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You’ve decided to outsource customer service to a third-party provider. Now you just have to choose which one—and where. Today, we will explore how call centers in the USA have an advantage when adhering to regulatory compliance. We’ll look at several key regulations that affect call center compliance. We’ll also discuss the hidden costs and challenges of working with an offshore service provider.
Image by Gerd Altmann from Pixabay Throughout my career in the contact center, I’ve had a love-hate relationship with quality assurance (QA). I was already two years into a role as a customer support manager when I hired someone with actual contact center experience (I had none) who informed me that I should be “doing quality.” He helped me create a basic form with a somewhat elaborate scoring system and I began scoring my team’s interactions with customers.
So, you’ve been handed responsibility for investigating the benefits of potentially outsourcing your company’s customer service for the first time. How do you start to compare your in-house apples to those outsourced oranges? What math should go into the business case around call center outsourcing costs? (Or if you’re keen on delegating that chore, skip this read and contact us today for a cost analysis of your center !
Every year, $75 billion is lost to bad customer service — and your business could be bleeding loyalty without realizing it. AI is rewriting the rules. Imagine instant answers, 24/7 self-service, faster resolutions, and skyrocketing satisfaction scores. Companies like Amazon are already cashing in, and the technology is easier than you think — plug, play, and profit.
Learn more about Colin Shaw : Join over 80,000 people on our LinkedIn Newsletter list or visit our website for more great podcast episodes. Listen to the podcast: Customer research is an essential part of managing their experiences to foster customer loyalty. However, many firms look at customer research as a one-and-done project. Worse, they often don’t know what to ask to find out what they want to know.
What are customers seeking when they contact a CSR? It’s a no-brainer that the secret sauce to success in customer service has one evident and basic element: clear and understandable communication. It’s pretty hard to come to terms if there’s a gap in getting the message across let alone indulge in troubleshooting issues. Therefore, the requirements set to contact center agents are crystal clear - a high level of the language they are working with and a good accent, and the accent of an agent is
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What are customers seeking when they contact a CSR? It’s a no-brainer that the secret sauce to success in customer service has one evident and basic element: clear and understandable communication. It’s pretty hard to come to terms if there’s a gap in getting the message across let alone indulge in troubleshooting issues. Therefore, the requirements set to contact center agents are crystal clear - a high level of the language they are working with and a good accent, and the accent of an agent is
Many companies still believe that customer service is what happens when something goes wrong. However, that is only one part of customer service. The bigger picture is that customer service happens throughout a customer’s entire experience while doing business with you. It starts the moment they interact with your company, and that might not even be with a live human.
Digital communications have changed drastically over the past few decades, shaping how businesses communicate. With. The post The Pros and Cons of Having A Virtual Call Center appeared first on TCN.
Have you ever heard the following? Then, Bob’s your uncle. It’s the difference between chalk and cheese. On your bike, then. If you haven’t and you don’t live in the UK, Colin wouldn’t be surprised. They are British idioms and when he employ these expressions with his American pals, they usually don’t know he is talking about. However, his friends and family on the other side of the pond do.
AI adoption is reshaping sales and marketing. But is it delivering real results? We surveyed 1,000+ GTM professionals to find out. The data is clear: AI users report 47% higher productivity and an average of 12 hours saved per week. But leaders say mainstream AI tools still fall short on accuracy and business impact. Download the full report today to see how AI is being used — and where go-to-market professionals think there are gaps and opportunities.
This episode of Amazing Business Radio with Shep Hyken answers the following questions and more: What are the challenges in creating a more customer-centric culture? How can leaders support employees in executing customer-centric initiatives? What is the key to successfully transforming work culture to better serve customers? Why must employees in all roles understand how their actions impact the customer experience, regardless of direct customer contact?
Resilience plays a pivotal role in the development of any workload, and generative AI workloads are no different. There are unique considerations when engineering generative AI workloads through a resilience lens. Understanding and prioritizing resilience is crucial for generative AI workloads to meet organizational availability and business continuity requirements.
Generative AI , such as Large Language Models (LLMs), will dramatically change multiple industries, including the service and customer experience (CX) space. This new class of technology brings incredible opportunity, as well as a new set of challenges. This post will explore the promise, the potential pains, and why you should take an optimistic view of this technology.
Spotting Customer-Centric Companies I. Introduction Envision a world where every interaction with a company leaves you feeling not just satisfied, but genuinely valued. In today’s fast-paced marketplace, this vision is a reality for some, and it all centers around the compass of customer service. As consumers, we are not merely transactional entities; we are individuals seeking experiences that resonate with us.
What does customer service excellence look like in 2024? According to our report with insights from CX expert Shep Hyken, customer expectations are at an all-time high, and there’s a bigger shift toward self-service and leveraging AI capabilities.
Each week, I read many customer service and customer experience articles from various resources. Here are my top five picks from last week. I have added my comments about each article and would like to hear what you think too. What Can Disneyland Teach Us about the Customer Journey? by Tricia Cleppe-Fortier (MyCustomer) Why is Disneyland the most magical place on earth?
Embeddings play a key role in natural language processing (NLP) and machine learning (ML). Text embedding refers to the process of transforming text into numerical representations that reside in a high-dimensional vector space. This technique is achieved through the use of ML algorithms that enable the understanding of the meaning and context of data (semantic relationships) and the learning of complex relationships and patterns within the data (syntactic relationships).
Is sales still a viable profession today? Is it something needed or that people even want to do? Many who are currently in sales positions or are considering a role in sales are beginning to question what the job really means today and whether it’s one they can be proud of — especially when it feels like their whole purpose can feel like it’s to pressure or coerce buyers into doing something.
In the rapidly advancing era of high-speed internet, fiber optics, and cutting-edge telecommunications technologies, it’s easy to overlook the humble yet remarkably resilient POTS line. Standing for Plain Old Telephone Service, the POTS line has a rich history deeply intertwined with the evolution of communication technology and has served as the steadfast backbone of telecommunication systems for decades.
Start building the AI workforce of the future with our comprehensive guide to creating an AI-first contact center. Learn how Conversational and Generative AI can transform traditional operations into scalable, efficient, and customer-centric experiences. What is AI-First? Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
Are you struggling with overcoming Call Blocking for your Call Center Business? It’s clear by now that maintaining uninterrupted channels for outbound calling is vital for any business that is aiming to grow, especially call centers. That being said, call center blockage is one of the critical issues in customer service. It occurs when a business’s communication channels are overwhelmed and unable to handle incoming contacts and calls.
With the advent of generative AI, today’s foundation models (FMs), such as the large language models (LLMs) Claude 2 and Llama 2, can perform a range of generative tasks such as question answering, summarization, and content creation on text data. However, real-world data exists in multiple modalities, such as text, images, video, and audio. Take a PowerPoint slide deck, for example.
What are the key steps to scaling your small business? Our blog uncovers the tools and strategies needed for lasting growth and a competitive edge. The post Scaling your business: Essential considerations for sustainable growth. appeared first on AnswerConnect Blog.
In 2025, contact centers aren’t just changing—they’re being rebuilt by AI. This no-fluff, executive-ready guide shows you how to capitalize on the transformation. Inside: proven ROI calculators, workforce optimization tactics, deflection strategies, and a 90-day AI deployment plan. Built for CIOs, COOs, CX leaders, and contact center strategists, it goes beyond buzzwords into play-by-play implementation.
Your customers are talking, and they have a lot to say. As a contact center leader, there’s no question you’re at the heart of the conversation. But do you know how your customers really feel about your brand, products, services, and support? If you’re not analyzing customer sentiment, you’re only getting part of the story. The whole story—the one necessary to make informed decisions about measurable CX improvements—doesn’t come from multiple-choice answers in a customer survey
When deploying a large language model (LLM), machine learning (ML) practitioners typically care about two measurements for model serving performance: latency, defined by the time it takes to generate a single token, and throughput, defined by the number of tokens generated per second. Although a single request to the deployed endpoint would exhibit a throughput approximately equal to the inverse of model latency, this is not necessarily the case when multiple concurrent requests are simultaneous
Multiple choice questions are used in almost every survey: their simplicity makes surveying easier for both creators and respondents. They’re a surefire way to gather clear, concise survey data that can be easily parsed and shared. Well-crafted multiple choice questions can fast-track surveyors to actionable findings from their survey data. Below, we cover what multiple choice questions are, types of multiple choice questions, examples, tips for writing them, and the advantages of including them
ZoomInfo customers aren’t just selling — they’re winning. Revenue teams using our Go-To-Market Intelligence platform grew pipeline by 32%, increased deal sizes by 40%, and booked 55% more meetings. Download this report to see what 11,000+ customers say about our Go-To-Market Intelligence platform and how it impacts their bottom line. The data speaks for itself!
Ransomware can spread in multiple ways, but most typically, through phishing emails or by unknowingly visiting an infected website. Ransomware can be catastrophic to your organization, preventing critical information and systems from being accessed.
One of the most useful application patterns for generative AI workloads is Retrieval Augmented Generation (RAG). In the RAG pattern, we find pieces of reference content related to an input prompt by performing similarity searches on embeddings. Embeddings capture the information content in bodies of text, allowing natural language processing (NLP) models to work with language in a numeric form.
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