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Technology selection for human behaviour modelling in contact centres

By Satya Ramesh Shah, Rajkumar Roy and Ashutosh Tiwari

Abstract

Customer service advisors can play different roles and have different level of autonomy, but at the end they are humans with heart and voice. While product purchases, lifestyle information and billing data provide important information about customers, it is call detail records that describe a customer’s behaviour and define their satisfaction with the services offered. Call detail records describe the transactions between customer and the company. This study looks on different techniques that can be used to model customer and CSA (customer service advisor) behaviour within a contact centre environment. A brief overview of the contact centre environment is discussed focusing on issues of customer and service advisor and the need to categorise customer and advisor within contact centre environment. The findings from the case study analysis within the current contact centres, provides the authors with understanding of different behaviour observed for customer and CSA’s within contact centres. The study also examines different human behaviour modelling techniques which the authors are interested in using to develop a model which can categorise the human with respect to demographic, experience and behavioural attributes within the context. Through the study it can be seen that soft computing techniques provide a major role in modelling of human behaviour and thus providing better results where this technique can be applied. The authors have also carried out a comparative analysis of all the techniques discussed within the paper and as seen from the analysis that soft computing techniques are widely used to model the user/human behaviour and thus can provide a platform for future research. Soft computing represents a significant paradigm shift in the aim of computing, a shift that reflects the fact that the human mind, unlike state of the art computers, possesses a remarkable ability to store and process information, which is pervasively imprecise, uncertain, and lacking in categori

Topics: Customer behaviour modelling, Customer Service Representatives, Soft Computing, Human Behaviour modelling, Contact/Call Centre environment, DEG report
Year: 2006
OAI identifier: oai:dspace.lib.cranfield.ac.uk:1826/1212
Provided by: Cranfield CERES

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Citations

  1. (2002). A case-based customer classification approach for direct marketing', doi
  2. (2003). A concurrent fuzzy-neural network approach for Technology Selection for Human Behaviour Modelling in Contact Centres
  3. (2003). A connectionist model of spatial knowledge acquisition in a virtual environment',
  4. (2002). A data-driven methodology for evaluating and optimizing call center IVRs',
  5. (2001). A fuzzy rule based agent for web retrieval -filtering. doi
  6. (2003). A fuzzy-based customer classification method for demand-responsive logistical distribution operations', doi
  7. (2002). A genetic algorithm application in bankruptcy prediction modeling', doi
  8. (2000). A literature survey on applications of neural networks for humancomputer interaction', doi
  9. (2004). A method for identifying and assessing key customer group needs', doi
  10. (2005). A methodology for dynamic data mining based on fuzzy clustering', doi
  11. (1999). A soft computing approach for modelling the supervisor of manufacturing systems',
  12. (2003). A system based on hierarchical fuzzy clustering for web users profiling', System Security and Assurance, doi
  13. (2003). Adaptive user modeling in intelligent telephone and email assistants', doi
  14. (2002). Agent-based interaction analysis of consumer behavior', doi
  15. (2002). Agent-based modelling of customer behaviour in the telecoms and media markets', doi
  16. (2004). An expert system for job matching of the unemployed', doi
  17. (1999). Application of Neuro-fuzzy systems to behavioural representation in computer generated forces, available at: http://www.link.com/pdfs/neurofuzzy.pdf (accessed
  18. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioural intentions in service environments ', doi
  19. (2004). Beyond valence in customer dissatisfaction: A review and new findings on behavioural responses to regret and disappointment in failed services',
  20. (1997). Building agent based decision support system using soft computing techniques',
  21. (1999). Call centres in BT UK customer service',
  22. (2002). Combination of multiple classifiers for the customer's purchase behavior prediction', doi
  23. (2003). Combining web usage mining and fuzzy inference for website personalisation', Web Mining as Premise to Effective Web Applications,
  24. (2001). Consumer Behavior,
  25. (2002). Customer Service in UK call centres: : organisational perspectives and employee perceptions', doi
  26. (1999). Customer Trust in the Salesperson: An Integrative Review and Meta-Analysis of the Empirical Literature', doi
  27. (2002). Data mining for decision support on customer insolvency in telecommunications business', doi
  28. (2005). Detecting the change of customer behavior based on decision tree analysis', doi
  29. (2005). Development of fuzzy expert system for categorising customer and advisors in contact centres',
  30. (2003). Ethos: A MAS framework for modelling human social behaviour and culture', Agent Based Simulation Conference 4,
  31. (2002). Evolution in groups: a genetic algorithm approach to group decision support systems',
  32. (2003). Explaining consumer choice through neural networks: the stacked generalization approach', doi
  33. (2000). Fuzzy cognitive maps: a soft computing technique for intelligent control', doi
  34. (2004). Fuzzy logic with engineering applications, doi
  35. (2000). Improving customer satisfaction, loyalty and profit: an integrated measurement and management, Jossey Bass, doi
  36. (1998). Information system project selection using fuzzy logic', doi
  37. (1995). Introduction to fuzzy logic', doi
  38. (1990). Modeling human performance with neural networks. doi
  39. (2003). Modelling consumer behavior for customisation process’. In: The Customer Centric Enterprise: Advances in Mass Customization and Personalization. Edited doi
  40. (2003). Multivariate preference models and decision making with the MAUT matching', doi
  41. (1996). Neural networks and genetic algorithms for bankruptcy predictions', Third World Congress on Expert Systems, doi
  42. (1998). Performance modeling of distributed automatic call distribution systems', doi
  43. (2002). Predicting customer behavior in the market-space: a study of Rayport and Sviokla's framework', doi
  44. (2005). Satisfaction and dimensions of control among call centre customer service representatives', doi
  45. (1995). Selecting fuzzy if-then rules for classification problems using genetic algorithms', doi
  46. (1998). Services marketing and management: Implications for organisational behaviour',
  47. (2002). Social class influences on purchase evaluation criteria', doi
  48. (2006). Soft computing in service industry', Advances in Soft Computing, doi
  49. (1997). Soft computing: the convergence of emerging reasoning technologies', doi
  50. (1998). Sources of customer satisfaction and dissatisfaction Technology Selection for Human Behaviour Modelling in Contact Centres
  51. (2006). Technology Selection for Human Behaviour Modelling in Contact Centres
  52. (1996). The birth and evolution of fuzzy logic (FL), soft computing (SC) and computing with words (CW): a personal perspective', doi
  53. (1999). The development of behavior-based user models for a computer system', doi
  54. (1997). The influence of salesperson selling behaviours on customer satisfaction with products', doi
  55. (1996). The management of customer contact service employees: an empirical investigation', doi
  56. (2000). The past, present and future of customer access centres', doi
  57. (1995). The role of employee effort in satisfaction with service transactions', doi
  58. (1999). The Telecommunications Review, Mitretek Systems White
  59. (1991). The theory of planned behaviour', Organisational behaviour and human decision processes, doi
  60. (2001). Towards flexible modeling of collective human behaviour with cognitive process', doi
  61. (2002). User profiles and fuzzy logic for Web retrieval issues', doi
  62. (2004). When Conscientiousness Isn't Enough: Emotional Exhaustion and Performance Among Call Centre Customer Service Representatives', doi

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