Valid Customer Data: The Foundation for Omni-channel Marketing

Simone Braun () and Andreas Heißler ()
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Simone Braun: Offenburg University of Applied Sciences
Andreas Heißler: Uniserv GmbH

A chapter in Marketing and Sales Automation, 2023, pp 159-176 from Springer

Abstract: Abstract Marketing and sales have high expectations of new methods such as Big Data, artificial intelligence, machine learning, and predictive analytics. But following the “garbage in—garbage out” principle, the results leave much to be desired. The reason is often insufficient quality in the underlying customer data. This article sheds light on this problem using the data quality and value pyramid as an example. The higher up the value-added pyramid the data is located, the higher its quality and the more value it generates for a company. In addition, we show how the use of monitoring systems, such as a data quality scorecard, makes data quality visible and improvements measurable. In this way, the actual value of data for companies becomes obvious and manageable.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:mgmchp:978-3-031-20040-3_10

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DOI: 10.1007/978-3-031-20040-3_10

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