Enhancing Customer and Supplier Relationship through the Iterative Customer Relationship Management Process

CRM Process is considered the main critical success factor of CRM systems implementations, so special care should be given for each and every process in the organization supply chain for goal achievements.This paper provides an extensive review of the etiquette regarding the CRM processes. This review aims to increase the understanding of the different perspectives, levels of CRM processes, and CRM process models.The CRM Process either macro process or micro process. On the macro level, we consider merging Knowledge Management (KM) with Customer Relationship Management (CRM) to have Customer knowledge Management (CKM) to reduce the risk of relationship failure and customer intelligence for the profitability of the organization supply chain. The knowledge management process starts with data collection, followed by intelligence generation and eventually, intelligence dissemination as an iterative process. On the other side the Micro-level process (Interaction Management) where its quality determined by Consistency, Relevancy, and Appropriateness. In the same context, other scholars classified the CRM process into three levels: (Customer facing level, The Functional level, and the Companywide level (Customer-oriented CRM process). Then, in the article, we are going to demonstrate the CRM process models and the proposed Iterative CRM process model by the author

Optimizing Product-Market Fit: A Digital Marketing Approach for Performance Measurement

In today's digital economy, digital marketing has grown in scope and now acts as a liaison connecting digital interactions and key start-up activities. The low investment and dynamic elements of digital marketing favor the start-up environment and enable a flexible match between digital interactions and start-up growth. However, start-ups are usually unfamiliar with all the possibilities digital marketing offers and connect its influence solely with marketing and sales. Digital marketing, powered by data analytics, can support start-ups in different key activities such as testing and experimentation, customer education, and others. This thesis first explores how digital marketing impacts start-up development within a set of growth drivers supporting different key activities and associated areas. Through a systematic literature review, the Macro- dynamic Framework was developed to identify and connect fifteen growth drivers and digital marketing impact for achieving start-up growth in four different areas. Secondly, as Product-Market fit is identified as one of the key drivers of start-up growth, this research focused on investigating how can product-market fit be influenced through digital marketing. One of the major challenges start-ups have in this perspective is measuring digital marketing performance and interpreting the collected data. As Product-Market fit and performance measurement both largely rely on the provided digital marketing analytics and received feedback, the DM_Optima framework is developed to connect the touchpoints of both areas. Through multiple case study research with nine start-ups, the thesis demonstrates this Framework application. The DM_Optima Framework is developed with a Balanced Scorecard and enables start-ups to test their ability to optimize product-market fit through digital marketing and performance measurement. The results of DM_Optima help start-up founders and managers to achieve or maintain their product-market fit and establish efficient practices of digital marketing performance measurement from an internal organizational perspective.Na economia digital de hoje, o marketing digital cresceu no seu âmbito e actua agora como um elo de ligação entre as interacções digitais e as principais actividades de arranque. O baixo investimento e os elementos dinâmicos do marketing digital favorecem o ambiente de arranque e permitem uma combinação flexível entre as interacções digitais e o crescimento de arranque. Contudo, as start-ups não estão normalmente familiarizadas com todas as possibilidades que o marketing digital oferece e ligam a sua influência apenas ao marketing e às vendas. O marketing digital, impulsionado pela análise de dados, pode apoiar start-ups em diferentes actividades chave como testes e experimentação, educação de clientes, e outras. Esta tese explora primeiro como o marketing digital tem impacto no desenvolvimento inicial dentro de um conjunto de factores de crescimento que apoiam diferentes actividades e áreas associadas. Através de uma revisão sistemática da literatura, a Estrutura Macrodinâmica foi desenvolvida para identificar e ligar quinze motores de crescimento e marketing digital para alcançar o crescimento inicial em quatro áreas diferentes. Em segundo lugar, uma vez que o ajuste Produto-Mercado é identificado como um dos principais motores do crescimento inicial, esta investigação centrou-se na investigação de como pode o ajuste produto-mercado ser influenciado através do marketing digital. Um dos maiores desafios que as novas empresas têm nesta perspectiva é medir o desempenho do marketing digital e interpretar os dados recolhidos. Uma vez que a adequação e a medição do desempenho do produto ao mercado dependem largamente da análise de marketing digital fornecida e do feedback recebido, a estrutura DM_Optima é desenvolvida para ligar os pontos de contacto de ambas as áreas. Através de múltiplos estudos de caso com nove start-ups, a tese demonstra esta aplicação da estrutura. A estrutura DM_Optima é desenvolvida com um Balanced Scorecard e permite às start-ups testar a sua capacidade de optimizar a adequação do produto ao mercado através do marketing digital e da medição do desempenho. Os resultados da DM_Optima ajudam os fundadores e gestores em fase de arranque a alcançar ou manter a sua adequação ao mercado de produtos e a estabelecer práticas eficientes de medição do desempenho do marketing digital de uma perspectiva organizacional interna

Measuring Customer Value and Market Dynamics for New Products of a Firm:An Analytical Construct for Gaining Competitive Advantage

The role of customer value has been largely recognized over time by the firms as an instrument towards stimulating market share and profit optimization. The customer values for a new product of firm in competitive markets are shaped more by habits, reinforcement effects, and situational influences than strongly-held attitudes. A strong and sustainable customer value associated with a new product launched by a firm may also lead to build the customer loyalty in the long run. An analysis of the new product-market structuring based on customer value may be developed well within the microeconomic framework of a firm. The measure of customer value as the efficiency of new product may be viewed from the customer’s perspective towards a ratio of outputs (e.g., perceived use value, resale value, reliability, safety, comfort) that customers obtain from a product relative to inputs (price, running costs) that customers have to deliver in exchange. However, the aggregate returns on the customer value towards the new product from the perspective of a firm may be observed manifesting in enhancing the market share, market coverage and augmenting profit in a given market. There has not been many contributions emerged in the past addressing the measurement of the customer value as an intangible asset of the firms, though substantial literature is available discussing the customer relations and loyalty building perspectives. This paper attempts to critically examine the available literature on the subject, discuss a model that provides a framework for analyzing the variables associated with customer value and to identify potential research areas. A basic premise of the paper is that the focus should be on maximizing total customer value and customer satisfaction which are inter-dependent in the decision making process towards buying new products. The framework of the construct is on a proposed model which integrates all aspects so as to maximize the potential of the organization and all its subsystems to create and sustain satisfied customers. The discussion in the paper on the customer value gaps in the process of marketing new products explores the possible situations that may lead to lower the customer value.New product management, customer value measurement, market coverage, aggregate returns, market penetration, model construct and estimation, profitability

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

The role of big data analytics in industrial Internet of Things

Big data production in industrial Internet of Things (IIoT) is evident due to the massive deployment of sensors and Internet of Things (IoT) devices. However, big data processing is challenging due to limited computational, networking and storage resources at IoT device-end. Big data analytics (BDA) is expected to provide operational- and customer-level intelligence in IIoT systems. Although numerous studies on IIoT and BDA exist, only a few studies have explored the convergence of the two paradigms. In this study, we investigate the recent BDA technologies, algorithms and techniques that can lead to the development of intelligent IIoT systems. We devise a taxonomy by classifying and categorising the literature on the basis of important parameters (e.g. data sources, analytics tools, analytics techniques, requirements, industrial analytics applications and analytics types). We present the frameworks and case studies of the various enterprises that have benefited from BDA. We also enumerate the considerable opportunities introduced by BDA in IIoT.We identify and discuss the indispensable challenges that remain to be addressed as future research directions as well

Customer retention

A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in partial fulfillment of the requirements for the degree of Master of Science in Engineering. Johannesburg, May 2018The aim of this study is to model the probability of a customer to attrite/defect from a bank where, for example, the bank is not their preferred/primary bank for salary deposits. The termination of deposit inflow serves as the outcome parameter and the random forest modelling technique was used to predict the outcome, in which new data sources (transactional data) were explored to add predictive power. The conventional logistic regression modelling technique was used to benchmark the random forest’s results. It was found that the random forest model slightly overfit during the training process and loses predictive power during validation and out of training period data. The random forest model, however, remains predictive and performs better than logistic regression at a cut-off probability of 20%.MT 201