Behavioral targeting, digital advertising, web analytics, viral
marketing, social, mob, buzz markeing, etc., whatever term you use: it comes down to the analysis of consumers’ behaviors
via the Web, wireless and other consumer channels for the marketer and advertiser
of today. Behavioral analytics is the future of all digital advertising – furthermore the convergence
of offline and online data enables advertisers and marketers to monetize consumers’ behaviors – for personalized
growth marketing for their clients.
Behavioral analytics can be leveraged by
not only digital marketers but also by digital enterprises at their websites and within all their marketing channels.
All digital advertising segments will be driven by behavioral analytics, whether display, search, rich media, DVR,
in-game, Web, mobile, etc., in a market projected to exceed $20 billion in a few years.
Behavioral analytics
is the underlying process enabling digital advertising and marketing, in the placement of products or services via multiple
channels to consumers, in a relevant and personal manner as they interact with websites and enterprises. Behavioral analytics
vendors are scrambling to gather new forms of data to make digital advertising more personal and comprehensive which require
capturing, analyzing and acting on consumer actions and reacting with precise counter-actions, which are beneficial to both.
Behavioral analytics
is made possible by subscription and partnering with advertising, demographics or recommendation networks, as well as by the
use of new real-time streaming analytical software or a combination of both. Behavioral analytics enables
digital marketers and advertisers to position the right product or service in front of the right consumer via targeted messages
in multiple formats: Web, email, mobile, etc.
Behavioral analytics initially existed exclusively on the Web however those same techniques and technologies can
today be integrated and leverage by marketers and advertisers to service and sell to their existing and future customers via
multiple channels including wireless devices. Not all consumer groups clusters along the traditional dimensions of offline demographics
such as household income as they align with propensity to purchase the same products or content and follow the same type of
spending habits.
For this reason, static demographic data should not be used as the building blocks
of a well-defined customer segmentation system. Demographic data may be used to describe customer segments (profiling), but
it is much less effective in distinguishing interests and spending habits than customer behavioral data. Behavioral
data goes beyond knowing that a customer has purchased a certain product. It involves capturing customer events and actions
over time and using these stored interactions to determine typical behavior and deviations from that behavior.
At
the lowest and most fundamental level behavioral analytics is made possible by embeddable chunks of code in the form or cookies,
forms, beacons and widgets which have existed since the start of ecommerce over a decade ago and is also made possible by
software agents retrieving, organizing and mining across clouds of data sources – networked via the Web.
Code aside, most importantly behavioral analytics enables enterprises and digital ad gals and guys to calibrate and
react with precision to consumer preferences, tendencies, and desires with methods of communication that are instantly gratifying,
enticing and entertaining such as rich media.
New behavioral analytics techniques and
technologies are evolving from the decade old cookie-reliant methods for getting a 360 view of consumer behavior.
Some new behavioral analytics vendors focus on purchase activity as a more direct and relevant indicator of interests,
or the mix with clickstream behavior with real-time demographic and psychographic data to find likely consumer targets.
The success of behavioral analytics involves
strategic planning and measured improvement of predictive evolving models. The modeling of wired and wireless
consumers by digital marketers and advertisers is the future and everybody knows it – via strategic behavioral targeting
and social engagement marketing. In addition, the modeling of existing and future customers by enterprises
is at the core of a new paradigm for real-time business intelligence – designed to react to interactions and consumer
events as they occur.
