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Valid Customer Data: The Foundation for Omni-channel Marketing

  • 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 anMarketing 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.show moreshow less

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Metadaten
Document Type:Part of a Book
Zitierlink: https://opus.hs-offenburg.de/7296
Bibliografische Angaben
Title (English):Valid Customer Data: The Foundation for Omni-channel Marketing
Author:Simone BraunStaff MemberORCiDGND, Andreas Heißler
Edition:1.
Year of Publication:2023
Date of first Publication:2023/05/03
Place of publication:Cham
Publisher:Springer
First Page:159
Last Page:176
Parent Title (English):Marketing and Sales Automation : Basics, Implementation, and Applications
Editor:Uwe Hannig, Uwe Seebacher
ISBN:978-3-031-20039-7 (Hardcover)
ISBN:978-3-031-20042-7 (Softcover)
ISBN:978-3-031-20040-3 (eBook)
DOI:https://doi.org/10.1007/978-3-031-20040-3_10
URL:https://link.springer.com/chapter/10.1007/978-3-031-20040-3_10
Language:English
Inhaltliche Informationen
Institutes:Fakultät Wirtschaft (W)
Institutes:Bibliografie
DDC classes:000 Allgemeines, Informatik, Informationswissenschaft
GND Keyword:Datenmanagement; Datenqualität; Kundendaten
Tag:Data Governance; Data Quality Scorecard
Formale Angaben
Relevance:Buchbeitrag
Open Access: Closed 
Licence (German):License LogoUrheberrechtlich geschützt