Skip to main content

Analysis of Customers’ Spatial Distribution Through Transaction Datasets

Part of the Lecture Notes in Computer Science book series (TLDKS,volume 9860)

Abstract

Understanding people’s consumption behavior while traveling between retail shops is essential for successful urban planning as well as determining an optimized location for an individual shop. Analyzing customer mobility and deducing their spatial distribution help not only to improve retail marketing strategies, but also to increase the attractiveness of the district through the appropriate commercial planning. For this purpose, we employ a large-scale and anonymized datasets of bank card transactions provided by one of the largest Spanish banks: BBVA. This unique dataset enables us to analyze the combination of visits to stores where customers make consecutive transactions in the city. We identify various patterns in the spatial distribution of customers. By comparing the number of transactions, the distributions and their respective properties such as the distance from the shop we reveal significant differences and similarities between the stores.

Keywords

  • Consumer behaviors
  • Transaction data
  • Human mobility
  • Urban studies
  • Barcelona

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-662-53416-8_11
  • Chapter length: 13 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   84.99
Price excludes VAT (USA)
  • ISBN: 978-3-662-53416-8
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   109.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.

References

  1. Jacobs, J.: The Death and Life of Great American Cities. Random House, New York (1961)

    Google Scholar 

  2. Gehl, J.: Life Between Buildings: Using Public Space. Island Press, Washington-Covelo-London (2011)

    Google Scholar 

  3. Taneja, S.: Technology moves in. Chain Store Age 75, 136–138 (1999)

    Google Scholar 

  4. Porta, S., Latora, V., Wang, F., Rueda, S., Strano, E., Scellato, S., Cardillo, A., Belli, E., Càrdenas, F., Cormenzana, B., Latora, L.: Street centrality and the location of economic activities in Barcelona. Urban Stud. 49(7), 1471–1488 (2012)

    CrossRef  Google Scholar 

  5. Krumme, C., Llorente, A., Cebrian, M., Pentland, A., Moro, E.: The predictability of consumer visitation patterns. Sci. Rep. 3, 1645 (2013). doi:10.1038/srep01645

    CrossRef  Google Scholar 

  6. Sobolevsky, S., Sitko, I., Grauwin, S., des Combes, R.T., Hawelka, B., Arias, J.M., Ratti, C.: Mining urban performance: scale-independent classification of cities based on individual economic transactions (2014). arXiv:1405.4301

  7. Sobolevsky, S., Sitko, I., des Combes, R.T., Hawelka, B., Arias, J.M., Ratti, C.: Money on the move: big data of bank card transactions as the new proxy for human mobility patterns and regional delineation. The case of residents and foreign visitors in spain. Big Data (BigData Congress) In: 2014 IEEE International Congress, pp. 136–143 (2014)

    Google Scholar 

  8. Leenheer, J., Bijmolt, Tammo, H.A.: Which retailers adopt a loyalty program? an empirical study. J. Retail. Consum. Serv. 15, 429–442 (2008)

    CrossRef  Google Scholar 

  9. González, M.C., Hidalgo, C.A., Barabási, A.L.: Understanding individual human mobility patterns. Nature 453, 779–782 (2008)

    CrossRef  Google Scholar 

  10. Hoteit, S., Secci, S., Sobolevsky, S., Ratti, C., Pujolle, G.: Estimating human trajectories and hotspots through mobile phone data. Comput. Netw. 64, 296–307 (2014)

    CrossRef  Google Scholar 

  11. Kung, K.S., Greco, K., Sobolevsky, S., Ratti, C.: Exploring universal patterns in human home/work commuting from mobile phone data. PLoS ONE 9(6), e96180 (2014)

    CrossRef  Google Scholar 

  12. Ratti, C., Pulselli, R., Williams, S., Frenchman, D.: Mobile landscapes: using location data from cell phones for urban analysis. Environ. Plan. B Plan. Des. 33(5), 727–748 (2006)

    CrossRef  Google Scholar 

  13. Sobolevsky, S., Szell, M., Campari, R., Couronné, T., Smoreda, Z., Ratti, R.: Delineating geographical regions with networks of human interactions in an extensive set of countires. PLoS ONE 8(12), e81707 (2013)

    CrossRef  Google Scholar 

  14. Kanda, T., Shiomi, M., Perrin, L., Nomura, T., Ishiguro, H., Hagita, N.: Analysis of people trajectories with ubiquitous sensors in a science museum. In: Proceedings 2007 IEEE International Conference on Robotics and Automation (ICRA 2007), pp. 4846–4853 (2007)

    Google Scholar 

  15. Larson, J., Bradlow, E., Fader, P.: An exploratory look at supermarket shopping paths. Int. J. Res. Mark. 22(4), 395–414 (2005)

    CrossRef  Google Scholar 

  16. Delafontaine, M., Versichele, M., Neutens, T., Van de Weghe, N.: Analysing spatiotemporal sequences in Bluetooth tracking data. Appl. Geogr. 34, 659–668 (2012)

    CrossRef  Google Scholar 

  17. Kostakos, V., O’Neill, E., Penn, A., Roussos, G., Papadongonas, D.: Brief encounters: sensing, modelling and visualizing urban mobility and copresence networks. ACM Trans. Comput. Hum. Interact. 17(1), 1–38 (2010)

    CrossRef  Google Scholar 

  18. Versichele, M., Neutens, T., Delafontaine, M., Van de Weghe, N.: The use of bluetooth for analysing spatiotemporal dynamics of human movement at mass events: a case study of the ghent festivities. Appl. Geogr. 32, 208–220 (2011)

    CrossRef  Google Scholar 

  19. Yoshimura, Y., Girardin, F., Carrascal, J.P., Ratti, C., Blat, J.: New tools for studing visitor behaviours in museums: a case study at the louvre. In: Fucks, M., Ricci, F., Cantoni, L. (eds.) Information and Communication Technologies in Tourism 2012, pp. 391–402. Springer, New York (2012)

    CrossRef  Google Scholar 

  20. Yoshimura, Y., Sobolevsky, S., Ratti, C., Girardin, F., Carrascal, J.P., Blat, J., Sinatra, R.: An analysis of visitors’ behaviour in The Louvre Museum: a study using Bluetooth data. Environ. Plan. B Plan. Des. 41(6), 1113–1131 (2014)

    CrossRef  Google Scholar 

  21. Huff, D.L.: Defining and estimating a trade area. J. Mark. 28, 34–38 (1964)

    CrossRef  Google Scholar 

  22. Huff, D.L.: A programmed solution for approximating an optimum retail location. Land Econ. 42, 293–303 (1966)

    CrossRef  Google Scholar 

  23. Asakura, Y., Iryo, T.: Analysis of tourist behaviour based on the tracking data collected using a mobile communication instrument. Transp. Res. Part A Policy Pract. 41(7), 684–690 (2007)

    CrossRef  Google Scholar 

  24. Shoval, N., McKercher, B., Birenboim, A., Ng, E.: The application of a sequence alignment method to the creation of typologies of tourist activity in time and space. Environ. Plan. B Plan. Des. 42(1), 76–94 (2013)

    CrossRef  Google Scholar 

  25. Christaller, W.: Central Places in Southern Germany. English edition, 1966, translated by Carlisle W., Baskin. Englewood Cliffs, Printice-Hall, New Jersey (1935)

    Google Scholar 

  26. Losch, A.: The Economics of Location (translated by Woglam W H). Yale University Press, New Haven (1954)

    Google Scholar 

  27. Fujita, M., Krugman, P., Venables, A.: The Spatial Economy-Cities, Regions and International Trade. MIT Press, Cambridge (1999)

    MATH  Google Scholar 

Download references

Acknowledgments

We would like to thank the Banco Bilbao Vizcaya Argentaria (BBVA) for providing the dataset for this study. Special thanks to Juan Murillo Arias, Marco Bressan, Elena Alfaro Martinez, Maria Hernandez Rubio and Assaf Biderman for organizational support of the project and stimulating discussions. We further thank MIT SMART Program, Accenture, Air Liquide, The Coca Cola Company, Emirates Integrated Telecommunications Company, The ENEL foundation, Ericsson, Expo 2015, Ferrovial, Liberty Mutual, The Regional Municipality of Wood Buffalo, Volkswagen Electronics Research Lab and all the members of the MIT Senseable City Lab Consortium for supporting the research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yuji Yoshimura .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2016 Springer-Verlag GmbH Germany

About this chapter

Cite this chapter

Yoshimura, Y., Amini, A., Sobolevsky, S., Blat, J., Ratti, C. (2016). Analysis of Customers’ Spatial Distribution Through Transaction Datasets. In: , et al. Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVII. Lecture Notes in Computer Science(), vol 9860. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-53416-8_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-53416-8_11

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-53415-1

  • Online ISBN: 978-3-662-53416-8

  • eBook Packages: Computer ScienceComputer Science (R0)