Data-Driven Archives - gettectonic.com - Page 4
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 Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 31, 2024in Data, Salesforce, Salesforce Sales Cloud
Pitfall of Process Optimization
31Oct

Pitfall of Process Optimization

In 1963, Peter Drucker wrote one of the most influential articles on business, Managing for Business Effectiveness. Much like Fred Brooks’ 1975 classic, The Mythical Man-Month, it has profound lessons. However, through today’s lens of AI and automation, it seems we may have misinterpreted Drucker’s insights, inadvertently industrializing the problem rather than solving it. Pitfall of process optimization. Pitfalls of process optimization. One pivotal point from Drucker’s essay (highlighted by Dave Duggal) is: “The major problem is the confusion between effectiveness and efficiency. There is nothing more useless than doing efficiently what should not be done at all. Yet our tools — especially accounting concepts and data — all focus on efficiency. What we need is a way to identify areas of effectiveness and a method to concentrate on them.” While Drucker emphasized focusing on results and making data-driven decisions, his warning that “our data and accounting focus on efficiency” has been largely overlooked. Instead of addressing this, businesses have industrialized the pursuit of efficiency at the expense of effectiveness. The Efficiency Trap Drucker’s assertion that “there is nothing more useless than doing with great efficiency what should not be done at all” remains true, yet much of the business and IT landscape has fixated on eliminating steps, even if the return on this effort is minimal. He warned that too much focus is placed on problems rather than opportunities and on areas where even exceptional performance yields little impact. This mirrors many process optimization efforts, where the goal is often to remove unnecessary steps, focusing on efficiency rather than true effectiveness. The Pitfall of Process Optimization Entire business methodologies were built around simplifying processes and eliminating redundant steps. Companies created cultures centered on optimization, believing that by cutting out inefficiencies, they would achieve success. Yet, as Drucker noted, this focus on efficiency has often resulted in neglecting broader opportunities. Poor Data, Poor Outcomes Drucker’s concerns about tools and data have proven strangely prophetic. Instead of focusing on effectiveness, many organizations now face data problems, often rooted in over-optimized processes. Some of the firms most dedicated to process optimization are the very ones known for slow responses to market changes, as their data fails to keep pace with business needs. Focusing on Process, Missing the Bigger Picture When businesses focus narrowly on processes, they overlook key information needed downstream. This might improve micro-level efficiency, but it often damages macro-level outcomes. For instance, optimizing an order submission process may mean critical data isn’t captured, leading to issues further along in the supply chain. This process-driven thinking fosters data silos—disconnected systems that, while progressing individual steps, fail to offer the necessary insights for broader business decisions. Effectiveness Requires Understanding Reality AI amplifies these challenges. To fully leverage AI, businesses must shift from process-centric to reality-based thinking. Companies that can manage their digital reality, enabling AI to make smart, outcome-driven decisions, will outperform those stuck in outdated process mentalities. AI won’t just optimize individual steps like restocking inventory; it will manage complex tasks such as provisioning networks, negotiating with suppliers, or resolving customer complaints. To support this, businesses must move beyond step-based optimization and embrace new approaches that focus on multi-dimensional KPIs and AI-driven outcomes. A Shift from Process to Reality The future of business optimization will require understanding KPIs in a multi-dimensional way, embedding AI into operations, and allowing it to drive business outcomes. This will necessitate a shift in data architecture, with a focus on operational reality rather than reporting. The Dangers of Ignoring the Shift Businesses that cling to process thinking may find isolated success with AI but risk falling behind competitors that embrace a broader transformation. Like retailers who tried to compete with Amazon by merely launching websites without addressing underlying fulfillment challenges, companies may see short-term gains but falter in the long run. The Cultural Challenge of Transformation Switching from process-focused thinking to a reality-based approach will be difficult. Since Drucker’s 1963 essay, the industrialization of step-elimination has become deeply ingrained in business culture. Processes are comfortable; they allow for focused problem-solving in isolated areas. Moving to a mindset that prioritizes operational reality, dependencies, and cross-functional collaboration is a significant cultural shift. Embracing the Change However, the businesses that make this transition will gain a competitive advantage. Those that recognize the scale of change required—making cultural, organizational, and architectural shifts—will operate in a different league than those who don’t. By shifting from efficiency-driven processes to reality-based effectiveness, organizations can unlock the full potential of AI, ensuring not just operational improvements but transformational business success. You can avoid the pitfalls of process optimization. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 31, 2024in Salesforce
Salesforce Connected Assets
28Oct

Salesforce Connected Assets

Salesforce has unveiled Connected Assets, a robust suite of capabilities in Manufacturing Cloud, designed to offer manufacturers a comprehensive, real-time perspective on connected asset data. This includes data on service history, asset status, customer records, and telematics, allowing manufacturers to monitor asset health and performance while proactively addressing maintenance needs to reduce downtime and boost customer satisfaction. Enhanced AI Capabilities for Connected AssetsConnected Assets integrates Salesforce’s advanced AI to empower teams with actionable insights. Sales, customer service, and field teams can now receive real-time alerts and quickly access asset history and health, enabling faster, data-driven support and the delivery of more personalized offers. AI-driven insights and recommendations based on asset condition, service history, and performance data enhance the ability of manufacturers to predict maintenance needs and provide proactive support, including on-site recommendations to field technicians. Innovative Features for Optimized Asset Management Salesforce PerspectiveAchyut Jajoo, SVP and GM of Manufacturing and Automotive, states, “The manufacturing industry is embracing a historic transformation toward AI-enabled modernization. Connected Assets and our sector-specific AI tools in Manufacturing Cloud empower our customers to lead with improved customer experiences, optimized asset performance, and new revenue-generating services. With Agentforce, our customers will soon be able to leverage autonomous agents to monitor connected asset data at scale, enabling them to focus on strategic, high-value initiatives.” Real-World ApplicationKawasaki Engines exemplifies Connected Assets in action, using Manufacturing Cloud to enhance customer relationships by offering proactive support and minimizing equipment downtime. “Salesforce’s Connected Assets will enable us to deliver exceptional service, keeping our customers satisfied and our products operating efficiently,” says Tony Gondick, Senior Manager of IT Business Strategy at Kawasaki Engines. Extending Across IndustriesBeyond Manufacturing Cloud, Connected Assets is also being introduced to Salesforce’s other industry clouds, such as Energy & Utilities, Communications, and Media, allowing a wide range of sectors to tap into the benefits of connected asset management, minimize downtime, and generate new value. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 28, 2024in Agentforce Platform, AI Tools, Data, Salesforce, Salesforce Development Services, Salesforce Health and Life Sciences Solutions, Salesforce Manufacturing Automotive Energy
Transform Customer Experience
25Oct

Transform Customer Experience

In today’s AI-driven business environment, customer experience (CX) has evolved from being a buzzword to a critical factor in determining success. It’s no longer enough for businesses to offer high-quality products or excellent service alone—today’s customers are always online, engaged, and seeking the most convenient, relevant, and enjoyable experiences. This is where Salesforce Data Cloud becomes a game-changer, providing the tools needed to meet modern customer expectations. Transforming Customer Experience with Salesforce Data Cloud Salesforce enables businesses to collect, integrate, and leverage critical customer information within its ecosystem, offering an all-encompassing view of each customer. This unified customer data allows organizations to forecast visitor trends, assess marketing impact, and predict customer behavior. As data-driven decision-making becomes increasingly central to business strategy, Salesforce Data Cloud and its Customer Data Platform (CDP) features provide a significant competitive edge—whether in e-commerce, fintech, or B2B industries. Data Cloud is more than just your traditional CDP. It’s the only data platform native to the world‘s #1 AI CRM. This means that marketers can quickly access and easily action on unified data – from across the entire business – to drive growth and increase customer lifetime value. Data Cloud’s Role in Enhancing CX By unifying data in one place, Salesforce Data Cloud enables organizations to access real-time customer insights. This empowers them to track customer activity across channels like email, social media, and online sales, facilitating targeted marketing strategies. Businesses can analyze customer behavior and deliver personalized messaging, aligning marketing, sales, and customer service efforts to ensure consistency. With these capabilities, Salesforce customers can elevate the CX by delivering the right content, at the right time, to the right audience, ultimately driving customer satisfaction and growth. New Features of Salesforce Data Cloud Salesforce continues to evolve, introducing cutting-edge features that reshape customer interaction: To fully maximize these features, partnering with a Salesforce Data Cloud consultant can help businesses unlock the platform’s full potential and refine their customer engagement strategies. Agentic AI Set to Supercharge Business Processes Salesforce’s vision extends beyond customer relationship management with the integration of Agentic AI through its Customer 360 platform. According to theCUBE Research analysts, this signals a shift toward using AI agents to automate complex business processes. These AI agents, built on Salesforce’s vast data resources, promise to revolutionize how companies operate, offering customized, AI-driven business tools. “If they can pull this off, where it becomes a more dynamic app platform, more personalized, really focused on those processes all the way back to the data, it’s going to be a clear win for them,” said Strechay. “They’re sitting on cloud; they’re sitting on IaaS. That’s a huge win from that perspective.” AI agents create a network of microservices that think and act independently, involving human intervention only when necessary. This division of labor allows businesses to capture expertise in routine tasks while freeing human workers to focus on more complex decision-making. However, the success of these AI agents depends on access to accurate and reliable data. As Gilbert explained, “Agents can call on other agents, and when they’re not confident of a step in a process or an outcome, they can then bounce up to an inbox for a human to supervise.” The goal isn’t to eliminate humans but to capture their expertise for simpler processes. Empowering Developers and Citizen Creators At the core of this AI-driven transformation is Salesforce’s focus on developers. The platform’s low-code tools allow businesses to easily customize AI agents and automate business processes, empowering both experienced developers and citizen creators. With simple language commands or goal-setting, companies can build and train these AI agents, streamlining operations. “It’s always going to be about good data—that’s the constant,” Bertrand said. “The second challenge is how to train agents and humans to work together effectively. While some entry-level jobs may be replaced, AI will continue to evolve, creating new opportunities in the future.” Is Salesforce Data Cloud the Right Fit for Your Business? Salesforce Data Cloud offers comprehensive capabilities for businesses of all sizes, but it’s essential to assess whether it aligns with your specific needs. The platform is particularly valuable for: For businesses that fit these scenarios, working with Salesforce’s partner ecosystem or a Data Cloud consultant can help ensure successful integration and optimization. What’s New in Salesforce’s Latest Release? The latest Salesforce Spring Release introduced several exciting features, further enhancing Salesforce Data Cloud: These updates reflect Salesforce’s commitment to providing innovative, data-driven solutions that enhance customer experiences and drive business success. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 25, 2024in AI Tools, Data, Generative AI, Salesforce, Salesforce Data Cloud
Slack User Personas
25Oct

Slack User Personas

A research team at Slack recently surveyed 5,000 full-time desk workers to understand what drives their use of AI-enhanced workplace tools. They found that people typically fall into one of five distinct personas, as identified by Slack’s Workforce Lab: What’s fascinating about this approach is how it aligns with the concept of managing people through “employee personas.” If you’re unfamiliar, workforce platform Envoy defines employee personas as “semi-fictional characters that represent the behaviors, needs, and preferences of a group of employees,” based on data and interviews. These personas help organizations tailor communications, plan training, and develop career paths, offering a data-driven approach to workforce management. Slack has extended this framework to AI adoption strategies. As reported by HR Dive, Christina Janzer, Slack’s SVP of research and analytics, noted during a press call that AI adoption is complex, with individuals experiencing it differently. She suggested that understanding employees’ emotional responses to AI could help predict whether they’ll experiment with or avoid the technology. This research mirrors the approach of the Slack-backed Future Forum, which surveyed 10,000 global workers each quarter on topics like flexibility, burnout, and hybrid work. Slack’s Workforce Lab takes a similar approach but focuses on productivity and employee experience across desk workers globally, including those at Slack, Salesforce, and beyond. The release of this report on AI personas—complete with a quiz—continues this work by asking how management can foster effective AI adoption. It’s crucial to note that personas aren’t fixed; people’s attitudes and enthusiasm for AI can evolve with experience. If Slack’s findings reflect broader trends, only a third of employees are truly excited about AI, with the rest hesitant or disengaged. A future challenge for Slack Workforce Lab may be uncovering what can motivate the remaining personas to embrace AI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 25, 2024in Salesforce Slack
Cohere-Powered Slack Agents
21Oct

Cohere-Powered Slack Agents

Salesforce AI and Cohere-Powered Slack Agents: Seamless CRM Data Interaction and Enhanced Productivity Slack agents, powered by Salesforce AI and integrated with Cohere, enable seamless interaction with CRM data within the Slack platform. These agents allow teams to use natural language to surface data insights and take action, simplifying workflows. With Slack’s AI Workflow Builder and support for third-party AI agents, including Cohere, productivity is further enhanced through automated processes and customizable AI assistants. By leveraging these technologies, Slack agents provide users with direct access to CRM data and AI-powered insights, improving efficiency and collaboration. Key Features of Slack Agents: Salesforce AI and Cohere Productivity Enhancements with Slack Agents: Salesforce AI and Cohere AI Agent Capabilities in Slack: Salesforce and Cohere Data Security and Compliance for Slack Agents FAQ What are Slack agents, and how do they integrate with Salesforce AI and Cohere?Slack agents are AI-powered assistants that enable teams to interact with CRM data directly within Slack. Salesforce AI agents allow natural language data interactions, while Cohere’s integration enhances productivity with customizable AI assistants and automated workflows. How do Salesforce AI agents in Slack improve team productivity?Salesforce AI agents enable users to interact with both CRM and conversational data, update records, and analyze opportunities using natural language. This integration improves workflow efficiency, leading to a reported 47% productivity boost. What features does the Cohere integration with Slack AI offer?Cohere integration offers customizable AI assistants that can help generate workflows, summarize channel content, and provide intelligent responses to user queries within Slack. How do Slack agents handle data security and compliance?Slack agents leverage cloud-native DLP solutions, automatically detecting sensitive data across different file types and setting up automated remediation processes for enhanced security and compliance. Can Slack agents work with AI providers beyond Salesforce and Cohere?Yes, Slack supports AI agents from various providers. In addition to Salesforce AI and Cohere, integrations include Adobe Express, Anthropic, Perplexity, IBM, and Amazon Q Business, offering users a wide array of AI-powered capabilities. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 21, 2024in Data, Salesforce Slack
Salesforce Government Cloud Premium
21Oct

Salesforce Government Cloud Premium

Software company Salesforce announced on Monday that it has rolled out a new version of its government cloud that has Top Secret authorization and is geared toward U.S. national security agencies and intelligence organizations.

The new offering, called Government Cloud Premium, is hosted on Amazon Web Services’ Top Secret cloud.

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October 21, 2024in Data, Hyperforce, Public Sector Solutions, Salesforce, Salesforce Government Cloud, Salesforce Government Cloud Premium
Salesforce and Stripe Integration
19Oct

Salesforce and Stripe Integration

Processing weekly payments can often become time-consuming, with organizations spending significant time just tracking payments post-invoice. Timely updates on payment processing have been a longstanding priority, particularly for companies needing flexible payment options to meet beneficiary needs. The integration of Stripe with Salesforce addresses these challenges, offering a streamlined, efficient solution. Salesforce and Stripe Integration. With a focus on faster processing, this integration enhances payment management, invoicing, and financial oversight. Here’s an overview of the benefits that Stripe and Salesforce integration brings to businesses. Key Benefits of Integrating Stripe with Salesforce Modern businesses demand efficient, seamless transactions. Here are some of the major advantages of combining Stripe and Salesforce: Why Businesses Should Consider Salesforce and Stripe Integration Having implemented this integration for various clients, we have seen how it supports efficient operations. Here are a few reasons why businesses should consider this approach: Simplify Payments with Salesforce and Stripe Integration The Stripe and Salesforce integration represents a transformative opportunity for businesses to improve operational efficiency and customer experience. Beyond a simple tool pairing, this integration paves the way for scalable, complex business operations. Successful integration, however, requires knowledgeable professionals who understand the nuances of customization to fit each organization’s unique needs. Reach out to experienced experts to optimize your integration and harness its full potential. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 19, 2024in Data, Marketing Automation, Salesforce Communications Cloud, Salesforce Optimization
AI Customer Service Agents Explained
19Oct

AI Customer Service Agents Explained

AI customer service agents are advanced technologies designed to understand and respond to customer inquiries within defined guidelines. These agents can handle both simple and complex issues, such as answering frequently asked questions or managing product returns, all while offering a personalized, conversational experience. Research shows that 82% of service representatives report that customers ask for more than they used to. As a customer service leader, you’re likely facing increasing pressure to meet these growing expectations while simultaneously reducing costs, speeding up service, and providing personalized, round-the-clock support. This is where AI customer service agents can make a significant impact. Here’s a closer look at how AI agents can enhance your organization’s service operations, improve customer experience, and boost overall productivity and efficiency. What Are AI Customer Service Agents? AI customer service agents are virtual assistants designed to interact with customers and support service operations. Utilizing machine learning and natural language processing (NLP), these agents are capable of handling a broad range of tasks, from answering basic inquiries to resolving complex issues — even managing multiple tasks at once. Importantly, AI agents continuously improve through self-learning. Why Are AI-Powered Customer Service Agents Important? AI-powered customer service technology is becoming essential for several reasons: Benefits of AI Customer Service Agents AI customer service agents help service teams manage growing service demands by taking on routine tasks and providing essential support. Key benefits include: Why Choose Agentforce Service Agent? If you’re considering adding AI customer service agents to your strategy, Agentforce Service Agent offers a comprehensive solution: By embracing AI customer service agents like Agentforce Service Agent, businesses can reduce costs, meet growing customer demands, and stay competitive in an ever-evolving global market. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 19, 2024in Agentforce Platform, Data, Generative AI, Salesforce, Technology
Customer Engagement with AI
18Oct

Customer Engagement with AI

Funlab Explores AI to Boost Customer Engagement in Leisure Venues In a push to enhance customer experiences across its “leisure-tainment” venues, Funlab has begun experimenting with artificial intelligence. Speaking at a Salesforce Agentforce event in Sydney, Funlab’s Head of Customer Relationships and Retention, Tracy Tanti, shared that the company is “excited to be able to start experimenting” with AI. Agentforce, a Salesforce platform designed to create autonomous agents for supporting employees and customers, serves as a key part of Funlab’s AI exploration efforts. According to Tanti, Funlab has a range of AI-focused projects on its roadmap, with the goal of blending digital experiences into real-life interactions and supporting both venue and corporate teams with AI-driven tools. Reflecting the company’s dedication to careful planning, Tanti described how Salesforce connected Funlab with another customer, Norths Collective, to discuss its own AI implementation journey. Robert Lopez, Chief Marketing and Innovation Officer at Norths Collective, has seen success with enhanced personalization and analytics, which have contributed to increased membership and engagement. Tanti noted that Norths Collective’s transformation work would provide valuable insights for Funlab as it optimizes its data in preparation for AI adoption. Currently, Funlab is in a post-digital transformation phase, refining its processes to deliver more connected and personalized guest experiences throughout the customer lifecycle. With ongoing expansion into the U.S. market—including recent openings of Holey Moley venues—Funlab is also focusing on building robust support infrastructure and engaging local audiences through Salesforce. Tanti highlighted the company’s vision for the U.S. to become a significant portion of total revenues and emphasized how Salesforce will help Funlab nurture a strong customer database in this new market. Additionally, Funlab is leveraging Salesforce to grow its event and function sales, which are projected to reach 39% of total online revenue by year’s end, up from 23% earlier this year. This expansion underscores Funlab’s commitment to using AI and data-driven insights to fuel growth and deepen customer engagement across all its markets and venues. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 18, 2024in Artificial Intelligence, Data, Salesforce
AI Agents and Digital Transformation
18Oct

AI Agents and Digital Transformation

In the rapidly developingng world of technology, Artificial Intelligence (AI) is revolutionizing industries and reshaping how we interact with digital systems. One of the most promising advancements within AI is the development of AI agents. These intelligent entities, often powered by Large Language Models (LLMs), are driving the next wave of digital transformation by enabling automation, personalization, and enhanced decision-making across various sectors. AI Agents and digital transformation are here to stay. What is an AI Agent? An AI agent, or intelligent agent, is a software entity capable of perceiving its environment, reasoning about its actions, and autonomously working toward specific goals. These agents mimic human-like behavior using advanced algorithms, data processing, and machine-learning models to interact with users and complete tasks. LLMs to AI Agents — An Evolution The evolution of AI agents is closely tied to the rise of Large Language Models (LLMs). Models like GPT (Generative Pre-trained Transformer) have showcased remarkable abilities to understand and generate human-like text. This development has enabled AI agents to interpret complex language inputs, facilitating advanced interactions with users. Key Capabilities of LLM-Based Agents LLM-powered agents possess several key advantages: Two Major Types of LLM Agents LLM agents are classified into two main categories: Multi-Agent Systems (MAS) A Multi-Agent System (MAS) is a group of autonomous agents working together to achieve shared goals or solve complex problems. MAS applications span robotics, economics, and distributed computing, where agents interact to optimize processes. AI Agent Architecture and Key Elements AI agents generally follow a modular architecture comprising: Learning Strategies for LLM-Based Agents AI agents utilize various learning techniques, including supervised, reinforcement, and self-supervised learning, to adapt and improve their performance in dynamic environments. How Autonomous AI Agents Operate Autonomous AI agents act independently of human intervention by perceiving their surroundings, reasoning through possible actions, and making decisions autonomously to achieve set goals. AI Agents’ Transformative Power Across Industries AI agents are transforming numerous industries by automating tasks, enhancing efficiency, and providing data-driven insights. Here’s a look at some key use cases: Platforms Powering AI Agents The Benefits of AI Agents and Digital Transformation AI agents offer several advantages, including: The Future of AI Agents The potential of AI agents is immense, and as AI technology advances, we can expect more sophisticated agents capable of complex reasoning, adaptive learning, and deeper integration into everyday tasks. The future promises a world where AI agents collaborate with humans to drive innovation, enhance efficiency, and unlock new opportunities for growth in the digital age. AI Agents and Digital Transformation By partnering with AI development specialists at Tectonic, organizations can access cutting-edge solutions tailored to their needs, positioning themselves to stay ahead in the rapidly evolving AI-driven market. Agentforce Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 18, 2024in Agentforce Platform, Artificial Intelligence, Data, Enterprise, Salesforce Copilots, Technology
RIG and RAG
17Oct

RIG and RAG

Imagine you’re a financial analyst tasked with comparing the GDP of France and Italy over the last five years. You query a language model, asking: “What are the current GDP figures of France and Italy, and how have they changed over the last five years?” Using Retrieval-Augmented Generation (RAG), the model first retrieves relevant information from external sources, then generates this response: “France’s current GDP is approximately $2.9 trillion, while Italy’s is around $2.1 trillion. Over the past five years, France’s GDP has grown by an average of 1.5%, whereas Italy’s GDP has seen slower growth, averaging just 0.6%.” In this case, RAG improves the model’s accuracy by incorporating real-world data through a single retrieval step. While effective, this method can struggle with more complex queries that require multiple, dynamic pieces of real-time data. Enter Retrieval Interleaved Generation (RIG)! Now, you submit a more complex query: “What are the GDP growth rates of France and Italy in the past five years, and how do these compare to their employment rates during the same period?” With RIG, the model generates a partial response, drawing from its internal knowledge about GDP. However, it simultaneously retrieves relevant employment data in real time. For example: “France’s current GDP is $2.9 trillion, and Italy’s is $2.1 trillion. Over the past five years, France’s GDP has grown at an average rate of 1.5%, while Italy’s growth has been slower at 0.6%. Meanwhile, France’s employment rate increased by 2%, and Italy’s employment rate rose slightly by 0.5%.” Here’s what happened: RIG allowed the model to interleave data retrieval with response generation, ensuring the information is up-to-date and comprehensive. It fetched employment statistics while continuing to generate GDP figures, ensuring the final output was both accurate and complete for a multi-faceted query. What is Retrieval Interleaved Generation (RIG)? RIG is an advanced technique that integrates real-time data retrieval into the process of generating responses. Unlike RAG, which retrieves information once before generating the response, RIG continuously alternates between generating text and querying external data sources. This ensures each piece of the response is dynamically grounded in the most accurate, up-to-date information. How RIG Works: For example, when asked for GDP figures of two countries, RIG first retrieves one country’s data while generating an initial response and simultaneously fetches the second country’s data for a complete comparison. Why Use RIG? Real-World Applications of RIG RIG’s versatility makes it ideal for handling complex, real-time data across various sectors, such as: Challenges of RIG While promising, RIG faces a few challenges: As AI evolves, RIG is poised to become a foundational tool for complex, data-driven tasks, empowering industries with more accurate, real-time insights for decision-making. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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October 17, 2024in Data
Zendesk Launches AI Agent Builder
15Oct

The State of AI

The State of AI: How We Got Here (and What’s Next) Artificial intelligence (AI) has evolved from the realm of science fiction into a transformative force reshaping industries and lives around the world. But how did AI develop into the technology we know today, and where is it headed next? At Dreamforce, two of Salesforce’s leading minds in AI—Chief Scientist Silvio Savarese and Chief Futurist Peter Schwartz—offered insights into AI’s past, present, and future. How We Got Here: The Evolution of AI AI’s roots trace back decades, and its journey has been defined by cycles of innovation and setbacks. Peter Schwartz, Salesforce’s Chief Futurist, shared a firsthand perspective on these developments. Having been involved in AI since the 1970s, Schwartz witnessed the first “AI winter,” a period of reduced funding and interest due to the immense challenges of understanding and replicating the human brain. In the 1990s and early 2000s, AI shifted from attempting to mimic human cognition to adopting data-driven models. This new direction opened up possibilities beyond the constraints of brain-inspired approaches. By the 2010s, neural networks re-emerged, revolutionizing AI by enabling systems to process raw data without extensive pre-processing. Savarese, who began his AI research during one of these challenging periods, emphasized the breakthroughs in neural networks and their successor, transformers. These advancements culminated in large language models (LLMs), which can now process massive datasets, generate natural language, and perform tasks ranging from creating content to developing action plans. Today, AI has progressed to a new frontier: large action models. These systems go beyond generating text, enabling AI to take actions, adapt through feedback, and refine performance autonomously. Where We Are Now: The Present State of AI The pace of AI innovation is staggering. Just a year ago, discussions centered on copilots—AI systems designed to assist humans. Now, the conversation has shifted to autonomous AI agents capable of performing complex tasks with minimal human oversight. Peter Schwartz highlighted the current uncertainties surrounding AI, particularly in regulated industries like banking and healthcare. Leaders are grappling with questions about deployment speed, regulatory hurdles, and the broader societal implications of AI. While many startups in the AI space will fail, some will emerge as the giants of the next generation. Salesforce’s own advancements, such as the Atlas Reasoning Engine, underscore the rapid progress. These technologies are shaping products like Agentforce, an AI-powered suite designed to revolutionize customer interactions and operational efficiency. What’s Next: The Future of AI According to Savarese, the future lies in autonomous AI systems, which include two categories: The Road Ahead As AI continues to evolve, it’s clear that its potential is boundless. However, the path forward will require careful navigation of ethical, regulatory, and practical challenges. The key to success lies in innovation, collaboration, and a commitment to creating systems that enhance human capabilities. For Salesforce, the journey has only just begun. With groundbreaking technologies and visionary leadership, the company is not just predicting the future of AI—it’s creating it. The State of AI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 15, 2024in Artificial Intelligence, Data, Salesforce, Technology
Multi AI Agent Systems
15Oct

Multi AI Agent Systems

Building Multi-AI Agent Systems: A Comprehensive Guide As technology advances at an unprecedented pace, Multi-AI Agent systems are emerging as a transformative approach to creating more intelligent and efficient applications. This guide delves into the significance of Multi-AI Agent systems and provides a step-by-step tutorial on building them using advanced frameworks like LlamaIndex and CrewAI. What Are Multi-AI Agent Systems? Multi-AI Agent systems are a groundbreaking development in artificial intelligence. Unlike single AI agents that operate independently, these systems consist of multiple autonomous agents that collaborate to tackle complex tasks or solve intricate problems. Key Features of Multi-AI Agent Systems: Applications of Multi-AI Agent Systems: Multi-agent systems are versatile and impactful across industries, including: The Workflow of a Multi-AI Agent System Building an effective Multi-AI Agent system requires a structured approach. Here’s how it works: Building Multi-AI Agent Systems with LlamaIndex and CrewAI Step 1: Define Agent Roles Clearly define the roles, goals, and specializations of each agent. For example: Step 2: Initiate the Workflow Establish a seamless workflow for agents to perform their tasks: Step 3: Leverage CrewAI for Collaboration CrewAI enhances collaboration by enabling autonomous agents to work together effectively: Step 4: Integrate LlamaIndex for Data Handling Efficient data management is crucial for agent performance: Understanding AI Inference and Training Multi-AI Agent systems rely on both AI inference and training: Key Differences: Aspect AI Training AI Inference Purpose Builds the model. Uses the model for tasks. Process Data-driven learning. Real-time decision-making. Compute Needs Resource-intensive. Optimized for efficiency. Both processes are essential: training builds the agents’ capabilities, while inference ensures swift, actionable results. Tools for Multi-AI Agent Systems LlamaIndex An advanced framework for efficient data handling: CrewAI A collaborative platform for building autonomous agents: Practical Example: Multi-AI Agent Workflow Conclusion Building Multi-AI Agent systems offers unparalleled opportunities to create intelligent, responsive, and efficient applications. By defining clear agent roles, leveraging tools like CrewAI and LlamaIndex, and integrating robust workflows, developers can unlock the full potential of these systems. As industries continue to embrace this technology, Multi-AI Agent systems are set to revolutionize how we approach problem-solving and task execution. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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October 15, 2024in Artificial Intelligence, Data, Technology

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