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Wie kann überwachtes maschinelles Lernen das digitale Marketing unterstützen?

In: Praxishandbuch Digitales Management

Author

Listed:
  • Gerd Nufer

    (Hochschule Reutlingen, ESB Business School)

  • Manuel Muth

    (Philipps-Universität Marburg, School of Business and Economics)

Abstract

Zusammenfassung In Anbetracht der bedeutenden Stellung des überwachten maschinellen Lernens zur Gestaltung digitaler Geschäftsprozesse wird dessen systematischer Einsatz ausführlicher aufbereitet. Anhand von Beispielen und einschlägiger Literatur wird analysiert, wie überwachte Lernmodelle im Allgemeinen und im speziellen Marketingrahmen funktionieren können. Kritische Anwendungskomponenten wie die initiale Eignungsprüfung, kontextsensitive Algorithmenauswahl und Modellbewertung werden dabei identifiziert. Neben Potenzialen werden auch Herausforderungen wie Modelltransparenz, vorurteilsfreie Daten und die Einbindung von Marketing-Expertise dargestellt. Die Strukturierung des wachsenden Wissensbestands beider Fachrichtungen soll so eine konkrete Orientierungshilfe für den realen Marketingeinsatz bieten.

Suggested Citation

  • Gerd Nufer & Manuel Muth, 2026. "Wie kann überwachtes maschinelles Lernen das digitale Marketing unterstützen?," Springer Books, in: Stefan Detscher & Michael Hepp (ed.), Praxishandbuch Digitales Management, pages 319-337, Springer.
    • Handle: RePEc:spr:sprchp:978-3-658-49614-2_73
    DOI: 10.1007/978-3-658-49614-2_73
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