Advanced methods in Sales Strategy
- Credits: 10
- Ending: Examination
- Range: 16sP
- Semester: winter
- Year: 2
- Faculty of Business Management
Teachers
Included in study programs
Teaching results
Knowledge:
• Gaining knowledge of current / modern dimensions of the sales strategy, its variants and the process of its creation.
• Gaining knowledge of complex analytical and specific methods of sales engineering, applied in preparing and choosing the proper sales strategy .
• Gaining knowledge about the possibilities of evaluating already implemented sales strategies and measuring its performance.
Skills:
• Managing the preparation and implementation of selected types of sales strategies (from the initial analysis to the formulation of tasks and application of marketing programmes and activities).
• Applying complex analytical tools and specific methods of sales engineering.
• Evaluating the effectiveness of implemented sales strategies.
Competencies:
• Ability to synthesize knowledge from defined areas and then apply them in solving a specific selected problem in the field of sales strategies.
• Ability to identify, analyze and critically assess sales issues and sales strategies in accordance with the assigned task.
• Ability to set goals, systematize the necessary data and information, use appropriate methods, formulate proposals and conclusions.
• Preparing a presentation of solving the assigned task in the field of sales strategies using ICT and the ability to answer questions in a qualified and independent manner.
Indicative content
1. Introduction to quantitative methods in sales strategies.
2. Advanced market segmentation methods.
3. Integrated methodological approach to targeting and market positioning.
4. Predictive and optimization methods for new product design and forecasting of future sales. Conjoint analysis as a method for optimizing product design to maximize future market share. The classification of predictive models. Bass model and ASSESSOR model as forecasting models, predicting future sales of product innovation. Panel regression.
5. Resource allocation.
6. Dimensions of modern sales approaches and strategies.
Support literature
1. Majtán, Š. et al. (2013). Odbytová stratégia. Bratislava: Vydavateľstvo Sprint2, 2013. ISBN 978-80-89393-92-3
2. Lilien, G.L., Rangaswamy, A., De Bruyn, A. (2018) Principles of Marketing Engineering and Analytics, 3rd Edition. DecisionPro, Inc.; 328 p. ISBN 978-0985764821.
3. Lilien, G.L., Kotler, Ph., Moorthy, K. S. (1991). Marketing Models. Prentice Hall, 803 p. ISBN 978-0135446447.
4. Šlosár, Róbert, Majtán, Štefan, Štetka, Peter, Grisáková, Nora. Vizuálne podnety a responzívne správanie spotrebiteľov. Recenzenti: Peter Štarchoň, Miroslava Szarková. 1. vydanie. Praha : Wolters Kluwer ČR, 2019. 213 s.
5. Jean-Claude Usunier, Julie Anne Lee. (2012). Marketing Across Cultures, 6th Edition. Pearson, 478 p. ISBN 978-0273757733.
6. Everett M. Rogers (2003). Diffusion of Innovations, 5th Edition. Free Press, 518 p. ISBN 978-0743222099
7. Štetka, Peter, Grisáková, Nora, Kintler, Jakub, Hrušovská, Dana. (2019). Faktory difúzie produktovej inovácie. Recenzenti: Štefan Majtán, Alena Trsťanská. 1. vydanie. Praha : Wolters Kluwer ČR, 2019. 197 s. ISBN 978-80-7598-629-0.
8. Hojdik, Vladimír, Hrušovská, Dana, Grančičová, Katarína. (2020). Reputácia nielen v kontexte eko-inovácií: možnosti merania a hodnotenia reputácie a online reputácie : vedecká monografia. České Budějovice : Vysoká škola evropských a regionálních studií, 2020. 159 s. ISBN 978-80-7556-078-0.
9. Bass, Frank M. (1969). A new product growth for model consumer durables. Management Science, 15 215-227
10. Mahajan, Vijay, Charlotte H. Mason, V. Seenu Srinivasan. (1986). An evaluation of estimation procedures for new product diffusion models. In Innovation Diffusion Models of New Product Acceptance, Vijay Mahajan and Yoram Wind, eds. Cambridge, MA: Ballinger Publishing Company.
11. Schmittlein, David C., Vijay Mahajan. (1982). Maximum likelihood estimation for an innovation diffusion model of new product acceptance. Marketing Science 1 (1) 57-78.
12. Srinivasan, V. Seenu and Charlotte Mason. (1986). Nonlinear least squares estimation of new product diffusion models. Marketing Science, 5 (2), 169-178.
13. Cooper, Robert G. (2017). Winning at New Products: Creating Value Through Innovation. Basic Books; 5th edition (September 19, 2017). 448 pages, ISBN-13 : 978-0465093328
14. Greene, William H. (2017). Econometric Analysis (Eighth edition), New York, Pearson. ISBN-13 : 978-9353061074
15. Pesaran, M. Hashem. (2015). Time series and panel data econometrics, Oxford, Oxford University Press. 1062 pages, ISBN-13: 978-0198759980
16. Thomas W. Valente. (1995). Network Models of the Diffusion of Innovations (Quantitative Methods in Communication Subseries). 2nd ed. Hampton Press (NJ); Second Printing edition (January 10, 1995). 171 pages, ISBN-13 : 978-1881303220
17. Vithala R. Rao. (2014). Applied Conjoint Analysis. Springer; 2014th edition (February 20, 2014). 587 pages, ISBN-13: 978-3540877523
18. Thomas Zoëga Ramsøy. (2015). Introduction to Neuromarketing & Consumer Neuroscience. Neurons Inc; 1st edition (May 13, 2015). 204 pages, ISBN-13 : 978-8799760206
19. Simon Kingsnorth. (2019). Digital Marketing Strategy: An Integrated Approach to Online Marketing. 2nd ed. Kogan Page; 2nd edition (April 28, 2019). 384 pages, ISBN-13 : 978-0749484224.
Syllabus
1. Introduction to quantitative methods in sales strategies. Classification of analytical tools and their sales-strategic implications. Interconnected analytical process, building analytical skills and implementation of tools supporting qualified decision-making on sales strategies. Basic definition and types of models. Small models and their benefits (Trial / Repeat model). Model diagnostics. Basic concept of response models. Response functions and dynamic effects. 2. Advanced market segmentation methods. Need-based market segmentation (hierarchical clustering) and choice-based market segmentation, using the MNL model (logistic regression), linear regression, RFM model (Recency, Frequency and Monetary value) and CART (Classification and Regression Tree). Extension of latent class methods (latent clustering and latent regression) and Bayesian classification. 3. Integrated methodological approach to targeting and market positioning. The use of segmentation results to target specific consumers and classify existing customers. Customer profitability analysis, scoring models and score classes. The use of GE / McKinsey matrix in measuring the segment appeal. Perceptual mapping, preference mapping and JointSpace maps. Analysis of preference elasticity. 4. Predictive and optimization methods for new product design and forecasting of future sales. Conjoint analysis as a method for optimizing product design to maximize future market share. The classification of predictive models. Bass model and ASSESSOR model as forecasting models, predicting future sales of product innovation. Panel regression. 5. Resource allocation. ADBUG model for preparing the optimized budget for marketing communications, CALLPLAN for optimizing the sales resources. Current approaches and developments in the field of sales performance measurement and additional assessment (key performance indicators, sentiment analysis, panel data analysis). 6. Dimensions of modern sales approaches and strategies. Current knowledge in the field of neuromarketing (eyetracking, EEG), online marketing, global and intercultural marketing and their implications in relation to sales strategies.
Requirements to complete the course
10 % continuous performance of assigned tasks, 30 % continuous written work (scientific essay), 60 % oral examination
Student workload
260 h - participation in consultations 16 h, preparation for consultations 32 h, processing of continuous assignments 16 h, processing of scientific state 90 h, preparation for the exam 106 h)
Language whose command is required to complete the course
Slovak, English
Date of approval: 11.03.2024
Date of the latest change: 14.05.2022