|Complex maps that integrate geospatial targeting tools provide analysis of potential 'likely to purchase' areas that marketers could target with local ads.|
Last summer's move by General Motors to apply Google Earth technology revealed an interesting step in the right direction: using more accessible, cost-effective web-mapping technology to target customers. But even with the addition of corporate data for a proprietary overlay of corporate information on these maps -- called "mash-ups" -- Google Earth and Microsoft Virtual Earth still can't show enough data to make precision-targeting decisions for marketers.
As a Washington-based agency, we see different uses for mapping technologies at the federal level all the time. The various military and homeland-security tools in the marketplace have demonstrated the plausibility of an unusually large and complex amount of data analysis on a single map. These maps use "hot spots" -- denoted by circles of color overlaid on a map-to visualize a wide variety of information that includes several, or sometimes thousands of sets of data and qualifying information, including income, age, sex, marital status, ethnicity and number of children. In Washington, several companies meet the needs of the homeland-security and defense industries by building maps that analyze complex amounts of data and visualize them with hot spots. Using hot-spot visuals, the Department of Homeland Security can determine potential weaknesses, and the military targets potential enemy sites.
Like so many other government-initiated breakthroughs, including the internet and Velcro, high-end, defense-oriented geospatial targeting tools could be applied to today's business world. Such tools would enable marketers to execute marketing campaigns with guaranteed results.
On a commercial basis, hot spots would enable marketers to discover promising demographic areas. Consider an image demonstrating potential store locations for a national ice-cream retailer in the Washington metro area. The hot spots show ideal neighborhoods for stores based on average-unit-volume history and demographic profile, while pins indicate competitor stores. Underused or open areas are visible, enabling marketing activity with the least amount of competition.
Complex maps that integrate such tools provide analysis of potential "likely to purchase" areas that marketers could target with ads in local newspapers, magazines and broadcast outlets as well as with direct mail, telemarketing and billboard advertising.
Many in the industry are familiar with the wide variety of traditional targeting solutions from companies such as Claritas and ESRI and new solutions from Google Earth and Microsoft Virtual Earth. These old and new technologies each have unique aspects and disadvantages.
Let's start with the old-line technologies. By compiling only free public data from the Census Bureau and other public sources, these systems tend to lack the high-end decision-making tools that enable marketers to effectively target customers. Even with this abundance of public data, marketers still are forced to guess at audiences by looking at neighborhoods and ZIP codes. Further, these technologies lack the computational sophistication to process multiple layers of information, which would enable marketers to strategically approach complicated demographics.
More commonly, CMOs subscribe to costly proprietary tools, which are primarily used by large media corporations, publicly traded agency networks and large independent agencies. In some cases, the software is so complicated you need your own degree in geospatial analysis to understand the maps, modeling and how these variables affect marketing efforts. At the end of the day, these tried-and-true segmentation and analysis models still require human beings to make subjective decisions about how to "cluster" and define segments.
With this new generation of mapping technology, we can know, with 99% accuracy, who will take action or purchase. For example, a luxury-car marketer may want to target consumers most likely to purchase a new car this year. Given purchase-history files and other public data, we can view spots (denoted by the warmer colors on the map) that have a 99% likelihood of purchase.
Multiple data layers
Indeed, the recent introductions of Google Earth, Microsoft Virtual Earth and other web-based map solutions provided a new way of viewing our world. Large marketing organizations were eager to see how the satellite images -- connected with their own data -- could provide new ways of visualizing demographic audiences. Companies as big as GM signed up with Google and Microsoft to mesh their data with satellite-map imagery.
But even these advances have limitations, and have failed to fully meet the complicated needs of the 21st-century marketer. The fact is that today's marketer must find potential buyers by using five to eight different qualifying data sets. That's why, to better address marketing intelligence and decision support, web maps must display multiple data layers including population, market-specific data, behavioral mapping and geospatial information.
Currently, an inordinate amount of these data -- once thought public -- is only available in special software packages from private companies. These data need to become readily accessible for web-mapping applications so that marketers may better integrate their data for marketing mash-ups. As this happens, marketers will be able to mesh their own data with public information to create super mash-ups, in turn enabling precision marketing, site selection and campaign management. As a critical tool in their marketing toolbox, hot-spot-enabled maps will help CMOs to know exactly which advertising dollars will work and why.