Abstract
With the advent of new technologies and the increase in customers’ expectations, services are becoming more complex. This complexity calls for new methods to understand, analyze, and improve service delivery. Summarizing customers’ experience using representative journeys that are displayed on a Customer Journey Map (CJM) is one of these techniques. We propose a genetic algorithm that automatically builds a CJM from raw customer experience recorded in a database. Mining representative journeys can be seen a clustering task where both the sequence of activities and some contextual data (e.g., demographics) are considered when measuring the similarity between journeys. We show that our genetic approach outperforms traditional ways of handling this clustering task. Moreover, we apply our algorithm on a real dataset to highlight the benefit of using a genetic approach.
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Lemon, K.N., Verhoef, P.C.: Understanding customer experience throughout thecustomer journey. J. Mark. 80, 69–96 (2016)
Gürvardar, İ., Rızvanoğlu, K., Öztürk, Ö., Yavuz, Ö.: How to improve the overall pre-purchase experience through a new category structure based on a compatible database: Gittigidiyor (Ebay Turkey) case. In: Marcus, A. (ed.) DUXU 2016. LNCS, vol. 9747, pp. 366–376. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-40355-7_35
Peltola, S., Vainio, H., Nieminen, M.: Key factors in developing omnichannel customer experience with finnish retailers. In: Nah, F.F.-H., Tan, C.-H. (eds.) HCIB 2015. LNCS, vol. 9191, pp. 335–346. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-20895-4_31
Research priorities 2018–2020. Technical report, Marketing Science Institute (2018). https://www.msi.org/research/2018-2020-research-priorities/cultivating-the-customer-asset/1.1.-characterizing-the-customer-journey-along-the-purchase-funnel-and-strategies-to-influence-the-journey/
Bernard, G., Andritsos, P.: A process mining based model for customer journey mapping. In: Proceedings of the Forum and Doctoral Consortium Papers Presented at the 29th International Conference on Advanced Information Systems Engineering (CAiSE 2017) (2017)
Bernard, G., Andritsos, P.: Discovering customer journeys from evidence: agenetic approach inspired by process mining. In: Cappiello, C., Ruiz, M. (eds.) CAiSE 2019. LNBIP, vol. 350, pp. 36–47. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21297-1_4
Gabadinho, A., Ritschard, G., Studer, M., Müller, N.S.: Summarizing sets of categorical sequences: selecting and visualizing representative sequences, pp. 94–106, October 2009
Gabadinho, A., Ritschard, G., Studer, M., Müller, N.S.: Extracting and rendering representative sequences. In: Fred, A., Dietz, J.L.G., Liu, K., Filipe, J. (eds.) IC3K 2009. CCIS, vol. 128, pp. 94–106. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-19032-2_7
Bernard, G., Andritsos, P.: CJM-ex: goal-oriented exploration of customer journey maps using event logs and data analytics. In: 15th International Conference on Business Process Management (BPM 2017) (2017)
Harbich, M., Bernard, G., Berkes, P., Garbinato, B., Andritsos, P.: Discovering customer journey maps using a mixture of Markov models, December 2017
Buijs, J.C., van Dongen, B.F., van der Aalst, W.M.: A genetic algorithm for discovering process trees. In: 2012 IEEE Congress on Evolutionary Computation (CEC), pp. 1–8. IEEE (2012)
Vázquez-Barreiros, B., Mucientes, M., Lama, M.: ProDiGen: mining complete, precise and minimal structure process models with a genetic algorithm. Inform. Sci. 294, 315–333 (2015)
van der Aalst, W.M.P., de Medeiros, A.K.A., Weijters, A.J.M.M.: Genetic process mining. In: Ciardo, G., Darondeau, P. (eds.) ICATPN 2005. LNCS, vol. 3536, pp. 48–69. Springer, Heidelberg (2005). https://doi.org/10.1007/11494744_5
Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions, and reversals. Sov. phys. dokl. 10, 707–710 (1966)
Caliński, T., Harabasz, J.: A dendrite method for cluster analysis. Commun. Stat. Theory Methods 3(1), 1–27 (1974)
Gabadinho, A., Ritschard, G.: Searching for typical life trajectories applied to childbirth histories. Gendered life courses-between individualization and standardization. A European approach applied to Switzerland (2013), pp. 287–312 (2013)
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Bernard, G., Andritsos, P. (2019). Contextual and Behavioral Customer Journey Discovery Using a Genetic Approach. In: Welzer, T., Eder, J., Podgorelec, V., Kamišalić Latifić, A. (eds) Advances in Databases and Information Systems. ADBIS 2019. Lecture Notes in Computer Science(), vol 11695. Springer, Cham. https://doi.org/10.1007/978-3-030-28730-6_16
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DOI: https://doi.org/10.1007/978-3-030-28730-6_16
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