Understanding the value of customer data

Abstract

That customer or consumer data have a value is universally accepted, as is the difficulty of quantifying that value. However, more organizations are finding it necessary to try. This paper provides businesses with a conceptual framework for valuing customer data in a way that can support both operational and investment decisions. It argues that this is equally possible for data-rich and data-poor organizations. It first looks at the need to understand the reasons behind the need to understand the value of customer data, and relates this to the degree of accuracy and granularity required of any valuation in order to reduce the risk of over-investment. It then proposes a framework for understanding how customer data, through the activity it enables, drives values and thus links to sustainable incremental profitability. Using this as the basis for a customer data model, it suggests an approach to attributing value to customer data at various levels from the macro 'overall value' down to the granular value of different data elements. The approach includes consideration of whether data elements are actually drivers, or merely indicators, of value. The paper concludes with suggestions on how to present data value and quality information together in a simple and compelling dashboard in order to grab the attention of senior executives and elevate consideration of customer data to the status of regular executive meeting agenda item. © 2012 MACMILLAN PUBLISHERS LTD.