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Salesforce Data Cloud Dictionary

Core Components of Data Cloud Integration Data Cloud: Data Cloud is a platform that gathers data from different sources into one place, giving you a complete view of your data to make smarter decisions. Data Connection: A data connection is a secure link between Data Cloud and external sources, allowing data to flow smoothly between systems. Data Lake Object (DLO): A Data Lake Object temporarily stores raw data as it’s imported into Data Cloud, keeping it organized and ready for processing. Data Model Object (DMO): A Data Model Object organizes and maps data into specific fields, making it structured and usable within Data Cloud. Data Stream: A data stream is a continuous pipeline that transfers data from a source (like a database) into Data Cloud on a regular schedule. 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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Reasons to Automate Your Sales Commission Process

Reasons to Automate Your Sales Commission Process

Optimizing your sales commission process through automation can create significant efficiencies, reduce errors, and increase team satisfaction across the organization. Sales commission software provides the real-time data and transparency that today’s sales, finance, and revenue operations (RevOps) teams need to keep pace with business growth. Here are four key benefits of implementing automated commission software: 1. Real-Time Visibility into the Commission Process Sales commission software offers instant access to commission data for reps, managers, and executives. This real-time visibility empowers sales reps to stay focused on high-value deals, knowing their commission data is accurate and transparent. Sales managers can use metrics like quota attainment and earned commissions to track team performance and motivate reps effectively. Automating commission tracking also streamlines end-of-month reporting for finance and RevOps, eliminating the need for manual calculations. And with transparent, accessible data, sales reps can trust the accuracy of their earnings without having to double-check formulas or request manual verifications—freeing them to focus on closing more deals. 2. Increased Productivity Across Teams Manually calculating commissions is both time-consuming and prone to errors, which can erode trust and impact productivity across sales, finance, and RevOps. Automating this process reduces human error and saves teams hours of administrative work, allowing them to redirect energy toward business-critical activities. Manual commission management can also limit scalability; each change in team structure or territory often requires a full recalibration in spreadsheets. With automated software, these adjustments are streamlined, allowing for seamless scalability and supporting growth without adding manual overhead. 3. Improved Accuracy in Commission Calculations Replacing unhappy sales reps is costly, and one common cause of dissatisfaction is inaccurate commission calculations. Studies show nearly 90% of spreadsheets contain errors, and in a process as complex as commission calculation, these errors can lead to mistrust and turnover. Automating commissions removes the risk of errors, helping keep reps happy and reducing friction between sales and finance. A reliable, accurate commission process means reps can trust the data, while finance teams can confidently manage compensation without chasing down mistakes. Few things negatively impact employee focus and loyalty than feeling cheated at payday. 4. Enhanced Access to Data and Actionable Insights Sales commission software does more than calculate earnings—it collects and organizes critical data on sales performance. With these insights, organizations can identify areas for improvement, analyze trends, and optimize their sales strategies. Transform Your Organization with Automated Commission Management Automating your sales commission process isn’t just about efficiency—it’s a powerful way to build trust, enable productivity, and make data-driven decisions that drive growth. By leveraging dedicated incentive compensation management tools, you can empower your teams, reduce operational burdens, and maximize the impact of your sales data. 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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Informed Decision-Making

Informed Decision-Making

Informed Decision-Making Through Data Visualization: Power BI vs. Tableau Today’s businesses need to make informed decisions by leveraging organized and analyzed data. Data visualization is a key method for extracting insights from this data, and Power BI and Tableau are two leading tools that often spark debate among experts. Both are highly regarded for their ability to visualize data, and CTOs frequently compare Power BI vs. Tableau to determine the best fit for their needs. Why Power BI and Tableau Stand OutBoth tools excel at data visualization, making them top choices for business intelligence (BI) solutions. They offer seamless integration with various platforms, can handle large volumes of data, and provide predictive analytics capabilities. To help CTOs and other decision-makers boost efficiency, let’s dive into a comparison of Power BI vs. Tableau and examine how each tool measures up. Power BI Microsoft’s Power BI is a leading BI tool designed to transform data from diverse sources into insightful visual reports. It allows users to create, share, and manage analytical reports, ensuring accessibility at all times. As part of the Microsoft ecosystem, Power BI is ideal for large organizations that already use Microsoft products. Tableau Tableau delivers powerful data visualization with flexible deployment options, allowing users to seamlessly access insights. With its integration into Salesforce Data Cloud, Tableau offers a fast and scalable way to work with customer data in real time. Its strong data-handling capabilities make it popular among larger organizations and data experts. Power BI vs. Tableau: Key Differences Let’s explore the key differences between Power BI and Tableau to guide your informed decision-making. Data Visualization and User Interface Data Integration and Connectivity for Informed Decision-Making Data Handling and Performance Ease of Learning Programming Tools Support Pricing Microsoft Power BI vs. Salesforce Tableau: Pros and Cons Power BI Pros Tableau Pros Which is Better: Power BI or Tableau? When comparing Microsoft Power BI vs. Tableau, the right choice depends on your organization’s size, technical expertise, and specific needs. For smaller businesses and those already using Microsoft tools, Power BI is often the best fit. On the other hand, larger organizations managing substantial datasets might favor Tableau for its advanced capabilities. Ultimately, the decision between Power BI vs. Tableau should be based on your unique business requirements and the level of technical expertise available within your team. 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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Winter 25 Release Notes

Winter 25 Release Experience Cloud

Salesforce Winter ’25 Release: 6 Key Enhancements to Experience Cloud The Salesforce Winter ’25 Release brings a fresh suite of updates to Experience Cloud, focusing on design customization, SEO optimization, and streamlined navigation for enhanced user engagement. We’ve summarized six major updates and additional enhancements that make this release a significant step forward for Experience Cloud sites. 1. Enhanced Design Options for LWR Sites Winter ’25 empowers site designers with more granular control over the look and feel of LWR (Lightning Web Runtime) sites. New customization options in the Experience Builder Theme panel now allow for specific styling of individual components like columns and buttons, offering a new level of precision in visual design. Additional features include a Scoped Header and Footer layout that allows fixed positioning for headers and footers, enhancing user experience with persistent navigation elements. Site admins can define unique color palettes for buttons across various states (default, hover, focus), and apply color schemes to individual columns, which can now be set in the Theme panel. Further text customizations for headings have also been added, allowing a personalized touch for every element on LWR sites. 2. SEO-Friendly URLs for Accounts and Contacts (Generally Available) To drive organic traffic, the Winter ’25 Release introduces SEO-friendly URL slugs for Account and Contact pages, replacing traditional record IDs with easily readable URLs. This enhancement allows search engines to better index content, making it easier for users to find your pages. Site managers can configure SEO-friendly URLs directly in the Administration panel and import slugs in bulk for faster setup. 3. Data Providers for LWR Sites (Beta) Experience Cloud now includes an option to configure data providers on LWR site pages, enabling seamless integration with data from various sources, including Apex and Record providers. Admins can specify data sources within Experience Builder, allowing for real-time data updates across components and pages, providing a more dynamic and responsive experience for users. 4. Revamped Navigation and New Components The Navigation Menu component has been revamped, allowing admins to design a more intuitive navigation experience for both desktop and mobile users. The beta Site Header component further enhances branding with logo placement and customizable headers, while the Grid component now ensures consistent cell height, improving the visual balance of page layouts. Tailored navigation menus for desktop and mobile screens can be customized for color, spacing, text styles, and more to provide an optimized experience across devices. 5. Expanded Data Cloud Integration for Event Tracking Winter ’25 expands Data Cloud integration to capture checkout, order, and cart events on enhanced LWR sites. Ecommerce-focused organizations can now record user interactions—like checkout initiation and address input—automatically, giving businesses richer insights into customer behavior. Data captured through these events can be viewed within Data Cloud, allowing admins to understand user engagement and optimize site design accordingly. 6. Salesforce File Linking for LWR Sites (Beta) The new File Upload Lightning Web Component enables file uploads directly from an LWR site to Salesforce, an option previously available only on Aura sites. This update streamlines the file transfer process, allowing guest users to upload files securely, which are then accessible within Salesforce. Additional Experience Cloud Enhancements In addition to the primary updates, Winter ’25 introduces several valuable, albeit smaller, features: Availability of Features Some Winter ’25 features will be accessible immediately after release, while others require setup by admins. Consider notifying users about these updates to ensure a smooth transition and to leverage the full potential of new functionalities. 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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Being AI-Driven

Being AI-Driven

Imagine a company where every decision, strategy, customer interaction, and routine task is enhanced by AI. From predictive analytics uncovering market insights to intelligent automation streamlining operations, this AI-driven enterprise represents what a successful business could look like. Does this company exist? Not yet, but the building blocks for creating it are already here. To envision a day in the life of such an AI enterprise, let’s fast forward to the year 2028 and visit Tectonic 5.0, a fictional 37-year-old mid-sized company in Oklahoma that provides home maintenance services. After years of steady sales and profit growth, the 2,300-employee company has hit a rough patch. Tectonic 5.0’s revenue grew just 3% last year, and its 8% operating margin is well below the industry benchmark. To jumpstart growth, Tectonic 5.0 has expanded its product portfolio and decided to break into the more lucrative commercial real estate market. But Tectonic 5.0 needs to act fast. The firm must quickly bring its new offerings to market while boosting profitability by eliminating inefficiencies and fostering collaboration across teams. To achieve these goals, Tectonic 5.0 is relying on artificial intelligence (AI). Here’s how each department at Tectonic 5.0 is using AI to reach these objectives. Spot Inefficiencies with AI With a renewed focus on cost-cutting, Tectonic 5.0 needed to identify and eliminate inefficiencies throughout the company. To assist in this effort, the company developed a tool called Jenny, an AI agent that’s automatically invited to all meetings. Always listening and analyzing, Jenny spots problems and inefficiencies that might otherwise go unnoticed. For example, Jenny compares internal data against industry benchmarks and historical data, identifying opportunities for optimization based on patterns in spending and resource allocation. Suggestions for cost-cutting can be offered in real time during meetings or shared later in a synthesized summary. AI can also analyze how meeting time is spent, revealing if too much time is wasted on non-essential issues and suggesting ways to have more constructive meetings. It does this by comparing meeting summaries against the company’s broader objectives. Tectonic 5.0’s leaders hope that by highlighting inefficiencies and communication gaps with Jenny’s help, employees will be more inclined to take action. In fact, it has already shown considerable promise, with employees being five times more likely to consider cost-cutting measures suggested by Penny. Market More Effectively with AI With cost management underway, Tectonic 5.0’s next step in its transformation is finding new revenue sources. The company has adopted a two-pronged approach: introducing a new lineup of products and services for homeowners, including smart home technology, sustainable living solutions like solar panels, and predictive maintenance on big-ticket systems like internet-connected HVACs; and expanding into commercial real estate maintenance. Smart home technology is exactly what homeowners are looking for, but Tectonic 5.0 needs to market it to the right customers, at the right time, and in the right way. A marketing platform with built-in AI capabilities is essential for spreading the word quickly and effectively about its new products. To start, the company segments its audience using generative AI, allowing marketers to ask the system, in natural language, to identify tech-savvy homeowners between the ages of 30 and 60 who have spent a certain amount on home maintenance in the last 18 months. This enables more precise audience targeting and helps marketing teams bring products to market faster. Previously, segmentation using legacy systems could take weeks, with marketing teams relying on tech teams for an audience breakdown. Now, Tectonic 5.0 is ready to reach out to its targeted customers. Using predictive AI, it can optimize personalized marketing campaigns. For example, it can determine which customers prefer to be contacted by text, email, or phone, the best time of day to reach out, and how often. The system also identifies which messaging—focused on cost savings, environmental impact, or preventative maintenance—will resonate most with each customer. This intelligence helps Tectonic 5.0 reach the optimal customer quickly in a way that speaks to their specific needs and concerns. AI also enables marketers to monitor campaign performance for red flags like decreasing open rates or click-through rates and take appropriate action. Sell More, and Faster, with AI With interested buyers lined up, it’s now up to the sales team to close deals. Generative AI for sales, integrated into CRM, can speed up and personalize the sales process for Tectonic 5.0 in several ways. First, it can generate email copy tailored to products and services that customers are interested in. Tectonic 5.0’s sales reps can prompt AI to draft solar panel prospecting emails. To maximize effectiveness, the system pulls customer info from the CRM, uncovering which emails have performed well in the past. Second, AI speeds up data analysis. Sales reps spend a significant amount of time generating, pulling, and analyzing data. Generative AI can act like a digital assistant, uncovering patterns and relationships in CRM data almost instantaneously, guiding Tectonic 5.0’s reps toward high-value deals most likely to close. Machine learning increases the accuracy of lead scoring, predicting which customers are most likely to buy based on historical data and predictive analytics. Provide Better Customer Service with AI Tectonic 5.0’s new initiatives are progressing well. Costs are starting to decrease, and sales of its new products are growing faster than expected. However, customer service calls are rising as well. Tectonic 5.0 is committed to maintaining excellent customer service, but smart home technology presents unique challenges. It’s more complex than analog systems, and customers often need help with setup and use, raising the stakes for Tectonic 5.0’s customer service team. The company knows that customers have many choices in home maintenance providers, and one bad experience could drive them to a competitor. Tectonic 5.0’s embedded AI-powered chatbots help deliver a consistent and delightful autonomous customer service experience across channels and touchpoints. Beyond answering common questions, these chatbots can greet customers, serve up knowledge articles, and even dispatch a field technician if needed. In the field, technicians can quickly diagnose and fix problems thanks to LLMs like xGen-Small, which

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10 Top AI Jobs in 2025

10 Top AI Jobs in 2025

10 Top AI Jobs in 2025 As we approach 2025, the demand for AI expertise is on the rise. Companies are seeking professionals with a strong background in AI, paired with practical experience. This insight explores 10 of the top AI jobs, the skills they require, and the industries that are driving AI adoption. If you are of the camp worrying about artificial intelligence replacing you, read on to see how you can leverage AI to upskill your career. AI is increasingly becoming an integral part of our lives, influencing various sectors from healthcare and finance to manufacturing, retail, and education. It is automating routine tasks, enhancing user experiences, and improving decision-making processes. AI is transitioning from data centers into everyday devices such as smartphones, IoT devices, and autonomous vehicles, becoming more efficient and safer thanks to advancements in real-time processing, lower latency, and enhanced privacy measures. The ethical use of AI is also at the forefront, emphasizing fairness, transparency, and accountability in AI models and decision-making processes. This proactive approach to ethics contrasts with past technological advancements, where ethical considerations often lagged behind. The rapid growth of AI translates to an increasing number of job opportunities. Below, we discuss the skills sought in AI specialists, the industries adopting AI at a fast pace, and a rundown of the 10 hottest AI jobs for 2025. Top AI Job Skills While many programmers are self-taught, the AI field demands a higher level of expertise. An analysis of 15,000 job postings found that 77% of AI roles require a master’s degree, while only 8% of positions are available to candidates with just a high school diploma. Most job openings call for mid-level experience, with only 12% for entry-level roles. Interestingly, while remote work is common in IT, only 11% of AI jobs offer fully remote positions. Being a successful AI developer requires more than coding skills; proficiency in core AI programming languages (like Python, Java, and R) is essential. Additional skills in communication, digital marketing strategies, effective collaboration, and analytical abilities are also critical. Moreover, a basic understanding of psychology is beneficial for simulating human behavior, and knowledge of AI security, privacy, and ethical practices is increasingly necessary. Industries Embracing AI Certain sectors are rapidly adopting AI technologies, including: 10 Top AI Jobs AI job roles are evolving quickly. Specialists are increasingly in demand over generalists, with a focus on deep knowledge in specific areas. Here are 10 promising AI job roles for 2025, along with their expected salaries based on job postings. As AI continues to evolve, these roles will play a pivotal part in shaping the future of various industries. Preparing for a career in AI requires a combination of technical skills, ethical understanding, and a willingness to adapt to new technologies. As we’ve seen with Salesforce a push for upskilling in artificial intelligence is here. 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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Cool and New AI

Cool and New AI Cool and New AI

AI is revolutionizing the way we work, offering a wide range of tools beyond ChatGPT that can enhance efficiency, creativity, and productivity. Whether you’re working with data, code, marketing, videos, images, AI bots, or research, here are the top AI tools that can transform your workflow. Cool and New AI. Don’t get spooked. There will be a cornucopia more in November. 🌟 Code 1️⃣ GlideTurn spreadsheets into powerful mobile apps without writing a single line of code. Glide makes it easy for non-developers to create professional apps with minimal effort. 2️⃣ BubbleA visual programming platform that allows users to build web applications without any coding knowledge. Ideal for entrepreneurs and startups looking to launch digital products quickly. 3️⃣ AskCodiThis AI coding assistant speeds up coding tasks, offers helpful suggestions, and simplifies debugging for developers, making it a must-have tool for coding professionals. 🌟 Data 1️⃣ BasedLabsA robust data analytics platform designed for scientists and engineers. BasedLabs offers complex data processing and model building with exceptional precision. 2️⃣ Coral AIPerfect for data-driven professionals, Coral AI provides efficient edge AI tools for processing large datasets and delivering insights with on-device intelligence, speeding up tasks. 3️⃣ JuliusAn AI-powered tool for market researchers and data analysts, Julius streamlines data processes and offers powerful insights into market trends. 🌟 Marketing 1️⃣ Sprout SocialThis all-in-one social media management platform leverages AI to help marketers optimize their social presence, engage with audiences, and track detailed analytics. 2️⃣ AdCreative AIEnhance your marketing campaigns with AI-generated ads that convert. AdCreative AI allows marketers to design high-impact, creative ads effortlessly. 3️⃣ Jasper AIA top tool for content creators, Jasper AI assists in crafting high-conversion marketing copy, blogs, and ad texts at scale, making it indispensable for digital marketing. 🌟 Video 1️⃣ SynthesiaCreate professional videos without the need for cameras or actors. Synthesia’s AI avatars enable you to produce multilingual videos, making it ideal for corporate and educational content. 2️⃣ HeygenThis AI tool simplifies video production by allowing users to create AI-generated videos, perfect for marketing campaigns or training materials. 3️⃣ Opus ClipOpus Clip transforms long-form video content into short, engaging clips optimized for social media, helping creators repurpose content easily. 🌟 Image 1️⃣ Getimg.AIAutomate image creation with Getimg.AI, which enhances your visual content by generating high-quality images in minutes, speeding up the design process. 2️⃣ PicsartA versatile image editing and design platform with AI tools that make creating stunning visuals effortless, making it ideal for social media, advertising, and creative projects. 3️⃣ Leonardo AIA powerful AI-driven tool for creators, Leonardo AI helps generate high-quality images, illustrations, and graphics, making it an essential tool for designers and artists. 🌟 AI Bot 1️⃣ LiveChatAn AI-powered live chat solution that integrates seamlessly into websites to provide real-time customer support, enhancing business communication. 2️⃣ LandbotThis tool helps create conversational experiences with AI-powered chatbots for customer support, sales, and lead generation, automating client interactions. 3️⃣ CustomGPTA customizable GPT-powered AI chatbot tailored for specific industries and businesses, perfect for providing personalized customer support. 🌟 Research 1️⃣ ChatPDFTurn PDFs into interactive documents with ChatPDF, allowing users to easily navigate and extract information using an AI-based assistant. 2️⃣ VidIQVidIQ provides AI-powered tools to optimize YouTube content for better engagement and visibility, making it invaluable for content creators. 3️⃣ SemrushAn advanced SEO platform powered by AI, Semrush gives marketers and researchers deep insights into online visibility, helping boost content performance. AI extends far beyond ChatGPT. This diverse range of tools is designed to make your work more efficient and productive, whether you’re coding, marketing, creating content, or conducting research. Embrace these AI tools to unlock new levels of creativity and efficiency. 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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Sales Incentives That Work

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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user q and a

Join Datasets From Multiple Salesforce Connections

Combining Data from Two Salesforce Instances and Publishing to Tableau Server If you’re working with two Salesforce instances and need to create a unified dataset for Tableau, here’s how you can tackle the challenges and achieve your goals. Challenges Identified Recommended Approach 1. Use Tableau Prep for Data Combination Tableau Prep is an ideal tool to connect to multiple Salesforce instances and combine data into a single dataset. Steps to Union/Join Data in Tableau Prep: Advantages: 2. Create Extracts in Tableau Desktop If you need to stick with Tableau Desktop: 3. Version Compatibility and Troubleshooting Resources for Success Outcome Using Tableau Prep or carefully leveraging Tableau Desktop blending, you can create a unified dataset from two Salesforce instances and publish it for broader use. Prep is particularly effective for your scenario, offering streamlined workflows and better server compatibility. 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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Pitfall of Process Optimization

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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Intelligent Adoption Framework

Intelligent Adoption Framework

Intelligent Adoption Framework Marks a New Era for AI IntegrationAfter a surge of initial excitement, AI has now entered a phase of more thoughtful and strategic adoption, focusing on sustainable progress and measurable results. Following years of hype in which artificial intelligence was hailed as a revolutionary force poised to instantly transform industries, AI is now facing a more tempered reality. As it settles into Gartner’s “Trough of Disillusionment,” organizations are grappling with the reality of high costs and challenges scaling experimental projects. However, this phase of learning is typical for any emerging technology, and the journey to unlock AI’s full potential is far from over. Steve Daly, Senior Vice President of Solutions at New Era Technology, explains: “AI has been around for 70 years, but the recent hype inflated expectations. At $30 per user per month for tools like Microsoft 365 Copilot, they’re appealing for proof-of-concept projects. But once those initial tests are over, many companies struggle to find a clear ROI when scaling.” Cost is not the only barrier to broader AI adoption. Concerns over data security and sharing sensitive information are top priorities for many organizations. Daly adds, “New Era’s robust data and security practice has shifted to offer Copilot Studio, allowing companies to build GenAI solutions with tighter security controls. With Copilot Studio, you can limit access to specific files or libraries, ensuring greater control over sensitive data.” Moving Beyond OverpromisesBuilding confidence in AI requires addressing several factors. First, organizations must tackle security and data control issues, alongside developing a clear business model to justify AI investments. Equally important is maintaining momentum—patience and persistence are key to seeing projects through to success, or determining when to pivot. Daly observes, “We’re seeing many projects lose steam. Around half of AI initiatives stall due to poor security practices and suboptimal data management. Projects must demonstrate progress, and that’s difficult in the innovation phase when you don’t always know what you don’t know.” Introducing Intelligent AdoptionThis is where Copilot Studio and New Era’s Intelligent Adoption Framework come into play. The framework is designed to help organizations chart their AI development journey and ensure investments yield tangible results. Copilot Studio supports IT teams by focusing on the tasks that truly drive value, helping them stay on track toward their goals. The Intelligent Adoption Framework is built around three core pillars: technical redesign, organizational readiness, and user readiness. New Era’s framework leverages its expertise to guide businesses through the steps necessary to define their AI strategy, align their corporate vision, and identify the most valuable use cases for AI adoption. Daly concludes, “It’s not just about purchasing licenses—it’s about creating a roadmap for successful adoption. We’re developing packaged solutions, such as ‘train the trainer’ programs from day one, followed by proof-of-concept demonstrations using Copilot Studio. Our goal is to help customers answer key questions, like when to build a GenAI chatbot, while navigating the complexities of AI adoption and managing the pressures CIOs face from stakeholders.” In this new era of AI, success will be determined not by rushed deployment, but by strategic, intelligent adoption that ensures sustained value over time. 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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Provider Hybrid Care Model

Provider Hybrid Care Model

Primary care in the United States urgently needs a redesign, as rural hospital closures and a shortage of providers are severely limiting access for nearly one-third of the population. While advanced technologies like virtual care have helped expand primary care access, there is still a strong preference for in-person visits. To address this, healthcare providers must create a hybrid care model that integrates both virtual and in-person services to better meet patient needs. Hackensack Meridian Health, a New Jersey-based health system, has embraced an AI-based solution to establish this hybrid care model. Through a partnership with K Health, the system aims to create a seamless patient journey that fluidly transitions between virtual and in-person care as needed. According to Dr. Daniel Varga, chief physician executive at Hackensack Meridian Health, the need for this partnership became apparent during the COVID-19 pandemic, which disrupted in-person care across New Jersey. “Before the pandemic, we did zero virtual visits in our offices,” Varga said. “By early 2020, we were doing thousands per day, and we realized there was real demand for it, but we didn’t have the skill set to execute it properly.” With the support of K Health, Varga believes the health system now has the technology and expertise to integrate AI-driven virtual care into its network of 18 hospitals. However, successful implementation requires overcoming technology integration challenges. The AI-Powered Virtual Care Solution The partnership between Hackensack Meridian Health and K Health has two key components, Varga explained. The first is a 24/7 AI-driven virtual care service, and the second is a professional services agreement between K Health’s doctors and the Hackensack medical group. The AI system used in the virtual care platform is built to learn from clinical data, distinguishing it from traditional symptom-checking tools. According to K Health co-founder Ran Shaul, the AI analyzes data from patients’ EHRs and symptom inputs to provide detailed insights into the patient’s health history, giving primary care providers a comprehensive view of the patient‘s current health concerns. “We know about your chronic conditions, your recent visits, and whether you’ve followed up on key health checks like mammograms,” Shaul explained. “It creates a targeted medical chart rather than a generic symptom analysis.” In addition, K Health’s virtual physicians and Hackensack Meridian’s medical group are integrated, sharing the same tax ID and EHR system, which ensures continuity of care between virtual and in-person visits. Varga highlighted that this integration allows for seamless transitions between care settings, where virtual doctors’ notes are readily available to in-person providers the following day. “If a patient sees a virtual doctor at 2 a.m., I have the 24/7 notes right in front of me the next morning in the office,” Varga said. The service is accessible to all patients, including new patients and those recently discharged from Hackensack Meridian Health’s inpatient services who require follow-up care. Overcoming Challenges in Implementation Deploying an AI-driven virtual care system across 18 hospitals presents significant challenges, but Hackensack Meridian Health has developed several strategies to ensure smooth implementation. First, the health system provided training to all 36,000 team members to familiarize them with the platform. Additionally, a dedicated team was created to enhance collaboration between the traditional medical group and the virtual care team. One major focus was connecting hospitals and 24/7 virtual care services to ensure continuity of care for patients leaving emergency departments or being discharged from inpatient care. “Many patients don’t have a primary care doctor when they leave the hospital,” Varga explained. “With this virtual service, we can immediately book a virtual appointment for them before they leave the ED.” Provider Hybrid Care Models provide better patient care, follow-up, and outcomes. The system also offers language accessibility, with patients able to interact with the platform in Spanish and request Spanish-speaking clinicians. This feature is part of the health system’s broader strategy to break down barriers to care access and improve health equity. Improving Access and Health Equity-Provider Hybrid Care Model Shaul noted that the convenience of scheduling virtual appointments at any time helps patients who would otherwise struggle to see a doctor due to work schedules or long travel distances. The virtual care service also addresses the needs of patients with limited English proficiency, allowing them to access care in their native language. By connecting patients who lack a usual source of care with primary care providers through the virtual platform, Hackensack Meridian Health aims to close care gaps. Access to primary care is critical for improving health outcomes, yet the number of Americans with a regular source of care has dropped by 10% in the past 18 years. This decline disproportionately affects Hispanic individuals, those with lower education levels, and the uninsured. Varga emphasized that the virtual care service aligns with Hackensack’s goal of meeting patients where they are—whether virtually, in their hospitals, or at brick-and-mortar medical offices. “The reason we have such a geographically diverse spread of sites is that we believe in meeting patients where they are,” Varga said. “If that means a virtual visit, we’ll meet them there. If it means the No. 1 ranked hospital in New Jersey, we’ll meet them there. And if it’s a medical office, that’s where we’ll meet them.” Salesforce and Tectonic can help your provider solution offer the same diversity. Contact us today! Heath and Life Sciences are winning a competitive edge with Salesforce for better patient outcomes. 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

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AI Agents

AI Agents Interview

In the rapidly evolving world of large language models and generative AI, a new concept is gaining momentum: AI agents. AI Agents Interview explores. AI agents are advanced tools designed to handle complex tasks that traditionally required human intervention. While they may be confused with robotic process automation (RPA) bots, AI agents are much more sophisticated, leveraging generative AI technology to execute tasks autonomously. Companies like Google are positioning AI agents as virtual assistants that can drive productivity across industries. In this Q&A, Jason Gelman, Director of Product Management for Vertex AI at Google Cloud, shares insights into Google’s vision for AI agents and some of the challenges that come with this emerging technology. AI Agents Interview How does Google define AI agents? Jason Gelman: An AI agent is something that acts on your behalf. There are two key components. First, you empower the agent to act on your behalf by providing instructions and granting necessary permissions—like authentication to access systems. Second, the agent must be capable of completing tasks. This is where large language models (LLMs) come in, as they can plan out the steps to accomplish a task. What used to require human planning is now handled by the AI, including gathering information and executing various steps. What are current use cases where AI agents can thrive? Gelman: AI agents can be useful across a wide range of industries. Call centers are a common example where customers already expect AI support, and we’re seeing demand there. In healthcare, organizations like Mayo Clinic are using AI agents to sift through vast amounts of information, helping professionals navigate data more efficiently. Different industries are exploring this technology in unique ways, and it’s gaining traction across many sectors. What are some misconceptions about AI agents? Gelman: One major misconception is that the technology is more advanced than it actually is. We’re still in the early stages, building critical infrastructure like authentication and function-calling capabilities. Right now, AI agents are more like interns—they can assist, but they’re not yet fully autonomous decision-makers. While LLMs appear powerful, we’re still some time away from having AI agents that can handle everything independently. Developing the technology and building trust with users are key challenges. I often compare this to driverless cars. While they might be safer than human drivers, we still roll them out cautiously. With AI agents, the risks aren’t physical, but we still need transparency, monitoring, and debugging capabilities to ensure they operate effectively. How can enterprises balance trust in AI agents while acknowledging the technology is still evolving? Gelman: Start simple and set clear guardrails. Build an AI agent that does one task reliably, then expand from there. Once you’ve proven the technology’s capability, you can layer in additional tasks, eventually creating a network of agents that handle multiple responsibilities. Right now, most organizations are still in the proof-of-concept phase. Some companies are using AI agents for more complex tasks, but for critical areas like financial services or healthcare, humans remain in the loop to oversee decision-making. It will take time before we can fully hand over tasks to AI agents. AI Agents Interview What is the difference between Google’s AI agent and Microsoft Copilot? Gelman: Microsoft Copilot is a product designed for business users to assist with personal tasks. Google’s approach with AI agents, particularly through Vertex AI, is more focused on API-driven, developer-based solutions that can be integrated into applications. In essence, while Copilot serves as a visible assistant for users, Vertex AI operates behind the scenes, embedded within applications, offering greater flexibility and control for enterprise customers. The real potential of AI agents lies in their ability to execute a wide range of tasks at the API level, without the limitations of a low-code/no-code interface. 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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