Uniphore Glossary of Terms
Word of the Week
Virtual sales describes the process in which salespeople integrate with technology applications in order to interact with customers online. Designed to replace traditional, in-person sales conversations, virtual sales allow for both synchronous (communications occurring at the same time) and asynchronous (communications at different times) functionality.Read More
After Call Work (ACW)
What is After Call Work?
Definition of After Call Work:
After Call Work (ACW) begins in the moments after a call concludes. These are the steps an agent takes when they hear the dial tone that wraps up and processes the call. In order to be ready for another call, an agent must complete any ACW.
The tasks associated with after call work may vary depending on company protocols and desires. However, there are a few common ACW duties that agents often complete after the call ends. These can include:
- Logging information, from the reason for contact to the outcome
- Scheduling any follow-up contacts or actions
- Analyzing call data
- Sharing information with coworkers and/or other departments
After call work ties up a conversation’s loose ends. When calls aren’t cemented into a system that recognizes their importance, valuable customer information is lost. That’s why ACW ensures all valuable data is recorded for Interaction Analytics and other analysis purposes.
Watch Vijai Shankar, Uniphore’s VP of Product Marketing & GTM, break down the role of automation in after-call work in Season 2 Episode 9 of Conversations That Matter.
What is Agent Assist?
Definition of Agent Assist:
An agent assist is a service that supports agents in real-time during conversations. Even the most prepared and skilled agents can struggle during periods of high call volume or with complicated customer conversations. An agent assist helps navigate difficult calls, routine responses, and customer requests all the while improving phone interactions and speeding up response time.
Agent assist solutions provide aid and workflow management in all areas of agent work, including:
- Beginning every call with automated customer data
- Quickly diagnosing customer intent and need
- Providing guidance during each conversation
- Implementing workflows in conversations and with task completion
- Assembling call summaries for After Call Work
- And much more
What is Agent Guidance?
Definition of Agent Guidance:
Agent guidance is the direct support and real-time coaching that guides agents through calls. Complete with live insights and next-best actions for delivering consistent customer experience, agent guidance provides call center workers with the right tools to prevent customer churn.
Calls can be as frustrating for the agents as they are for the customers. But with the right tools to handle the rise in high-effort interactions, customers have better experiences and agents are prepared to handle their queries and needs. These tools are gap-filling techniques, teaching agents on the fly — and often in the middle of difficult calls — while ensuring customers receive consistently positive care.
Average Handle Time (AHT)
What is Average Handle Time?
Definition of Average Handle Time:
An agent’s Average Handle Time (AHT) is the average amount of time it takes for a call to be completed. AHT consists of the duration of the call, from the moment an agent picks up the call to the final tone. This time is spent discovering what customers need – listening to their complaints, information or stories to provide a diagnosis – and resolving or answering their query. Transfers, hold time and conversations are just a few of the elements included in AHT.
Average handle time length will depend on the agent’s ability to respond to the customer as well as the customer’s monologuing time. The amount of time it takes to help a customer results in the AHT, and is human-focused. While a customer might be happier with faster service, call centers in general have to walk the line between reducing average handle time and ensuring customers feel listened to and supported for the entirety of their call.
What is Buyer Engagement?
Definition of Buyer Engagement:
Buyer engagement refers to the level of participation and/or interaction a buyer has with a company’s portfolio of products or services. Companies measure buyer engagement through buyer behaviors at various touchpoints, such as opening an email, clicking on a video or answering an agent’s phone call. The stronger the level of engagement, the more likely a potential buyer will make a purchasing decision.
Forecasting buyer engagement is accomplished through data collected specifically regarding the messaging, content, training resources, coaching opportunities and historical successes that drive buyers’ decisions. This data is combined with insights into what specific avenues see greater engagement in order to maximize visibility to targeted buyers.
Buyer engagement is valuable for sales teams, marketing departments and management alike, driving customer-facing methodologies, developing client loyalty and generating new revenue streams.
What is Buyer Sentiment?
Definition of Buyer Sentiment:
Buyer sentiment refers to a buyer’s initial, emotional reaction to a sales presentation or offer. Buyer sentiment can provide insight into the likelihood of a purchase. As a result, a positive initial contact can influence the future purchasing decisions of potential clients.
Buyer sentiment data provides insight into the effectiveness of both a sales representative’s messaging and the method of communication. Engagement over phone, for example, can be contrasted with engagement via email communications in order to quantify the efficacy of contact center processes.
Buyer sentiment can assist agents in forecasting realistic sales timelines and leverage positive initial contact with products and services to ensure client acquisition. The data analysis of buyer sentiment across multiple delivery methods and communication outcomes provides valuable insight into what comprises effective customer engagement.
What is Conversational AI?
Definition of Conversational AI:
Conversational AI allows humans and machines to have conversations via verbal or written channels. Using Natural Language Processing (NLP) and Machine Learning (ML), AI-powered software systems that handle interactions learn to recognize speech and text patterns and respond in kind. In customer service applications, conversational AI responds to customer requests, dilemmas and situations as a human agent would. It can also augment live agent interactions by transcribing and analyzing customer input, autopopulating form fields and feeding agents relevant data in real-time.
The applications of conversational AI span industries and corporations, and are already in use in many day-to-day operations. From chatbots to automated messaging services to voice searching software available on many platforms, conversational AI helps businesses and customers by offering smooth interactions and solutions.
What is Emotion AI?
Definition of Emotion AI:
Emotion AI tools use artificial intelligence to “read” emotions based on audio and visual cues. When technologies compute feelings using information from the lilt of your voice or your expression to your words, they are attempting to better understand your state of being. These machines collect data based on inflection, tone, word choice and many other systems and analyze them to recognize patterns in behavior and choices.
Whether interpreting voice analytics or using facial expression analysis, emotion AI understands stress, anger, happiness and joy and can offer a deeper level of understanding in CX applications. It can strengthen customer relationships, engagement and brand loyalty. With emotion AI, enterprises can predict customer reactions and improve outcomes, including higher sales conversion and First Call Resolution (FCR) rates and better customer satisfaction (CSAT) and Net Promoter Scores (NPS).
What is Emotional Intelligence?
Definition of Emotional Intelligence:
Emotional intelligence in AI refers to a machine’s ability to learn and respond to human emotion. Given the importance of feelings, passions and emotions in decision making – especially when it comes to products and services – training AI with emotional intelligence improves customer experience (CX). Now, agents don’t have to decipher a customer’s emotions and desires alone. AI systems that are equipped with emotional intelligence are able to pinpoint how conversations are going and how clients truly feel, allowing the root of their problem or challenge to be elevated and responded to quickly and effectively.
Call center agents are assisted by the emotional intelligence offered by AI, but the benefits extend far beyond the dialing and tone of a call. Artificial intelligence is able to gauge and map customer satisfaction and happiness across the entirety of the customer journey, and adjusted approaches offer opportunities to improve CX.
Emotional Quotient (EQ)
What is Emotional Quotient?
Definition of Emotional Quotient:
Emotional Quotient (EQ) is the measurement used to evaluate levels of emotional intelligence in customer interactions. Artificial intelligence tools that use EQ can accurately evaluate customer emotions and prompt appropriate responses based on emotional data. With emotional quotient in effect, users can be sure that their AI is doing its job to the fullest ability, improving conversations and overall customer satisfaction.
EQ enhances customer experience (CX) by providing AI-powered tools with a precise and actionable benchmark for interpreting a wide array of customer emotions. When customers feel listened to and are given the highest quality of service by their agents and tools, their entire customer journey benefits – as does their trust and loyalty to a company.
First Call Resolution (FCR)
What is First Call Resolution?
Definition of First Call Resolution:
First Call Resolution, also known as First Contact Resolution, refers to a call center resolving an issue for a customer on the first call. When customers call for help they expect a solution for their problem to be found during the length of the call. Factors that impact FCR include the complexity of the customer request, agent access to relevant information and knowledge of appropriate next-best actions.
First Call Resolution is a valuable metric for measuring individual agent performance as well as overall contact center efficiency. FCR directly correlates to customer experience – feeling listened to, respected, and understood in their dilemmas – as well as the tools call agents have at their disposal to find success. As a result, contact centers with high FCR rates see higher customer satisfaction (CSAT) scores and lower customer churn.
What is Interaction Analytics?
Definition of Interaction Analytics:
Interaction analytics is the analysis of every conversation. It is the practice of taking the valuable records of conversations that occur on calls, chat transcripts, and emails and distilling the information into meaningful insight for company-wide benefit. Conversations in these and other formats are reviewed using artificial intelligence and natural language processing (NLP) tools.
Interaction analytics takes the wealth of information and data that exists within conversations and draws conclusions about sticking points, miscommunication, customer satisfaction and more. Interaction analytics tools ensure a company understands their customers’ needs and desires related to the offered product or service. Additionally, because they can analyze 100 percent of interactions, these tools are invaluable for quality assurance and compliance auditing needs.
What is Promise Management?
Definition of Promise Management:
Promise management occurs after promises have been made during a call, ensuring that each commitment is kept with smooth and timely follow-through. Every conversation will likely involve some element of commitment-making. These may include billing requests, appointment scheduling and other tasks that an agent approves. After promising a certain effort, promise management comes into play.
In order to build long-lasting, positive and growing customer confidence, there must be consistent and dependable delivery. When promises are managed effectively, a customer can expect their request to be taken care of as quickly as possible. An agent’s promise management should include timely responses as well as an accurate and pinpointed resolution. A customer that experiences immediate, high-quality promise fulfillment will have enhanced commitment to the company and product – as well as a strengthened relationship with the brand.
What is Revenue Intelligence?
Definition of Revenue Intelligence:
Revenue Intelligence (RI) refers to the sales and product data gathered and analyzed by artificial intelligence (AI). Collected from a variety of sources, including current customers and prospective clients, RI takes data and turns it into actionable insights.
By focusing on trends with revenue generation opportunities, businesses utilize RI technologies to forecast customer demands. This data-centric approach gathers information from all applicable segments of a business, pooling insights from sales and marketing departments with historical successes and additional context from customer support teams in order to coalesce customer truths.
RI provides valuable, scalable insights for a sales team. The ability to pinpoint targeting data and buying signals with granularity arms a sales rep with powerful tools to better highlight lead opportunities and deliver communications specifically tailored to consumer needs. Contact centers with RI programs see higher lead conversion rates by targeting the contacts, channels and times that prove to be most successful.
What is Revenue Operations?
Definition of Revenue Operations:
Revenue Operations (RevOps) consolidates sales, marketing and customer service operations to drive revenue generation and client acquisition.
Utilizing marketing resources, sales processes and customer retention strategies in one cohesive platform, RevOps consolidates data streams and communication across departments. This results in increased efficiency and a reduction in the downtime associated with waiting for feedback from siloed teams.
RevOps benefits the business by establishing shared goals. Goals related to conversion rates, sales cycle rates and win rates can thus be achieved in unison through streamlined cross-department collaboration.
What is Sales Engagement?
Definition of Sales Engagement:
Sales engagement refers to a seller’s effectiveness in delivering a valuable customer experience (CX). Sales engagement encompasses all of the interactions that occur between call center staff and buyers, from phone conversations to email campaigns to direct mail and chat services. This information is valuable to sales reps and marketing departments alike.
Data collected from sales engagement interactions can help drive sales performance by offering detailed levels of insight into successful conversations that have resulted in client acquisition and retention. Sales engagement data allows for the creation of best practices and standards that are backed by metrics. Individual sales rep performance can thusly be measured against performance thresholds in order to provide coaching opportunities and continued education.
Sales engagement data provides marketing departments a clear line of sight into the campaigns, services and verbiage that is most effective in driving customer buying patterns. Exceptional sales engagement equals exceptional CX.
What is Sales Operations?
Definition of Sales Operations:
Sales Operations (SO) refers to the series of processes, technology and data that coalesce in order to maximize revenue generation capabilities. A subset of SO, Sales & Operations Planning (S&OP) creates a comprehensive sales plan to manage the efficiency and productivity of the sales team as they work towards a sales goal.
Sales operations utilize multiple systems tools (e.g. CRM software) along with inter-department communications, training and other resources to ensure revenue optimization. SO provides a calculated, systems-based approach to sales. By eliminating unnecessary challenges facing a sales team, members can focus on revenue generation unencumbered.
Sales Performance Management
What is Sales Performance Management?
Definition of Sales Performance Management:
Sales performance management (SPM) refers to the automation and unification of sales processes. Designed to improve operational success, SPM informs quota achievement outcomes by combining quota management and planning with gamification and analytics.
Sales performance management utilizes machine learning technologies to collect and analyze data that contact centers can use to maximize revenue opportunities. Aligning individual sales goals with a businesses’ overall strategy, SPM combines reporting and analytics with objectives management in three key areas:
- Quota management: Set individual, achievable goals based on the overall revenue potential of a territory
- Territory management: Create territories based on geography, business units or other custom factors
- Incentive compensation: Calculate variable incentive targets leveraged with customer data and forecast potential compensation scenarios
Sales performance management reinforces contact center data by providing a streamlined sales process and insight into the factors affecting performance outcomes and incentives.
What is Speech Analytics?
Definition of Speech Analytics:
Speech analytics is the process of extracting meaningful insights from calls in order to improve future conversations. There are thousands of hours of audio and text-based interactions that hold a goldmine of data on customer journeys, experience and desires. When these recorded calls are analyzed, the valuable unstructured data can help inform practices in order to facilitate smoother interactions.
Modern speech analytics software delivers actionable insights into the details and nuances that make up the true voice of the customer. These elements include everything from the feelings and sentiments of a customer to the context and meaning of their interactions. What’s more, speech analytics software generates these insights automatically without cumbersome, time-consuming effort on the part of call center workers.
What is Value-Based Sales?
Definition of Value-Based Sales:
Value-based sales are the conveyance of the worth of a product or service to the potential buyer. Rather than exclusively featuring the product or service itself, value-based selling highlights the significance of the resulting purchase and how it might impact the buyer in a positive way.
By showcasing the enrichment opportunities a product or service can provide a potential buyer, agents utilizing this sales approach tap directly into the wants and needs of a customer. Value-based sales put the intended buyer first, guiding them through both the process of purchase and the feelings of satisfaction they are likely to experience once the transaction is complete.
Identifying pain points and offering immediate solutions is the key to the value-based sales approach. A focus on educating the potential buyer regarding the improvements they’re sure to enjoy with a given product or service makes value-based selling advantageous over simply listing product features.
What is Virtual Sales?
Definition of Virtual Sales:
Virtual sales describes the process in which salespeople integrate with technology applications in order to interact with customers online. Designed to replace traditional, in-person sales conversations, virtual sales allow for both synchronous (communications occurring at the same time) and asynchronous (communications at different times) functionality.
Virtual sales have become a popular solution for businesses in the wake of the COVID-19 pandemic. Virtual sales conversations occur at the convenience of the customer, regardless of their time zone or location. And with today’s agent assist solutions, salespeople can leverage a wealth of data and logistics information from their workstations in order to ensure customer satisfaction.
Virtual sales allow a business to ascertain customer needs via personalized conversations, and enable remote purchasing of goods and services based on similarly remote interactions. This level of service and communication, as well as the overall ease of use of virtual sales, can increase consumer confidence in a brand or business.