Abstract
The paper proposes an advanced Multilevel Analytics Model –MAM-, applied on a specific case of study
referring to a research project involving an industry mainly working in roadside assistance service (ACI
Global S.p.A.). In the first part of the paper are described the initial specifications of the research project by
addressing the study on information system architectures explaining knowledge gain, decision making and
data flow automatism applied on the specific case of study. In the second part of the paper is described in
details the MAM acting on different analytics levels, by describing the first analyzer module and the second
one involving data mining and analytical model suitable for strategic marketing e business intelligence –BI-.
The analyzer module is represented by graphical dashboards useful to understand the industry business trend
and to execute main decision making. The second module is suitable to understand deeply services trend and
clustering by finding possible correlations between the variables to analyze. For the data mining processing
has been applied the Rapid Miner workflows of K-Means clustering and the Correlation Matrix. The second
part of the paper is mainly focused on analytical models representing phenomena such as vehicle accidents
and fleet car sharing trend, which can be correlated with strategic car services. The proposed architectures
and models represent methodologies and approaches able to improve strategic marketing and –BI- advanced
analytics following ‘Frascati’ research guidelines. The MAM model can be adopted for other cases of study
concerning other industry applications. The originality of the paper is the scientific methodological approach
used to interpret and read data, by executing advanced analytical models based on data mining algorithms
which can be applied on industry database systems representing knowledge base.
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