The document outlines the framework for data-driven marketing (DDM) by utilizing measurable factors of behavior and attitudes to predict customer needs and enhance business intelligence. It discusses the significance of technology in marketing, the importance of identifying valuable customer segments, and the need for timely and precise data to drive successful marketing strategies. Additionally, it addresses challenges in implementing DDM and provides consultancy services for effective strategy execution.

1. Business Intelligence 2.0
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2. AGENDA
Executive Summary Exec Summary Challenges
Background Challenges
Statistics Implementation
Exec Summary on Technology Services I.C.A.R.O.S. GmbH
Data Sources Contact I.C.A.R.O.S. GmbH
Technique
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3. Executive Summary
Data Driven Marketing
Behavior is a consequence of attitude together with
individual norms and values.
Attitudes and strategies of apology have statistically
significant influence to human behavior.
Given the possibility to extract measurable and
influenceable factors of behavior this information
would help to predict future activities, needs and
wishes of individuals.
Agenda

4. Theory of Planned Behavior
attitude
Intention Behavior
Individual
norms & values
Agenda
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5. Statistics
Statistical studies* have found evidence that there is a
statistically significant influence of attitude to behavior.
The same evidence was found for past behavior.
An extension of the model to strategies of apology for
past behavior is another significant variable for current
behavior.
* Beispiel: http://www.uns.ethz.ch/res/crp/sustlearn/wadis_dt/erg3/Liz_arbeit_littering-verhalten.pdf
Agenda
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6. SUMMARY
The theory behind Data Driven Marketing delivers a
framework for data driven Business Intelligence by
extraction of measurable and influenceable factors of
attitudes
strategies of apology
explaining human behavior.
Agenda
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7. Executive Summary
Technology of DDM
New Marketing-Tools like Smartphone Ads are sources of
information at the same time and so could be used for
Business Intelligence.
Reporting of daily behavior, together with field studies and
interpretation of social interactions will be the basis of
future marketing actions.
The identification of most valuable customers and their
retention will succeed even without knowing the
personalized data of individuals - only by knowing habits.
Agenda

8. Data sources for DDM*
Data sources for DDM could be segmented into 3
groups:
Activities of customers
General field studies about behavior
Interpretation of social interactions
Combining these sources could be managed
technically and/or by intuition of the marketer.
Agenda * See also Market Research 2.0 http://www.slideshare.net/viktorriemer
Copyright I.C.A.R.O.S. GmbH 2011

9. Data sources for DDM*
Examples
barcoo (Smartphone used as product scanner)
productfinder (virtual sales assistant)
theSteward (mobile service platform)
With these tools an integration between marketing
activity and market research measurement could
easily be installed.
Agenda * See also Market Research 2.0 http://www.slideshare.net/viktorriemer
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10. Technique of DDM 1
Records about activities and behavior of customers will
be generated by electronical marketing tools and/or
CRM sources.
The questions WHY and HOW an attitude is built will be
generated by individually styled fiels studies.
Knowledge and interpretation of social interactions will
be won from social platforms, blogs, forums out of the
Internet.
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11. Technique of DDM 2
With cluster and factor analysis the most valuable
target group can be identified by combining the three
sources above.
Even more effective is the structured observation of
behavior and its anomalies. In-time interpretation of
behavior anomalies will avoid losses of customers,
dissatisfaction and building a bad reputation.
Indicated actions could be planned and executed in-
time.
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12. Technique of DDM 3
DDM is to aim for:
Prevention of customer losses and winning new
clients
Identifying most valuable target groups
Adressing attitudes and values of these customers
Agenda
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13. Challenges for DDM 1
Biggest challenge for DDM is defining and identifying
the right and most influential parameters of attitude
and strategies of apology.
Particularly the needed granularity of informationen its
link attitude of customers is the huge question mark
behind Data Driven marketing and Business
Intelligence.
The second crucial topic is in-time delivery of the above
information.
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14. Challenges of DDM 2
Jim Novo, the most important professional behind
DDM (1), answers these challenges by a rather simple
advice:
„I think social folks would find more success by not
focussing so much on measuring engagement, but
instead by measuring „dis-engagement“ (2).
(1) http://www.jimnovo.com (2) http://marktamis.com/2010/04/15/data-driven-social-crm/
Agenda
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15. DDM implementation
To successfully implement DDM in an organization you
need the following:
Strategic focus of top management
Existence of structured data sources and marketing
tools
Clear vision, what performance indicators measure
aiming the business targets best AND can be
influenced by company management
Agenda
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16. Services I.C.A.R.O.S. GmbH
Assessment of relevance and effectiveness of a
DDM strategy for the client company
Consultancy, conception and implementation of
DDM frameworks including marketing tools
Support for market research data generation
Selection of tools and business partner for
implementation of DDM strategy
Agenda
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17. More Informationen
I.C.A.R.O.S. GmbH
Viktor Riemer
mobile +491715422715
v_riemer@icaros.de
www.icaros.de
Agenda
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