PREDICTING THE SIZE OF THE COMPANY-CUSTOMER BASE BASED ON THE MARKOV CHAINS
Table of contents
Share
Metrics
PREDICTING THE SIZE OF THE COMPANY-CUSTOMER BASE BASED ON THE MARKOV CHAINS
Annotation
PII
S042473880000616-6-1
Publication type
Article
Status
Published
Pages
79-94
Abstract
The article represents the information and logical complex model to manage the company’s customer base in order to calculate the index of long-term value of the client. In contrast to the previous issues this model takes into account the peculiarities of consumer behavior and sociodemographic characteristics of the client groups, and the movement of customers within the customer base is represented as a Markov chain. Developed complex dynamic model to manage the company’s customer base makes possible to forecast the cluster frequency and the client base at all on any period, to analyze the population-change-dynamics of client cluster and to highlight the most important stages in the formation and development of the customer base. On each stage highlighted groups of clients are estimated according to future company’s profit and potential for cross selling of products/services. The estimates allow to calculate the budget for marketing activities on retention of given profit level and to compose the most effective plan of address-directed marketing activities.
Keywords
management of customer base of the company, retail trade, group of clients, customer loyalty, buying behavior, Markov chain, dynamic model, long-term value of the customer base
Date of publication
01.01.2016
Number of purchasers
0
Views
57
Readers community rating
0.0 (0 votes)
Cite Download pdf 100 RUB / 1.0 SU

To download PDF you should sign in

Full text is available to subscribers only
Subscribe right now
Only article
100 RUB / 1.0 SU
Whole issue
0 RUB / 0.0 SU
All issues for 2016
0 RUB /  SU
1

References



Additional sources and materials

Andreeva A.V. (2010). Model' upravleniya klientskoj bazoj - novyj shag v razvitii CRM? // Direktor informatsionnoj sluzhby (CIO.RU). № 3. M.: Otkrytye sistemy. S. 26-28.   

Andreeva A.V. (2012). Optimal'noe upravlenie klientskoj bazoj na osnove pokazatelya dolgosrochnoj stoimosti klienta // Biznes-informatika. № 4(22). S. 61-68.              

Andreeva A.V. (2011). Razrabotka modeli prognozirovaniya chislennosti klientskoj bazy kompanii // Audit i finansovyj analiz. № 6. S. 104-109.                 

Dobrovidova M.A. (2003). Ehffektivnye tekhnologii povysheniya loyal'nosti potrebitelej // Marketing i marketingovye issledovaniya. № 3(45). S. 48-53.        

Karasev A.P. (2008). Razrabotka faktornoj modeli loyal'nosti dlya rynka uslug sotovoj svyazi // Marketing i marketingovye issledovaniya. № 2(74). S. 98-111.     

Kryukova A.A., Kuz'min E.V. (2009). Razrabotka kontseptsii kompleksnogo upravleniya klientami // Vestnik SGEhU: ezhemesyachnyj zhurnal. № 7. S. 61-64. 

Lamben Zh.-Zh. (1996). Strategicheskij marketing. Evropejskaya perspektiva. SPb.: Nauka.  

Mejer M.V. (2004). Otsenka ehffektivnosti biznesa. M.: Vershina.  

Peppers D., Rodzhers M. (2006). Upravlenie otnosheniyami s klientami. M.: Mann, Ivanov i Ferber.        

Polezhaev I.E. (2006b). Metod segmentatsii klientskikh baz dannykh na osnove zhiznennogo tsikla klienta. [Ehlektronnyj resurs] // Issledovano v Rossii. S. 1875-1902. Rezhim dostupa: http://zhurnal.ape.relarn. ru/articles/2006/200.pdf, svobodnyj. Zagl. s ehkrana. Yaz. rus. (data obrascheniya: iyul' 2015 g.).           

Polezhaev I.E. (2006a). Markovskaya model' dlya prognozirovaniya sostoyaniya klientskoj bazy dannykh. [Ehlektronnyj resurs] // Issledovano v Rossii. S. 1903-1907. Rezhim dostupa: http://zhurnal.ape.relarn. ru/articles/2006/201.pdf, svobodnyj. Zagl. s ehkrana. Yaz. rus. (data obrascheniya: iyul' 2015 g.).           

Staroverov O.V. (1997). Azy matematicheskoj demografii. M.: Nauka. S. 56-59.         

S'yuehll K., Braun P. (2007). Klienty na vsyu zhizn'. M.: Mann, Ivanov i Ferber.     

Tret'yak O.A., Sloev I.A. (2012). Otsenka marketingovoj deyatel'nosti po sostoyaniyu klientskogo potoka // Rossijskij zhurnal menedzhmenta. T. 10. № 1. S. 29-50.            

Tsysar' A.V. (2002). Loyal'nost' pokupatelej: osnovnye opredeleniya, metody izmereniya, sposoby upravleniya // Marketing i marketingovye issledovaniya. № 5(41). S. 55-61.       

Cherkashin P.A. (2004). Gotovy li Vy k vojne za klienta? Strategiya upravleniya vzaimootnosheniyami s klientami. M.: iNtUIT.RU. Aaker D.A. (1991).

Managing Brand Equity. N.Y.: The Free Aress.   

Berger P.D., Nasr N.L. (1998). Customer Lifetime Value: Marketing Models and Applications // Journal of Interactive Marketing. Vol. 12. Nc. 1. Winter. R. 17-30.        

Berry M.J.A., Linoff G.S. (2004). Data Mining Techniques. Indianapolis: Wiley Publishing, Inc.     

Dipak J., Siddhartha S. (2002). Customer Lifetime Value Research in Marketing: A Review and Future Directions // Journal of Interactive Marketing. Vol. 16. Na 2. R. 34-45.              

Fader P.S., Hardie B.G.S., Lee K.L. (2005). Counting Your Customers the Easy Way: An Alternative to the Pareto/NBD Model // Marketing Science. Vol. 24(2). P. 275-284.        

Fader P.S., Hardie B.G.S. (2009). Probability Models for Customer-Base Analysis // Journal of Interactive Marketing. Vol. 23. P. 61-69.             

Hofmeyr J., Rice B. (2000). Commitment-Led Marketing. Chichester: John Wiley and Sons.         

Malthous E.C., Blattberg R.C. (2005). Can We Predict Customer Lifetime Value? // Journal of Interactive Marketing. Vol. 19. P. 2-16.

Pfeifer P.E., Carraway R.L. (2000). Modeling Customer Relationships as Markov Chains // Journal of Interactive Marketing. Vol. 14.         

Spring. P. 43-55. Reichheld F. (1996). The Loyalty Effect: The Hidden Force Behind Growth, Profits, and Lasting Value. Boston: Harvard Business School Press.

Schmittlein D.C., Morrison D.G., Colombo R. (1987). Counting Your Customers: Who Are They and What Will They Do Next? // Management Science. Vol. 33. January. P. 1-24.