By Steve Seabury
While the 2010 U.S. Census is still months away, a recent advance in data analytics demonstrates how amazing things can happen when customer and location intelligence comes together.
For years, real estate specialists and strategic planners have relied on spatial analysis to make decisions that required significant investments. The power of location intelligence proved invaluable on many fronts. The stability of neighborhood demographics enabled decision-makers to hone in on trends that could impact long-term profitability. The precise nature of geocoding provided for year-over-year consistency. Plus, the ability to visualize and map customers, prospects and competition against existing and planned sites let to key insights… insights that have enabled banks, retailers, utilities and many other industry executives to exceed expectations.
At the other end of the spectrum, marketers turned to household segmentation models. Robust demographic data at the household level could be used to create clusters—segments of consumers who shared similar lifestyles, characteristics and needs. This lifecycle approach made it easy to target the ‘retired affluent’, ‘young families’, ‘single post-grads’ and dozens of other key markets. And with records updated quarterly (or even more frequently), marketers could respond quickly to life events.
Now for the first time, these distinct approaches have been combined to deliver enhanced network performance management and customer analytics solutions. Using deeper, more precise demographic data, organizations can make more informed and timely decisions about critical real estate and marketing initiatives. These next generation demographic data tools incorporate advantages from both disciplines and can help organizations overcome today’s top challenges, for example:
- Enables marketers and strategic planers to work from the same platform
- Compares changes in household make-up with neighborhood shifts to uncover pockets of opportunity
- Normalizes household data to block out the noise of short-term events to create more accurate projections
- Eliminates the need for ZIP Code targeting, which rarely reflect true neighborhood and lifecycle segments
- Links store network performance with customer relationship management strategies
Of course, creating the best of both worlds requires you to start with the best in both worlds. That’s why Pitney Bowes Business Insight teamed up with the Gadberry Group and Acxiom® Corporation and their PersonicX® segmentation system.
These data sources compile consumer data from over 100 sources, including public records, the U.S. Census and self-reported data. Measurements for accuracy and completeness are part of a sophisticated multi-source build process where individual data attributes are compared across multiple providers. While mapping and analytic tools previously dealt with neighborhood and block-level data, these new tools drill down to race, ethnicity, gender, education, marital status, occupation, income and lifecycle on an individual household level.
In many ways, incorporating Gadberry and Acxiom data into PBBI predictive analytics models will enable organizations to bridge the gap between real estate decision-making and marketing strategy – incorporating the best of both.
For more information on the newest technologies, visit http://go.pbinsight.com/household-derived-demographics.