Identify retail gaps with void analysis

Define the reference area

Void analysis compares two areas with similar demographic profiles. The area in which you want to identify gaps is called the analysis area, while the area that you already know contains businesses of interest is called the reference area.

You'll create a project in ArcGIS Business Analyst Web App and define the reference area: Frisco, Texas, where the juice bar chain is already located.

  1. Go to Business Analyst.
  2. If you are not already signed in, click Sign In. Sign in with your ArcGIS organizational account.
    Note:

    If you don't have an organizational account, you can sign up for an ArcGIS free trial. Your account must be licensed to use Business Analyst. If you are the administrator of your organization, you can assign yourself a license. Otherwise, you'll need to contact your administrator for permission.

    The Business Analyst home page appears. On this page, you can see recent updates and a quick-start video, as well as your own content. If you have used Business Analyst before, your latest content will be displayed at the bottom of the screen.

  3. Click Create New Project.

    Create New Project button

    The Create Project window appears, with the option to name your project. The project name must be unique in your organization.

  4. For Project name, type Juice Bar Void Analysis and add your name or initials. Click Create.

    A notification appears, explaining that a project is being created. The process may take a few moments. When it finishes, either a message appears to explain that the project has been created, or the project opens automatically.

    Note:

    If a message appears, you can check Open new projects as soon as they are created to open projects automatically in the future.

  5. If necessary, in the message window, click OK. In the list of projects, point to your Juice Bar Void Analysis project and click Open.

    The project opens.

    Default project

    Note:

    Depending on your organization's settings, the default extent and appearance of your project may differ from the example image.

    Next, you'll define the reference area of Frisco, Texas.

  6. On the ribbon, click Define Areas and choose Select Geography.

    Select Geography button in the Define Areas menu

    The Select Geography pane appears. You can either search for a specific geography, select a geography from a layer on the map, or browse a full list of available geographies based on country, state, city, or other subdivisions. Because you know the exact geography you want, you'll search for it by name.

  7. In the Select Geography pane, click Search. For Search for your geography, type Frisco, TX and press Enter.

    The search results are divided by category.

  8. For Search results, expand Cities and Towns (Places) and check Frisco City, TX.

    Frisco City, TX, in the list of search results

    The map navigates to Frisco. A polygon representing the city boundaries is added.

    Frisco, Texas, on the map

    Frisco is located in Collin and Denton counties and is part of the Dallas-Fort Worth metropolitan area. It is one of the fastest-growing cities in the United States and has a population of about 200,000.

  9. In the Select Geography pane, click Next.

    The Frisco polygon is saved to the project. A pop-up appears with options for analyzing and editing the polygon. (You'll use this pop-up later, so do not close it.)

  10. In the Select Geography pane, click I'm Done.

Define the analysis area

The analysis area is the area you plan to analyze to determine whether it's a good market for a new juice bar. Juice bars are primarily frequented by millennials and health-conscious people with high income. The best analysis area will be comparable to Frisco in these demographic categories.

To determine the analysis area, you'll compare Frisco to neighboring cities in Collin County based on their millennial populations, median household incomes, and spending potential for juices and food services.

  1. On the map, in the Frisco City, TX pop-up, click Comparisons.

    Comparisons option in the Frisco City, TX pop-up

    Note:

    The color of your map's Frisco polygon may differ from the example images.

  2. If necessary, in the Import Sites window, click Add this site to the current report.

    The Comparison Reports window appears. It displays your most recent comparison report for the selected area. You'll create a report that compares areas based on the demographic information you choose.

  3. Click Create new report.

    Create new report button

    Note:

    If you have created a report in a previous Business Analyst project, you may receive a confirmation window asking if you want to switch to another report. If so, click Yes.

    The Add Variables window appears. You can choose demographic variables based on several categories. If you have added variables for analysis in a previous Business Analyst project, those variables may be selected by default.

  4. If necessary, for Selected variables, click Clear all.

    Clear all option if variables are already selected

    First, you'll add a variable for millennial population. Millennials are defined as people born between 1981 and 1998.

  5. Select Population.

    Population category

    This category contains population information for a variety of demographics. A list of popular variables is displayed, but these variables do not contain the one you want.

  6. Under Keep browsing, click Generations.
  7. Expand 2021 Population by Generation (Esri).

    Expand Population by Generation menu

    Note:

    Demographic data is updated periodically. You may see more recent data than the data used in this lesson and shown in the example images. Feel free to use more recent data if it exists.

    A list of population variables by generation appears. You can choose to add population data as a number or as a percentage of the total population. To account for differences in total population between cities, you'll choose the percentage.

  8. For 2021 Millennial Population (Born 1981 to 1998) (Esri), click the percent button. Check the variable.

    Millennial Population variable as a percentage of total population

    The Selected variables list updates with the selected variable. Next, you'll add a variable for median household income. This variable is a good indicator of income in an area. Low-income areas may not be able to spend as much at a juice bar compared to higher-income areas.

  9. Click the Categories button.

    Categories button

    You return to the list of categories.

  10. Click the Income category. In the Popular variables list, check 2021 Median Household Income (Esri).

    Median Household Income variable

    The next variable you'll add indicates an area's retail sales potential for food and beverage places, including juice stores.

  11. Click the Categories button. Click the arrow to scroll right on the list of categories and click the Supply and Demand variable.
  12. For Search within the current category, type Drinking Places and press Enter. In the search results, check 2017 Retail Sales Potential: Food Services & Drinking Places (NAICS 722).

    Retail Sales Potential variable

    You'll also add demographic variables that specifically track juice consumption.

  13. Click the Categories button. Above the list of categories, in the search bar, type Juice and press Enter.

    The search returns several groups that contain juice-related variables.

  14. Expand 2021 Food at Home - Dairy/Fruit/Vegs (Consumer Spending).
  15. For 2021 Food at Home - Fresh Fruit Juice and 2021 Food at Home - Vegetable Juice, choose Index. Check both variables.

    Juice variables

    The Selected variables list contains five variables. These variables should provide a good indication as to whether an area has demand for a juice store.

    Selected variables list with five selected variables

  16. Click Apply.

    The variables are added to the Comparison Reports page. Next, you'll choose the geographies to compare based on the variables. You want to compare Frisco to its nearby cities.

  17. Click Add sites.

    Add sites button

    The Add Sites window appears.

  18. Click Neighboring geographies and uncheck States and USA.

    Uncheck States and USA under Neighboring geographies

  19. Expand Cities and Towns (Places). Check all of the cities and towns except Frisco (there are six total)

    Cities that neighbor Frisco, Texas

  20. Click Apply.

    The neighboring cities are added to the comparison report, with their values for each of the demographic variables listed. Rather than compare each city to Frisco one by one, you'll make Frisco the benchmark and automatically style the values for the other cities by their similarity to Frisco's values.

  21. For Frisco City, TX, click the options button and choose Make benchmark.

    Make benchmark option for Frisco City, TX

    The other values are styled based on their similarity to Frisco's values. Darker colors indicate values that are higher than the benchmark, while lighter colors indicate values that are lower than the benchmark.

    Comparison table with Frisco set as the benchmark

    No city matches the demographic profile of Frisco exactly. Most of the neighboring cities have higher millennial populations but lower median household income and retail sales potential for food services and drinking places.

    The city of Plano stands out as having high retail sales potential compared to Frisco, along with relatively close values in the other variables.

    You'll choose Plano as your analysis area. Next, you'll add its city boundaries to the map.

  22. On the ribbon, click Maps.

    Maps option on ribbon

  23. Click Define Areas and choose Select Geography. In the Select Geography pane, click Search.
  24. Search for Plano, Texas. In the search results, expand Cities and Towns (Places) and check Plano City, TX.

    A polygon representing the city boundaries of Plano is added to the map.

  25. Click Next. Click I'm Done.

    Plano city boundaries added to the map

Perform void analysis

You've defined the reference area, where the juice bar chain already has a successful location, and the analysis area, an area to which the chain may want to expand. When you compared the demographic information, you determined that Plano had a high retail sales potential for drinking places.

However, it's possible that Plano already contains several juice bars. Even if Plano is demographically favorable, if there is too much competition, a new store in the area may not be successful.

You'll use void analysis to compare the amount of juice bar businesses in Frisco and Plano. If Plano has fewer juice bars than Frisco, there is probably demand for a new juice bar. If it has more juice bars, opening a juice bar may be inadvisable.

  1. On the ribbon, click Run Analysis and choose Void Analysis.

    Void Analysis button

    The Void Analysis pane appears. If you've never used void analysis, the pane displays a brief outline of the void analysis workflow.

  2. If necessary, click Get Started.

    Next, you'll choose your analysis area and reference area.

  3. Click Select Analysis Area. In the Select Analysis Area window, check Plano City, TX.

    Plano chosen as the analysis area

  4. Click Apply. In the Void Analysis pane, click Select Reference Area.
  5. In the Select Reference Area window, check Frisco City, TX and click Apply.

    You've selected both areas to be used in the void analysis.

  6. In the Void Analysis pane, click Next.

    Next, you'll choose the business data to analyze. For this scenario, you want to analyze juice bars and other drinking places.

    There are three options for choosing business data:

    • You can choose from Esri-provided business data categories.
    • You can search for businesses and services using the United States Census Bureau's North American Industry Classification System (NAICS) and Standard Industrial Classification (SIC) codes.
    • You can import a custom business data layer with your own business data.

    For this lesson, you'll use NAICS and SIC codes. These codes are helpful when searching for business data in the United States.

    Note:

    In this lesson, you'll be provided with the correct codes to search for, but if you want to look up NAICS or SIC codes yourself, you can do so at the NAICS Association.

  7. Click More options.

    More options

  8. choose Search by code and iIn the search box, type 72251518. From the menu, choose 72251518 (Juice Bars).

    NAICS code for juice bars

    This code represents juice bar businesses. You'll also add codes for coffee shops, cookie shops, and ice cream parlors, which are similar drinking establishments that might compete with juice bars among millennial populations.

  9. Click Add code and add 72251505 (Coffee Shops), 72251506 (Cookie Shops), and 72251512 (Ice Cream Parlors).

    All NAICS codes added

    The final parameter is the field used to compare businesses in the analysis and reference areas. You can choose to compare by business name or by NAICS or SIC codes. If you compare by business name, you can still filter the results by NAICS code later.

    Note:

    SafeGraph is another available Data source for Void Analysis. See the ArcGIS Blog article Why and when to use SafeGraph data in your analysis for more information on when to use SafeGraph.

  10. For Field to determine void, confirm that Business Name is chosen.

    Field to determine void parameter set to Business Name

  11. Click Run Analysis.

    The analysis is run. Juice bars, coffee shops, cookie shops, and ice cream parlors in Frisco and Plano are added to the map as point locations. In areas where dense clusters of points are located, the points are replaced by numbers that indicate how many shops are in the area.

    Note:

    Business data updates periodically. Your results may not match the example images.

    Map with juice bars, coffee shops, cookie shops and ice cream parlors

    The Void Analysis pane summarizes the results.

    Summary of void analysis results

    According to the summary, Plano (the analysis area) has 65 businesses matching the chosen criteria, while Frisco (the reference area) has 60. Plano has a surplus of 5 businesses compared to Frisco. (Your numbers may vary.)

    This comparison is based on the combination of all three NAICS codes you chose. You can filter the results by individual code. You'll check to see if Plano has a surplus specifically in juice bars.

  12. Under Summary, click All and choose 72251518 (Juice Bars).

    Juice Bars option under Summary

    The data is filtered on the map and in the Void Analysis pane. According to the results, there are 13 juice bars in Frisco and 11 in Plano, meaning there is a gap of 2 juice bar in Plano. These results indicate that the Plano area might be able to support the opening of a new juice bar, which is promising for your chain.

  13. Filter the results by 72251505 (Coffee Shops) and then by 72251512 (Ice Cream Parlors).

    Plano has 10 more coffee shops than Frisco and a gap of 3 ice cream parlors. Coffee shops are the primary driver of the total surplus. Coffee shops may provide competition for juice bars, so a large surplus of them could potentially diminish the success of a new juice bar in Plano.

  14. Filter the results by All.
  15. Under Top three gaps by Business Name, click View full table.

    View full table

    The Void Analysis pane expands, showing a table with the names of all of the businesses in Frisco and Plano.

    Table showing businesses by name

    Rows highlighted in red represent voids, meaning the business appears in the reference area (Frisco), but not the analysis area (Plano). Rows highlighted in blue represent businesses that appear in both cities.

    Looking at the results by business name may be useful if there are particular brands or franchises that are of interest to your analysis. You can also organize the results by the NAICS code.

  16. Click the All filter and choose 72251518 (Juice Bars).

    The table is filtered to only show juice bar businesses.

    Your void analysis results seem to indicate that Plano has a small gap in juice bars that can be filled by opening a new store. Although juice bar coverage is balanced between the two cities, with 13 juice bars in Frisco and 11 in Plano, there are a large number of coffee shops that might compete and draw away business. However, your analysis results have one major problem: the data is not normalized.

Normalize the results

Normalization is when two values are adjusted to account for differences in scale. For instance, your void analysis indicates that Frisco and Plano have the same number of juice bars, so there does not seem to be a void. However, this analysis does not take into account the population of each city. A city with more people will have more demand for businesses than a city with fewer people.

You'll normalize your results by adjusting the number of juice bars by population. Through this method, you can better compare the two cities.

  1. Above the table, for Normalize results by, click None and choose 2021 Total Population (Esri).

    Normalize results by population

    The table updates to show the populations of the analysis area and the reference area, as well as the difference in population between them. Although Plano has the same number of juice bars as Frisco, it also has over 100,000 more people.

    Void analysis normalized by population

    The normalization results also list the expected number of juice bars in Plano based on its population compared to Frisco. When accounting for population, 18 juice bars are expected, 7 more than the actual total of 11.

  2. Point to the Expected in Analysis Area value.

    Expected in Analysis Area ToolTip

    A Tool Tip appears with the formula for how the expected number of juice bars was calculated. The formula divided Plano's total population by the density of juice bars in the reference area of Frisco. In short, normalization calculated the number of juice bars per person in Frisco, and then multiplied that value by the number of people in Plano.

    You can also normalize the results by other variables. You can pick a variable from the Normalize results by variable, or browse for a variable using the data browser.

  3. For Normalize results by, choose 2021 Total Households (Esri).

    When normalizing results by this variable, Plano is expected to have 21 juice bars, 11 more than it actually has.

  4. Click Minimize table.

    Minimize the table to show the map again

    The table is minimized, showing the map again.

    Note:

    If you want to export your results, click Export in the Void Analysis pane. You can export the results as a table to either Excel or PDF. Including individual business locations in the analysis report uses credits.

    Although there is a balanced number of juice bar business in both areas, normalizing the results reveals that the expected number of businesses in the analysis area of Plano is greater than what the initial analysis showed. These results indicate that Plano is underserved by juice bars compared to Frisco. Your conclusions actually match those made by a real-life juice bar company in the area, which expanded to Plano in summer 2021.

In this lesson, you defined a reference area and an analysis area to compare. Then, you performed void analysis to find out if there were any gaps in juice bar businesses in the analysis area. After normalization, you learned that the analysis area had fewer juice bars than expected, given its population. Ultimately, you provided critical analysis that could be instrumental in the opening of a new location.

Although the workflow you followed in this lesson applies to juice bars in Frisco and Plano, it works just as well with any other business data and any United States location. If you have your own business data, you can also perform this analysis for locations outside of the United States.

You can find more lessons in the Learn ArcGIS Lesson Gallery.