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Domain Driven Data Mining to Improve Promotional Campaign ROI and Select Marketing Channels . Presenter : Tsai Tzung Ruei Authors: Thomas Piton, Julien Blanchard, Henri Briand and Fabrice Guillet. 國立雲林科技大學 National Yunlin University of Science and Technology. CIKM.2009. Outline. - PowerPoint PPT Presentation
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.
Domain Driven Data Mining to Improve Promotional Campaign ROI and Select Marketing Channels
Presenter : Tsai Tzung Ruei Authors: Thomas Piton, Julien Blanchard, Henri Briand and Fabrice Guillet
CIKM.2009
國立雲林科技大學National Yunlin University of Science and Technology
Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Outline
Motivation Objective Methodology Experiments Conclusion Comments
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Motivation
For each customer, there may be a large number of possible actions that can be applied . But actions, such as emailing, direct mailing and salespersons’ visits cost the company money .
To overcome this drawback, marketing managers need to acquire relevant knowledge on a one-to-one basis to decide which are the most effective communication channels to use for each customer.
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Objective
To propose an actionable knowledge discovery methodology, for one-to-one marketing, which allows to contact the right customer through the right communication channel.
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RigrhtRigrht
Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
THE RIGHT CUSTOMER
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
Naive profit curve
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
Choice of marketing channels
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
Model generation
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KIKR
Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
Model interpretation
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Experiments
Model application
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Experiments
Model validation
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Experiments
During the previous operation, the rate of buyers was 18 %. Whereas in the last one, by applying our methodology, the rate of buyers raised up to 22 %, the turnover was increased by 5 %, and 115 new customers participated, representing about 1 200 000 euros of additional turnover.
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Conclusion
MAJOR CONTRIBUTION To offer effective solutions to extract actionable knowledge to
intelligent CRM for companies.
FUTURE WORK To try to combine other methods of data mining to improve our
methodology (associations rules for instance) with customer purchasing potential, with a view of preventing customer ”churning” during promotional campaigns, and of suggesting high profit materials to customers with the highest tendency.
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Comments
Advantage To improve customer relationship
Drawback …..
Application MRM, CRM
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