AI and platform features work together. This includes how users engage with AI and how AI content updates based on feature interactions: Scope of Generative AI By considering these different perspectives—system scope, spatial, and functional—you can drive more meaningful conversations about how Generative AI can best enhance your product’s capabilities. Each approach offers unique value, and careful thought can help teams choose the integration path that aligns with their needs and goals. Scope of Generative AI conversations with Tectonic can assist in planning the best ROI approach to AI. Contact us today. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

Read More
October 24, 2024in Data, Generative AI, Google
salesforce ai pitchfield
21Oct

Salesforce AI Pitchfield

AI Pitchfield is more than a showcase of entrepreneurial talent—it’s a launchpad for the next generation of AI pioneers. By fostering connections and providing critical investment opportunities, Salesforce and its partners are driving the evolution of AI across India and Southeast Asia. This initiative reflects Salesforce’s commitment to advancing technology, empowering startups, and shaping a future where AI continues to transform industries and unlock untapped potential.

Read More
October 21, 2024in Artificial Intelligence, Salesforce, Technology
LLMs and AI
19Oct

LLMs and AI

Large Language Models (LLMs): Revolutionizing AI and Custom Solutions Large Language Models (LLMs) are transforming artificial intelligence by enabling machines to generate and comprehend human-like text, making them indispensable across numerous industries. The global LLM market is experiencing explosive growth, projected to rise from $1.59 billion in 2023 to $259.8 billion by 2030. This surge is driven by the increasing demand for automated content creation, advances in AI technology, and the need for improved human-machine communication. Several factors are propelling this growth, including advancements in AI and Natural Language Processing (NLP), large datasets, and the rising importance of seamless human-machine interaction. Additionally, private LLMs are gaining traction as businesses seek more control over their data and customization. These private models provide tailored solutions, reduce dependency on third-party providers, and enhance data privacy. This guide will walk you through building your own private LLM, offering valuable insights for both newcomers and seasoned professionals. What are Large Language Models? Large Language Models (LLMs) are advanced AI systems that generate human-like text by processing vast amounts of data using sophisticated neural networks, such as transformers. These models excel in tasks such as content creation, language translation, question answering, and conversation, making them valuable across industries, from customer service to data analysis. LLMs are generally classified into three types: LLMs learn language rules by analyzing vast text datasets, similar to how reading numerous books helps someone understand a language. Once trained, these models can generate content, answer questions, and engage in meaningful conversations. For example, an LLM can write a story about a space mission based on knowledge gained from reading space adventure stories, or it can explain photosynthesis using information drawn from biology texts. Building a Private LLM Data Curation for LLMs Recent LLMs, such as Llama 3 and GPT-4, are trained on massive datasets—Llama 3 on 15 trillion tokens and GPT-4 on 6.5 trillion tokens. These datasets are drawn from diverse sources, including social media (140 trillion tokens), academic texts, and private data, with sizes ranging from hundreds of terabytes to multiple petabytes. This breadth of training enables LLMs to develop a deep understanding of language, covering diverse patterns, vocabularies, and contexts. Common data sources for LLMs include: Data Preprocessing After data collection, the data must be cleaned and structured. Key steps include: LLM Training Loop Key training stages include: Evaluating Your LLM After training, it is crucial to assess the LLM’s performance using industry-standard benchmarks: When fine-tuning LLMs for specific applications, tailor your evaluation metrics to the task. For instance, in healthcare, matching disease descriptions with appropriate codes may be a top priority. Conclusion Building a private LLM provides unmatched customization, enhanced data privacy, and optimized performance. From data curation to model evaluation, this guide has outlined the essential steps to create an LLM tailored to your specific needs. Whether you’re just starting or seeking to refine your skills, building a private LLM can empower your organization with state-of-the-art AI capabilities. For expert guidance or to kickstart your LLM journey, feel free to contact us for a free consultation. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

Read More
October 19, 2024in Artificial Intelligence, Data, Google, Salesforce, Technology
Deploying Salesforce Einstein Copilot
17Oct

Deploying Salesforce Einstein Copilot

Best Practices for Safely Deploying Salesforce Einstein Copilot When deploying Salesforce Einstein Copilot, following best practices ensures a secure, efficient, and effective integration of AI into your workflows. Here are the key steps to safely deploy Einstein Copilot: By adhering to these best practices, you can ensure a smooth, secure, and successful deployment of Salesforce Einstein Copilot, enhancing your team’s productivity while maintaining data integrity and security. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

Read More
October 17, 2024in Data, Salesforce, Salesforce Einstein
Benioff Excited About AI
14Oct

Benioff Excited About AI

Salesforce CEO Marc Benioff recently critiqued Microsoft for overhyping the capabilities of its Copilot AI tool, arguing that the tech giant has done a “tremendous disservice” to the industry. In a Rapid Response interview with Bob Safian, Benioff emphasized that Salesforce’s Agentforce is “what AI was meant to be.” More excited than ever, he sees Agentforce as a technology poised to transform industries in ways comparable to past cloud, mobile, and social revolutions. Benioff Excited About AI. Reflecting on Dreamforce 2024Benioff called this year’s Dreamforce the most significant yet. With 45,000 attendees and millions joining online, Agentforce took center stage, allowing users to build their own AI agents firsthand. This hands-on experience was vital, he said, to clear up misconceptions caused by overpromised AI products. Salesforce already handles trillions of AI transactions through its Einstein platform, but Benioff believes Agentforce represents a groundbreaking shift in enterprise AI. Agentforce vs. Copilot: A Clear DifferenceBenioff drew a sharp contrast between Agentforce and Microsoft’s Copilot, comparing the latter to the infamous Microsoft Clippy. According to Benioff, Copilot often fails to deliver meaningful results, creating confusion and dissatisfaction among customers. In contrast, Agentforce is set to deliver powerful outcomes by connecting customers, raising revenues, and augmenting employees. He anticipates that within a year, Salesforce will operate over a billion AI agents worldwide. Benioff Excited About AI. Benioff Excited About AI Agentforce’s Real-World ImpactSharing a story from the healthcare sector, Benioff illustrated how Agentforce has resolved over 90% of patient inquiries and scheduling needs for one large provider, enabling rapid and meaningful interactions. He foresees similar applications across media, finance, and travel, as Agentforce helps industries implement AI-driven agents with high success rates. Scheduled to go live on October 25, Agentforce is expected to be adopted by hundreds of thousands of companies. MIT IDE Annual Conference Insights: AI’s Potential and ChallengesWhile businesses explore AI’s possibilities, researchers at MIT’s Initiative on the Digital Economy (IDE) are investigating the complexities and ethical considerations of AI. At the 2024 MIT IDE Annual Conference, findings on AI’s influence on various domains were presented, with highlights including: These MIT findings highlight both the immense promise and the challenges AI presents, as companies like Salesforce aim to harness AI’s true potential while navigating ethical and practical concerns. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

Read More
October 14, 2024in Agentforce Platform, Einstein 1 Platform, Generative AI, Salesforce
Salesforce Success Story
14Oct

Case Study: Children’s Hospital Use Cases

In need of help to implement requisite configuration updates to establish a usable data model for data segmentation that supports best practices utilization of Marketing Cloud features including Contact Builder, Email Studio and Journey Builder.

Read More
October 14, 2024in Data, Google, Life Sciences Cloud, Salesforce, Salesforce Development Services, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud, Salesforce Implementation Services, Salesforce Marketing Cloud, Salesforce Shield, Salesforce Success Stories
Gen AI to Predict and Automate Discharge
11Oct

Gen AI to Predict and Automate Discharge

While electronic health records (EHRs) have improved data exchange for care coordination, they have also increased the clinical documentation burden on healthcare providers. Research from 2023 suggests that clinicians may now spend more time on EHRs than on direct patient care. On average, providers spend over 36 minutes on EHR tasks for every 30-minute patient visit. Generative AI, however, holds the potential to transform this. As defined by the Government Accountability Office, generative AI (GenAI) is a technology that can create content—such as text, images, audio, or video—based on user prompts. With the rise of chatbot interfaces like Chat-GPT, health IT vendors and healthcare systems are piloting GenAI tools to streamline clinical documentation. While the technology shows promise in reducing the documentation burden and mitigating clinician burnout, several challenges still hinder widespread adoption. Ambient Clinical Intelligence Ambient clinical intelligence leverages smartphone microphones and GenAI to transcribe patient encounters in real time, producing draft clinical documentation for providers to review within seconds. A 2024 study examined the use of ambient AI scribes by 10,000 physicians and staff at The Permanente Medical Group. The results were promising—providers reported better patient conversations and less after-hours EHR documentation. However, accuracy is critical for patient safety. A 2023 study found that ambient AI tools struggle with non-lexical conversational sounds (NLCSes)—like “mm-hm” and “uh-uh”—which patients and providers use to convey information. For instance, a patient might say “Mm-hm” to confirm they have no allergies to antibiotics. The study found that while the AI tools had a word error rate of 12% for all words, the error rate for NLCSes conveying clinically relevant information was as high as 98.7%. These inaccuracies could lead to patient safety risks, highlighting the importance of provider review. Patient Communication Patient portal messaging has surged since the COVID-19 pandemic, with a 2023 report showing a 157% increase in messages compared to pre-pandemic levels. To manage inbox overload, healthcare systems are exploring generative AI for drafting responses to patient messages. Clinicians review and edit these drafts before sending them to patients. A 2024 study found that primary care physicians rated AI-generated responses higher in communication style and empathy than those written by providers. However, the AI-generated responses were often longer and more complex, posing challenges for patients with lower health or English literacy. There are also potential risks to clinical decision-making. A 2024 simulation study revealed that the content of replies to patient messages changed when physicians used AI assistance, introducing an automation bias that could impact patient outcomes. Although most AI-generated drafts posed minimal safety risks, a small portion, if left unedited, could result in severe harm or death. Although GenAI may reduce the cognitive load of writing replies, it might not significantly decrease the overall time spent on patient communications. A recent study showed that while providers felt less emotional exhaustion when using AI to draft messages, the time spent on replying, reading, and writing messages remained unchanged from pre-pilot levels. Discharge Summaries Generative AI has also been shown to improve the readability of patient discharge summaries. A study published in JAMA Network Open demonstrated that GenAI could lower the reading level of discharge notes from an eleventh-grade to a sixth-grade level, which is more appropriate for diverse health literacy levels. However, accuracy is still a concern. Physician reviews of these AI-generated summaries found that while some were complete, others contained omissions and inaccuracies that raised safety concerns. Balancing AI’s Benefits with Oversight While generative AI shows promise in alleviating the documentation burden and improving patient communication, challenges remain. Issues such as accurately capturing non-verbal cues and ensuring document accuracy underscore the need for careful provider oversight. As AI technologies continue to evolve, ensuring that the benefits are balanced with provider review will be crucial for safe and effective healthcare implementation. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

Read More
October 11, 2024in Generative AI, Salesforce Health and Life Sciences Solutions, Salesforce Managed Services, Salesforce Optimization
Managing Salesforce Roles and Profiles
10Oct

Managing Salesforce Roles and Profiles

How to Set Up Salesforce Roles Salesforce is a powerful platform used by many organizations to streamline operations across departments, from sales and marketing to customer support. With so many users working within the platform, it’s essential to manage access to data securely. Salesforce achieves this through its system of roles and profiles, which define who can see and do what in the system. Salesforce Roles vs. Profiles Roles determine what data users can view. They establish a hierarchy of access, with higher roles having visibility into records owned by those below them. This helps ensure that only authorized users can access sensitive information. Profiles, on the other hand, define what actions users can take within Salesforce, such as creating or editing records. Profiles are assigned when user accounts are created and can be customized to suit specific job functions. Role Hierarchy in Salesforce The role hierarchy in Salesforce is designed to control data access, not mirror the organizational chart. Higher roles can generally view data from roles below them, but access can be restricted based on business needs. Types of Salesforce Profiles Salesforce comes with several standard profiles, and administrators can create custom profiles as needed. Some key profiles include: In addition to profiles, permission sets allow admins to grant users specific permissions without changing their profile. Managing Salesforce Roles and Profiles Setting up Salesforce roles and profiles is crucial for maintaining data security and ensuring users have the correct access for their responsibilities. By efficiently configuring roles and profiles, businesses can tailor the platform to their needs, enhancing both user experience and operational security. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

Read More
October 10, 2024in Salesforce
AI All Grown Up
07Oct

AI All Grown Up

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

Read More
October 7, 2024in Agentforce Platform, AI Tools, Data, Google, Mulesoft, Salesforce, Technology
gettectonic.com