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Digital Marketing Analytics
With the growth of online commerce and the development of sophisticated data
collection methods, organizations have more data than ever before about their
customers. At the same time, computational power and sophisticated modeling is
becoming increasingly cheap. Analytics performed on this data, if used well,
have the potential to revolutionize marketing by providing firms with the right
knowledge at exactly the right moment to gain a new customer, complete a sale to
an existing customer, or stop a customer from churning. It is time, therefore,
to connect the dots between the marketing and information systems, bringing
customer data and marketing efforts together with advanced computational methods
and robust modeling techniques to provide easy-to-use but powerful analytical
methods. Such a combination will enable the creation of data scientists who are
able to study, learn from and predict the effect of marketing actions. However,
in order for advanced analytics to be useful they also have to be understandable
and automatic, giving managers the ability to find the right piece of
information at a moment’s notice. Developing digital marketing analytics that
take advantage of the rich data in existence and at the same time are functional
is a complex and interesting challenge.
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