Contact Centre Definitions

Adaptive customer journeys use real-time data and insights to adjust the customer experience based on individual behaviors and preferences. This dynamic approach allows companies to personalise interactions and improve engagement by delivering relevant experiences at each touchpoint.

Admin copilot focuses on providing administrative personnel in contact centres with AI-powered tools to streamline operations. This includes automating scheduling, workforce management, analytics and reporting tasks. By leveraging AI, admin copilot helps in optimising resource allocation, predicting call volumes and enhancing overall operational efficiency.

The application of sophisticated analytical tools and techniques to glean insights from data, enabling a business to identify and predict trends, understand customer behavior, and orchestrate experiences that satisfy customers and drive revenue.

Agent copilot refers to an AI-driven feature within contact centre software that assists customer service agents by providing real-time information, suggestions and automated actions. It leverages natural language processing (NLP) and machine learning to understand customer queries and guide agents with the best responses, knowledge articles or next steps, thereby improving efficiency and customer satisfaction.

Agentic AI refers to an artificial intelligence system that can make autonomous decisions and take frequent actions with minimal human intervention.

An agentic system is any software framework that shows “agency” by perceiving its environment, processing information and taking actions to meet defined goals.

Companies can enhance customer loyalty over the long term by using artificial intelligence (AI) technologies that enable them to personalise experiences, predict needs and engage customers in meaningful ways. With AI-powered technologies, companies can anticipate customer needs and provide personalised services that differentiate their brand across every interaction.

An AI call centre agent is a virtual agent powered by AI technologies designed to handle customer service interactions. It can understand and respond to customer queries, resolve issues and perform transactions. This offers a scalable and cost-effective way to handle high volumes of inbound requests without hiring additional human agents.

Leveraging artificial intelligence (AI) to coordinate and manage customer experiences across various touchpoints and channels. AI compiles and analyses customer data, finding patterns and making recommendations on the next best step for a customer based on their needs and prior actions. Using AI, a much higher level of personalisation is possible.

AI summarisation in contact centres involves the use of AI technologies to automatically summarise customer interactions such as calls, chats and emails. This helps in quickly understanding the essence of customer queries or feedback without going through the entire content, enabling faster response times and more personalised service.

The use of artificial intelligence to drive the gathering and analysis of large datasets, uncovering patterns and insights that can be used to inform business tactics and strategy. AI can be helpful in improving the customer experience, as it can surface the full range of customer data to see where an individual has been, what they’ve done, and then determine what they’re likely to do next.

The application of artificial intelligence (AI) technology to dynamically manage and optimise the customer journey. AI gathers data from each customer touchpoint to discover where the customer has been, and uses that data to determine where they need to go next — working at scale, allowing for a fully personalised experience for every customer.

Using artificial intelligence (AI) to tailor experiences to individual customers. When an organisation uses a modern customer experience (CX) platform with embedded AI capabilities, the organisation can deliver truly personalised experiences at scale across its global regions. Not only can AI understand and predict a customer’s intent, but it can also help them reach a resolution faster; if an interaction requires human support, the AI can recognise this and pass all the conversational history and context to the agent.

Delivering personalised offers and recommendations to customers at the moment of engagement by using artificial intelligence (AI) to analyse customer behavior and context in real time. These precisely timed content offers provide exceptional service and drive sales conversions.

Insights derived from analysing customer data using artificial intelligence (AI). An example of these insights is AI-powered predictive engagement, which identifies customers’ behavior patterns to predict the segments they fit into and the outcomes that will occur. Those predictions can drive automated offers and more personalised conversations that increase satisfaction and strengthen loyalty.

Platforms that use artificial intelligence (AI) to automate and enhance customer interactions across voice and digital channels. These modern AI-powered platforms enable organisations to surprise and delight their customers with effortless, empathetic experiences. And these platforms enable organisations to compose their ideal solution from a vast array of native components, a broad partner ecosystem and open APIs.

AI-powered customer insights leverage artificial intelligence and machine learning to analyse vast amounts of customer data more quickly and efficiently than a person can. The insights delivered from this analysis allow businesses to predict customer behaviors, personalise individual interactions and optimise customer journeys based on data-driven recommendations.

AMD technology, improved through machine learning, accurately identifies whether an incoming call is answered by a human or an answering machine. This enhances agent productivity by reducing the time spent on calls that do not reach a live person.

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think, learn and adapt. It encompasses technologies like machine learning, natural language processing and robotics, among others. AI is used in a wide range of industries and situations, including enhancing efficiency and enabling advanced problem-solving capabilities within customer service software platforms.

Automated call routing uses AI to analyse incoming calls and direct them to the most appropriate agent based on the query’s complexity and the agent’s expertise. This technology improves efficiency by reducing wait times and ensuring customers are connected to the best available resource.

The use of technology to automatically deliver personalised content and experiences to customers based on data-driven insights into their needs, preferences and behaviors. Smart automation leverages customer, employee and interaction data to drive real-time action and simplify workflows — improving the user experience while increasing efficiency. Modern solutions enable organisations to leverage this real-time automation easily — and clearly understand and optimise outcomes — without a team of data scientists.

Automated speech recognition (ASR) is technology that allows a computer to recognise and process human speech into text. ASR is used in applications such as transcription services and virtual assistants, enabling a bot to communicate with a person by translating the spoken word into a form the bot can understand.

An automatic call distributor (ACD) is a telephony software system that answers incoming calls and routes them to a specific agent or department within a company.

Automatic number identification. A series of numbers associated with a call. These numbers identify the phone number of the caller. Sometimes referred to as a “caller ID.”

The use of automation, including conversational AI (bots), to perform certain customer service tasks with limited or no human intervention.

The amount of time an agent is occupied on an incoming call.

Back-office optimisation is the process of streamlining and automating workforce tasks that occur in a contact centre.

The public’s level of knowledge and perception of a brand, which can be influenced by things like marketing, events and word of mouth. The ability to provide a seamless customer experience is one of the main pillars of a positive reputation.

A call centre is where an organisation handles customer telephone calls. Call centres typically use some amount of computer automation software.

Call centre customer relationship management (CRM) is a technology solution that stores critical customer information and improves agent access to customer data like account details and interaction history.

The way in which organisations manage the daily operations of the call centre, including forecasting, scheduling, employee training, reporting, and all customer interactions. Call centre management can be modernised through use of workforce optimisation solutions.

Call centre workforce planning is the process of aligning the strategic and operational elements of a call centre workforce with organisational objectives.

AI enables self-service options for customers, allowing them to complete tasks such as placing orders or checking balances without human agent intervention. Call deflection refers to the strategy of using AI to handle simple requests, freeing agents to focus on more complex interactions.

Chat messages are a type of communication that occur over the Internet. The most widely known way to use chat messages is on a website that lets you interact with a bot or agent to address a question or concern.

A cloud call centre is a web accessible platform where customer calls and interactions are handled.

A cloud contact centre is an approach to customer support that enables businesses to manage customer communications and interactions via the internet.

AI technologies can ensure compliance by monitoring call interactions for adherence to scripts, regulations and company standards. This reduces the risk of non-compliance and enhances the quality of customer interactions.

Consistency in practice and measurement allows businesses to orchestrate consistent experiences for their customers seamlessly across all touchpoints and channels that a brand offers, regardless of the medium or the platform.

Consumer behavior refers to the study of how individuals make decisions about purchasing goods and services, including the factors that influence their choices. Understanding consumer behavior helps businesses tailor their marketing, product development and customer engagement strategies to meet consumer needs more effectively.

A contact centre is a centralised facility or system where customer interactions across various communication channels — such as phone, email, chat and social media — are managed.

Contact Centre as a Service (CCaaS) is a cloud-based solution that provides contact centre functionality as a subscription service.

Contact centre customer relationship management (CRM) is a contact centre software solution that provides agents with quick access to customer account information to deliver great customer experience. Learn more at Genesys.com now.

Contact centre customer relationship management (CRM) systems are a set of specialised software solutions designed to manage and analyse customer interactions and data throughout the customer lifecycle.

The way in which organisations manage the daily operations of the contact centre workforce, across multiple touchpoints and channels, in order to accommodate omnichannel customer journeys.

Workflow management is the process of optimising a company’s business processes using automation.

Contact centre workforce management (WFM) encompasses the strategies and tools used to optimise the scheduling, forecasting and management of agents in a contact centre.

A customer experience strategy that integrates contact centre technologies and processes in order to deliver seamless omnichannel customer journeys in a multi-channel workforce.

Contact centre workforce planning is the process of aligning the strategic and operational elements of a contact centre workforce with organisational objectives.

Providing relevant, effective customer assistance that takes into account the context of the customer’s situation, history and current needs — even anticipating what they might need next. Artificial intelligence (AI) enables this contextual support by listening, understanding and engaging with customers through natural language. And since AI understands and predicts intent, it can help customers reach resolutions faster. It can even recognise when a customer needs human support, and then pass that conversational history and insight to an agent.

Conversational AI refers to the use of artificial intelligence to power automated communication tools, such as chatbots and virtual assistants, that can engage in natural language conversations with customers. This technology enhances customer support, allowing businesses to offer faster and more efficient interactions across channels. Conversational AI is a powerful customer journey management tool because it allows for greater self-service offerings, giving human agents the time to handle more critical, less repetitive tasks and further personalise and enhance customer experiences.

Conversational AI refers to the use of chatbots and virtual assistants powered by AI technologies to simulate humanlike conversations with customers. In call centres, it’s used to automate responses, handle routine inquiries and provide 24/7 support, improving efficiency and customer satisfaction.

In the context of AI and contact centre software, copilot is a general term for an AI assistant that supports various roles (agents, supervisors and admins) by providing real-time assistance, insights and automation capabilities. It enhances decision-making, productivity and customer experiences through intelligent recommendations and actions.

The process of breaking down silos within an organisation in order to allow various departments to work together toward common business goals.

The study of consumers’ purchasing patterns and engagement with a brand to better understand their preferences, needs and decision-making processes

Customer behavior analytics refers to the process of analysing how customers interact with a brand across various channels. By understanding patterns in behavior, businesses can optimise the customer experience, improve engagement and drive conversions through a customer journey management strategy.

The rate at which customers stop doing business with a company. This could be a symptom of dissatisfaction with a product, preference for the experience of buying from a competitor and more. Seamless, individualised customer experiences help to reduce churn by building emotional connections and increasing brand loyalty.

The process of gathering, consolidating and managing customer information from all available sources to provide a single, comprehensive view of the customer across an organisation.

A customer data platform (CDP) is software that centralises customer data from various sources into a single, unified view. CDPs enable businesses to analyse and act on customer data in real time, allowing for better personalisation and improved customer experience strategies. A CDP is a critical part of any customer journey management strategy; in order to optimise journeys, you need to be able to gather and analyse all your customer data in one place.

The strategic use of customer data to inform business decisions, personalise customer experiences and drive growth. While modern companies find themselves awash in information from various channels, customer journey analytics empowers them to gain the full power of data across previously disconnected business units and channels. By integrating data across all touchpoints, leading organisations can see the complete picture of customer interactions, understand how that affects their bottom line and make improvements accordingly.

Customer experience (CX) refers to the overall perception a customer has of their interactions with a brand. It encompasses every stage of the customer journey, from awareness to post-purchase, and includes both direct and indirect interactions. Optimising CX is crucial for building loyalty and driving business success.

Customer experience (CX) metrics are key performance indicators that measure various aspects of the customer experience. Common CX metrics include Net Promoter Score, customer satisfaction and customer effort score. These metrics help businesses assess how well they are meeting customer needs.

Contact center infrastructure, available from the cloud or on-premises, that supports the design, orchestration, monitoring, and tuning of customer journeys across voice and digital channels.

Leveraging artificial intelligence (AI) to analyse customer feedback across a variety of channels such as product reviews, social media and emails. This AI-powered analysis enables an organisation to extract valuable insights that it can use to improve its products, services and customer experiences over time.

The customer journey consists of multiple touchpoints and key interactions each customer or prospect has with a company—including messaging, employees, processes, products or services. Single or multiple interactions can be considered a customer journey and are part of a holistic customer experience lifecycle.

Customer journey governance refers to the policies, practices and frameworks that ensure consistency and alignment across all customer interactions and touchpoints. It helps organisations maintain a cohesive strategy for managing customer experiences while ensuring compliance and meeting business goals.

Customer journey management is the practice of using behavioral trends and technology to influence and optimise the customer experience (CX). Customer journey management aims to minimise the customer effort across all channels and touchpoints, ensuring a seamless experience every time a customer interacts with your company.

A customer journey map is a visualisation of the paths customers take across channels and over time. These maps enable teams to broaden their perspective beyond internal goals to include the customer's perspective.

Customer journey optimisation is the process of connecting and mapping customer interactions, across multiple touchpoints, in order to direct or influence the end-to-end experience.

Customer journey pain points refer to the obstacles or frustrations customers encounter during their interactions with a brand. Identifying and addressing these pain points is critical to improving the overall customer experience, reducing churn and boosting customer satisfaction. The main goal of customer journey management is to proactively eliminate as many pain points as possible so that customers enjoy the smoothest experience possible.

Strategies and practices aimed at building long-term relationships with customers, encouraging repeat business and fostering a positive connection between the brand and its customers.

The ability of a company to retain its customers over time, often achieved by providing a customer experience that continuously meets or exceeds expectations.

Approaches and tactics that companies use to keep their customers engaged and loyal over time. These strategies can range from promoting shared values to providing empathetic customer service to fostering word-of-mouth support. Businesses that are effective in retaining their customers over the long term increase their earnings while enhancing their brand recognition and industry prominence.

A measurement that determines how an organisation meets the expectations of its customers based on satisfaction. Customers are asked a question following a transaction about their satisfaction with the company, which is then rated from one (very dissatisfied) to five (very satisfied).

Using artificial intelligence to match a prospect or customer to the appropriate segments. These segments can classify intent and priority, identifying the likely interests, shopping preferences and buying behaviors of a customer based on similar previous customers. This enables organisations to personalise experiences by determining when and where to engage customers with an automated content offer, bot or agent-assisted service.

Customer service is the assistance and service provided by an organisation to customers before, during, and after the purchase of products or services.

Enhancing the effectiveness and efficiency of customer service operations to create a more seamless end-to-end experience for the customer. Optimising customer support and orchestrating smoother experiences improves response times, resolution rates and overall customer satisfaction.

Tailoring educational content and experiences to fit the individual needs of learners. With modern workforce engagement management capabilities, businesses can empower each employee with a personalised development hub that puts them in control. They can manage their performance and access assigned learning content and coaching sessions — all while staying on top of their work. And the business can build learning modules to train or inform its employees, and assign assessment modules to better evaluate their knowledge and skill levels.

Customer experience (CX) automation uses technology to streamline and automate repetitive tasks and processes related to customer interactions. This can include the use of chatbots, automated emails and workflow automation, allowing businesses to scale their customer service and engagement efforts. Automation makes customer journey management easier by taking rote tasks away from people and giving them more time to focus on problems that require a human touch.

A CX maturity model is a framework used to assess how advanced a company’s customer experience strategies and processes are. It helps organisations understand their current level of customer experience capability and provides a roadmap for continuous improvement.

A customer experience strategy is a plan that defines how a company will manage and improve the interactions that customers have with their brand. It includes objectives for enhancing customer satisfaction, loyalty and advocacy, and it typically involves a mix of technology, processes and employee engagement.

Dialogue management is the component of a voicebot or chatbot that manages the flow of conversation, ensuring responses are coherent and contextually appropriate. It plays a crucial role in maintaining natural and effective interactions between the user and the system by handling multiple conversational turns and context shifts.

The design and delivery of online shopping experiences that are personalised, engaging and convenient for customers. When a company uses a modern customer experience (CX) platform, it can enhance interactions across various digital touchpoints, providing the right web content that offers the right next steps based on a customer’s individual needs, preferences and experiences.

Digital-first CX refers to a customer experience strategy that prioritises digital channels such as websites, apps and social media as the primary means of interacting with customers. This approach focuses on delivering seamless and efficient experiences in a digital environment.

Building meaningful relationships with customers based on empathy and feeling. A smooth and seamless customer journey that serves your customers in the way they’re looking for displays empathy and builds that connection.

Designing customer interactions and experiences that demonstrate an understanding of and care for the customer’s needs and feelings.

The practice of designing, developing and deploying artificial intelligence systems in a manner that is morally responsible and aligns with ethical values. Ethical AI should follow strict guidelines that safeguard businesses by applying AI with a purpose, adhering to data standards and addressing bias. There should be privacy design principles that protect customer and employee data along with intellectual property. Explainability and transparency should offer insight into how algorithms are applied, enabling comprehension of operational impacts while maintaining control over the outcomes.

Strategies used to customise individual touchpoints for customers based on knowledge of their needs, preferences and behaviors. Personalising events is an important part of the process of experience orchestration, which intends to personalise entire experiences for customers. This increases customer engagement and satisfaction alike.

Experience orchestration enables you to coordinate technology based on the experience you want your customers to have across all channels of engagement. Businesses use it to build deeper, more loyal relationships as part of a guided process for consistent service. It also helps derive valuable context for the business. It works by using automation to create real-time insight about customer interactions. You can use this for proactive decision-making, taking action when it will be most impactful and appropriate.

Gamification in customer experience (CX) uses game-like elements, such as rewards, points and challenges, to engage customers and encourage specific behaviors. It can improve engagement and customer loyalty by making interactions more fun and rewarding. Gamification can also be useful for internal employee experience enhancement.

A hosted call centre solution is a cloud-based service where an organisation’s inbound, outbound and voice-based self-service customer interactions are handled.

A hosted contact centre is a customer experience solution where an organisation’s central point of inbound and outbound communications are hosted on a service provider’s back-office systems, therefore offering lower cost of ownership.

A hosted dialler is a contact centre cloud-based technology that enables cross-channel contact strategies to maximise the time agents spend on the phone.

An advanced level of personalisation that leverages real-time data and artificial intelligence (AI) to deliver highly relevant and individualised customer experiences. It’s both an art and a science that requires sharing information and context across voice and digital channels. And this requires the deployment of a modern customer experience platform that breaks down silos across channels, departments and touchpoints to create seamlessly connected experiences, journeys and relationships.

Hyperpersonalisation uses advanced data analytics and AI to provide highly tailored experiences for individual customers. By analysing real-time data, businesses can deliver content, recommendations and offers that are uniquely suited to each customer’s preferences and behaviors. Personalised experiences are one of the goals of customer journey management (CJM), making hyperpersonalisation an important CJM tool.

Identity resolution, sometimes known as “identity stitching,” is the process of aggregating disparate identifiers into a unified customer profile in order to identify an individual in real time across various digital touchpoints. 

Creating unique customer experiences that cater to the specific needs and preferences of the individual customer. An individualised customer experience that’s orchestrated by your business to meet your customer’s goals can help build a deeper connection — as well as customer loyalty.

IVAs are AI-powered agents capable of managing two-way text conversations in addition to voice interactions. They can set sales appointments, schedule callbacks and handle customer service inquiries, allowing human agents to focus on more complex tasks.

Customer journey analytics is the science of analysing customer behavior across touchpoints and over time to measure the impact of customer behavior on business outcomes.

Journey continuity refers to ensuring that a customer’s experience is consistent and seamless across various channels and touchpoints. It means that customers can pick up their interactions right where they left off, regardless of how or where they engage with the brand. Continuity is key to an orchestrated experience because the ability to prevent customers from having to repeat steps again and again — or from missing important information — drastically improves the experience.

Journey mapping is the process of visually outlining the stages a customer goes through when interacting with a product or service. This customer journey management tool helps organisations better understand the touchpoints where their customers meet them, as well as customer needs and pain points, allowing for improved service delivery and customer experience strategies.

Journey optimisation focuses on improving the overall customer journey by analysing interactions and touchpoints to identify and eliminate pain points. It involves continuously refining the customer experience to increase satisfaction, retention and conversions. Ideally, journeys will be optimised on an individual, personalised basis to provide the ideal experience for each and every customer; this can be done by leveraging your stores of customer data as well as artificial intelligence to predict needs before they’re a reality.

Journey orchestration is the process of coordinating customer interactions across multiple touchpoints and channels in real time. This ensures personalised, relevant experiences throughout the customer’s journey, improving engagement and satisfaction at every stage in that journey. Journey orchestration is a part of a larger customer journey management strategy.

A technology platform that enables businesses to design, manage and optimise customer journeys across multiple channels and touchpoints. Most effective journey orchestration engines will use artificial intelligence (AI) to surface and analyse customer data, delivering the best next step toward the goal the customer wants to achieve.

In AI and contact centre contexts, knowledge management refers to the systematic management of information and resources through AI to support agents and customers. This includes creating, curating and delivering the right information at the right time, improving resolution rates and self-service capabilities.

Live sentiment analysis employs AI to gauge the emotional tone of customer interactions in real time. By analysing the words and phrases used during a call, this technology helps supervisors identify and intervene in calls where customers may be dissatisfied or experiencing issues.

Machine learning is a subset of artificial intelligence (AI) that involves developing algorithms that allow computers to learn from and make predictions based on data. Through techniques like neural networks and deep learning, machine learning enables systems to improve their performance over time without being explicitly programmed. Machine learning is widely used in applications such as predictive analytics, allowing a business to quickly uncover changes in customer data.

Mobile voice is the emerging technology that combines recent advances in mobile and voice recognition.

A moderns contact centre is a central point in an enterprise from which all inbound and outbound customer communications are managed.

A multichannel cloud call centre is a CX platform that integrates multiple touchpoints while reducing incremental costs to modernising call centre capabilities

A multi-channel cloud contact centre is a customer experience (CX) solution that integrates multiple touchpoints – including voice, text, social media and the web – making them accessible via an Internet server. A multi-channel cloud contact centre can be accessed from virtually anywhere, eliminating the need for increased physical infrastructure while meeting the evolving demands of today’s customer communication preferences.

Natural language processing (NLP) is a branch of artificial intelligence that enables computers to understand, interpret and generate human language. It involves breaking down language into smaller pieces; analysing grammar and semantics; and understanding context.

Interactions with a brand that fail to solve a customer’s problem, make an issue worse or create a new concern.

Next-best action is a decision-making strategy that uses data analytics to recommend the most appropriate action to take with a customer at any given point in their journey. This approach helps businesses offer personalised experiences that align with the customer’s needs and preferences.

Next-best action is an AI-driven recommendation system that analyses customer data and interaction history to suggest the most appropriate action an agent should take next. This could involve offering a specific product, resolving an issue or providing personalised advice, thereby enhancing customer engagement and satisfaction.

An omnichannel cloud call center is a multi-channel contact center that delivers seamless customer experiences across all touchpoints leveraging modern cloud based infrastructure and services. In a cloud-based contact center, the company does not actually own, host or operate any equipment that the call center runs on; rather a third party service provider hosts the call center infrastructure in their own data center and the company will pay a monthly or annual service fee for hosting the infrastructure.

An omnichannel cloud contact centre is a comprehensive customer service platform hosted in the cloud that integrates multiple communication channels into a unified system.

An omnichannel customer experience is made up of individual customer touchpoints, over a variety of channels that seamlessly connect, allowing customers to pick up where they left off on one channel and continue the experience on another.

An omnichannel customer journey consists of key interactions over multiple touchpoints between customer or prospect and a company during the point of sale and throughout the customer lifecycle.

Omnichannel customer service consists of numerous interactions across multiple touch points between a customer, or prospective customer, and product or service provider.

Omnichannel engagement refers to providing a seamless customer experience across all the various communication channels where your customers might encounter your brand. This can include social media, email, live chat, in-store and more. An omnichannel engagement strategy ensures that your customers have consistent and integrated interactions, regardless of how or where or when they engage with a brand.

A personalisation engine is a technology platform that automates the process of delivering personalised content, offers and interactions to customers based on their data, behavior and preferences. It helps businesses create individualised experiences at scale, leading to better engagement and conversions. As a leading AI-Powered Experience Orchestration platform, Genesys Cloud™ is an example of a personalisation engine.

Marketing efforts that are tailored to the individual preferences, behaviors and needs of specific customers. Personalisation helps ensure every part of a customer’s experience is relevant to their goals, removing unnecessary friction and improving engagement and conversion rates — along with customer satisfaction.

Promotions or deals created for individual customers, based on their preferences, purchase history and behavior. Personalisation helps to ensure a business offers specific customers things that they want, thereby improving their buying experience.

Predicting customer churn involves using data analytics and machine learning to identify customers who are at risk of leaving or disengaging. By analysing behavior patterns and other indicators, businesses can take proactive steps to retain customers and improve loyalty.

Predictive analytics in customer experience (CX) involves using historical data and AI-powered machine learning algorithms to predict future customer behaviors, needs and outcomes. This applies both to your customer base as a whole, as well as individuals based on their own past actions. This allows businesses to be proactive in addressing customer concerns and optimising their journeys.

Using data analytics and machine learning to predict future customer behaviors and the goals they’re trying to achieve based on information such as their past interactions. With these predictive insights, organisations can engage the customer at the right time and in the right way. For example, a company could proactively offer a precisely timed chat that’s personalised using insights from the data analysis. Over time, machine learning can iterate and improve the predictive model based on additional customer interactions.

A predictive outbound dialer is a sophisticated telephony system used in contact centres to automate the process of making outbound calls.

Predictive personalisation leverages data analytics and machine learning to predict customer preferences and behaviors. By anticipating customer needs, businesses can deliver personalised experiences, recommendations and offers that improve engagement and satisfaction. Personalised experiences are one of the goals of customer journey management (CJM), making predictive personalisation an important CJM tool.

Private branch exchange (PBX) is a private telephone network used within a company. Users can communicate internally and externally using different communication channels like VoIP, ISDN or analogue.

Proactive customer service involves anticipating customer issues or needs before they arise and addressing them without the customer having to reach out. This can include sending helpful information, alerts or solving problems preemptively, resulting in higher customer satisfaction and loyalty. Artificial intelligence is a powerful tool in providing proactive customer service, as it helps to organise and analyse data to predict customer needs before they occur.

Quality assurance (QA) in a call centre refers to the systematic process of monitoring and evaluating the performance of agents to ensure they meet the company’s standards and customer service objectives — crucial for customer satisfaction and loyalty.

The ability of a business to rapidly assess, address and solve customer service issues. Customer journey management allows a business to predict potential issues and either eliminate them preemptively or solve them more quickly on a case-by-case basis.

Real-time customer engagement refers to the ability of businesses to interact with customers instantaneously across various channels, particularly live chat, speech and social media. It allows companies to provide timely, relevant responses and offers, creating more dynamic and personalised customer experiences.

The practice of monitoring and influencing a customer’s journey as it happens, using data analytics and automation to orchestrate experiences that align your actions with your customer’s goals.

Powered by AI, real-time data and analytics provide instant snapshots of business operations, customer behavior and market trends at a moment in time, allowing businesses to react to changes in the customer experience immediately and solve issues quickly.

Tailoring the customer’s experience in real time, based on live interactions and instant data. As a part of the experience orchestration process, this is typically accomplished with the help of artificial intelligence (AI). Real-time personalisation allows a business to enhance the relevance of every customer interaction and increase engagement, helping each customer achieve their distinct goals.

An auto dialer is an outbound call centre solution that automatically dials customer telephone numbers and can deliver important information through an automated message.

Call centre management is the way in which organisations manage the daily operations of the call centre, including forecasting, scheduling, reporting & training.

Dividing a market into distinct groups of buyers with different needs, characteristics or behaviors who might require separate products or marketing approaches. Leading companies now use artificial intelligence (AI)-powered insights to segment their customers based on their behavior and surface cross-channel histories of their interactions. With these insights, these industry leaders can increase satisfaction and loyalty by showing how deeply they know the customer, predicting intent, delivering precisely-timed actions and more.

Semantic understanding is the process of comprehending the meaning and context of words in a conversation. It enables systems to interpret and generate responses that are relevant and appropriate, playing a critical role in natural language processing and conversational AI applications.

Sentiment analysis is the process of using natural language processing to determine the emotional tone behind customer interactions, such as reviews, social media comments and support conversations. It helps businesses understand how customers feel about their products or services, enabling them to respond accordingly.

An advancement in call routing, skills-based routing uses customer data and AI to match callers with agents best suited to address their needs. This method considers the agent’s skills and the nature of the request, enhancing customer satisfaction by providing more personalised and effective service.

Speech recognition is a technology that enables machines to identify and process spoken language, converting it into text. It is used in various applications, including virtual assistants and other customer service tools, allowing for efficiencies like rapid transcription of customer interactions and more powerful voicebots.

Speech synthesis is the artificial production of human speech. It converts written text into spoken words using text-to-speech technology, providing a voice to digital content and enabling interactions with systems through auditory feedback in applications like virtual assistants and accessibility tools. Speech synthesis allows a person to converse with voicebots, making the interaction more natural and empathetic.

Supervisor copilot is an AI tool designed to aid supervisors in monitoring and managing the performance of agents in a contact centre. It offers insights into call quality, agent productivity and customer satisfaction metrics. By analysing interactions, it can identify coaching opportunities and recommend interventions to improve team performance and ensure compliance with service standards.

Customising communications between a business and a customer so that each customer’s unique needs are met.

A touchpoint is any interaction or point of contact between a customer and a brand, whether online or offline. Touchpoints can include website visits, social media interactions, emails, phone calls and in-person visits, and are critical for shaping the overall customer experience.

A trunk is a communication line or physical link, such as a wire or optical line, designed to carry multiple signals simultaneously.

A unified customer view consolidates all data from different interactions and touchpoints into a single, comprehensive profile for each customer. This enables businesses to better understand customer needs and deliver more personalised, consistent experiences across channels. This view is absolutely necessary for any customer journey management strategy to be possible.

Selling a customer either a superior/higher-priced version of a product, or a product from a different category that complements their original purchase.

A user journey is the series of steps a user takes to achieve a specific goal while interacting with a product or service. Mapping the user journey helps businesses identify pain points, improve design, and create more intuitive and satisfying experiences for customers.

A virtual agent is a contact centre capability that uses a virtual character, created through computer generation, animation and artificial intelligence, that acts as a virtual customer service agent.

A virtual call centre is a solution that supports contact centre agents who are dispersed geographically to provide customer service interactions.

A virtual contact centre (VCC) is a solution that supports contact centre agents in various geographical locations instead of a single physical location.

Voice biometrics is a technology that uses the unique characteristics of a person’s voice to identify and authenticate them. It analyses voice patterns to provide secure and convenient user verification, and is commonly used in customer service for things like matching a caller with an existing customer profile or to verify a customer’s identity before accessing private information.

A voice command is a spoken directive given to a voicebot or virtual assistant to perform a specific task. Voice commands enable more natural interactions between customers and bots, enhancing convenience and accessibility by allowing users to control systems through speech to approximate a conversation with a human.

Voice interaction refers to the act of communicating or interfacing with a system or device using spoken language. It involves the use of voice commands and responses, enabling natural and intuitive user experiences in applications such as virtual assistants and customer service.

Voice of the Customer (VoC) refers to the collection and analysis of customer feedback and sentiments to understand their needs, expectations and preferences. By capturing VoC, businesses can make data-driven decisions to improve products, services and the overall customer experience.

Voice over IP (VoIP) is a technology that converts your voice into a digital signal, allowing you to make a call directly from a computer, a VoIP phone or another data-driven device.

A voice platform executes the commands and logic specified by a voice application, provides speech processing capabilities and enables application creation.

A voicebot is an artificial intelligence (AI)-driven software application that interacts with users through spoken language using voice recognition, natural language processing (NLP) and speech synthesis technologies. It converts spoken words into text, understands the user’s intent and generates spoken responses, facilitating seamless, hands-free interactions. Voicebots are widely used in customer service to provide quick and accurate responses, enhancing user experience and operational efficiency.

Workforce optimisation is a strategy used to integrate siloed technologies and automate processes to reduce operational costs.

Workforce planning is the process of aligning the operational and strategic elements of a workforce with organisational objectives.