The new targeting strategy you should know

While digital marketers have evolved, the strategies for targeting online audiences largely have not. Here is why cookie-based targeting is sub-par and why you should embrace IP audience targeting.

Replacing the dinosaur in the cockpit

Can a major construct of an industry that is only 15 years old be considered a dinosaur? It may seem counter intuitive, but in an industry where the landscape is as quickly evolving as online advertising, the answer is yes. The fact that we are relying almost solely on the same cookie-based targeting strategies that were born at the dawn of the industry is like allowing a Tyrannosaurus to pilot a jet plane.

From the beginning, cookie-based behavioral targeting attempted to leverage the strengths of the online world while downplaying its limitations. But, this online targeting relic has begun to show its age, and while the expectations of online marketers have evolved, the strategies for targeting online audiences largely have not. Now more than ever before, there is a desire for a new targeting paradigm that delivers on the promise of pinpoint focus and scalable reach. Our complex and powerful jet plane of an industry deserves a pilot with more finesse than a prehistoric carnivore.

IP audience targeting is an online targeting strategy that brings the strength, accuracy, and flexibility of offline direct-mail campaigns into the online era by mapping IP address ranges to real-world addresses and leverages the publically available information known about those addresses. Continuing the analogy, partnerships between old-school, offline data-crunching tech companies and online distribution engines are now replacing the Tyrannosaurus in the cockpit with skilled and stealthy Air Force academy graduates.

Limitations of the cookie

With the advent of the Netscape Navigator browser in 1997, cookies introduced the ability to personalize the web-surfing experience based on perceived personal interests. When placed on a user's browser, these anonymous markers could later be tracked and reviewed by websites the user visited so that the website would "know" information about the user and "interact" appropriately.

Today, identifying a prospect audience for an online display campaign still largely depends on cookies. At its best, however, the scale and accuracy of cookie-based targeting pales in comparison to its old-school analog cousin, direct mail.

It is surprising that marketers accustomed to hitting every household in a geographic area with direct mail and filtering those targeted geos by all manner of publically available information (home values, auto ownership, voter registration information), have been so complacent in accepting the limitations of a cookie-based system.

While offline targeting opens up the entire universe of street addresses as a starting target pool, cookie-based targeting is limited to users that have a "live" cookie on their browser.

Forrester Research recently surveyed data service providers and the largest search and ad networks and estimated that "active" cookie coverage at any given time was approximately 34 percent of the online population: ComScore Media Metrix, Inc. estimated 40 percent and JupiterResearch estimated 38 percent. At a high level, this means that from the online population of 200 million people in the U.S., it is likely that no more than 75 to 80 million people are active at any given time.

In the offline world, customer transaction data is coupled with hundreds of verified demographic attributes to statistically define what the likely buyer looks like. The data is used to build a predictive model and score the entire prospect population. Likely buyers are prioritized and unlikely buyers are suppressed. This is the standard process used for targeting by most professional marketing departments and service providers -- except in the online advertising world.

In the online world, algorithmic optimization takes the place of predictive models because there is far less data to work with. Targeting methodologies in the online world are driven by site traffic and click-through-rates because personally identifiable demographic information is either unavailable or too generalized to be useful. In the end, however, online targeting has only been able to make predictions of users' interests based on websites they have visited and not truly based upon "facts" known about the users.

IP audience targeting basics

Rising to save the industry from its own complacency is a new kind of targeting strategy that both eschews cookies and marries the offline consumer data world with the algorithm-friendly world of digital advertising. Based on predictive modeling and extensive offline data, IP audience targeting is a way to score and target 100 percent of the available internet traffic without compromising privacy.

IP audience targeting starts by segmenting every IP address in the U.S. into its basic user type: home, business, government, education, or wireless. There are more than 1.5 million identifiable home zones and approximately 5 million business zones in the U.S. Each home zone is approximately 77 times more precise than a zip code, with an average of 145 people in each zone. The geographic footprint of each IP zone is defined by the predictive modeling and varies in size; however, a zone could accurately be described as "neighborhoods" of similar socio-economic households.

Using publically available offline data and genetic-modeling technology to map IP address ranges to real-world addresses makes it possible to segment any IP audience zone into geo-demographic clusters, which can be appended with more than 750 distinct variables for each household. These publically available data variables include affluence, social status, life stage, political affiliation, interests, auto and home ownership, as well as propensities to acquire hundreds of products and services. Business zones can be targeted by variables including business type, revenue, number of employees, location, and SIC and NAISC codes, so that the B2B marketer can target by industry. Appropriate IP audience zones can then be isolated online as IP ranges and then targeted as part of a standard online display campaign.

Robust predictive models that run analogous to offline direct mail strategies can now be a regular part of online campaign planning and execution.

A new carnivore on the block

In the end, it may well be an exaggeration to predict the death of the cookie. Its existence goes a long way in defining the internet experience that we have come to know, and nothing written here should be interpreted as a call for its total demise. The point is simply that the industry has been slow to look beyond the cookie for new targeting technologies that can either be coupled with cookie-based campaigns or, in many cases, can supply greater granularity and ROI -- and IP audience targeting presents a real opportunity to rethink reliance on an industry dinosaur. To complete (and perhaps scuttle) the analogy introduced earlier, cookie-based targeting may well escape the doomed fate of the Tyrannosaurus, but one thing is certain: It is no longer the only carnivore on the block.

iMedia article: http://www.imediaconnection.com/content/31075.asp