With the rapid advancement of Artificial Intelligence, Large Language Models (LLMs) have become indispensable in Question Answering (QA) systems, enhancing response efficiency and reducing human workload, particularly in customer service. The rise of Vietnamese LLMs (ViLLMs) has positioned lightweight open-source models as the preferred choice due to their efficiency, accuracy, and privacy advantages. However, systematic evaluations of their performance in domain-specific contexts remain scarce, making it challenging for enterprises to identify the most suitable LLM for customer support applications, especially given the lack of benchmark datasets reflecting real-world customer interactions. To bridge this gap, we introduce Customer Support Conversations Dataset (CSConDa), a high-quality benchmark comprising over 9,000 QA pairs, meticulously curated from customer interactions with human advisors at a large-scale Vietnamese software company. Covering diverse service-related topics, including pricing inquiries, product availability, and technical troubleshooting, CSConDa serves as a representative dataset for evaluating ViLLMs in real-world scenarios. Furthermore, we present a comprehensive evaluation framework, bench-marking 11 lightweight open-source ViLLMs on CSConDa using not only well-suited automatic metrics but also an in-depth syntactic analysis to uncover their strengths, weaknesses, and underlying linguistic patterns. This analysis provides insights into model behavior, explains performance variations, and identifies critical areas for improvement, guiding future advancements in ViLLM development. Thus, by establishing a robust benchmark for LLM-driven customer service applications, our work provides a quantitative evaluation dataset and a comprehensive ViLLM performance comparison, offering key insights into intrinsic model performance, including accuracy, fluency, and consistency, while enabling informed decision-making for next-generation QA systems. Our dataset is publicly available on Hugging Face.

"Enterprises are trying to rush to figure out how to implement or incorporate generative AI into their business to gain efficiencies," says Will Fritcher, deputy chief client officer at TP. "But instead of viewing AI as a way to reduce expenses, they should really be looking at it through the lens of enhancing the customer experience and driving value." Doing this requires solving two intertwined challenges: empowering live agents by automating routine tasks and ensuring AI outputs remain accurate, reliable, and precise. Generative AI's potential impact on customer support is twofold: Customers stand to benefit from faster, more consistent service for simple requests, while also receiving undivided human attention for complex, emotionally charged situations. For employees, eliminating repetitive tasks boosts job satisfaction and reduces burnout.The tech can also be used to streamline customer support workflows and enhance service quality in various ways, including: Automated routine inquiries: AI systems handle straightforward customer requests, like resetting passwords or checking account balances. Real-time assistance: During interactions, AI pulls up contextually relevant resources, suggests responses, and guides live agents to solutions faster.

I might have inadvertently insulted Bret Taylor and Clay Bavor when I interviewed them about their new AI startup last week. Their new company, Sierra, is developing AI-powered agents to "elevate the customer experience" for big companies. Among its original customers are WeightWatchers, Sonos, SiriusXM, and OluKai (a "Hawaiian-inspired" clothing company). Sierra's eventual market is any company that communicates with its customers, which is a pretty big opportunity. Their plan strikes me as a validation of the widely voiced prediction that 2024 will be the year when the AI models that have bended our minds for the past year will turn into real products.

In today's digital age, marketing has taken on a completely different approach with the shift towards social media and online interactions. ChatGPT is one such tool that can enhance the digital marketing game. ChatGPT is a chatbot that is powered by advanced AI technology, and it is designed to provide unique and personalized user experiences. With the use of ChatGPT, digital marketers can leverage its capabilities to create a more interactive and engaging environment for potential customers. By automating communication processes and being available 24/7, ChatGPT can handle a multitude of tasks such as lead generation, customer interactions, and queries.

With the exponential growth of the digital age, Contact Center Software has become the primary repository of customer interaction data. To maintain a competitive edge in this dynamic industry, it is crucial to leverage the availability of enormous data. With the power of Machine learning and the d brands can understand their customers better. C-Zentrix, with its innovative machine learning capabilities, is empowering businesses to achieve these goals by automating processes, reducing costs, and enhancing customer satisfaction. Machine learning (ML) is a subset of artificial intelligence (AI) that involves the use of algorithms and statistical models to enable computer systems to learn from data, identify patterns and make decisions without explicit instructions.

CONTACT centers in the Philippines have long been the driving force behind the exponential growth of the business process outsourcing (BPO) industry, providing superlative customer service to companies around the world. However, with the advancement of technology, outsourcing providers are now turning to Artificial Intelligence (AI) and advanced data analytics to enhance the Customer Experience (CX). Advanced analytics, including machine learning (ML), allows computers to learn and improve their performance without being explicitly programmed. In call centers, these technologies can be used to analyze customer interactions and identify patterns, allowing for a more personalized and efficient customer service experience. For example, a company can use advanced analytics to examine customer interactions and identify common complaints or issues; the company can then proactively address these concerns and improve the customer experience still further.

It can also help small- and medium-sized businesses (SMBs) sell smarter and more efficiently, regardless of a company's resources. In the very near future, I imagine a world in which SMBs use generative AI through Sales Cloud to streamline the sales process and close more deals faster and with fewer resources. Capabilities like automated, AI-generated proposals and customer communications, along with predictive sales modeling, will give SMBs even more powerful tools to help them provide great customer experiences, manage operating expenses, and achieve sustainable growth. Generative AI is technology built on pre-trained, large-language models that help users create unique text, images, and other content from text-based prompts. Although it has the potential to transform sales, it will face several hurdles before it can become mainstream.

AI-powered conversational commerce is quickly becoming a widely used tool to provide more efficient and personalized customer service. According to a recent study by Juniper Research, AI-powered chatbots are predicted to play a significant role in customer interactions over the next few years, handling 70% of customer conversations in 2023. This demonstrates the growing reliance on AI-powered tools to improve customer interactions and create a more seamless shopping experience. AI-powered conversational commerce will take ecommerce to the next level in 2023, benefiting customer and retailer alike.

Check out all the on-demand sessions from the Intelligent Security Summit here. As the world increasingly relies on technology, the way we shop has also undergone a significant transformation. Gone are the days of physically visiting a store to make a purchase -- now, we can shop from the comfort of our homes, thanks to ecommerce. However, even ecommerce-based shopping is set to change with the emergence of AI-powered conversational commerce. In retail, artificial intelligence is quickly becoming a widely used tool to provide more efficient and personalized customer service.

Consumer expectations are being set by voice assistants like Siri, Google Assistant, and Alexa. And we're coming to expect this same type of interaction and rapid response when we communicate with businesses. Given this, solutions like conversational AI will soon be a requirement for every company's contact center. Conversational AI enables consumers to interact with computer applications as they would with humans, similar to our experiences with digital assistants in the home. With conversational AI, organizations can replace inadequate chatbots and unwieldy interactive voice response (IVR) menus and simply ask customers, "How can I help?" -- and then get them to the right place.