Digital Technologies for Ordering and Delivering Fashion: How Baur Integrates the Customer’s Point of View

Part of the Management for Professionals book series (MANAGPROF)


  1. (a)

    Situation faced: Digital technologies such as augmented/virtual reality, chatbots, image processing, messaging services, or speech recognition have the potential to fundamentally change ordering and delivery in online-fashion shops: Disrupting customer interaction formats like attended shopping, curated shopping, scanned shopping, or virtual fitting may increase customer experience, satisfaction, and sales. However, when smaller amounts of money are available, the question arises as to in which of them to invest. Baur, a major German online fashion retailer, is faced with this question and wants to integrate the customer’s point of view in the site engineering process explicitly.

  2. (b)

    Action taken: Secondary research as well as workshops with experts and customers were applied to generate lists of aspects to be improved and potential improvements by digital technologies in the company’s ordering and delivery process. A representative sample of 15,865 customers was confronted with these aspects and potential improvements and asked to evaluate them. 9722 customers returned completed questionnaires. Many of them additionally included detailed comments. The survey data were analyzed and the improvements were prioritized for implementation. The survey methodology yielded recommendations for action to such an extent that it is now integrated in the company’s site engineering process.

  3. (c)

    Results achieved: Overall, the survey showed that the customers are satisfied with the company’s current ordering and delivery process. However, with regard to selection, packaging, and delivery several changes are necessary. Many customers rated potential improvements like virtual fitting and curated shopping as attractive whereas most of them were indifferent with regard to scanned shopping, personalized areas, attended shopping, or C2C inspiration. The survey research resulted in valuable input for the company what actions should be taken in terms of digital technologies to implement. In addition, the company received valuable information on how to improve the ongoing site engineering process.

  4. (d)

    Lessons learned: Improvements aimed at integrating digital technologies—in particular virtual fitting by relying on virtual reality as well as curated shopping by making use of chatbots and messaging services—were rated by many customers as attractive and should also be implemented by other online fashion retailers. Other digital technology-based improvements are of lower priority. From a methodological point of view, customer surveys—if developed carefully and integrated in the company’s site engineering process—provide valuable support when selecting digital technologies for implementing improvements.



Online Fashion Retailer Virtual Fitting Chatbot Increasing Customer Experience Delivery Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Amazon (2014) Annual report 2013., Inc., Seattle, WA. Google Scholar
  2. Amazon (2017) Annual report 2016., Inc., Seattle, WA. Google Scholar
  3. Baier D, Rese A (2017) Online-shop site engineering using eye tracking, TAM, and A/B-tests: an empirical application. Paper presented at the 4th German-Polish Symposium on Data Analysis and its Applications (GPSDAA-2017), Wroclaw, September 25Google Scholar
  4. Baier D, Stüber E (2010) Acceptance of recommendations to buy in online retailing. J Retail Cust Serv 17(3):173–180CrossRefGoogle Scholar
  5. Baier D, Rese A, Schreiber S (2015) Analyzing online reviews to measure technology acceptance at the point of scale: the case of IKEA. In: Pantano E (ed) Successful technological integration for competitive advantage in retail settings. IGI Global, Hershey, PA, pp 168–189CrossRefGoogle Scholar
  6. Berger C, Blauth R, Boger D et al (1993) Kano’s methods for understanding customer-defined quality. Cent Qual Manag J 2(4):3–36Google Scholar
  7. BEVH (2017) Interaktiver Handel in Deutschland 2016. Studie des Bundesverbands E-Commerce und Versandhandel e.V. (BEVH), Berlin.
  8. Cronin JJ Jr, Taylor SA (1992) Measuring service quality: a reexamination and extension. J Mark 56(3):55–68CrossRefGoogle Scholar
  9. DHL (2016) DHL Customer Journey Studie 2016: Vom Klick bis zur Klingel – Von der Online-Bestellung bis zum Paketempfang. DHL Express Germany GmbH, Bonn. Google Scholar
  10. Flanagan JC (1954) The critical incident technique. Psychol Bull 51(4):327–359CrossRefGoogle Scholar
  11. Ganeshan S (2016) The dead-zone: why customer surveys are dead.
  12. hmmh (2016) hmmh Studie: Fulfillment Benchmarking – im Fokus: Fashion. hmmh multimediahaus AG, Bremen. Google Scholar
  13. Kano N, Seraku N, Takahashi F, Tsuji S (1984) Attractive quality and must-be quality. J Jpn Soc Qual Control 14(2)Google Scholar
  14. IFH Köln (2017) Branchenfokus Damen- und Herrenbekleidung 2017. IFH Köln and BBE Handelsberatung GmbH, Köln. Google Scholar
  15. Lauber D (2013) E-Commerce an der Schwelle zur Sättigungsphase – Produktivität von E-Commerce-Aktivitäten wird erfolgskritisch. In: Heinemann G, Haug K, Gehrckens M (eds) Digitalisierung des Handels mit ePace. Springer Gabler, Wiesbaden, pp 105–122CrossRefGoogle Scholar
  16. Löffler S, Baier D (2013) Using critical incidents to validate the direct measurement of attribute importance and performance when analyzing services. J Serv Sci Manag 6(5a):1–11Google Scholar
  17. Martilla JA, James JC (1977) Importance-performance analysis. J Mark 41(1):77–79CrossRefGoogle Scholar
  18. Otto Group (2017): Geschäftsbericht 2016/17. Otto GmbH & Co KG, Hamburg. Scholar
  19. Pantano E (ed) (2015) Successful technological integration for competitive advantage in retail settings. IGI Global, Hershey, PAGoogle Scholar
  20. Pantano E, Rese A, Baier D (2017) Enhancing the online decision-making process by using augmented reality: a two country comparison of youth markets. J Retail Cust Serv 38:81–95CrossRefGoogle Scholar
  21. Rese A, Schreiber S, Baier D (2014) Technology acceptance modeling of augmented reality at the point of sale: can surveys be replaced by an analysis of online reviews? J Retail Cust Serv 21(5):869–876CrossRefGoogle Scholar
  22. Rese A, Baier D, Geyer-Schulz A, Schreiber S (2017) How augmented reality apps are accepted by customers: a comparative analysis using scales and opinions. Technol Forecast Soc Change 127(November):306–319CrossRefGoogle Scholar
  23. Schreiber S, Baier D (2015) Multivariate landing page optimization using hierarchical bayes cbc analysis. Stud Classif Data Anal Knowl Organ 50:465–474CrossRefGoogle Scholar
  24. Stüber E (2013) Personalisierung im Internethandel: Die Akzeptanz von Kaufempfehlungen in der Bekleidungsbranche, 2nd edn. Springer Gabler, WiesbadenCrossRefGoogle Scholar
  25. Swinscoe A (2016) Some people say that customer surveys are dead, they’re wrong and here’s why. Forbes.
  26. UPS (2015) 2015 UPS pulse of the online shopper. A customer experience study. UPS of America, Inc., Atlanta, GA. Google Scholar
  27. Zalando (2017) Geschäftsbericht Zalando 2016. Zalando SE, Berlin. Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.University of BayreuthBayreuthGermany
  2. 2.empiriecom GmbH & Co KG and Baur GroupBurgkunstadtGermany
  3. 3.Baur Versand GmbH & Co KG and Baur GroupBurgkunstadtGermany

Personalised recommendations