Asterop is a business intelligence data company based in France. The company recently announced Asterop On-Demand, and the company's CEO and chairman, Christophe Girardier, will be speaking at this year's Location Intelligence Conference. Girardier answered some questions about the company's offerings.
Nora Parker (NP): Can you tell us exactly what the new "On-Demand" solution is and how it will affect retailers in the United States?
Christophe Girardier (CG): Asterop is delivering a direct, on-demand solution through the Internet called Asterop On-Demand that provides an approach to answering the most common questions faced by consumer-oriented businesses. With Asterop On-Demand, retailers, real estate brokers, marketers and other consumer-facing businesses access Asterop's online Web applications to explore expansion strategies, quantify local consumer demand and align their offerings with the best markets.
NP: How are the data derived and what sources are used?
CG: Asterop's data products are specifically designed to meet the specialized requirements of the retail industry. They have been produced using Asterop's advanced statistical modeling techniques and are validated by an independent scientific review committee.
Our demographics have been built using statistical estimation techniques applied to the U.S. Census Bureau's annual estimates and surveys, resulting in an accurate demographic representation down to the lowest levels across the country. Our approach entails modeling each of the factors that is driving growth across U.S. demographics, and then using these models to extend results across the entire U.S. landscape. These models are then coupled with advanced algorithms to weigh, adjust and ensure coherence with the U.S. Census at all levels. Our data include current year and 5-year forecasted data on household composition, income breaks, population age groups, housing characteristics and employment patterns, at both the block group and ZIP Code levels.
Asterop's consumer expenditure data were introduced in 2007 to provide realistic estimates of U.S. household consumption and include more than 600 categories of product and service expenditures, at both the block group and ZIP Code levels. These data are based on the most up-to-date consumer panel survey figures issued by the U.S. Bureau of Labor Statistics - the Consumer Expenditure survey, the most objective data available for understanding consumer behavior. Using the panel survey data, we created specific predictive models for each expenditure category that, when applied to a block group, produce detailed estimates of consumer spending in the block group, thus providing more accurate market data than are achievable with methods relying on averaging to generate block group level estimates. The results are comprehensive consumption data for food and drink items, household products, personal products and services, furniture and furnishings, appliances, apparel, electronics, recreational and sports activities and equipment, pet expenses, education and more.
Our consumer segmentation system provides improved alignment with consumer purchasing behavior, compared to conventional segmentation systems. This system was created because U.S. consumer behavior is too complex now to be explained accurately by typical lifestyle segmentation systems that fit consumers into a few dozen categories. Asterop's segmentation approach distinguishes consumer behavior among three high-level product groupings: personal goods and services, household equipment and fast moving consumer goods. Each of these segmentation themes contains clusters that are tied to factual buying patterns derived from the U.S. Bureau of Labor Statistics Consumer Expenditure Survey, and are not approximations. Asterop's approach captures the nuance of consumer behavior evident in the U.S. today, where people with the same demographics can actually differ dramatically from each other in their purchasing decisions across these three product groups.
Our goal is not to fit people into a single box to explain all buying behavior, but rather to use confirmed buying behavior within a discrete product category to predict future behavior within that category. The result is an infinitely more flexible, insightful and useful segmentation system that improves retail site selection and product assortment decisions, based solidly on facts. With a direct linkage between consumer behavior and clusters in each segmentation system, it is much easier to recognize clusters that align with a particular retail concept, which in turn makes it much easier to search retail markets and discover concentrations of the clusters that best suit your needs.
NP: You describe the product as "the first true Web solution to allow retailers, real estate brokers, marketers ... to conduct their own research and obtain valuable analysis on consumer demographic, consumption and segmentation information with the click of a mouse." How would you distinguish it from other, similar offerings?
CG: Other products provide access to demographic data, and do not provide the business-oriented analytics contained in On-Demand. We are answering a very specific need faced by retailers, real estate and marketing professionals. Asterop On-Demand offers new business-oriented applications that are focused on providing the specific answers that retailers seek, without a lot of complexity. For example, to identify the markets with the highest potential for a retail concept, a user can create a customized scoring function composed of the specific criteria for the concept's core customers. Asterop's market scoring feature returns a completed hierarchy of highest potential local markets for the concept, providing a useful benchmark for network expansion planning.
We believe that professionals today require more immediate access to quality applications and data than has been available in the past. We are committed to providing these applications directly to the end user through the Internet with Asterop On-Demand. All it takes is simple credit card payment and the click of a mouse to get access to targeted applications that provide retail business-oriented solutions, like locating the best centers for a concept, or markets with the highest potential.
NP: Can you tell us a little more about the company?
CG: Asterop, Inc. was founded in 1999 in France. We grew very rapidly in the international marketplace and entered the U.S. in 2005 with the acquisition of California-based Market Insite Group. We serve a wide range of leading businesses, such as IKEA, Jos. A. Bank, IntermarchÃ©, Anchor Blue Retail Group, Kingfisher Group, L'Oreal USA, Galeries Lafayette Group, Intersport, BNP Paribas, Barclays Bank, Jones Lang LaSalle and Viacom. Asterop remains privately held and has a staff of 55 worldwide.
We develop business intelligence solutions that optimize the sales, marketing and commercial performance of consumer-facing businesses. Our technology ranges from the new On-Demand solution available on the Web to the full suite of custom-built Asterop GeoIntelligence solutions for retail, consumer products, financial services and automotive. These solutions are based on the Asterop GeoIntelligence Platform, our own modeling methodologies and relevant, high-value data to provide the most comprehensive decision-support solutions available for optimizing strategies and guiding local operations.
NP: What will you be discussing/ showing at the Location Intelligence Conference?
CG: There are too many organizations that are basing their business decisions on inaccurate or outdated information. Our presentation at Location Intelligence 2008 will discuss the need for accurate predictive analytics and the effect of inaccurate data on the present and future retail landscape in the United States. In 2007, we conducted a survey of market potential across all the U.S. local markets using our business intelligence dataset. The survey revealed striking amounts of underserved consumer demand across numerous product categories, equating to nearly $250 billion in untapped revenue potential. The ability to use validated predictive analytics could have a significant impact on the U.S. economy, enabling retailers to discover untapped retail potential, while designing more successful store network expansion strategies and in-store product mixes. These are the things I'll be discussing.