The importance of analysis and planning in customer relationship marketing: Verification of the need for customer intelligence and modelling

Abstract

to Bergeron 4 and Crosby, 5 CRM is a strategy for managing the relationships among people within the organisation and between customers and the organisation, cementing long-term, collaborative relationships which are based on mutual trust with those customers. From this, as stated by Ryals, 6 strategies that increase customer value and customer satisfaction are developed. The most valuable customer segments are identified and retention strategies to is a consultant employed with Marketing Databasics and is one of the developers and users of the DATASTEPS evaluation tool.Abstract Customer revenue management (CRM) is widely recognised as beneficial, yet many organisations who have used this approach have not found the results they had hoped for. This paper reports a survey of businesses using CRM to assess if activity in this area can be correlated with business success and to allow verification of the findings of Woodcock 1 who found a positive correlation. Interviews with managers responsible for CRM and scoring are reported and their effort in customer data collection, maintenance, segmentation and modelling are assessed. This analysis and planning is perceived to be the foundation of CRM. It is found that companies who scored well in analysis and planning also performed well in regard to business performance metrics.

Unravelling the integrated information systems and management control paradox: enhancing dynamic capability through business intelligence

“…It allows organisations to identify customer needs and preferences and to (re)configure activities and processes to deliver products and services that satisfy these needs at a lower cost (Park and Kim, 2003). This requires acquisition of transactional and non‐transactional customer data and the generation of business models that allow the organisation to infuse specific customer requirements and metrics into the way customers are served (Park and Kim, 2003; Alvarez et al , 2006; Appelbaum et al , 2017). Consequently, we posit that an integrated MCS that has the combinative capacity of providing customer data and analytically modelling this data will be assimilated into the customer relationship processes.…”

“…Customer responsiveness requires the collection, processing and application of customer profile and transaction data to create an in‐depth understanding of customer needs and to provide fair value (quality, cost and time) to customers (Slater and Narver, 2000; Park and Kim, 2003). This implies acquiring transactional and non‐transactional customer information, creating business models and infusing the information from these models into customer service (Park and Kim, 2003; Alvarez et al , 2006). This requires a strong customer information infrastructure that generates sufficient data (quantity and quality), in a suitable form for analysis (Alvarez et al , 2006).…”

“…This implies acquiring transactional and non‐transactional customer information, creating business models and infusing the information from these models into customer service (Park and Kim, 2003; Alvarez et al , 2006). This requires a strong customer information infrastructure that generates sufficient data (quantity and quality), in a suitable form for analysis (Alvarez et al , 2006). Such information infrastructure should be complemented with analytical tools capable of creating appropriate metrics from the data and converting customer information into knowledge useful for improving customer value (Park and Kim, 2003; Alvarez et al , 2006).…”

“…This requires a strong customer information infrastructure that generates sufficient data (quantity and quality), in a suitable form for analysis (Alvarez et al , 2006). Such information infrastructure should be complemented with analytical tools capable of creating appropriate metrics from the data and converting customer information into knowledge useful for improving customer value (Park and Kim, 2003; Alvarez et al , 2006). We argue that the assimilation of integrated MCS information into customer relations and marketing and sales provides an organisation with the capability to enhance customer responsiveness.…”

Churn management in the telecom industry of Pakistan: A comparative study of Ufone and Telenor

“…9 Operators have to invest in CRM and database management in order to understand clients ' needs and anticipate churn before it happens, putting in place actions to generate fi delity. 10,11 Caruana 12 investigates the dimensions of switching costs, which infl uence customer loyalty by working out a correlation analysis among the corporate customers of a mobile phone operator. A better understanding of customer satisfaction, churn and win-back initiatives can reverse customer attrition, 13 thus proving the adage, prevention is better than cure.…”