Centre Agent Research Articles

Mining customer reviews to evaluate the contact centre agent performance using custom kernel functions

Mining customer reviews to evaluate the contact centre agent performance using custom kernel functions

Where are the customers’ bots? The AI paradigm shift in retail banking

Financial institutions are already using artificial intelligence (AI) to cut costs and deliver new services. Robo-advisers, chatbots and ‘copbots’ auto-detecting fraudulent transactions are increasingly common. These uses are undoubtedly valuable, but the business model is still the consumers being sold a financial product by a bank, whether by a call centre agent or a robot that impersonates a mortgage vendor. The big change in financial services will come when customers use AI to assess offers from financial institutions for themselves. They will have access to AI as powerful as the banks have, because Google, Facebook, Apple and Amazon (and companies like them) will be giving it to them. And this will mean individuals will not be the customers: their bots will be. Since most retail financial services offer products that just service a need at a point in time (eg paying for parking) rather than create an extraordinary user experience or are too complicated for normal people to make informed decisions about (eg pensions), we might expect most consumers to abdicate in favour of intelligent agents operating under the new duty of care umbrella. This has been a subject of futurist speculation for some time, but the rapid growth of ChatGPT and its ilk means that banks now have an urgent need to develop strategies to take advantage of this significant change in the nature of the financial services in the mass market. This paper looks at the imminent confluence of open finance and AI to consider the consequences of giving bots access to consumers’ cash (through open banking, for example). This will mean a world of smart wallets, capable of making decisions on behalf of consumers. They will be capable of deciding what services to use, who to get them from and how to maximise their financial well-being, leaving their users to spend more time on human activities.

Aspect-based automated evaluation of dialogues

Evaluating human dialogue is a complex task, as our conversation are never structured. There are, however, cases where there is some structure in our conversation, e.g., in a typical call centre, dialogue between a call centre agent and customer revolves around certain topics of conversation. These dialogues can be evaluated based on some pre-specified criteria as well as sub-criteria. This evaluation is typically done manually, which can be time-consuming, motivating the need for an automated system that employs Artificial Intelligence (AI) algorithms to evaluate dialogues efficiently. In this paper, we have proposed a novel dialogue-evaluation framework that leverages recent advancements in deep learning research. The contributions of this work are two fold. Firstly, we introduce a straightforward end-to-end framework – CallAI, for evaluating dialogues in any domain, based on some predefined hierarchical criteria. Secondly, we present a novel algorithm – TAABLM, utilizing a novel combination of aspect-based learning along with traditional TF-IDF features for text. We show in this paper, that TAABLM outperforms conventional baselines such as BERT, LSTM, etc, delivering improved performance in automated dialogue evaluation, whereas CallAI offers a simple yet elegant framework for an AI-based solution to hierarchical dialogue evaluation. We demonstrate the efficacy of our proposed framework and proposed algorithm on three datasets, where we quantify performance in terms of an aggregated dialogue-score as well as in terms of either accuracy or AuROC metrics.

It’s about people: Caring agents and satisfied patients are key to a successful healthcare call centre culture

Although healthcare is the fifth largest industry in the United States, it ranks 25th and last for simplicity of experience, according to the Siegel+Gale World Simplest Brands report. Wait times, paper forms, complex language and complicated insurance plans have created a significant gap between the engagement experience patients want as opposed to what they receive. As patients transform into demanding healthcare consumers, they expect the same experience from healthcare providers that they receive in other aspects of their everyday life. Patients become frustrated when they compare their healthcare interactions with the attention and ease of use they encounter with most online retailers. One recent study revealed that 75 per cent of consumers want the same experience in healthcare that they get from other industries. The key to providing the type of experience patients want begins on the front line — with the people at the other end of the phone who first engage with the patient. In many cases, this is the healthcare’s call centre agent, trained to help a patient that is looking for an appointment and could be anxious and in need. In the following paper, discover how to find, attract, train and retain the best talent for your healthcare call centre and understand why being able to do this consistently is a critical link to ensuring patient satisfaction and loyalty.

Predictive Skill Based Call Routing Using Multi-Label Classification Techniques

This article is in the context of a call centre whose agents possess a heterogeneous skillset. The significant challenge for such a call centre would be skills based call routing: to match an inbound customer call to a call centre agent possessing the relevant skillset. This article will present an alternative to the usual Interactive Voice Recording (IVR) menu based approach to skill based call routing. This article will also make use of a multi-label classification techniques to predict the purpose of the customer call in advance and route it to the appropriate call centre agent without the customer's intervention. This hassle-free call routing technique produces efficient interactions and helps enhance customer experience, resulting in higher customer satisfaction and better cross-sell opportunities.

Personality as predictor of customer service centre agent performance in the banking industry: An exploratory study

Orientation: Since service quality is an important differentiator in the banking industry, it is essential to select suitable customer service centre staff, particularly those who are responsible for handling queries from clients who hold significant lifetime value in this industry.Research purpose: The aim of the study was to identify personality traits, as measured by the Occupational Personality Questionnaire 32r (item response theory scored version), including the more parsimonious Big Five personality traits, that may act as job performance predictors for customer service centre (CSC) agents in the banking industry.Motivation for the study: This study provides an exploratory investigation of whether specific personality traits differ amongst CSC agents in the banking industry, based on their job performance. No published research in this field could be identified.Research design, approach and method: Purposive sampling was used to collect data from the entire CSC agent base of a particular banking group (N = 89). Responses were analysed by means of quantitative techniques.Main findings and practical/managerial implications: Results indicate that parsimonious traits of personality, expressed as the Big Five personality traits, predict job performance. The importance of carefully selecting suitable job performance criteria for a specific environment, however, emerged as a critical issue in performance prediction.Contribution: The study focuses attention on the importance of CSC agents’ performance as frontline staff in the banking industry and identifying valid criteria for selecting the most suitable agents. Providing a one-contact point of service such as a CSC is a fairly new approach in the South African banking industry and this study provides an initial investigation of personality traits that may serve as job performance predictors in this environment.

A semantic publish-subscribe coordination framework for IHE based cross-community health record exchange

This paper presents a semantic agent coordination framework for the automatic exchange of Electronic Health Records (EHR). The framework enables health organizations that comply with the existing interoperability standards, as proposed by the Integrating Healthcare Enterprise (IHE), to dynamically connect in a P2P network. A set of autonomous agents and a set of distributed coordination rules are used to coordinate the agents in the search of specific health records. The framework models the interactions among the communities as a combination of the tuple centre agent communication model with the publish-subscribe paradigm and semantic web technologies. In order to illustrate the scalability of our approach, we evaluate the proposed solution in distributed settings. The contribution of this work is that it proposes the coordination mechanisms for IHE compliant communities to dynamically connect and share EHR of patients.

The impact of call centre stressors on inbound and outbound call‐centre agent burnout

PurposeThe aim of this study is to draw on various models of burnout and test hypotheses relating to anticipated differences in the burnout process between inbound versus outbound call centre agents. This is achieved by comparing the magnitude of the relationships in the sequence of customer stressors → emotional exhaustion → depersonalization → reduced personal accomplishment across a sample of inbound and outbound call centre agents working in a large retail bank call centre in New Zealand.Design/methodology/approachData were collected from inbound and outbound call centre agents of a large retail bank call centre in New Zealand via a self‐administered survey questionnaire electronically distributed to all 195 call centre agents working in the bank's two call centre locations. Data obtained from the call centre agents were analysed using the SEM‐based partial least squares (PLS) methodology.FindingsThe findings of the study reveal significant differences between inbound and outbound call centre agents in terms of the extent to which emotional exhaustion impacts depersonalisation as well as the extent to which depersonalisation influences feelings of reduced personal accomplishment.Practical implicationsThe research advances understanding of differences in the burnout process as perceived by inbound versus outbound call centre agents. Call centre management might consider improving the work environment to bring about greater job discretion/autonomy, greater job variety and performance monitoring in order to attenuate the stronger impact of these relationships in an inbound context.Originality/valueThese findings extend our understanding of these phenomena in the largely unexplored yet important context of call centre agent‐customer interaction in specifically highlighting differences between inbound and outbound call centre agent burnout.

Linkages between CRM technologies, knowledge applications and first call resolution in inbound call centres

This empirical research aim at establishing the relationship between CRM technologies, knowledge management and first call resolution within the inbound call centres. The results indicate that CRM organisation and technology-based CRM are major antecedents of call centre knowledge management. The research finding also shows that the strength of conflict resolution in call centres strongly depend on proper knowledge management skills. It practically availed managers inherent opportunities in call centre agent’s ability to understand the impact of using CRM technologies and knowledge applications in adding value to job performance and meeting customers’ requirements. Alternative recommendations are suggested for future researchers.

Building Cross‐Sector Careers in India's New Service Economy? Tracking Former Call Centre Agents in the National Capital Region

ABSTRACT This article presents findings from a labour mobility survey of 250 former call centre agents in India's National Capital Region (September 2008) exploring individuals’ employment before, during and immediately after leaving India's high‐profile call centre ‘industry’. These data are combined with forty‐two in‐depth interviews conducted in India's NCR (July 2006 to August 2008) with call centre agents, managers, ex‐call centre agents, labour organizers and economic development officials, as well as representatives from different labour market intermediaries. The study gives a cautiously optimistic account about the call centre work and employment opportunities on offer in India's ‘IT Enabled Services – Business Processing Outsourcing’ (or ITES‐BPO) industry, and their implications for young urban middle class graduates based on: (i) the movement of around one fifth of the ex‐call centre agent sample into further study, facilitated by relatively high call centre salaries; (ii) the movement of ex‐call centre agents into higher paying job roles in a wide range of sectors including banking, IT, insurance, marketing, real estate and telecommunications; and (iii) the development of transferable skills in Indian call centres that are recognized by ex‐call centre agents and their subsequent employers as conferring a labour market advantage in other sectors of India's new service economy relative to colleagues without prior call centre work experience.

An exploration of call centre agents' CRM software use, customer orientation and job performance in the customer relationship maintenance phase

Exploratory research techniques are used to examine the relationships between call centre agents' customer relationship management (CRM) software use, agents' customer orientation, and agents' job performance in the maintenance phase of customer relationships. Maintenance activities, which focus on customer retention and cross- and up-selling, are important to study because prior research suggests they have the strongest effect on company performance. In the financial services industry, CRM software applications supporting retention and cross-/up-selling activities benefit firms by raising revenues and reducing costs. The context for this exploratory research is that of in-bound customer service and sales call centres at three different financial institutions. Based on the analysis of data from key informants across these different contexts, this research suggests that CRM software use is a separate antecedent of call centre agent job performance and has a minimal relationship with customer orientation. Given the suggestive nature of exploratory research results, further research is warranted.

Improving call centre agent performance

PurposeThe study was designed to understand important aspects of the call centre agents' job, from their point of view, and the relationships between these aspects and agent effectiveness as perceived by agents' supervisors.Design/methodology/approachQualitative data gathering (from 113 agents) involved three methods: critical incidents, behavioural events interviews and focus group interviews. Based on the items thus identified, a questionnaire was administered (n=169) to agents in two call centres, and the results were analysed using factor analysis and correlation analysis.FindingsFour distinct factors emerged from the analysis: intrinsic motivation (IM,α=0.91), reward/recognition (RR,α=0.56), customer stress (CS,α=0.85) and stress management (SM,α=0.74). IM correlated positively with effectiveness, especially among experienced agents. CS correlated negatively with IM and positively with RR; SM correlated positively with IM.Research limitations/implicationsSome limitations are: self‐reported data, representing one point in time, and with only two call centres. IM and CS present opportunities for further in‐depth study, among frontline employees in general.Practical implicationsThe study has many significant practical implications for call centre managers to improve agents' performance by tapping into IM rather than control. Further, higher levels of IM are likely to lead to a less stressed workforce.Originality/valueOur study has indicated two new and important constructs (IM and CS) that emerged from agents, and established important links between these constructs, and with effectiveness.

Core Competencies Of A Call Centre AgentCore Competencies Of A Call Centre Agent

Call centre agents are becoming increasingly important in the call centre context. They act as a contact point between the customer and the company. Call centre agents should have certain competencies to perform their duties sufficiently. Identifying competencies, required to be effective agents, will ease the task of training and recruitment. Due to the interrelatedness of the call centre agent, the management of a call centre and customers, all relevant role players’ perceptions were taken into account. By using qualitative analysis to analyse the data, various competencies needed to function effectively in a call centre were identified.