TITLE:
Modeling the Customer Satisfaction Influence on the Long Term Sales: Example with Leading OTC Analgesics INN on National Market
AUTHORS:
Guenka Petrova, Nikolay Mateev, Dimitar Barumov, Lily Peikova, Maria Dimitrova, Manoela Manova
KEYWORDS:
OTC Analgesics; Marketing; Customer Satisfaction; Markov Model
JOURNAL NAME:
Modern Economy,
Vol.4 No.9,
September
5,
2013
ABSTRACT: Background:
The customer satisfaction models are used to examine brand loyalty and sales.
The utilization of the counter medicines depends directly on the level of
knowledge of consumers, preferences and their satisfaction could be considered
as an important predictor for their revenue. Objectives: The goal of the
current study is to develop a Markov model for assessing the influence of the
customer satisfaction on long term sales of leading OTC international nonproprietary
names (INNs) of analgesics on the national market. Methods: Two
first-order stationary Markov models based on marketing data for OTC analgesics
sales and customer satisfaction inquiry, particularly from metamizole (MET),
paracetamol (PAR), acetysal (ASA), and ibuprofen (IBU) were created and
manipulated. The first model considered the very satisfied customers and the
second the very satisfied and the somewhat satisfied customers. Results:
MET is the INN with the most loyal customers followed by PAR. The product
Markov matrix was derived after multiplications of the matrixes with market
share and loyal customers’ probabilities. The steady state is achieved after 17
years for the group of satisfied customers and after 40 iterations for
the group of somewhat satisfied. The market fluctuations are more dynamic in
the second model probably due to lower determination of customers purchasing
behavior. Conclusions: The model allows prediction of the long term
changes in sales, differences between the groups of customers and long term
marketing fluctuations. It could be useful in companies’ strategic sales
management.