Skip to main content
SpringerLink
Log in

Customer Wallet Share Estimation for Manufacturers Based on Transaction Data

  • Conference paper
  • First Online:
Data Mining (AusDM 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1127))

Included in the following conference series:

  • 673 Accesses

Abstract

The value of customers for any business cannot be over-emphasised, and it is crucial for companies to develop a good understanding of their customer base. One of the most important pieces of information is to estimate the share of wallet for each individual customer. In the literature a related concept is often referred to as customer equity that provides aggregated measures such as the business market share. The current trend in personalising marketing campaigns have led to more granular estimation of wallet share, than the entire customer base or aggregated segments of customers. The current trend in personalising marketing and business strategies have lead to more granular estimation of wallet shares than the entire customer base or aggregated segments of customers. Existing research in this area requires access to additional information about customers, often collected via various surveys. However, in many real-world scenarios, there are circumstances where survey data are unavailable or unreliable. In this paper, we present a new customer wallet share estimation approach. In the proposed approach, a predictive model based on decision trees facilitates an accurate estimation of wallet shares for customers relying only on transaction data. We have evaluated our approach using real-world datasets from two businesses from different industries.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 74.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Baumann, C., Burton, S., Elliott, G.: Determinants of customer loyalty and share of wallet in retail banking. J. Financ. Serv. Mark. 9(3), 231–248 (2005)

    Article  Google Scholar 

  2. Chen, Y., Steckel, J.H.: Modeling credit card share of wallet: solving the incomplete information problem. J. Mark. Res. 49(5), 655–669 (2012)

    Article  Google Scholar 

  3. Çifci, S., Ekinci, Y., Whyatt, G., Japutra, A., Molinillo, S., Siala, H.: A cross validation of consumer-based brand equity models: driving customer equity in retail brands. J. Bus. Res. 69(9), 3740–3747 (2016)

    Article  Google Scholar 

  4. Glady, N., Croux, C.: Predicting customer wallet without survey data. J. Serv. Res. 11(3), 219–231 (2009)

    Article  Google Scholar 

  5. Keiningham, T.L., Cooil, B., Aksoy, L., Andreassen, T.W., Weiner, J.: The value of different customer satisfaction and loyalty metrics in predicting customer retention, recommendation, and share-of-wallet. Manag. Serv. Qual. Int. J. 17(4), 361–384 (2007)

    Article  Google Scholar 

  6. Keiningham, T.L., Perkins-Munn, T., Evans, H.: The impact of customer satisfaction on share-of-wallet in a business-to-business environment. J. Serv. Res. 6(1), 37–50 (2003)

    Article  Google Scholar 

  7. Keiningham, T.L., et al.: Perceptions are relative: an examination of the relationship between relative satisfaction metrics and share of wallet. J. Serv. Manag. 26(1), 2–43 (2015)

    Article  Google Scholar 

  8. Kursa, M.B., Rudnicki, W.R., et al.: Feature selection with the boruta package. J. Stat. Softw. 36(11), 1–13 (2010)

    Article  Google Scholar 

  9. Liaw, A., Wiener, M., et al.: Classification and regression by randomforest. R News 2(3), 18–22 (2002)

    Google Scholar 

  10. Mägi, A.W.: Share of wallet in retailing: the effects of customer satisfaction, loyalty cards and shopper characteristics. J. Retail. 79(2), 97–106 (2003)

    Article  Google Scholar 

  11. Merugu, S., Rosset, S., Perlich, C.: A new multi-view regression approach with an application to customer wallet estimation. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 656–661. ACM (2006)

    Google Scholar 

  12. Rosset, S., Perlich, C., Zadrozny, B., Merugu, S., Weiss, S., Lawrence, R.: Wallet estimation models. In: International Workshop on Customer Relationship Management: Data Mining Meets Marketing (2005)

    Google Scholar 

  13. Subramaniam, L.V., Faruquie, T.A., Ikbal, S., Godbole, S., Mohania, M.K.: Business intelligence from voice of customer. In: 2009 IEEE 25th International Conference on Data Engineering, pp. 1391–1402. IEEE (2009)

    Google Scholar 

  14. Weiss, S.M., Indurkhya, N.: Estimating sales opportunity using similarity-based methods. In: Daelemans, W., Goethals, B., Morik, K. (eds.) ECML PKDD 2008. LNCS (LNAI), vol. 5212, pp. 582–596. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-87481-2_38

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science, University of Adelaide, Adelaide, SA, 5005, Australia

    Xiang Li & Zbigniew Michalewicz

  2. Complexica Pty Ltd., 155 Brebner Drive, West Lakes, SA, 5021, Australia

    Xiang Li, Ali Shemshadi, Łukasz P. Olech & Zbigniew Michalewicz

  3. Wroclaw University of Science and Technology, Wybrzeze Stanislawa Wyspianskiego 27, 50-370, Wroclaw, Poland

    Łukasz P. Olech

  4. Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237, Warsaw, Poland

    Zbigniew Michalewicz

  5. Polish-Japanese Academy of Information Technology, Koszykowa 86, 02-008, Warsaw, Poland

    Zbigniew Michalewicz

Authors
  1. Xiang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ali Shemshadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Łukasz P. Olech
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zbigniew Michalewicz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiang Li .

Editor information

Editors and Affiliations

  1. School of Information Technology and Mathematical Sciences, University of South Australia, Adelaide, Australia

    Thuc D. Le

  2. La Trobe University, Melbourne, Australia

    Kok-Leong Ong

  3. CSIRO Scientific Computing, Canberra, Australia

    Yanchang Zhao

  4. CSIRO Scientific Computing, Canberra, Australia

    Warren H. Jin

  5. Consilium Technology, Adelaide, Australia

    Sebastien Wong

  6. School of Information Technology and Mathematical Sciences, University of South Australia, Adelaide, Australia

    Lin Liu

  7. Microsoft Proprietary Limited, Singapore, Singapore

    Graham Williams

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Li, X., Shemshadi, A., Olech, Ł.P., Michalewicz, Z. (2019). Customer Wallet Share Estimation for Manufacturers Based on Transaction Data. In: Le, T., et al. Data Mining. AusDM 2019. Communications in Computer and Information Science, vol 1127. Springer, Singapore. https://doi.org/10.1007/978-981-15-1699-3_14

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-1699-3_14

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1698-6

  • Online ISBN: 978-981-15-1699-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation