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Spatial models for online retail churn: Evidence from an online grocery delivery service in Madrid

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  • Miguel Angel de la Llave Montiel
  • Fernando López

Abstract

This paper presents evidence of the significant role that geography plays in customer churn behaviour in online retail. In an urban environment, mimetic behaviours are found to affect nearby individuals. This novel approach is based on the idea that customer churn is not randomly distributed across the map. This paper analyses more than 2,000 spatially georeferenced customers and demonstrates that customers show different patterns when deciding to cease activity, and that other factors besides spatial autocorrelation influence churn probability. Finally, the results prove that including spatial spillover in models improves predictability. This improvement results in substantial economic benefits since marketing managers can consequently reduce their company's loss of customers more effectively. Este artículo presenta pruebas del importante papel que desempeña la geografía en el comportamiento de la rotación de clientes en la venta en línea al por menor. En un entorno urbano, se ha comprobado que los comportamientos miméticos afectan a los individuos cercanos. Este novedoso enfoque se basa en la idea de que la rotación de clientes no está distribuida al azar en el mapa. En este artículo se analizan más de 2.000 clientes georreferenciados espacialmente y se demuestra que los clientes muestran patrones diferentes cuando deciden cesar la actividad, y que hay otros factores además de la autocorrelación espacial que influyen en la probabilidad de abandono como cliente. Por último, los resultados demuestran que la inclusión de los efectos de spillover espaciales en los modelos mejora la previsibilidad. Esta mejora se traduce en beneficios económicos sustanciales, ya que los gerentes responsables de la comercialización pueden, en consecuencia, reducir más eficazmente la pérdida de clientes de su empresa. 本稿では、ネット通販の顧客離反行動において地理が担う重要な役割のエビデンスを提示する。都市部の環境では、模倣行動が近隣の他者に影響することが認められる。今回の新規アプローチは、顧客離反は地図上ではランダムに分布しないという考えに基づいている。本稿では、空間的に地理参照された2,000以上の顧客を解析し、顧客が活動停止を決定する際のパターンは様々であること、および空間的自己相関以外の要因が離反の可能性に影響することを示した。また、結果から、空間的スピルオーバーをモデルに組み込むことが予測精度を改善することが判明した。マーケティング・マネージャーは結果的に顧客離反をより効果的に減らすことができるので、この改善は大きな経済的利益をもたらす。

Suggested Citation

  • Miguel Angel de la Llave Montiel & Fernando López, 2020. "Spatial models for online retail churn: Evidence from an online grocery delivery service in Madrid," Papers in Regional Science, Wiley Blackwell, vol. 99(6), pages 1643-1665, December.
  • Handle: RePEc:bla:presci:v:99:y:2020:i:6:p:1643-1665
    DOI: 10.1111/pirs.12552
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    1. Correa, Juan C. & Garzón, Wilmer & Brooker, Phillip & Sakarkar, Gopal & Carranza, Steven A. & Yunado, Leidy & Rincón, Alejandro, 2019. "Evaluation of collaborative consumption of food delivery services through web mining techniques," Journal of Retailing and Consumer Services, Elsevier, vol. 46(C), pages 45-50.
    2. Trivedi, Minakshi, 2011. "Regional and Categorical Patterns in Consumer Behavior: Revealing Trends," Journal of Retailing, Elsevier, vol. 87(1), pages 18-30.
    3. Buckinx, Wouter & Van den Poel, Dirk, 2005. "Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting," European Journal of Operational Research, Elsevier, vol. 164(1), pages 252-268, July.
    4. Vera Miguéis & Dirk Poel & Ana Camanho & João Falcão e Cunha, 2012. "Predicting partial customer churn using Markov for discrimination for modeling first purchase sequences," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(4), pages 337-353, December.
    5. Pradeep K. Chintagunta & Junhong Chu & Javier Cebollada, 2012. "Quantifying Transaction Costs in Online/Off-line Grocery Channel Choice," Marketing Science, INFORMS, vol. 31(1), pages 96-114, January.
    6. Roger S. Bivand & David W. S. Wong, 2018. "Comparing implementations of global and local indicators of spatial association," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 716-748, September.
    7. Ray, Arghya & Dhir, Amandeep & Bala, Pradip Kumar & Kaur, Puneet, 2019. "Why do people use food delivery apps (FDA)? A uses and gratification theory perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 221-230.
    8. Haenlein, Michael, 2013. "Social interactions in customer churn decisions: The impact of relationship directionality," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 236-248.
    9. Martinetti, Davide & Geniaux, Ghislain, 2017. "Approximate likelihood estimation of spatial probit models," Regional Science and Urban Economics, Elsevier, vol. 64(C), pages 30-45.
    10. Solmaria Halleck Vega & J. Paul Elhorst, 2015. "The Slx Model," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 339-363, June.
    11. Kim, Su Jung & Wang, Rebecca Jen-Hui & Malthouse, Edward C., 2015. "The Effects of Adopting and Using a Brand's Mobile Application on Customers' Subsequent Purchase Behavior," Journal of Interactive Marketing, Elsevier, vol. 31(C), pages 28-41.
    12. Pedro Amaral & Luc Anselin & Daniel Arribas-Bel, 2013. "Testing for spatial error dependence in probit models," Letters in Spatial and Resource Sciences, Springer, vol. 6(2), pages 91-101, July.
    13. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    14. Wang, Rebecca Jen-Hui & Malthouse, Edward C. & Krishnamurthi, Lakshman, 2015. "On the Go: How Mobile Shopping Affects Customer Purchase Behavior," Journal of Retailing, Elsevier, vol. 91(2), pages 217-234.
    15. Elms, Jonathan & de Kervenoael, Ronan & Hallsworth, Alan, 2016. "Internet or store? An ethnographic study of consumers' internet and store-based grocery shopping practices," Journal of Retailing and Consumer Services, Elsevier, vol. 32(C), pages 234-243.
    16. Park, Chang Hee, 2017. "Online Purchase Paths and Conversion Dynamics across Multiple Websites," Journal of Retailing, Elsevier, vol. 93(3), pages 253-265.
    17. Brian J.L. Berry & H. Gardiner Barnum & Robert J. Tennant, 1962. "Retail Location And Consumer Behavior," Papers in Regional Science, Wiley Blackwell, vol. 9(1), pages 65-106, January.
    18. Verbeke, Wouter & Dejaeger, Karel & Martens, David & Hur, Joon & Baesens, Bart, 2012. "New insights into churn prediction in the telecommunication sector: A profit driven data mining approach," European Journal of Operational Research, Elsevier, vol. 218(1), pages 211-229.
    19. Uroš Droftina & Mitja Å tular & Andrej Košir, 2015. "A diffusion model for churn prediction based on sociometric theory," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(3), pages 341-365, September.
    20. Basile, Roberto & Durbán, María & Mínguez, Román & María Montero, Jose & Mur, Jesús, 2014. "Modeling regional economic dynamics: Spatial dependence, spatial heterogeneity and nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 229-245.
    21. Timothy J. Richards & Stephen F. Hamilton & William J. Allender, 2014. "Social Networks and New Product Choice," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(2), pages 489-516.
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