The quality of customer information management in customer life cycle management

Abstract

their customer management strategies on their customer knowledge-IBM's global banking team's work on configuring systems to use customer data-the IBM Business Consulting Services analytics practice, which helps clients get value from their customer dataincluding improving analysis and business processes. In this paper, this information is presented with specific reference to the mobile telephony INTRODUCTION In the first paper in this series of three, the authors examined the theory and concepts of data quality management and briefly highlighted some empirical findings. This paper explains in more detail how these findings relate to using data to develop customer insight. The conceptual and experiential material used in this paper comes from:-QCi's work in helping clients base 240

Schema

“…In the decades since 1980, there was strong emphasis on the size and complexity of the customer database (whether managed in house or by a data management bureau), the complexity of telecommunications systems and contact centres required to support it, the central role of data in leading to a clear information-based picture about customers and interactions with them and the use of that information to improve customer management (Abbott et al, 2001b;Dobbs et al, 2002;Foss et al, 2003;Pula et al, 2003;Stone et al, 2003b;Stone et al, 2004;Stone and Woodcock, 2014). However, it became easier to use the CRM approach, as outsourcing companies competed to provide data management, software development and maintenance, marketing, customer service and sales resources.…”

Refining value-based differentiation in business relationships: A study of the higher order relationship building blocks that influence behavioural intentions

“…In an expanding market, the availability of products (supply, service) might be considered important, while in economically unsure times other factors (price, process cost, trust, quality) may become more important to customers. A longitudinal or historical case study of a suppliercustomer dyad might also indicate a customer life cycle (Stone, Foss, Henderson, & Irwin, 2003) factor.…”

Integrating the value of salespeople and systems: Adapting the benefits dependency network

“…Combining descriptive information on customer characteristics (eg from an external source such as Dun and Bradstreet) and events (from a news feed provider) with transaction histories and any behavioural / attitudinal data provides the potential for predictive prompts to salespeople. 20 Thus, a fall in orders may indicate risk of customer defection. A customer analytics system can then analyse the customer ' s lifetime value information and past behaviour (such as complaining about poor service) and suggest a response, such as contacting, diagnosing the situation and making a relevant offer.…”