Micromarketing was first referred to in the UK marketing press
in November 1988 in respect of the application of geodemographics to
consumer marketing.[1]
The subject of micromarketing was developed further in an article in
February 1990, which emphasised understanding markets at the local
level, and also the personalisation of messages to individual consumers
in the context direct marketing.[2]
Micromarketing has come to refer to marketing strategies which are
variously customised to either local markets, to different market
segments, or to the individual customer.
Micromarketing is a marketing strategy in which marketing and/or
advertising efforts are focused on a small group of tightly targeted
consumers.For example, markets can be grouped into narrow clusters based
on commitment to a product class or readiness to purchase a given
brand. The approach requires a company to define very narrow market
segments, and tailor offers or campaigns for that segment. Although, the
approach can be more expensive due to customization and difficulties
attaining scale economies, advancements in technology have facilitated
the delivery of highly customised products to small groups or even
individual customers. Nike ID [3] and Shoes of Prey [4]
are often cited as practical examples of this approach. It should be
evident that micromarketing is closely related to the concept of mass-customisation.
In some of the literature, different labels are used to describe
micromarketing. In a seminal article, Kara and Karnak (1997), referred
to finer segmentation (FS) as "the final advancement in market
segmentation as it combines the use of differentiated marketing and
niche marketing to reach the smallest groups in the marketplace".[5] Richard Tedlow (1993) thought that he detected evidence of what he called hyper-segmentation which he saw as a logical extension of the market segmentation era.[6]
These approaches combine multiple segmentation variables in ways that
have been elusive within conventional approaches to segmentation.
Micromarketing or hyper-segmentation rely on the extensive
information technology, big databases, computerized and flexible
manufacturing systems, and integrated distribution systems. Data is
captured from electronic communications devices, mapped and logged with a
management information system. This enables the integration of observed
behaviour (domains accessed) with motives (content involvement),
geographics (IP addresses), demographics (self-reported registration
details) and brand preferences (site-loyalty, site stickiness).
Additional data inputs might include behavioural variables such as
frequency (site visits), diversity including visitation across different
landscapes and fluidity spanning multiple time periods. Programmed
business intelligence software analyses this data and in the process,
may also source data inputs from other internal information networks.
Given this reliance on digital data inputs, some theorists have also
used the term, cyber-segmentation to describe micromarketing.[7]
With increased availability of electronic scanner data there has been a greater focus on research of micromarketing and pricing
problems that retailers encounter. Research in 1995 by Stephen J. Hoch
et al. provided empirical evidence for the micromarketing concept. In
1997, Alan Montgomery used hierarchical Bayes models to improve the estimation procedures of price elasticities, showing that micromarketing strategies can increase gross profits.[8]
"Global ad spending is predicted to reach $662.73 billion by 2018. Unfortunately, a lot of those dollars will go to waste."[9]
However, the advent of micromarketing or hypersegmentation allows
advertisers the opportunity to get "more bang for their buck" by
targeting consumers who exhibit a readiness to buy.
A report from 2007 by Tech Crunch
titled "Facebook Will Use Profiles To Target Ads, Predict Future" talks
about how Facebook was planning to target individuals based on each
particular profile.[10] Moreover, the Wall Street Journal
claimed in a report, that the new system will "let marketers target
users with ads based on the massive amounts of information people reveal
on the site about themselves."[11]
