Metodi Quantitativi per Economia,
Finanza e Management
Lezione n°2
Business Intelligence
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 decisionmaking. Thus one can also characterize a BI system as a
Decision Support System (DSS).
(*) http://en.wikipedia.org/wiki/Business_Intelligence
Business Intelligence & Data Sources
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 & Internal Data
Operational & Strategic Marketing Hints
Business
Intelligence
DW
agents
call center Management
systems
portals
operations
data collection
data modelling
& processing
data analysis
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.
http://en.wikipedia.org/wiki/Business_Intelligence
Customer Profiling & Data Mining
Segmentation
How to select target
marketing segments?
Evaluation
of results
Identify business
area
Marketing
Datamart Make behavioural
Marketing plan
data available
implementation
Analysis and
classification
Strategic decisions
Marketing
Datamart
Propensity Models
Who are the best prospect
to target for the campaign?
Identification of prior
cross-selling segment
Evaluation
of results
Campaign
implementation
Marketing
Datamart
Extract
sample data
Scoring model
building
Tactical actions
Customer Profiling & Data Mining
Scoring Model
Behavioural Segmentation
Credit Scoring
Basel II
Credit Scoring
Acceptance Score Card
Needs Based
Segmentation
2000
1990
Mail Order
Teleco
New Media
Finance
Publishing
Social
Network Analysis
Business Intelligence & External Data
• 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
Le ricerche di mercato
Ricerche Qualitative
L’ obiettivo è approfondire la conoscenza di un fenomeno di
mercato, mediante la raccolta e l’analisi di dati qualitativi
destrutturati.
Ricerche Quantitative
L’ obiettivo è fornire un’accurata misurazione del fenomeno
oggetto di ricerca, mediante la raccolta e l’analisi di dati
quantitativi e/o dati qualitativi strutturati.
Le ricerche di mercato
Cati
Metodi basati
su
questionario
Indagini
quantitative
Indagini
qualitative
Capi/face-to-face
Cawi
Postali/fax/auto
compilazioni
Focus group
Interviste
in
profondità
Le ricerche di mercato
L’esecuzione 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.
Quantitative Market Research
Set-up Protocol
Business Aim
Targeted population
Characters to be
assesed
Choice of
sample
Sampling error
Fieldwork
Techniques of data
collection
Data Audit
Set-up
questionnarie
Data Analysis
Pre-test
questionnarie
Presentation
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