Peer City Comparison
When considering business development strategies, it is often helpful to examine your downtown or business district relative to those in peer cities or cities that embody similar qualities. This section explains how this comparison can help you discover business development opportunities that will strengthen economic vitality in your downtown or business district. Mainly, this exercise will help you determine what kinds of retail or service business activities are supported in like places. In addition, this comparison will provide real-life examples of districts that have defined themselves with a clear position in their market in terms of goods and services offered and of primary consumer segments served. These examples of differentiation and niche development can help stimulate creative ideas for refining the market position of your district. The appendices provide tools to identify peer cities.
- Identifying Peer Cities
- Comparing Peer City Business Districts
- Learning from Peer Cities
- Using Existing Research
- Appendix 1– Database of all U.S. Municipalities
- Appendix 2– Database of Small Midwestern Cities by Type
Identifying Peer Cities
Choosing peer cities with downtowns or business districts that offer you a helpful comparison is critical. You want to select 3 to 5 cities that have similar market characteristics (geographic, demographic, economic, etc.). In addition, you will want to ensure these cities have successful business district(s) that serve clearly defined and strong positions in the market. These districts should offer us lessons on how to grow the economy in our particular business district.
Cities with Similar Market Characteristics
There are a number of ways to identify peer cities with similar business districts. First, start with the city’s demographic characteristics. Since the two biggest drivers of retail and service business expenditures are population and income, these two characteristics are good initial indicators of a comparable place. See the factsheet on retail hierarchy for further information on how population and income affects business mix. Use the database of U.S. Municipalities in Appendix 1 to begin your selection of peer cities
In addition, location characteristics, such as proximity to other major urban places or to major transportation routes can be useful. You might need to use additional criteria to suit your community’s unique functions. For example, if you are located in a small college town, a vacation destination, or an exurban bedroom community, you might select places which serve similar functions.
A final consideration in identifying a peer city is whether your own community has a particular cultural and/or historic characteristic that affects shopping habits. If so, you may want to find a peer city that embodies the same characteristic. Consider the following sample market characteristics when identifying peer cities.
- Population and growth trends
- Per capita income
- Distance to major highway
- Distance to a major urban area
- Proximity to natural amenity (lake or riverfront)
- Tourist town or gateway to amenity ( entrance of park, late, forest, or other resource)
- Bedroom community
- College town
- Industrial/corporate services
- Craft/specialty center (art or culinary specialties drive retail economy)
- County seat
- Themed town (casino-based town; cultural/historical reenactment; etc.)
Appendix 2 offers a first cut at identifying potential peers among small Midwestern cities. The appendix groups similar communities by focusing on basic town characteristics. In a previous study, we found that population, population change, distance to major urbanized area, and whether or not the town is the county seat were contributing factors to success. We used these same criteria to group towns in Indiana, Illinois, Michigan, Minnesota and Wisconsin. We selected towns of over 2,000 in population in 2000 (to ensure that the town had some retail activity) and towns that were not within (even partly) urbanized areas.
Cities that are Economically Vibrant
To further refine your selection of peer cities with similar business districts, it is important to narrow down candidates to those that are economically vibrant. The selected cities should have downtowns and business districts that successfully serve clearly defined and successful positions in the market. These should be places that can offer lessons on how to grow the economy in your particular district. Refine your list of peers based on:
- Knowledge of places shared by existing study group members;
- Case studies on successful downtowns (such as those recognized by the National Main Street Center, International Downtown Association, Urban Land Institute, American Planning Association, or other organization);
- Articles in travel and other magazines; and
- Websites and literature available from downtown and business district organizations.
Comparing Peer City Business Districts
Once you have identified your peer cities and narrowed down the differences between your city and your peers, it is helpful to assemble comparison data on each downtown or other business district. These data are intended to provide a glimpse into the economic drivers and characteristics of the business environment. These data should include attributes most important to your district’s business development priorities. Data points could include district-specific measures such as:
- Demographic and lifestyle characteristics;
- Employment numbers;
- Housing stock (number of units, ownership levels, interest rates);
- Available office space, vacancies, average rents
- Retail and service business mix (types and number of businesses);
- Traffic volume and patterns;
- Tourism industry statistics like visitor numbers; and
- Physical layout of the district (focusing on land uses).
You can obtain some of this data for each of the comparison business districts using secondary data providers such as the U.S. Census Bureau, ESRI’s Business Analyst data or Claritas Site Reports. A study area can be drawn around the midpoint of each district, forming a 0.5 or 1-mile radius, or ring. Data from these providers can then be extracted for these rings.
Comparison data provides information on whether your downtown or other business district lags behind or leads your peers. If your downtown leads your peers, what strengths can you build on? If your downtown lags your peers, are you missing opportunities to grow in certain sectors? Also compare your peer cities’ business mixes with your community’s. Have your peer cities developed successful niches that attract additional customers to their downtowns?
Learning from Peer Cities
Each peer city you select provides a unique “story.” These stories are often told best through an actual site-visit to the community. These visits can be an eye-opening experience for your study group and provide ideas that might be transferable to your downtown or other business district.
Visits to Peer Cities
As noted above, actual site visits offer an excellent way to learn about the successes of other downtowns and business districts. During these visits you should interview business and community leaders. Some communities send their study group on bus tours of their peer cities. These kinds of events give study group representatives an opportunity to hear perspectives and strategies from peer cities that might be applied to their own communities.
While many aspects of business district revitalization can be explored in these visits, the answers to the following questions are particularly relevant to market analysis:
- How has the peer city downtown or other business district defined a unique market position for itself?
- Specifically, what competitive advantages has the peer city cultivated through the goods and services it offers and the consumer groups (e.g., students, day workers, visitors, etc.) it serves?
- What specific economic development strategies have worked in the peer city downtown or other business district? What initiatives have helped expand or recruit businesses, including retail?
First Impressions Program
Engaging your community’s study group in a First Impressions Program provides a formal process for learning from peer cities. The First Impressions Program offered by a number of state Extension services, including those at the University of Wisconsin and Ohio State University, involves an exchange of visitors that gives each community an outside perspective on retail and service sectors. After you identify a willing peer community, ask it to send a visitation team to assess your community using criteria such as community attractiveness, access to and availability of services, and friendliness. Then your community should send a similar team to the peer community. The primary purpose of the First Impression Program is to inform community leaders about the perceptions that potential shoppers, tourists or employers might have of each community.
Using Existing Research
Conducting a peer city comparison of business districts can be a valuable, but time consuming effort. It may be more practical for some communities to consult existing research on success factors for downtowns and other business districts. While these studies may not focus on exact peer cities for your situation, they do contain information on general economic development principles that are transferable to many business districts. The following describes a study of the type you may find helpful in determining success factors for your downtown or other business district.
Example Research: Factors That Influence Sales per Capita in Exurban and Rural Communities
In 2008, a team at Ohio State University (Jill Clark, Greg Davis and Elena Irwin) conducted a study entitled “Central Business Districts: The Measures of Success.” This study analyzed more than 500 rural and exurban mid-size (population between 2,000 and 15,000) communities in the Great Lake states of Indiana, Illinois, Michigan, Pennsylvania and Ohio to determine what characteristics contributed to greater sales per capita. The study combined use of economic, demographic and geographic secondary data with primary data collected through 20 interviews with downtown business and government leaders—elected officials, city planners, downtown organization managers, chamber of commerce directors, and the like). The study team first grouped the 500+ cities and villages using a clustering technique described in Appendix 2. Next the team chose the city with the greatest per capita sales in each group to conduct the interviews. Following are key interview findings, which identify proven strategies and policies for developing successful central business districts (CBDs).
- Well-developed community and government relations built on trust
- Consistent pedestrian traffic
- Effective downtown promotion
- Easy access to good financial and educational resources
- Reliable communication network
- Active downtown business recruitment and retention
- Transparent and flexible planning and zoning
- Capable, collaborative business and civic organizations
- Physical design of the CBD
- Strong neighborhood customer base,(which yields daily and year-round sales)
- Completion of applicable research and development
You may access the full study here.
Appendix 1– Database of U.S. Municipalities
Below is a Microsoft Excel workbook that contains demographic data on U.S. cities, villages and other designated places. This workbook can be used to identify peer communities. Using Excel’s “Sort and Filter” tool, the database can be narrowed down from the 25,000+ locations to a select list of the most demographically and geographically similar locations.
Following is a list of some of the fields (columns) that are most useful in selecting peer communities:
- States – choose your state and possibly contiguous states
- City/village population range
- 10-mile ring population range
- Distance to nearest community with over 25,000 residents
- Per capita income
Use this database to select 25 to 50 possible peer candidates. These communities must be refined further to include only those that are economically vibrant.
Appendix 2– Database of Small Midwestern Cities by Type
A research team at Ohio State University demonstrated that communities could be grouped based on demographic, location and function characteristics. Researchers took this data and created clusters, or groups, of exurban and rural cities and villages for Ohio, Michigan, Indiana, Illinois, Wisconsin and Minnesota. The characteristics used to cluster these cities and villages were: base population in 1990, percent population change 1990-2008, average distance to an urbanized area in kilometers, and whether or not the city or village is the county seat.
The distribution of the clusters is presented in the table below. A link to the document containing the names of component communities follows the table. This database can be used to identify similar communities in the Midwest. The selected communities must be refined further to include only those that are economically vibrant. Dependence refers to the distance of the community to a major urban area, with independent meaning the community is far away and dependent meaning the community is nearby a major urban area. Central services refers to cities and villages that serve as county seats.
Cluster Distribution and Average Characteristics
|Cluster Membership (N)||Av. Pop. 1990||Av. Pop. Change, 1990-2008||Av. Distance to Urbanized Area, km||% County Seat|
|1. Dependent, rapidly growing, small hamlet (27)||2,234||221%||11||0|
|2. Semi-independent, growing, small hamlet (131)||3,666||14%||43||0|
|3. Independent, growing, small hamlet (30)||3,196||11%||112||0|
|4. Dependent, rapidly growing, small hamlet (207)||4,223||25%||12||0|
|5. Dependent, growing, mid-size town, w/central services (115)||5,240||10%||25||100|
|6. Semi-independent, stable, mid-size town, w/central services (71)||6,472||5%||61||100|
|7. Independent, declining, mid-size town, w/central services (26)||7,321||-3%||126||100|
|8. Distant, declining, mid-size town, w/central services (14)||7,171||-9%||211||79|
|9. Dependent, growing city, w/central services (39)||13,050||14%||19||100|
|10. Semi-independent, stable city, w/central services (31)||20,749||6%||38||100|
|11. Semi-independent, stable, city (28)||15,850||0%||28||0|
|12. Semi-independent, stable, large city, w/central services (11)||34,405||2%||46||91|
|About the Toolbox and this Section
The 2011 update of the Downtown and Business District Market Analysis toolbox is a result of a collaborative effort involving staff and educators from University of Minnesota Extension, Ohio State University Extension, and University of Wisconsin Extension. The update was supported with funding from the North Central Regional Center for Rural Development.
The toolbox is based on and upholds the economic restructuring principles of the National Trust Main Street Center. The Wisconsin Main Street Program (Wisconsin Department of Commerce) has been an instrumental partner in the development of this toolbox.
This section includes new methods added by Jill Clark, Ph.D., of Ohio State University Extension; Ryan Pesch of University of Minnesota-Extension; and Bill Ryan of University of Wisconsin-Extension.
 The project “Central Business Districts: Measures of Success” was conducted by a research team at the Ohio State University. To find out more, visit: http://aede.osu.edu/programs/rma/cbd_program.htm