Behavioral Targeting is an emergent field of methods and technologies employed by online website advertisers and publishers. These tools allow them to refine and target the effective elements of their campaigns by analyzing and then employing data generated through stat-gathering programs like Landing Page Visit logging programs and other related software. While it does pose a risk as a potential breach of browser security, simple disclaimers informing your clients that their visitation data is being recorded waives this problem.
Consumers visiting a website generate all kinds of data. Which pages do they view or visit, for how long do they view certain pages, which searches do they make and which searches do they repeat, what kind of media do they interact with most often; all of this data is collected by certain sites and compiled into profiles that link automatically to individual users’ browsers. Site publishers, once they are in possession of this data, can further group sets of users into marketable sectors based on similarities between profiles. Visitors returning to certain sites or groups of sites using the same web browser they did initially can be targeted for greater effect based on demonstrated interest and engagement.
Theoretically, targeted ads increase consumer interest and the publisher (or vendor) is able to increase their fees for these premium advertising services given their greater efficacy compared to context-based advertising or random ad placement. Behavioral Marketing (also referred to by professionals as “Audience Targeting) tactics can be employed on their own or in concert with other targeting-focused marketing techniques like demography, geographic dispersion assessment, and contextualizing Web page content.
Network Behavioral Targeting
Advertising Networks are longtime employers of behavioral targeting, although the manner in which they make use of it differs from the methods used by individual sites. Because advertising networks service a broad array of advertisements ranging across many different sites, they can build a reliable picture of the most likely demographic breakdown of internet users. For instance, consider a user who crops up on women’s fashion sites, ballet sites, and parenting sites; a safe assumption about that user is that they’re female. This kind of demography analysis, handled internally through user surveys or externally by third-party vendors, lets networks to offer entire audiences as products, rather than just sites.
Behavioral targeting has greatly increased the accuracy with which networks market. The handling of data allows a focused, targeted approach that lets networks cast their nets wider.
On-Site Behavioral Targeting
The following theses hold that the set of methods and techniques that comprise Behavioral Targeting as a marketing discipline can be applied to any online property, product, or agency: first that the visitor’s experience is improved by it, and second that it benefits the online property through improved conversion and spending. Initial users of the techno-philosophical approach to Behavioral Targeting were primarily editorial websites offering online advertising, e-commerce, or other retail services, used it as a way to pump their own relevance on an individual basis with each visitor. In the current market environment, though, less traditional companies who may not even engage with e-commerce have begun attempting to integrate Behavioral Targeting into their business plans.
The usual overture toward starting a Behavioral Targeting program is the use of web analytics to dissect the number and “types” of visitors into a variety of predetermined or organically generated categories. Each category, once analyzed, has a virtual profile or set of terms assigned to it as an arbiter. These profiles are often based on or referred to as Personas, giving Web operators reference points for determining the navigational layout, content types, and other factors presented to each of the site’s visitors according to their Persona association. Special software, Content Behavioral Platforms, assign unique ID cookies to every visitor to a given site and its constituent pages. This allows the website’s operators to track the users as they browse and make use of the Web. Based on the algorithms discussed above, the platform software then makes a ruling about which types of content to present to which visitors. A greater variety of data points and deeper information can be produced by incorporating demographic data and a user’s past purchase record.
Quality onsite behavioral targeting systems and platforms will perform a sort of rudimentary self-learning process, monitoring site users’ responses to content in order to further refine said content to produce the desire effect: a conversion event. Multivariate tests, conducted in large numbers and simultaneously, are the accepted method for producing content suited to the various Personas identified by the platform. On-site behavioral targeting efforts rely on substantial levels of traffic to develop the Personas they need to succeed, and statistical confidence in the matter of successful conversion rates can be dubious below a certain volume of traffic.
Privacy and Security: How to Use Behavioral Targeting Safely
Online users and advocacy groups concerned with issues of internet privacy often bring up behavioral targeting as a violator of internet privacy rights. Targeting-based online media marketing in general comes under fire regularly, but the behavioral targeting industry is taking steps to quell and minimize the controversy through advocacy, educational programs, and self-imposed product constraints designed to keep information garnered through data collection unconnected to users. End-user license agreements are another tactic used by behavioral targeting marketers to avoid clashes with users.
Since Web pages acquire personalization based on a user’s implicit data (age, interests, social standing, context, etc), personalization presents the implication that things like purchase history and pageview history are being recorded. Customization, a branch of behavioral targeting as a marketing discipline, is a term used only when the site’s changes are gleaned from explicit data (data provided personally by the user through reviews, ratings, preferences, comments, etc). Making sure your users understand the way in which their actions are recorded in order to improve their experience is essential to avoiding user discontent.
Methods of Personalization
Models for achieving Web personalization include rules-based logic engine filtering and processing and collaborative filtering (the serving of relevant material to users based on a combination of their own past preferences with the preferences of other individuals with similar tastes). Collaborative filtering is proven effective in the selling of media, especially books, DVDs, music, and related items. However, it can also be ineffective in certain situations, and has proven of mixed utility in selling apparel, cosmetics, and other personal hygiene and accessory purchases. A third model, Prediction Based on Benefit, has been gestated based on problems with this aspect of collaborative filtering as a way to market apparel, etc.
Addressing the subject more broadly, there are three usual methods of personalization. The first, implicit personalization, relies on Web pages and information systems derived from the categories discussed above. The second, explicit personalization, the information system or web page is affected by the user making use of the features it provides. Hybrid personalization combines these two approaches, trading on a best of both worlds approach to negate the weaknesses of implicit and explicit personalization.
Personalization and discretely collected lists and databases of user behaviors allow companies to exist as meta-marketers selling information, recommendations, and e-mail recommendations as lots. The industry of online retail has embraced third party personalization tools and services from vendors in all net sectors. Providers like MyBuys, Vignette, and PredictiveIntent all offer these and related services to retailers on the internet.
Conclusion and Implementation
Securing the services of a third-party information analysis and recommendation service, or else conducting similar operations in-house, are an essential part of running a competitive online network or vending site. Without the refined and targeted marketing provided by Behavioral Targeting, modern sites can’t compete with giants like Amazon and other internet vendors.
Remember that explicit behavioral targeting is just as powerful a tool as implicit targeting. Maintaining a database of associated items, media, services, etc, and working with algorithms that link and suggest these items to users who purchase within their fields is a great way to make sure your customers keep coming back, and that they go away satisfied. In short, behavioral targeting market tactics should be a key component of any serious marketing campaign. The business is about clients and consumers, and ensuring their satisfaction should always be a top priority for vendors, agencies, or service organizations.