Sujata Joshi

Enhancing Customer Experience Using Business Intelligence Tools with Specific Emphasis on the Indian DTH Industry

Abstract The Direct to Home industry has emerged as the key driver for the Indian entertainment industry. In October 2011 the Government announced implementation of a phase-wise digitization programme of pay TV services throughout the country. The Indian Direct to Home industry is expected to grow by 50% in 2016. A few challenges faced by the Direct to Home Industry are low Average Revenue per user (ARPU), high customer acquisition costs and high churn rate. DTH Service Providers consider superior service experience as the key differentiator that will help them acquire new customers and manage churn as well. Currently there is no standard available in the India market for DTH service providers to quantify and improve its customer experience. Hence the objective of this paper is to formulate various constructs that helps to understand the impact of different service attributes on customer experience for Direct to home customers using business intelligence tools.

A process model for identifying online customer engagement patterns on Facebook brand pages

Purpose The purpose of this paper is to develop and empirically test a process model (comprising of seven dimensions), for identifying online customer engagement patterns leading to recommendation. These seven dimensions are communication, interaction, experience, satisfaction, continued involvement, bonding, and recommendation. Design/methodology/approach The authors used a non-participant form of netnography for analyzing 849 comments from Australian banks Facebook pages. High levels of inter-coder reliability strengthen the study’s empirical validity and ensure minimum researcher bias and maximum reliability and replicability. Findings The authors identified 22 unique pattern of customer engagement, out of which nine patterns resulted in recommendation/advocacy. Engagement pattern communication-interaction-recommendation was the fastest route to recommendation, observed in nine instances (or 2 percent). In comparison, C-I-E-S-CI-B-R was the longest route to recommendation observed in ninety-six instances (or 18 percent). Of the eight patterns that resulted in recommendation, five patterns (or 62.5 percent) showed bonding happening before recommendation. Research limitations/implications The authors limited the data collection to Facebook pages of major banks in Australia. The authors did not assess customer demography and did not share the findings with the banks. Practical implications The findings will guide e-marketers on how to best engage with customers to enhance brand loyalty and continuously be in touch with their clients. Originality/value Most models are conceptual and assume that customers typically journey through all the stages in the model. The work is interesting because the empirical study found that customers travel in multiple different ways through this process. It is significant because it changes the way the authors understand patterns of online customer engagement.

Customer experience and associated customer behaviour in end user devices and technologies (smartphones, mobile internet, mobile financial services)

This research paper proposes to establish the relationship between customer experience and customer behavioural intentions of churn, advocacy, cross-sell, up-sell and complaint for cellular service providers for end user devices and technologies like smartphones, mobile internet and mobile financial services. The method adopted incorporates various determinants across the customer lifecycle which are sufficient in defining customer experience holistically. A primary survey was conducted on 5,231 respondents by means of a questionnaire along with personal interviews. Data was analysed using descriptive analysis as well as through statistical backing of logistic regression tests. Results indicate that there is a significant relationship between customer experience of smartphone users and mobile financial services users and their customer behavioural intentions of advocacy, churn, cross-sell, up-sell and complaints. The implications of this research can prove useful for cellular service providers in formulating their marketing strategy, cross-sell and up-sell strategy, churn management strategy and customer acquisition/retention strategy.