The Retail Revolution Makes Do-It-Yourself Data Dangerous
The data revolution has brought challenges to the science of site selection and tenant mix planning.
Carol Gies

The most recent revolution in retail is a dispersion of retailers from regional malls to new formats and venues: lifestyle and town centers, main streets, high-rise residential, train stations, entertainment facilities, parking decks, and points in between.

The result of this movement is that retail and foodservice can pop up just about anywhere — and that means the science of site selection and tenant mix planning has brand new challenges in this fragmented marketplace.

Four Trends Are Making Retail Markets More Complex

This rapid diversification of retail locations is being accelerated by the convergence of four widely reported trends:

1.City and town officials are looking to retail for increased tax revenue and rebuilding neighborhoods as manufacturing moves out.

2.Affluent suburbs are developing downtown retail districts for tax revenues and to attract homebuyers.

3.Retailers are testing a variety of new formats to fit into new venues as an alternative to the enclosed mall.

4.Shopping center developers are building smaller retail centers, mixed-use projects and main streets without traditional department store anchors.

Do-It-Yourself Data Is Risky In Complex Retail Markets

The dilemma is that even as markets are becoming more complex to analyze because of retail dispersion and fragmented of consumer shopping — an avalanche of market data is now readily available online and is being accessed and analyzed by much less-experienced people. It's like reading a few laws on the Internet and then acting as your own attorney.

During the past decade, most shopping center developers and major retailers greatly increased the sophistication of their market analysis methods. They moved from basic demographics to consumer lifestyle segmentation systems that predicted what consumers were likely to buy, based on where they lived. These systems were licensed, expensive, required extensive training, and were used by experienced market analysts. Market research was a powerful, “controlled substance,” limited to a small core of licensed users.

Recently, however, consumer and market data has become available on the web to anyone with a mouse and a credit card — with maps as colorful as USA Today. Software firms, from start-ups to international conglomerates have turned “do-it-yourself” consumer research into big business. Technically, anyone can now instantly analyze a market or select a site location.

For a few hundred dollars, you can find out where target consumers in your market are most likely to shop, eat, read or buy golf clubs. This data is based partly on fact: census data, purchase records, consumer surveys, television diaries, product registrations — and partly on interpretation — as the software companies create their own proprietary consumer behavior models. These reports are constructed on a national sampling basis, and then “modeled down” to local markets.

The software companies work hard to educate the novice user on these data products. They offer no end of workshops, webinars, conferences and help-desk assistance. Their level of knowledge and service is uniformly excellent. But like any good product representatives, they lead with the features and benefits of their software — not its limitations.

For anyone interested in the methodology, it's available online. But how many of the new online users will take the time to learn the technicalities of what this data really means?   Most often, it is just accepted as 100 percent fact. We report these consumer lifestyle segments as if they were hard and fast definitions of people's buying habits, instead of modeled data. The risk is that the inexperienced user can easily misinterpret the data — or not order a crucial report — and misdiagnose the market.

For example, did you remember to order the daytime population report?   Do you know how much these daytime workers really will shop — and what they are likely to buy?

How to Lower “Market Misdiagnosis” Risk

For larger companies with ample budgets ($30,000 to $50,000-plus), the consulting divisions of the software providers can create custom models for market screening, site selection and sales forecasting to ensure correct analysis using their data.

For the small or midsize retailers, developers and communities who go it alone in deciding which data to order and how to analyze it, there are steps you can take to lower the risk of market misdiagnosis.

Most important is to focus on market competition, because in today's dispersed retail landscape, it is the most difficult part of market analysis.

• Do your own analysis of the competition to compare with the on-line data reports. Nationally-generated data is likely to miss hidden pockets of retail in local trade areas, especially in the new unconventional venues  

• Do your own consumer survey to determine competitive shopping patterns. Compare where consumers in your trade area shop vs. the nationally modeled data. It will not be the same (guaranteed) because of different retail offerings in your market. You need to know this information precisely to plan a site location or tenant mix.

• Develop a list of all of the other factors that may affect the potential of your site location, especially those that are strong among your competitors. Standard data reports do not include these specific site factors like parking, access, visitor potential, co-tenancies, safety, etc., so you will have to create your own “model” to estimate the true potential of your site against local competition.

If you need help in deciding what data to order, and can articulate exactly what questions you need answered, the software companies can assist you. However, if you need help in blending all of the data and coming up with an analysis of the market and a retail strategy, you will need an experienced outside consultant.

The wealth of readily available data   can be an extraordinarily valuable tool for analyzing your market. But more information is not necessarily better. The key is to know how to select the right data, understand its limitations, and then be able to translate this information locally into the highest potential store mix — or the best site for your next unit. With the complex array of new retail venues coming to the marketplace daily, these choices are going to become more challenging than ever before.

Carol Gies is the president of 4Insights, Inc., a Naperville, Illinois-based firm specializing in market research and strategy for retailers, restaurants, shopping centers/districts, mixed-use and community economic development. She can be contacted by e-mail at 4Insights@comcast.net.