Autor: Rzepakowski, P. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Supporting telecommunication product sales by conjoint analysis
Autorzy:: Rzepakowski, P.
Powiązania:: https://bibliotekanauki.pl/articles/308095.pdf
Data publikacji:: 2008
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: decision analysis
multiple criteria analysis
utility theory
preference measurement
conjoint analysis
consumer behavior
purchase intent
marketing
marketing tools
Opis:: Conjoint analysis is widely used as a marketing research technique to study consumers' product preferences and simulate customer choices. It is used in designing new products, changing or repositioning existing products, evaluating the effect of price on purchase intent, and simulating market share. In this work the possibility of conjoint analysis usage in telecommunication filed is analyzed. It is used to find optimal products which could be recommended to telecommunication customers. First, a decision problem is defined. Next, the conjoint analysis method and its connections with ANOVA as well as regression techniques are presented. After that, different utility functions that represent preferences for voice, SMS, MMS and other net services usage are formulated and compared. Parameters of the proposed conjoint measures are determined by regression methods running on behavioral data, represented by artificially generated call data records. Finally, users are split in homogenous groups by segmentation techniques applied to net service utilities derived from conjoint analysis. Within those groups statistical analyses are performed to create product recommendations. The results have shown that conjoint analysis can be successfully applied by telecommunication operators in the customer preference identification process. However, further analysis should be done on real data, other data sources for customer preference identification should be explored as well.
Źródło:: Journal of Telecommunications and Information Technology; 2008, 3; 28-34
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 2.

Tytuł:: Incorporating Customer Preference Information into the Forecasting of Service Sales
Autorzy:: Rzepakowski, P.
Powiązania:: https://bibliotekanauki.pl/articles/309026.pdf
Data publikacji:: 2009
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: conjoint analysis
consumer behavior
decision analysis
forecasting
marketing tools
multiple criteria analysis
preference measurement
Opis:: Customers change their preferences while getting more familiar with services or being motivated to change their buying habits. Different sources of motivation induce customers to change their behavior: an advertisement, a leader in a reference group, satisfaction from services usage and other experiences, but usually those reasons are unknown. Nevertheless, people vary in susceptibility to suggestions and innovations, and also in preference structure change dynamics. Historical information about the preference structure gives additional information about uncertainty in forecasting activity. In this work the conjoint analysis method was used to find customer preference structure and to improve a prediction accuracy of telecommunication services usage. The results have shown that prediction accuracy increases about by one percent point, what results in a 20 percent increase after using proposed algorithm modification.
Źródło:: Journal of Telecommunications and Information Technology; 2009, 3; 50-58
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 3.

Tytuł:: Uplift Modeling in Direct Marketing
Autorzy:: Rzepakowski, P.
Jaroszewicz, S.
Powiązania:: https://bibliotekanauki.pl/articles/309211.pdf
Data publikacji:: 2012
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: decision trees
information theory
marketing tools
uplift modeling
Opis:: Marketing campaigns directed to randomly selected customers often generate huge costs and a weak response. Moreover, such campaigns tend to unnecessarily annoy customers and make them less likely to answer to future communications. Precise targeting of marketing actions can potentially results in a greater return on investment. Usually, response models are used to select good targets. They aim at achieving high prediction accuracy for the probability of purchase based on a sample of customers, to whom a pilot campaign has been sent. However, to separate the impact of the action from other stimuli and spontaneous purchases we should model not the response probabilities themselves, but instead, the change in those probabilities caused by the action. The problem of predicting this change is known as uplift modeling, differential response analysis, or true lift modeling. In this work, tree-based classifiers designed for uplift modeling are applied to real marketing data and compared with traditional response models, and other uplift modeling techniques described in literature. The experiments show that the proposed approaches outperform existing uplift modeling algorithms and demonstrate significant advantages of uplift modeling over traditional, response based targeting.
Źródło:: Journal of Telecommunications and Information Technology; 2012, 2; 43-50
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Informacja

Wyszukujesz frazę "Rzepakowski, P." wg kryterium: Autor

Źródło danych

Dostawca treści

Kolekcja

Rok wydania

Wydawca

Temat

Autor

Typ dokumentu

Język