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Metodi Quantitativi per Economia, Finanza e Management Lezione n°2.

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Presentation on theme: "Metodi Quantitativi per Economia, Finanza e Management Lezione n°2."— Presentation transcript:

1 Metodi Quantitativi per Economia, Finanza e Management Lezione n°2

2 Business intelligence (*) (BI) refers to skills, knowledge, technologies, applications, quality, risks, security issues and practices used to help a business to acquire a better understanding of market behavior and commercial context. For this purpose it undertakes the collection, integration, analysis, interpretation and presentation of business information. BI applications provide historical, current, and predictive views of business operations, most often using data already gathered into a Data Warehouse or a Data Mart. BI applications tackle sales, production, financial, and many other sources of business data to support better business decision- making. Thus one can also characterize a BI system as a Decision Support System (DSS). (*) Business Intelligence

3 Business Intelligence systems are data-driven DSS. Internal Data Operational digital transaction CRM digital transaction External Data Public Data Base (Bureau of Census, Central Bank,..) Private Data Base (Consodata, D&B,..) Market Research Business Intelligence & Data Sources

4 Business Intelligence & Internal Data agents portals Management systems DW data collectiondata modelling & processing data analysis call center Business Intelligence Operational & Strategic Marketing Hints operations

5 Business Intelligence & Internal Data Interaction between Customers & Company Digital transactions Billions of data Data Warehousing –Marketing Data Mart - Customer DataBase Data Mining (*) Customer Profiling (*) Data Mining is the process of extracting hidden patterns from data. As more data are gathered, data mining is becoming an increasingly important tool to transform this data into information. It is commonly used in a wide range of profiling practices, such as marketing, fraud detection and scientific discovery.

6 Customer Profiling & Data Mining Marketing Datamart Strategic decisions Segmentation How to select target marketing segments? Make behavioural data available Analysis and classification Marketing plan implementation Evaluation of results Identify business area Marketing Datamart Tactical actions Propensity Models Who are the best prospect to target for the campaign? Extract sample data Scoring model building Campaignimplementation Evaluation of results Identification of prior cross-selling segment Marketing Datamart

7 Customer Profiling & Data Mining Mail Order Finance Publishing Teleco New Media Scoring Model Behavioural Segmentation Credit Scoring Acceptance Score Card Credit Scoring Basel II Needs Based Segmentation Social Network Analysis

8 Public Data Base (Bureau of Census, Central Bank,..) Private Data Base (Consodata, D&B,..) Market Research –Interaction between Customers & Company –No digital transactions –Sampling –Few data – Customer Table –Classical Statistical tools –Demand Segmentation – Competitive Positioning Business Intelligence & External Data

9 Ricerche Qualitative L obiettivo è approfondire la conoscenza di un fenomeno di mercato, mediante la raccolta e lanalisi di dati qualitativi destrutturati. Ricerche Quantitative L obiettivo è fornire unaccurata misurazione del fenomeno oggetto di ricerca, mediante la raccolta e lanalisi di dati quantitativi e/o dati qualitativi strutturati. Le ricerche di mercato

10 Cati Capi/face-to-face Cawi Postali/fax/auto compilazioni Focus group Interviste in profondità Indagini quantitative Indagini qualitative Metodi basati su questionario Le ricerche di mercato

11 Lesecuzione di una ricerca di mercato può essere schematizzata in quattro fasi: a)-fieldwork: la raccolta dei dati elementari; b)-trattamento elementare dei dati raccolti; c)-analisi dai dati; d)-presentazione dei risultati. Le ricerche di mercato

12 Business Aim Targeted population Choice of sample Fieldwork Data Audit Data Analysis Presentation Characters to be assesed Sampling error Techniques of data collection Set-up questionnarie Pre-test questionnarie Quantitative Market Research Set-up Protocol

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