Download - Business Intelligence 2.0
Business Intelligence 2.0
I.C.A.R.O.S. GmbH
Copyright I.C.A.R.O.S. GmbH 2011
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Executive Summary
Background
Statistics
Exec Summary on Technology
Data Sources
Technique
Exec Summary Challenges
Challenges
Implementation
Services I.C.A.R.O.S. GmbH
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Executive SummaryData 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
Theory of Planned Behavior
attitude
Individualnorms & values
Intention Behavior
Copyright I.C.A.R.O.S. GmbH 2011
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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
Copyright I.C.A.R.O.S. GmbH 2011
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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.
Copyright I.C.A.R.O.S. GmbH 2011
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Executive SummaryTechnology 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.
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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.
* See also Market Research 2.0 http://www.slideshare.net/viktorriemer
Copyright I.C.A.R.O.S. GmbH 2011
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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.
* See also Market Research 2.0 http://www.slideshare.net/viktorriemer
Copyright I.C.A.R.O.S. GmbH 2011
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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.
Copyright I.C.A.R.O.S. GmbH 2011
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.
Copyright I.C.A.R.O.S. GmbH 2011
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
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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.
Copyright I.C.A.R.O.S. GmbH 2011
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/
Copyright I.C.A.R.O.S. GmbH 2011
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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
Copyright I.C.A.R.O.S. GmbH 2011
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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
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More Informationen
I.C.A.R.O.S. GmbH
Viktor Riemer
mobile +491715422715
www.icaros.de
Copyright I.C.A.R.O.S. GmbH 2011
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