Business Intelligence 2.0
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Business Intelligence 2.0

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How Business Intelligence and Data Driven marketing can help to focus on business strategy even in times of frequent change.

How Business Intelligence and Data Driven marketing can help to focus on business strategy even in times of frequent change.

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  • 1. Business Intelligence 2.0I.C.A.R.O.S. GmbH Copyright I.C.A.R.O.S. GmbH 2011
  • 2. AGENDAExecutive Summary Exec Summary Challenges Background Challenges Statistics ImplementationExec Summary on Technology Services I.C.A.R.O.S. GmbH Data Sources Contact I.C.A.R.O.S. GmbH Technique Copyright I.C.A.R.O.S. GmbH 2011
  • 3. 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
  • 4. Theory of Planned Behavior attitude Intention Behavior Individualnorms & valuesAgenda Copyright I.C.A.R.O.S. GmbH 2011
  • 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.pdfAgenda Copyright I.C.A.R.O.S. GmbH 2011
  • 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 Copyright I.C.A.R.O.S. GmbH 2011
  • 7. 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.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 Copyright I.C.A.R.O.S. GmbH 2011
  • 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. Copyright I.C.A.R.O.S. GmbH 2011
  • 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. Copyright I.C.A.R.O.S. GmbH 2011
  • 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 customersAgenda Copyright I.C.A.R.O.S. GmbH 2011
  • 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. Copyright I.C.A.R.O.S. GmbH 2011
  • 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 Copyright I.C.A.R.O.S. GmbH 2011
  • 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 managementAgenda Copyright I.C.A.R.O.S. GmbH 2011
  • 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 strategyAgenda Copyright I.C.A.R.O.S. GmbH 2011
  • 17. More Informationen I.C.A.R.O.S. GmbH Viktor Riemer mobile +491715422715 v_riemer@icaros.de www.icaros.deAgenda Copyright I.C.A.R.O.S. GmbH 2011