Generic algorithm and neural network based predictive modelling to optimize the customer experience using emotional signature

Timothy P. Jackson, Stan Oliver

Research output: Contribution to journalArticlepeer-review


There are many sales & marketing analytics solutions to target and attract new customers however to retain the existing customers, their experience with the company should be made smooth and pleasant. To carry out such a strategy, companies must gain an understanding of the customer’s journey – from the expectations they have before the experience occurs to the assessments they are likely to make when it’s over. Emotional experience plays a fundamental role in determining the customers’ preferences, which then influence their purchase decisions. For example, customers become frustrated when their actions trigger the wrong behaviours, and organizations should take action to reverse this. To persuade your customers to feel you “care for” them -is a powerful differentiator. Therefore, understanding and measuring the emotional aspects of your Customer Experience is vital to improving your Customer Experience and saving costs.The goal of Data Mining in this research is to discover new knowledge and facts from huge volumes of Data. The new knowledge and facts discovered can be used for taking critical business decisions that can improve both bottom-line as well as top line. Data Mining helps business managers discriminate between what is relevant and what is not by using a broad range of tools from statistics, database technologies and visualization.The business objectives of using Data Mining tools and techniques in Customer Experience function are - measuring, monitoring and improving Customer Experience holistically across all the customer touch points, detection of behavioural patterns which customers exhibit prior to terminating relationship with the company early enough to avert attrition and identification of internal organization and technology issues that impact customer experienceThe purpose of this study is to optimize the phenomenon of Customer Experience with specific focus on Emotional Signature. The reason for doing so is the determining of the factors which distinguish the successful optimization from the unsuccessful ones. To fulfil this purpose, it was necessary to review the literature on customer experience, emotions and data mining.This research has a predictive purpose in that it aims to explain the key determinants of successful optimization of customer experience.
Original languageEnglish
Pages (from-to)5-26
JournalBLIS Journal
Issue number1
Publication statusPublished - 10 Jan 2014


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