What is PRIZM in consumer behavior?

PRIZM targeting. We’ve all heard about it some time in our careers. Usually, people use the term loosely, dropping it casually into their vocabulary as if it were a word of the day. Most of the time it sounds like jargon media folks throw around more than anything else. Though it’s a familiar tool commonly utilized by direct mail marketers, PRIZM is still quite foreign to many of us who heavily align ourselves with digital media.

Through various meetings with sales reps and some personal research into behavioral targeting, I became fascinated with the PRIZM system and the amount of consumer insight it contains. Not only does it disclose the demographic traits (e.g., ethnicity, age range, education and employment level, income, etc.) of a particular segment, it also provides lifestyle characteristics, such as shopping and reading preferences and social and life-stage groups.

After glimpsing these consumer profiles, I started thinking about these attributes’ behavioral effects and their implications to consumers’ online habits and activities. Is PRIZM targeting useful for behavioral targeting?

More Than Meets the Eye

“PRIZM” stands for Potential Rating Index for Zip Markets. It provides marketers with a standardized set of characteristics (known as clusters) for each U.S. Zip Code. Each Zip Code is assigned one or more of 62 clusters, based on the area’s shared socioeconomic characteristics.

From census data, millions of purchase records, and customer surveys, Claritas (developer of PRIZM) integrates the information to create a sophisticated segmentation of geographically divided communities.

Whether it’s to learn about potential customers and their neighborhoods or to download targeted mailing lists based on specific consumer demographics, lifestyle data, and product preferences, marketers can discover their best targets using the sophisticated segmentation lens PRIZM offers.

A Geographical Perfect Match

Visit the “You Are Where You Live” portion of the Claritas site and enter a Zip Code. You’ll discover the top five clusters in that area.

After typing in 94107 for San Francisco, I learned, according to PRIZM, the most common segments in my neighborhood are #29 American Dreams (referring to the ethnically diverse residents); #16 Bohemian Mix (young, mobile, early adopter urbanites who represent the nation’s “most liberal lifestyles”); #31 Urban Achievers (college-educated and ethnically diverse up-and-coming immigrants from Asia, South America, and Europe); #59 Urban Elders (economically struggling segment located in the downtown neighborhoods of metros); and #4 Urban Digerati (highly educated, ethnically mixed, tech-savvy singles and couples in fashionable neighborhoods).

If online marketers can look past the uncanny cluster names and descriptions, they’ll realize the PRIZM database sheds important insights into consumer behaviors. This geo-based demography, as Poindexter’s VP of client services Ted Shergalis describes it, is a “predictive attribute for online marketing.”

With this type of background information on lifestyle, spending habits, and media preference, marketers can identify the geolocations (via IP geotargeting) and target their product to those most likely to buy.

What Does This Mean for Online Media?

The potential of combining the PRIZM and behavioral targeting databases may not be exempt from public legal scrutiny. If anything, we’ve all learned the lesson from the privacy crucible DoubleClick endured five years ago when it purchased a database in an attempt to link offline personally identifiable information with online surfing habits. Privacy will always be a sensitive concern for marketers and consumers alike.

During my research, I was glad to learn some behavioral vendors have remedied the privacy issue by simply incorporating cluster segmentation methodology without completely depending on it. Poindexter has worked with Claritas for three years and already integrated the PRIZM segmentation into its targeting and optimization system as an advanced marketing solution. Others, such as DRIVEpm and ValueClick, are implementing similar capabilities to boost their own targeting functionalities.

At the heart of behavioral targeting is a holistic understanding of consumer behaviors. Regardless of medium, information is still the key to understanding the market and consumers behaviors. If behavioral targeting is to fully deliver its promise of making advertising more relevant on the individual basis, incorporating PRIZM data seems a natural addition to the ever-changing behavioral kaleidoscope.

The Claritas Consumer Profiles datasets comprise three different geo-demographic segmentation products: ConneXions®, PRIZM® Premier, and P$YCLE® Premier.

Claritas Consumer Profiles help identify groups of consumers who are as likely, more likely, or less likely than the average segment, to engage in various behaviors. 

ConneXions, the Claritas segmentation system for communications marketers, classifies US households into 53 consumer segments based on the video, voice, and data purchasing preferences of that household. The ConneXions typology combines the Claritas Lifestage typology—Younger Years, Family Life, and Mature Years—with a proprietary model, Technodoption, that measures the willingness of a household to adopt new technology early in its lifecycle. The Technoadoption levels are defined as High, Mid, Low, and No Tech. Within the three Lifestage classes, the 53 segments are further grouped into 10 Lifestage Groups by combining three variables—Technodoption, householder age, and presence of children at home—to describe the likely lifestyle of the segments in that group. 

PRIZM Premier classifies US households into 68 consumer segments based on household purchasing preferences and demographic and socioeconomic characteristics. Segments are defined according to socioeconomic rank, including characteristics such as income, education, occupation, and home value, and are grouped into 11 PRIZM Lifestage Groups and Social Groups. In PRIZM Lifestage Groups, segments are classified as Younger Years, Family Life, and Mature Years, and further into 11 groupings, based on affluence, householder age, and presence of children at home to offer a more robust picture of the consumer. PRIZM Social Groups are based on urbanization class and affluence. Within each of four urbanization class categories—Urban, Suburban, Second City, or Town & Rural—segments are sorted into groups based on affluence. Statistics cover the purchasing behaviors of segments and segment groups with respect to products ranging from apparel, consumer package goods, and financial services to home furnishings and media/technology. 

P$YCLE Premier, the Claritas segmentation system for financial marketers, classifies US households into 60 consumer segments based in part on the income-producing assets (IPA) of the household. Within three Lifestage classes—Younger Years, Family Life, and Mature Years—the 60 segments are further grouped into 12 Lifestage Groups by combining three variables—affluence, householder age, and presence of children at home—to describe the likely lifestyle of the segments in that group. A proprietary model, the Claritas Income Producing Assets Indicators model, is used to estimate the liquid assets of a household based on responses to the Claritas Financial Track survey of financial behaviors. 

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