Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/230248 
Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Naval Research Logistics (NRL) [ISSN:] 1520-6750 [Volume:] 68 [Issue:] 6 [Publisher:] John Wiley & Sons, Inc. [Place:] Hoboken, USA [Year:] 2021 [Pages:] 683-700
Verlag: 
John Wiley & Sons, Inc., Hoboken, USA
Zusammenfassung: 
In their loyalty reward programs, large retailers adopt category-specific targeted promotions as an effective means to increase shoppers' basket values. However, neither the literature nor observed marketing practice provides category selection methods that maximize the promotion's profitability. Hence, we provide a predictive customer-centric category selection approach based on the return on marketing investment measure that accommodates both fixed and variable promotion costs, captures cherry-picking effects, and encompasses the retailer's entire category assortment. We use a real-world promotional data set from a leading German retailer to show that our approach predicts customer responses to these promotions with high out-of-sample accuracy tested over time and also across promotion frequencies. We find that the most promising categories in mobile promotions maximize cross-category profits to curtail cherry-picking and boost the sales of nonpromoted items—that is, the profitability-driving part of the profit uplift. In contrast, the different cost structure of print promotions requires that categories achieve a high (but not too high) redemption rate, as cross-category profit declines, in order to recoup customer contacting costs. Our benchmark analysis reveals that current marketing practice fails to hit the profitability functions' “sweet spot” and can even work against the retailer by producing negative returns.
Schlagwörter: 
category selection
category‐specific promotions
cross‐category profit
targeted marketing
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by Logo
Dokumentart: 
Article
Dokumentversion: 
Published Version

Datei(en):
Datei
Größe
965.42 kB





Publikationen in EconStor sind urheberrechtlich geschützt.