Across a network of stores or branches, you need to know whether customers can get a particular service where they live or work. A customer may be close to a branch that lacks the equipment for that service. The question is what the locations operating today can provide.
That review helps your operations team decide which customers need follow-up and where changes to the network deserve attention.
Define coverage for the service you mean
Write down the coverage question before you build the map. You might need to find customers more than a certain number of miles from a store, prospects outside a driving area, or addresses outside an assigned region. Each question calls for a different layer. A circle measures straight-line proximity. A drive-time area models road access. An assigned territory records a boundary your business uses.
Choose the threshold your team uses. If stores serve customers who make quick local trips, a broad radius may count people who would never use them. A destination business may draw customers from farther away. Wisconsin Extension's trade-area guidance makes this distinction because the purchase and the travel behavior matter to the area you draw.
Keep a short definition with the analysis. Include the service, threshold, demand period, and whether coverage means proximity or confirmed availability. The people reviewing the result need to know what would cause an address to fall outside it.
Your location file should have a Branch ID, address, status, and service fields. Add operating dates when the network has changed during the demand period. Keep customer or prospect IDs in the demand file, along with the location where service is needed. A billing office in another city can send the investigation in the wrong direction.
Use a Type column to distinguish branch rows from demand rows. If you want to compare demand by value, include a numeric field with a stated meaning, such as orders during the selected period. Keep its units clear. Annual revenue and monthly visits should remain separate measures.
Map the active network and eligible demand
Prepare one headered table with consistent columns for the records you want to map. Give each branch and demand record its own ID. Retain planned and closed locations if they're useful for comparison, but mark their status clearly. A column identifying eligible coverage origins can help you select the right branch group without treating every imported address as a starting point.
In Maptive, choose Create New Map, enter a name, and click Continue. Under Your Data, use Add File or drag in the file, then select Map Now. Check the location-column matches if prompted. In Categorize Data, address information belongs in Section 1, while titles and contact information belong in Section 2. Click Done after correcting the matches.
Inspect the placement of the branches first. An incorrect branch address changes the area you draw around it, which can affect many demand records. Then check demand addresses near the likely coverage edges and any points far from the rest of the dataset.
Open Map Tools and the Grouping Tool / Colored Pins Tool. Select Type as the Primary Group so you can tell branches from customers or prospects. The groups get different marker colors. Use the group controls to inspect the network and demand separately as you check the file.
For a narrower review, open the Filter Tool. Select Create Filters on first use, or the gear when filters already exist. Choose Group for categories such as status or service, and Date for a defined period. Confirm that the resulting demand matches the question you wrote down.
Take care with a mixed table. A demand filter can also hide branch rows that don't have a customer date or service value. Select your active origins deliberately, then check the area instances and active filters before collecting results. You want a service-specific demand view and the correct branch coverage on screen together.
Build comparable coverage areas
Draw distance circles for the active locations
Use Map Tools, then Distance Radius Circles. Enter the branch address in Starting Location, set the distance in Proximity Within, and choose miles or kilometers. Add the circle with Add Proximity Radius. You can also open a branch marker's tools and choose Add Radius.
For several branches using the same rule, use Apply To, select Group, choose Select Group Column, then Select Group. Select the group containing your eligible active branches and click Add Proximity Radius. Check that the selected group contains origins only. Customer rows accidentally included in that group would create customer-centered circles and change the meaning of coverage.
Use the same units and threshold across comparable branches. Click a circle to inspect its included location count and metrics. If the dataset mixes branches with demand, the raw location count can include both. Use a prepared numeric demand field and Customize Metrics when you need a customer-only measure, and reconcile it against the source file.
Circle overlaps are expected where branches are close. Keep them readable with restrained colors and opacity. To revise an instance, open its three-dot menu, select Edit Proximity, change the values, and Save. A change to the threshold should be recorded before you compare that result with another version.
Inspect road-based reach when needed
Choose the Drive Time Polygon Tool when road access is central to the question. These areas assume perfect driving conditions and exclude current and historical traffic. Use them to screen reach, then check real travel conditions where the result affects service promises.
Enter a branch address, set the hours or minutes, and choose Add Drive Time Polygon. You can start from a marker's right menu as well. Repeat this for the eligible branches you need to test. Name the areas so reviewers can connect each one with its branch.
A road-based area can help you inspect customers across a river, around a mountain, or beyond a limited crossing. Zoom in around the edges and check specific addresses rather than reading only the overall shape. If a customer is inside the model but local staff report difficult access, keep that exception in the review file. Use Edit Proximity and Save for changes to travel time or appearance.
Export the demand outside coverage
For a network of distance circles, open Export File to collect results across the areas. Choose your file format and select All Markers outside the Results. Review the remaining export options, including the distance basis, then click Export Now. Export Locations from one circle answers a different question because it collects that circle's records.
Open the exported file and check its Type values before counting customers. Planned branches, closed branches, and other reference locations may be outside the circles too. Keep those rows separate from the customer or prospect records you meant to investigate.
Check the IDs against the eligible demand file. If an address appears more than once because the source contains several transactions, decide whether the result should count transactions, customers, or service locations. For unique-customer coverage, each eligible customer ID needs to count once. Preserve legitimate separate service locations if those are the unit your network serves.
Avoid adding the included counts from all the circles to get network coverage. A customer inside two circles contributes to both local counts. The export options can include each row once for the closest circle when you're collecting included records. That gives you a way to reconcile unique demand with branch-level results without adding overlapping totals.
Calculate a coverage percentage in your spreadsheet if you need one. Divide unique eligible records inside the selected coverage by all eligible records from the same period. Keep unmapped or unresolved addresses in a separate category so they aren't removed from the denominator without being accounted for. State how you handled them beside the percentage.
The outside list describes your supplied demand and chosen threshold. It doesn't count every person without service in the region. Keep the export date, active branch list, filters, and reach rule with the file so another person can repeat the check.
Decide which gaps deserve attention
Check the data before the opportunity
Begin with the outside records, then look at the surrounding geography. Empty land on the map could have little demand. It could also reflect incomplete customer data, a natural barrier, or a market where you haven't collected prospects. A large blank shape alone doesn't establish the need for a branch.
If the demand file has a useful numeric weight, inspect how much demand is outside coverage as well as how many records are outside. A small group of frequent service locations can deserve more attention than a larger group with little activity. Use the same measurement period for both.
For a wider view, the Heat Mapping Tool can show Marker Density or Represents Numerical Data using a numeric-only column. Keep the meaning of the selected view with the map. Density shows where supplied rows concentrate. A numerical heat map weights those locations by the value you've selected.
You can also add population context with the Boundary Tool. Choose a Boundary Set, select Demographic Census Data, choose the Demographic Group and Fill Data, then Load Boundaries. Check the selected measure and its period before comparing it with customer demand. Residents and known customers are different populations.
Review Ignore Filters and Hide Areas W/O data in Boundary Settings. A fill that ignores your current filters can describe a different dataset from the pins. Hidden no-data areas can remove precisely the blanks you're trying to inspect.
Check actual service availability
Give the operations team a manageable subset of the outside records. Review service requirements, customer requests, branch capacity, and access problems with the people who handle them. Ask whether the gap calls for a new location or whether changes to hours, staffing, mobile service, or a partner could meet the need.
For the reviewed subset, use Export Data and Export Filtered Data, choose the format, and click Export Now. Include IDs and the fields that explain the proposed follow-up. Assign someone to confirm availability for the highest-priority records, with a date for checking the answer. Their findings become the next update to the coverage file.
