In the ever-evolving landscape of customer-centricity ,  the Voice of the Customer (VOC) emerges as a key driver, intricately woven into the fabric of Customer Experience (CX). This article explores the critical role of VOC in support teams, presenting a structured sequence of steps to implement a robust VOC program. From defining its purpose to fostering collaboration with key stakeholders, each step contributes to a transformative journey toward enhancing customer satisfaction and loyalty.  The Strategic Blueprint for VOC Success   The Strategic Blueprint for VOC Success 1. Defining the VOC Program  and Its Purpose   The foundation of any successful VOC initiative lies in a clear understanding of its purpose. Articulate the goals, scope, and intended outcomes to ensure alignment with broader customer experience objectives.  2. Identifying Target Customers Crafting a comprehensive list of   target customers ,  with criteria set collaboratively by support teams and management, establishes a focused approach. This step lays the groundwork for targeted feedback collection.  3. Collaboration with Account Management Engage with the Account Management team to glean  insights into customer backgrounds,  product nuances, and overall health. Effectively communicate the VOC program’s objectives to build a shared understanding and commitment.  4. Timing Is Key Assess the readiness of both internal teams and customers. Collaborate with stakeholders to determine the optimal timing for initiating the VOC program, ensuring it aligns with customer touchpoints.   5. Crafting a Pre-VOC Interview Checklist Prepare a comprehensive checklist to streamline pre-VOC interactions. This step ensures that all necessary groundwork is laid before engaging customers  in meaningful conversations.  6. Designing an In-Depth Questionnaire Construct an interview questionnaire encompassing critical categories such as Support, Product, Account Management, Cloud Maturity, and Leadership. Include a numeric section mirroring Net Promoter Score (NPS) questions for quantitative insights.  7. Gathering and Analyzing Feedback Consolidate feedback from customers and collaborate with cross-functional teams, including Account Management, Product Management, and Engineering. This collaborative approach ensures a holistic evaluation of customer sentiments.   8. Creating an Action Plan Translate feedback into actionable insights. Work in tandem with Account Management, Product Management, and Engineering teams to formulate a strategic action plan that addresses identified areas of improvement.  9. Closing the Loop Transparent communication is key. Share the action plan with customers through Quarterly Business Reviews (QBRs) or emails, closing the feedback loop. This not only demonstrates responsiveness but also reinforces the commitment to customer success. The AI (Artificial Intelligence) Frontier: VOC in the Digital Realm   In the era of artificial intelligence, extending the principles of VOC to the digital landscape becomes imperative. Establishing a Customer Advisory Board grouped by customer journey facilitates a structured approach to gathering insights, including Customer Effort Score (CES),   Customer Satisfaction (CSAT) , feedback, and bug reports.  VOC Emerges as a Key Driver Sharing scores, input, and roadmaps derived from the VOC program ensures a collaborative relationship between support teams and customers. This AI-driven extension of VOC not only enhances customer understanding but also positions support teams as proactive partners in the evolution of products and services.   In conclusion, the strategic implementation of a VOC program is not just a methodology; it is a commitment to continuous improvement and customer success. By following the outlined steps and embracing the digital frontier, support teams can leverage the power of customer insights to drive meaningful change, foster loyalty, and stay at the forefront of the ever-evolving CX landscape.  Learn more: Uncovering Trends and Redefining Success in Customer Support with AI-Powered Precision Voice of the Customer

As we wrap up a year of buzz, breakthroughs, and a healthy dose of reality checks, it's clear that the AI landscape is evolving—and so are expectations. Dr. Martin De Saulles’ insightful article, What to Expect from AI in the Enterprise in 2025 , paints a fascinating picture of where AI is heading. At Ascendo AI, we see these trends through a Technical Support lens, where efficiency, personalization, and customer experience intersect. Let’s unpack what these insights mean for AI-driven Technical Support and how agentic AI platforms like ours are redefining the game.  Slow and Steady: Why AI in Technical Support is Poised for Transformation in 2025 Beyond Hype: Building with Purpose   De Saulles reminds us that AI's purpose isn’t to replace humans but to augment their capabilities. In Technical Support, this mindset is crucial. An AI Agent doesn’t just answer questions—it collaborates with human agents to provide faster, smarter resolutions. Think of it as a teammate: one that handles routine queries at lightning speed, surfaces insights and learns from human feedback to improve over time.  For enterprises, this shift means empowering their teams with AI tools that elevate both efficiency and expertise. By pairing human empathy with AI precision, support becomes more about building relationships and less about troubleshooting tickets.  The Data-Driven Future of AI Agents   As De Saulles highlights, proprietary data will be the secret sauce for AI success in 2025. Retrieval Augmented Generation (RAG) promises to unlock AI’s potential by combining large language models (LLMs) with company-specific data. At Ascendo AI, we’re already leveraging these techniques to create tailored AI Agents that adapt to your unique knowledge base.  But let’s not sugarcoat it: getting data “AI-ready” is a journey. From cleaning and structuring data to ensuring compliance, these foundational steps set the stage for transformative support experiences. Companies that invest now in their data assets will reap the benefits of more accurate, context-aware AI Agents in the years to come.  Efficiency Without Compromise   Cost control is another critical theme in De Saulles’ article. AI isn’t cheap, and enterprises are rightly scrutinizing ROI. That’s why at Ascendo AI, we’re committed to ensuring our platform delivers measurable value—whether through reducing ticket resolution times, improving first-contact resolution rates, or increasing customer satisfaction.  AI teammates don’t just save time; they multiply impact. Imagine an AI Agent that learns the nuances of your customers’ needs and delivers personalized solutions in seconds. That’s the kind of efficiency we’re talking about—scalable, reliable, and human-centered.  Adaptability is Key   Perhaps the most powerful takeaway from De Saulles’ analysis is the warning to avoid irrelevance. The rise of generative AI tools like ChatGPT has already disrupted industries, and Technical Support is no exception. Businesses that cling to outdated models risk being left behind.  But here’s the silver lining: adaptation breeds opportunity. By embracing agentic AI platforms, companies can turn disruption into a competitive edge. AI teammates can help support teams not only keep pace but also stay ahead by anticipating customer needs, resolving issues proactively, and unlocking new avenues for engagement.  What This Means for You   2025 won’t be a year of AI revolution; it’ll be a year of thoughtful evolution. Enterprises that treat AI as a collaborator, not a replacement, will thrive. By investing in data readiness, cost-effective AI solutions, and adaptable strategies, businesses can position themselves for long-term success.  At Ascendo AI, we’re more than just a platform—we’re your partner in transforming Technical Support. Whether you’re just starting to explore AI’s potential or looking to scale your existing strategies, we’re here to help you navigate this journey with intelligence, reliability, and innovation.  Let’s continue the conversation. How do you see AI reshaping Technical Support in your organization? What challenges are you facing, and how can we work together to solve them? Drop your thoughts in the comments or reach out to explore how Ascendo AI’s AI teammates can empower your support strategy.  Here’s to a 2025 full of collaboration, innovation, and exceptional customer experiences. Learn More: Navigating the Integration of Large Language Models (LLMs) in Enterprise: A Comprehensive Guide How to Scale Support to a Large Number of Customers?

In the dynamic world of cloud security, delivering cutting-edge solutions isn’t enough—technical support must match the pace of innovation. Anjuna Security, a trailblazer in confidential computing, faced this exact challenge. With a small team supporting a sophisticated, evolving platform, they needed a solution to streamline support processes, scale technical responses, and enhance data privacy—all without expanding headcount. That’s where Ascendo AI stepped in, transforming Anjuna’s technical support experience with AI-driven coworkers. Scaling Technical Support Smarter: Anjuna Security’s AI-Driven Success Story Tackling the Challenges of Complexity Anjuna Security’s platform relies on hardware-assisted isolation to protect sensitive data. While their technology sets new standards in security, it requires deep technical expertise to support. Adding to the challenge, their lean team needed a way to scale effectively while managing an ever-growing knowledge base. Key pain points included: Complexity:  Highly specialized products demanded a steep learning curve for support agents. Scaling Small Teams:  A small support team is needed to handle complex, high-demand inquiries. Knowledge Gaps:  Creating support content was time-intensive, often pulling valuable time from product teams. The Ascendo AI Solution Anjuna Security turned to Ascendo AI for its intelligent, reliable, and innovative AI coworker solutions. With seamless integration into Anjuna’s systems, Ascendo AI’s features brought immediate value: Knowledge Agents :  These empowered the support team with instant access to relevant information, drastically cutting onboarding times and ensuring consistency in responses. Slack Integration :  By leveraging Ascendo AI’s Slack Agent, knowledge creation became a collaborative and frictionless process, instantly accessible across the organization. Cognitive Privacy Agent:  An extra layer of privacy was introduced, ensuring data protection during AI training and operations. This collaboration resulted in faster, smarter, and more secure support processes. Results That Redefined Customer Support The impact of Ascendo AI was transformative for Anjuna Security: Speed and Efficiency:  Response times dropped significantly, with faster resolutions even for complex inquiries. Knowledge on Demand:  Support teams could create knowledge articles directly from Slack interactions, building a robust, real-time support knowledge base. Enhanced Data Privacy:  Anjuna’s platform, combined with Ascendo AI’s Cognitive Privacy features, reinforced customer trust in data security. Key Metrics Time-to-Resolution:  Drastically reduced, boosting customer satisfaction. First-Touch Resolutions:  Increased, enabling the team to handle more cases efficiently. Support KPIs:  Overachieved, showcasing the value of AI-driven support. A Customer’s Perspective A Partnership for the Future Anjuna and Ascendo AI are just getting started. Their collaboration will continue to drive advancements in privacy, security, and customer support. By leveraging Ascendo AI’s predictive insights, the partnership aims to resolve issues before they arise, proactively addressing customer needs. With plans to expand AI-driven knowledge creation and further enhance privacy capabilities, Anjuna Security’s future looks as secure and innovative as its platform. Ready to Transform Your Support? Anjuna Security’s success story is a testament to the power of AI in reshaping customer support. Want to see how Ascendo AI can elevate your operations? Let’s explore what’s possible—together. Learn More: The Future of AI in Technical Support: Big Ideas for 2025 Why 2025 Will Redefine Technical Support: The Role of AI Teammates in Driving Efficiency

The field service industry is at a pivotal moment. As technology reshapes how we approach maintenance, troubleshooting, and customer interaction, the question isn't if organizations should embrace these changes but how they can do so effectively. Johann Diaz’s recent insights in “ Upskilling the Field Service Workforce: Preparing for a Less Hands-On Future ”  spotlight the importance of preparing today’s technicians for tomorrow's AI-driven demands. At Ascendo AI, we see this transformation as a chance to redefine what exceptional support looks like—with AI teammates leading the charge.  Revolutionizing Field Service: The Role of AI in Empowering Technicians AI: From Tools to Teammates   For decades, field service technicians relied on intuition and experience, often navigating reactive repair cycles with traditional tools. But the game has changed. As Diaz puts it, technicians must “swap toolbelts for tech platforms, intuition for insights, and reactive repairs for proactive, AI-driven service delivery.” This evolution aligns perfectly with the role of Ascendo AI’s intelligent AI Agents .  Our AI Teammates aren’t just tools—they're collaborators. These digital colleagues empower technicians to:  Access Instant Insights : AI agents analyze vast datasets in real-time, enabling predictive maintenance and issue anticipation before problems escalate.  Streamline Operations : By automating repetitive tasks like logging service calls or generating reports, AI frees technicians to focus on strategic, high-value activities.  Enhance Customer Interactions : With AI agents providing contextual information and empathetic responses, technicians can deliver faster, more personalized solutions.  Upskilling: A Strategic Imperative   As Neil McGeoch from ServiceNow  points out, “90% of organizations will face IT skills shortages by 2025.” This statistic underscores the urgency to upskill field teams—not just to use new tools but to embrace new ways of working. At Ascendo AI, we champion this mindset shift. Upskilling isn't about replacing human expertise; it’s about augmenting it. AI agents become co-pilots, guiding technicians through complex processes while enabling them to develop higher-value skills like data analysis and customer empathy.  From Reactive to Proactive Support   Vodafone’s success story, highlighted in Diaz’s article, exemplifies how AI-powered systems transform technicians into proactive problem-solvers. By leveraging IoT data and predictive analytics, Vodafone trained its teams to anticipate customer needs and address them before issues arose. This proactive approach not only reduced downtime but also elevated customer satisfaction—a testament to the power of AI-enabled upskilling.  At Ascendo AI, we take this a step further. Our AI teammates don’t just assist; they learn and adapt, becoming smarter with every interaction. This ensures that technicians are always equipped with the most relevant, actionable insights, driving operational efficiency and delighting customers.  Overcoming Challenges with Collaboration   Resistance to change is natural. Many technicians wonder, “Why do I need to learn AI when I’ve been fixing these systems for decades?”  Diaz’s solution—storytelling—resonates with us. By demonstrating how AI secures careers and enhances capabilities, organizations can inspire even the most skeptical employees.  We believe collaboration is key. At Ascendo AI, our AI agents work alongside technicians, mentoring them in real-time, much like a seasoned colleague would. This symbiosis reduces resistance and accelerates adoption, ensuring a smoother transition to an AI-augmented workforce.  Building a Future-Ready Workforce   As we move toward 2030, the field service landscape will continue to evolve. Robotics, AI copilots, and drones will take on routine tasks, while human technicians will focus on strategic, creative problem-solving. But as Diaz aptly states, “The future is less hands-on, but it’s not less human.”  At Ascendo AI, we couldn’t agree more. Our mission is to ensure that AI teammates enhance—not replace—the human touch. By investing in continuous learning and adopting intelligent AI systems, organizations can stay competitive, exceed customer expectations, and empower their workforce to thrive in this new era.  The future of field service is here. Is your team ready to embrace it? Explore how Ascendo AI ’s Agentic AI platform can transform your support strategies, streamline operations, and empower your workforce. Let’s reimagine what’s possible—together.  Learn More: Bridging the AI Knowledge Gap: Transforming Support Strategies with AI Teammates Navigating the AI Frontier: Transforming Technical Support Through Intelligent Automation

In the realm of AI-powered conversations , a persistent challenge has been the limitations posed by rule-based AI chatbots. However, we are excited to announce a significant breakthrough with our ResolveGPT—our AI Chat has undergone a remarkable upgrade with customer needs and preferences, now boasting Gen AI capabilities. This upgrade addresses the challenges of rule-based systems and elevates user interactions to unparalleled levels of customization and precision. Let us delve into these cutting-edge updates that are set to revolutionize the Artificial Intelligence experience. Overcoming the Challenge of Rule-Based Chatbots: Unveiling Gen AI Capabilities Context Option: Tailoring Conversations to Your Needs Our latest innovation, the "Context Option," serves as a powerful solution to the limitations of rule-based chatbots. This groundbreaking feature allows users to finely tune their interactions with the AI BOT by selecting specific data sources and grouping them into contexts. Imagine having a tailored Sales context or a Technical Support context - the choice is now yours. Based on your selection, you receive prediction results that precisely align with your chosen context. Customization is at your fingertips. Users can effortlessly switch between contexts with a simple click on the Context icon. This seamless context switching ensures that the AI Bot's focus matches your evolving questions or objectives, overcoming the rigid nature of rule-based chatbots. By incorporating context, you can anticipate highly accurate, tailored responses that align precisely with your intent, enhancing efficiency and satisfaction. Dynamic Context Switching: Precision on the Fly The challenge of rigidity is further conquered with dynamic context switching, allowing users to change the context of their query in the middle of an interaction with the AI Bot. Imagine troubleshooting an issue and receiving detailed steps along with a part that needs replacement. Need assistance ordering the part? Simply switch the context and get guidance on ordering, configuring, and integrating the part, all within the same conversation. No more sifting through multiple manuals—our AI Bot is your adaptable and comprehensive solution. Simple Start Option: Effortless Interaction Management To address the challenge of inflexibility in managing conversations , we've introduced the 'Simple Start' option. Users can now initiate a new conversation within an ongoing interaction seamlessly. Whether the conversation veers off-topic, or you have multiple questions, this option ensures a fluid and organized dialogue, conquering the rigidity often seen in rule-based chatbots. Tailored Results with Solution Display Preference Your preferences matter to us. In our intelligent AI Bot, we have introduced the 'Solution Display Preference' feature. Choose whether you want to view the top results from each data source or see all data sources for a comprehensive result. This level of control ensures that you receive information tailored to your needs, delivering a personalized and efficient interaction with the AI Bot, overcoming the limitations imposed by rule-based systems. Try It Now and Embrace the Future! Excited to experience the future of AI conversations? Try out these new enhancements and witness firsthand how they overcome the challenges of rule-based chatbots, providing a dynamic, user-centric experience with our ResolveGPT. The context switch significantly enhances the built-in Context engine, making conversations intuitive and user-friendly. These expanded capabilities ensure that every conversation with Ascendo AI Bot is a tailored and efficient experience, empowering you to optimize your workflow and enhance overall satisfaction. Ready to redefine the way you interact with AI? Go ahead and try these new features. If you need assistance setting them up, reach out to us—our team is here to help. The future of AI-driven interactions is now, and Ascendo AI Bot is at the forefront, leading the way into a new era of seamless and user-centric conversations. Learn more What sets Ascendo Apart? Revolutionizing Customer Support with Ascendo AI and SAP Service Cloud

In today's rapidly evolving business landscape, the integration of AI tools, particularly Large Language Models  (LLMs), has become indispensable for enhancing operational efficiency and staying competitive. However, this technological advancement brings along significant responsibilities and challenges, necessitating a nuanced approach toward its adoption.  Navigating the Integration of Large Language Models (LLMs) in Enterprise: A Comprehensive Guide Businesses are increasingly leveraging LLMs to reshape customer interactions, refine sales strategies, and streamline administrative tasks. These AI-powered tools  automate processes like lead scoring and provide instant call summaries with actionable insights, revolutionizing traditional workflows. Yet, as the potential of LLMs unfolds, it is imperative to acknowledge and address the accompanying risks.  The cornerstone of LLM (Large Language Models) integration lies in data – the most valuable asset in today's digital economy. As businesses entrust sensitive data  to LLMs, they must navigate complex data  custody issues. This demands a new playbook from solution providers, emphasizing the utmost importance of security and privacy.  Framework of Questions to Kick-Start To navigate these challenges, initiating transparent conversations with technology partners is paramount. Here is a framework of questions to kick-start these discussions:  Data Privacy Assurance : How do you guarantee that LLM answers derive solely from my data?  Data Usage and Accessibility : Are my LLM interactions used for training purposes? How accessible is my data outside my organization, and does this comply with my data privacy policy?  Security Measures : How do you prevent confidential data exposure to unauthorized individuals, both outside and inside my organization, capable of manipulating LLMs?  Accuracy and Error Mitigation : How do you ensure LLM accuracy and address inaccuracies, such as hallucinations?  Performance Benchmarks : What are your performance benchmarks for LLM interaction?  Beyond these initial discussions, businesses must also consider broader ethical implications, regulatory compliance, and practical implementation strategies: Ethical Considerations : Exploring the ethical implications of LLM usage, including biases and potential misuse, is essential for responsible AI deployment.  Regulatory Compliance : Adhering to regulatory frameworks such as GDPR ( General Data Protection Regulation ) or CCPA ensures that LLM integration aligns with legal requirements and protects consumer rights.  Practica l Implementation: Providing actionable strategies   for data anonymization, employee training, and cybersecurity measures to enhance the seamless integration of LLMs into existing workflows.  Moreover, incorporating real-life examples, case studies, and visual aids can enrich the discussion, making it more relatable and accessible to readers.  At Ascendo ,   we have an AI workshop  that caters to all of the above.  In conclusion, as Enterprises embark on the journey of integrating LLMs into their operations, prioritizing data privacy, security, and ethical considerations is paramount. Transparent communication  with technology partners, adherence to regulatory guidelines, and a proactive approach toward addressing challenges will pave the way for successful and responsible AI adoption. Let us navigate this transformative era with caution, foresight, and a steadfast commitment to ethical AI practices.  Learn More Why do we take SOC 2 seriously? How to Scale Support to a Large Number of Customers?

In the rapidly evolving landscape of technical support, artificial intelligence (AI) is no longer just an innovative tool—it's an essential component driving efficiency and enhancing customer experience. At Ascendo AI, we recognize the transformative power of AI agents and AI teammates in reshaping how businesses approach technical support. Drawing insights from a recent article  by DELL Technologies and NVIDIA, we explore how these advancements are not just meeting current industry demands but are also paving the way for future innovations.  Navigating the AI Frontier: Transforming Technical Support Through Intelligent Automation The AI Implementation Paradox Recent insights from a collaborative report by Dell Technologies and NVIDIA shed light on a critical industry challenge: while nearly every enterprise recognizes AI's potential, most struggle to implement it effectively across their organizations. The statistics  are telling—94% of IT decision-makers grapple with ethical implications and 50% face significant integration obstacles.  But here's what truly matters: These challenges are not roadblocks, but opportunities for strategic innovation.    Breaking Down the Barriers   Our experience at Ascendo AI has revealed three fundamental insights for successful AI integration:  Strategic Use Case Identification  AI isn't about wholesale replacement, but intelligent augmentation. Whether it's creating responsive chatbots or automating complex technical documentation, the key is targeted, purposeful implementation.  Infrastructure Flexibility  Modern AI solutions require adaptable, scalable infrastructure. Our  AI agents  are designed to seamlessly integrate across edge, cloud, and data center environments, providing the flexibility enterprises desperately need.  Continuous Learning and Adaptation  The most powerful AI platforms aren't static—they're dynamic ecosystems that continuously learn, improve and align with evolving organizational needs.  The Ascendo AI Approach: AI Teammates, Not Just Tools   We don't just provide AI solutions; we create AI teammates. Each of our intelligent agents is designed to:  Understand complex technical contexts  Provide nuanced, accurate support  Learn and improve with every interaction  Maintain absolute data privacy and ethical standards  Beyond Automation: Intelligent Collaboration   The Dell Technologies report highlights a critical point: 75% of organizations fail when attempting to build in-house AI agents. This isn't a limitation—it's an invitation to reimagine support strategies through collaborative intelligence.  Our AI agents aren't replacements for human expertise. They're amplifiers, extending your team's capabilities, handling routine tasks, and freeing your most valuable resource—human creativity and complex problem-solving—to focus on strategic initiatives.  Embracing Change: A Call to Action   As we look ahead, it’s clear that the integration of AI into customer service is not merely an option; it’s a necessity for companies aiming to stay competitive. The insights from DELL Technologies and NVIDIA remind us that while challenges remain—such as data management and tool limitations—the benefits far outweigh them. Organizations that embrace these changes will not only improve operational efficiency but also enhance customer satisfaction and loyalty.  At Ascendo AI, we encourage businesses to explore how our agentic AI platform can transform their support strategies. By leveraging the power of AI agents and teammates, organizations can create a more responsive, personalized, and efficient customer service experience. As we continue to innovate and collaborate with our partners, we invite you to join us on this journey towards redefining technical support in the age of artificial intelligence.  In conclusion, the future of customer service is bright with possibilities. Let’s harness the power of AI together to create exceptional experiences that not only meet but exceed customer expectations. The time to act is now—let's lead the way into this exciting new era of intelligent technical support.  Learn More: AI Agents: Redefining Technical Support in the Digital Era Beyond the Hype: How AI Can Become Your Reliable Teammate in Technical Support

Navigating Support Strategies for software solutions In the ever-evolving landscape of software solutions, managing support  for both cloud-hosted and customer-hosted software can be quite a challenge. At Ascendo AI , we believe in transparent communication and effective practices to ensure both our customers and support teams have the best experience possible. Let’s explore some strategies and insights shared by our community members on handling support requests for beta software versions.  Support for Betas: Setting the Right Expectations   When launching a beta product, it's crucial to set clear expectations for your  customers . At Ascendo AI, we communicate upfront that the product is in its beta stage. This transparency helps us manage expectations while we actively monitor the  Voice of the Customer (VOC).  We use this feedback  to prioritize feature  requests and refine the product’s usability, aiming to delight our customers so much that they’re eager to transition to the paid model.  Choosing Between Private and Public Beta Programs   Deciding whether to run a private or public beta depends on your goals:  Private Betas : These are great for evaluating specific features with a select group of customers. A private beta allows us to gather detailed feedback from a controlled environment, which is invaluable when refining specific functionalities.  Public Betas : These are more suited for broader adoption goals. A public beta encourages widespread feedback and is particularly effective when you want to test the market and gain diverse insights.  By understanding the distinctions and purposes of each type, you can better manage expectations and allocate  resources  effectively.  Handling Beta Support Requests: Streamlined and Efficient   At Ascendo AI, every interaction—including beta feedback —is meticulously tracked within our  CRM  system. This unified approach ensures that all feedback is considered, but traditional support tickets  are only generated if an issue persists and needs to be tracked as a long-term JIRA bug. This method not only streamlines our process but also maintains focus on the most pressing issues. We do have options to differentiate beta-related interactions if necessary. For more detailed insights, feel free to reach out directly.  Enablement for Support Teams: Empowerment Through Training and Tools   To handle beta support requests effectively, our support engineers  are equipped with comprehensive training , detailed documentation, and advanced tools. At Ascendo AI, we leverage AI tools to generate knowledge  from every interaction, whether it's with the product team, marketing, or directly with customers. This continuous learning  approach ensures that our support teams are always up-to-date, ready to handle new challenges, and capable of providing top-notch support.  Direct Routing to Engineering: Prioritizing What Matters Most   Our AI-driven  VOC  tool is a game-changer in managing beta feedback. It categorizes feedback based on various factors such as customer segment, product category, and the intensity of the issue. This data-driven  approach helps us prioritize engineering efforts, ensuring that the most critical feedback is addressed promptly. This not only optimizes product development but also significantly enhances customer satisfaction .  How does your company manage beta support? Share your strategies and see how they compare with the best practices discussed.    Community Insights: Different Perspectives on Beta Programs   Here are some valuable perspectives shared by our community members:  Jared : “From my experience, a public beta often means no formal support is provided. However, if you're looking for meaningful feedback from a select group of beta customers, it’s important to choose them carefully and provide a clear engagement strategy. This could involve close collaboration with a dedicated team, including developers, to address issues for mutual benefit.”  Kay : “All beta customers are potential paying customers, so they should receive the same level of support they would get after becoming a paying customer. In today's AI-driven world, virtual agent support is a minimum we can provide for everyone.”  These insights reflect the diverse ways companies approach beta programs, each with its unique strategy to balance customer satisfaction and product development.  Learn more: The Future of Customer Service: Generative AI CRM Copilots Tips to transition from Self-Assign to Automatic Assignment

In the evolving world of technical support and field service, compensation trends have become increasingly complex. As the economy shifts and the labor market adapts, understanding these trends is crucial for professionals in the industry, especially those in senior support roles. At Ascendo AI, we’re committed to keeping a pulse on the most relevant insights and developments in this space, and today, we want to delve into a comprehensive look at U.S. salary trends and how the role of AI is shaping compensation.   Navigating Salary Trends in Support and Service: The Impact of AI on Compensation The Growing Importance of AI in Salary Trends   Recent research paints a clear picture of the current state of U.S. compensation, with some interesting shifts in the support and service sectors. According to several reports, salaries have seen steady growth in the past few years. The average salary reached $5,000 per month by Q3 2024, up from $4,330 in 2021. Yet, despite these increases, many employees report dissatisfaction with their compensation—especially when accounting for inflation and the rising costs of living. This dissatisfaction has led to an important question: How can AI help drive more meaningful improvements in compensation?  AI-driven support solutions, like the ones we champion at Ascendo AI, are transforming how businesses approach service delivery. By automating repetitive tasks, optimizing workflows, and providing deeper data-driven insights, AI frees up senior support specialists to focus on higher-value work. This shift not only enhances operational efficiency but also increases the potential for better compensation structures as companies recognize the value of their human talent.  Salary Growth and Employee Expectations   Looking closely at some key statistics:  The average salary in the U.S. grew steadily over the last few years, reaching $5,000 per month by 2024 (Source: Consumer Shield ).  Salary increase budgets are expected to remain strong, with an average of 3.7% projected for 2025, slightly down from 3.8% in 2024, yet still higher than pre-pandemic norms (Source: WTW ).  Despite these increases, many employees remain dissatisfied, with 32% expressing discontent with their most recent salary raise (Source: BambooHR ).  Senior support specialists in the U.S. typically earn between $71,000 and $106,515 annually (Source: Zippia ).  For senior support professionals, these statistics reflect an important trend: While overall salaries are rising, many are still struggling to keep pace with inflation, especially with the increasing burden of living costs. In the context of AI’s growing role in technical support, these professionals are in a unique position to benefit from not only higher efficiency but also a potential shift in compensation strategies that more closely align with their evolving contributions.  The Gender Pay Gap and Opportunities for AI Integration   Another statistic that stands out is the persistent gender pay gap. In 2023, men received an average salary increase of 4.9%, while women saw only 3.5%. This disparity is something we cannot overlook in our discussions about compensation, especially as the workforce becomes more dynamic and diverse. By integrating AI into the support and service space, we can help level the playing field by creating fairer, data-driven approaches to salary allocation, ensuring that performance and value are the key drivers of compensation decisions, not gender or other biases.  These insights into the gender pay gap are taken from various reports, such as the findings in The Conference Board’s Salary Increase Projections  and other salary studies that highlight ongoing disparities in compensation across different demographics.  The Role of AI in Shaping Future Compensation Trends   Ascendo AI is currently conducting exclusive salary research  tailored specifically for senior support and service professionals. We are benchmarking salary compensation and evaluating how AI's presence is shaping the future of pay structures in this sector. The goal of our survey is not only to analyze existing compensation trends but also to uncover the real-world impact that AI is having on the salaries of technical support professionals and how these roles are evolving.  We believe that understanding the intersection between AI and compensation will empower professionals and organizations to make informed, forward-thinking decisions about talent retention, role development, and compensation strategies.  Be Part of the Conversation   The findings from this exclusive survey will serve as a critical resource in shaping compensation discussions for years to come. By participating, you’ll receive a sample copy of the report as soon as you complete the survey, and you’ll be among the first to access the full, in-depth version. More importantly, your insights will influence how senior support roles are compensated and how AI will continue to impact the future of work in this space.    Take the Survey   At Ascendo AI, we’re dedicated to bringing innovative AI solutions to the forefront of technical support and field service. We understand the importance of fair, transparent compensation practices, and we are committed to helping guide the industry toward a future where both technology and human talent are valued equally.  Final Thoughts   As we navigate the future of work in the technical support and field service sectors, understanding salary trends and the role of AI is essential. We invite you to join us in this pivotal research—your voice can help shape the future of compensation, roles, and AI integration in the industry. Together, we can ensure that professionals in this space are not just supported by technology but are rewarded in a way that reflects their value.  Stay tuned for the upcoming insights from our research, and feel free to fill out the survey today to be part of this important conversation!

In today's fast-paced digital landscape, efficient and effective support services are crucial for any organization. Leveraging the power of  artificial intelligence (AI)  and data correlation, support teams can transform their knowledge base  and streamline content creation  processes.   Enhancing Support Efficiency with AI-Powered Correlation and Content Optimization Strategy Overview   Identifying Common Issues and Solutions:  By analyzing case data , we can pinpoint prevalent customer challenges  and create targeted content that addresses these issues head-on. This ensures the knowledge base  is populated with relevant information for future inquiries.  Understanding Customer Needs and Trends:  Data analysis allows us to identify emerging trends and customer needs, enabling proactive content development. Keeping the knowledge base up-to-date and aligned with current trends enhances its value significantly.  Improving Content Quality and Accuracy:  By comparing case data against existing articles, we can identify content gaps or inaccuracies. This continuous improvement process ensures that the  knowledge base  remains accurate and relevant.  Optimizing Searchability:  Analyzing frequently used keywords in case data informs content tagging and titling strategies. This makes content more discoverable for both customers and support agents , leading to quicker resolutions.  AI-Powered Correlation and Content Optimization Enhancing Self-Service Options:  Insights derived from case data guide the creation or update of FAQs, how-to guides, and troubleshooting articles. Empowering customers with self-service  resources reduces reliance on direct support.  Customizing Training Materials:  Identifying recurring themes in case data allows for the development or customization  of training materials for support agents. Focusing on the most pertinent issues ensures effective training outcomes.  Facilitating Product Improvements:  Correlated case data serves as invaluable feedback for product development. By identifying areas for enhancement, we can mitigate similar issues in the future.  Supporting Personalized Support:  Creating content tailored to specific customer  segments or product lines promotes personalized and relevant support experiences, fostering customer satisfaction.  Value Proposition   Implementing this comprehensive data correlation and content optimization strategy offers numerous benefits, including:  Reduced Time and Resources:  Less time spent on repetitive inquiries frees up resources  for more complex issues.  Improved Customer  Satisfaction:  Relevant and accessible content empowers customers  and leads to higher satisfaction levels.  Empowered User Base:  A well-maintained knowledge base  fosters a knowledgeable  and self-reliant user community.  Increased Content Publish Rate:  By correlating content and identifying  patterns , we can ensure that a higher percentage of case data is transformed into valuable knowledge base articles .  Conclusion   By leveraging AI-Powered Correlation and Content Optimization, support teams can revolutionize their knowledge base and deliver superior customer experiences . This strategic approach ensures that every piece of content is valuable, actionable, and aligned with customer needs, leading to increased efficiency, customer satisfaction, and product improvement.  Are you ready to transform your support services? Embrace the power of AI  and data correlation to unlock a new era of support excellence.  Learn more: The Future of Customer Service: Generative AI CRM Copilots Tips to transition from Self-Assign to Automatic Assignment