targeting

With enough of the right kind of data, marketers can learn a lot more about what to do next, not just a lot about what they've already done.

With continued advances in technology and the parallel demands from advertisers for the extraction of greater value from marketing efforts, businesses and the services they employ are bringing those marketing efforts closer to their intended audience than they ever have before.

There are technologies marketers have at their disposal that can provide them with a dizzying array of data, from which all manner of information about a consumer or potential consumer habits can be gleaned. Numerous behavioral patterns can be discerned and, based on the articulation of these patterns, advertising and marketing strategies and tactics can be designed.

But this is only possible with appropriately defined metrics. Data on its own, and in particular given the speed and volume with which it is produced, can become a numbing buzz of numbers and graphs. 

Metrics are at the heart of nearly every marketing communications effort. They are used to tell us what happens and when. They are used to tell us what isn't working and what might be the problem. They are used to tell us what is working and how to repeat the actions that led to success. But there is a real need for metrics analysis at a level not typical to the traditional assessment of media and marketing activities. 

What so many advertisers don't understand is that data is not the same thing as knowledge, and knowledge more often than not is a wider pale than the pickets of data that set its boundaries.

Too often advertisers set about gathering data with no clear idea of what they want to do with it. Rolling out a campaign, clients want to conduct all manner of research, or collect all manner of data from potential customers through a registration process, but they don't plan what to do with the data.  This leads to a frenzied gathering of bits, collecting any bit that is collectable. The collection of data is almost done for its own sake. Because it can be done, it is done.

There is often a lack of definition, but this can be addressed when we have a deeper understanding of what the implications and meanings of certain metrics are within the scope of a client's activities. There is a need to set criteria, define them, and hopefully establish a "why" consistent with a real objective.

Kinds of metrics
Over the many years that businesses have been conducting market research and analyzing the outcome of advertising activities, regular sets have emerged that are regularly used to define the success or failure of an advertising campaign.

These metrics have almost always focused on branding. They are typically:

1. Brand awareness
2. Message association
3. Brand favorability
4. Purchase intent

The research done to put data with these metrics has historically only been made possible through the rigorous and resource-heavy process of conducting interviews with customers or focus groups. 

But there are technological solutions available now to marketers and advertisers that were never available before that can collect and look at a much more robust array of data than ever before. This can lead to a more detailed, accurate and precise reading of customer activity and the context in which the consumer operates.

Some of these solutions come with a rich, preexisting database of logged variables. These allow advertisers to significantly expand the variables in use for both an existing consumer base as well as allow for the development of new prospects. It is using this kind of database, in concert with click-stream data, that behavioral targeting depends on.

These data inputs can consist of four types:
A) IP-based

1. Standard

B) Geography/ZIP code

1. Claritas PRIZM
2. Bandwidth
3. Day-part
4. Domain
5. Demographics

C) Client member data

1. Product ownership
2. Client-developed propensity scores
3. Membership declarative data
4. Credit card match data

D) Behavioral data

1. Online activity
2. Referral stream
3. Proprietary profile segments

The technology also enables customized definitions of metrics. Though there are some fundamental points of interest common to all marketers, each marketer has a unique value proposition and a unique marketing solution to solve a specific marketing problem.

The technology is equipped with an expansive palette of micro-metric criteria from which marketers can articulate their own knowledge quest. Marketers are able to directly input their distinctive set of objectives, product values or business constraints (e.g., registration goals, communication delivery goals, etc.) from which they can then read the outcome of their advertising activities. 

Once the technology is told what to be on the look out for, it can be used to turn that particular data into information; not through the painstaking manual process of "reading" the data, but through sophisticated automated decision engines. Not only can the technology "tell" a marketer what has happened, but, if part of a bundled solution, it can also act on the information it is itself responsible for producing.

These developments are being driven in no small part by the aforementioned desire to extract greater value from a marketing effort. The equation of that value is typically represented by ROI.

But ROI really has to be set in the context of what consumer action you need people to take and not just relative to CPM or a simple, short-term metric of payout. There has to be a long-term view of brand value, and that value cannot always be defined by an immediate end result.

The interest on the part of marketers is one of "looking forward." But too much focus on ROI can have us looking backwards rather than forwards.  For the most part, you can only measure things in the past. Looking forward is the real challenge. And spending clients' money better is the true task of the agency in the marketer's employ. That is a proposition that requires projection rather than reflection.

A communication strategy that seeks to influence is one that must be projective. In order to be projective, knowing what an advertiser is trying to achieve is key.
 
The real need isn't so much ROI, as we've come to understand, but instead to understand what it is worth to the brand to achieve that goal and what it takes at each stop along a consumer's way toward being a part of that achievement

This requires us to quantify those goals, like "intent" or "awareness." While advertisers and their agencies are still trying to figure that out, they are also establishing tactile brand goals that can be measured and monetized. The most compelling form this can take are agencies phrasing what is going to happen to a brand by virtue of the advertisers marketing in financial terms.

The kinds of questions agencies still can't adequately answer, however, are just the kinds of questions raised by establishing tactile brand goals couched in financial terms. If I reduce a budget by X amount, how much less product will I sell? How do advertising investments actually affect a business?

What advertisers and marketers are really after is something predictive, not reflective. With enough data -- and enough of the right kind of data -- marketers can learn a lot more about what to do next, not just a lot about what they've already done.

Media Strategies Editor Jim Meskauskas is vice president and director of online media for ICON International, Inc., an Omnicom Company. Read full bio.