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Good data is good retail therapy for Minnesota's communities

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Retail is a mainstay for Minnesota’s economy, accounting for 5.4 percent of the state’s economic output and 282,700 part-time and full-time jobs. That’s an important contribution. But look deeper. The contributions of Minnesota’s shops and retail go beyond economic success.

"Minnesota’s communities need a strong retail sector,” says Matt Kane, program leader for Extension’s Community Economics programs. “Successful retail keeps communities vibrant.  And the civic contributions of retailers can’t be overlooked. From supporting a local sports team to spearheading community events, retailers keep communities vital. Some also create public spaces where community conversations happen.”

Keeping retail healthy is a priority for economic development leaders throughout the state. In Fairmont, Minnesota, the number one job in supporting retailers is getting them the numbers – solid data about how their retail sector is doing. “We want to know what our gaps are,” says Bob Wallace, president of Fairmont’s Chamber of Commerce. “Our gaps are opportunities for new businesses to come in, and they also provide opportunities for our businesses to expand their merchandise offerings."

Fifteen years ago, Fairmont looked south to get their numbers. That’s because Ken Stone, Ph.D., of Iowa State University was doing nationally lauded work examining changes in local retail economies, especially in light of the introduction of big box stores.

Extension’s Community Economics program team was as impressed as Fairmont with Dr. Stone’s ability to measure the health of retail economies.  So, a few years after Fairmont brought Dr. Stone’s analysis to their community, Extension partnered with Iowa State to bring retail analysis to all of Minnesota. Now, Extension uses Stone’s methods of analysis, along with yearly data from the Minnesota Department of Revenue, to maintain a database for a Retail Trade Analysis of any county, and many cities over 5,000 in population. In 2012, Extension provided reports to 46 Minnesota counties and towns. Some, like Fairmont, have received reports every year since 2005.

A wellness check-up for retailers

Bruce Schwartau, Extension Community Economics educator in Southeast Minnesota, leads the statewide Retail Trade Analysis program, making him chief number cruncher. He and other community economics educators also consult with community leaders and groups to help them understand the data. “Retail Trade Analyses are like a yearly doctor’s visit for retail economies,” says Schwartau. “When you get your blood pressure or cholesterol readings, you see how your body is faring in comparison to the norm, as well as how your body changes when you take steps to improve your health. That’s what community leaders and retailers can do — look at the numbers, consider what’s happening that affects the numbers, and take steps to improve them.”

Communities interested in data will be impressed with the number of numbers available — and may even be a bit overwhelmed. After all, a local economy includes many individual retail and service sectors, each with fluctuating trends. The most common are:

Retail sectors Service sectors
  • Motor vehicle and parts dealers
  • Furniture and home furnishings stores
  • Electronics and appliance stores
  • Building material and garden equipment and supplies dealers
  • Food and beverage stores
  • Health and personal care stores
  • Gasoline stations
  • Clothing and clothing accessories store
  • Sporting goods, hobby, musical instrument and book stores
  • General merchandise stores
  • Miscellaneous store retailers
  • Non-store retailers
  • Amusement, gambling, and recreation industries
  • Accommodation
  • Food services and drinking places
  • Repair and maintenance
  • Personal and laundry services

Seventeen sectors, two analyses

The health and well-being of these 17 sectors can be analyzed two ways, each presenting information comparing success to statewide norms.

The Pull Factor considers whether a merchandise sector is bringing in more or less revenue per capita than the average state revenue per capita for that type of merchandise. Pull factors help communities understand which of the categories are strong and which are weak. For example, Minnesota’s sales of Health and Personal products (that’s medications and health products, as well as cosmetics and the like) average $117 per Minnesotan. But for Alexandria, 11 Health and Personal retail stores sold an average of $366 per resident in 2011. That means Alexandria’s Health and Personal Retail Pull Factor is 3.08 (366/117). Obviously, Alexandria residents didn't buy all of those goods. Alexandria’s stores attracted customers from other areas.  So, Alexandria is pulling in sales in this category.

Expected sales analysis considers whether a community’s economy is over- or under-performing for sales in comparison to towns with similar populations and income levels. “Just as age and other factors come into play when we analyze our health, communities need to consider their size, location and income levels,” says Schwartau. “So we don’t compare Fairmont’s data to Minneapolis data. We find communities more like theirs.”

Community-informed data, data-informed decisions

Numbers don’t tell the whole story, but they do help communities shape their own unique story.  “Over time, communities spot trends,” says Schwartau.  “They ask, ‘Is our city becoming a shopping destination for certain purchases? Or for everything? Did the loss of one key business start a downward trend? If we replace that business, can we bring people back?’”

Such long-term investment in data has been successful for Fairmont. Bob Wallace notes that Fairmont has used the numbers as a tool to recruit new businesses. “We can show potential businesses that there is an opportunity here in certain areas.”  When a local lumberyard went for sale in 2001, for example, companies interested in bidding reviewed data in Fairmont and surrounding communities to understand the potential. In the end, the lumberyard entertained multiple bids for the property.

Tips for using data

After providing hundreds of retail trade analysis reports to Minnesota’s communities, Extension’s Community Economics educators offer the following suggestions for using the data and the discussion it stimulates to strengthen local retail economies.

  • Find your niche.  Schwartau helps communities pay close attention to which existing stories are doing well. “Look at specialty stores to find out why they are successful. What are they providing that people can’t get elsewhere? Could other businesses mirror that success or build on that market?”
  • Pay close attention to food and beverage sales.  People don’t tend to travel great distances for groceries. They’re going to go to the most convenient spot that has a reasonable price. And while they are getting those “must buy” goods, they can be attracted to buy other things.
  • Guide the flow of traffic. Parking, clear signage, snarl-free traffic flow, and walkable distances between stores can all help customers spend more dollars in town.
  • Find your untapped customers.  In Winona, Minnesota, the retail sector discovered that their city wasn’t pulling in retail business from local students. To promote local buying, the town coordinated a scavenger hunt, utilizing quick response (QR) codes to connect students to the merchandise and services local businesses offer.
  • Involve local media. News stories about key information from retail analysis reports can help local residents understand the challenges and successes of their local retailers, and mobilize the town to buy locally.
  • Reward success.  The yearly data that Fairmont receives is critical to identifying and addressing gaps, but Bob Wallace also notes that leaders use the numbers to build the morale of their local retailers. “When we see that stores in some areas are succeeding, we share those numbers as encouragement to local retailers who are making an economic difference for our city. We want to cheer them on.”

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Author: Joyce Hoelting

Reviewed in 2013

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