Your sales report ties revenue or units sold to particular customer locations. You want to know where those sales concentrate across the area you serve. A few locations with large sales values may account for much of an area's recorded sales. Several customer addresses close together may have smaller sales amounts.
Choose the sales measure before mapping
Use a consistent row meaning
Start with the sales question you need to answer. Revenue from the last quarter, units sold this year, and lifetime account value describe different things. Choose one measure and one date window, and use them throughout the list.
Decide whether each row represents a customer or a transaction. A customer-level file can have one row per location with that location's sales total for the chosen period. An invoice file can include several transactions at the same address. Both can represent sales, but the invoice rows can't also be treated as a count of unique customers.
Retain a stable customer or location ID and the address used for the analysis. If you need to study where products are delivered, a headquarters billing address can give you the wrong geography. Use the address that describes the activity behind the sales figure.
Check for accidental repeated transactions before adding values together. Multiple invoices from one customer can be legitimate. The same invoice imported twice adds revenue twice. Keep the record identifiers you need to tell those cases apart, and total the selected sales measure in the source file before uploading it.
Make the sales column numerical
The column selected for numerical heat mapping must contain only numerical values. Check that the cells contain numbers rather than text that happens to look like a number. Currency labels, notes, and inconsistent exports deserve attention before the map is built.
In Excel, select affected cells and use the warning menu's Convert to Number option when it appears. The VALUE function is another way to convert numerical text. Once the conversion is complete, compare the total with the original sales report so you know the change didn't alter the measure.
Keep postal codes as text. They identify locations and may need leading zeros, while sales values need to work as quantities. Those columns have different jobs even when both contain digits.
Resolve blanks and unusual entries in the source. A blank can mean missing data rather than zero sales. A refund or adjustment may need a decision under the measure you've chosen. Don't replace every questionable entry with zero just to finish the import. Make the source consistent with the question, then reconcile its total again.
Create the sales heat map in Maptive
Import the prepared location and sales file into Maptive and check that the locations are plotted where you expect. Then build the numerical surface in this order.
- Open Map Tools.
- Choose Heat Mapping Tool.
- Select Represents Numerical Data as the heat map style.
- Under Numerical Data, choose the sales column you prepared.
- Choose All Markers in Data or Specific Group.
- Click Add Heat Map.
Use All Markers in Data for the full imported sales set. With Specific Group, select the category column and the value that identifies the records you want. That can help you look at one sales team or customer segment while preserving the same sales measure.
Check the group labels in your file before using them to select a sample. Two spellings for the same team can split records that belong together. Confirm the selected group's sales total in the source so you know what the surface is meant to represent.
The other heat map style is Marker Density. It gives locations equal weight and answers a count-based question. For a map of sales numbers, keep Represents Numerical Data selected. A dense set of small accounts and a smaller set of high-value accounts can produce different patterns under the two styles.
Adjust the heat map for the question
Set radius and intensity
Adjust the radius after you generate the heat map. A wider radius spreads each location's contribution across more space and can join nearby patches. A smaller radius keeps the view more local. Choose the scale that fits the geography you need to discuss.
Keep the input fixed while you try a different radius. That lets you see which changes come from the display setting. If two patches join when you widen the radius, the customers haven't moved and their sales haven't increased. The surface has changed how it displays their contributions.
Review the intensity threshold too. A high-value location can dominate the color pattern, so trace a strong patch back to the records before judging the surrounding area. Confirm whether the color comes from several locations or one large sales value.
Color intensity doesn't establish statistical significance. Use it to find concentrations worth inspecting, and use the sales records to explain them. Keep the chosen radius and intensity threshold with your analysis notes if you need to recreate the view later.
Keep pins and background readable
Set the opacity so you can read the heat surface alongside the geography beneath it. If the fill hides streets or place names you need, reduce it. If the surface is hard to see, adjust it while keeping the background readable.
You can change the colors and use Gradient to switch between a multicolor and single-color display. Pick a display whose meaning you can explain. Changing colors can improve readability, but it doesn't change the sales values contributing to the surface.
Use the marker toggle to hide the pins when you want to inspect the heat pattern without marker clutter. Bring the pins back when you need to examine the locations behind a patch. Check the view at the zoom level you'll use in the review, and record the appearance settings with the measure and period.
Decide whether filters should change the surface
Make the filter behavior part of the analysis. If the surface should follow the markers being filtered, leave it linked to the other tools and check the result after applying a filter. If you want a fixed sales surface while exploring a subset of pins, select Unlink From Other Tools.
An unlinked surface can stay in place while the visible marker set changes. That is useful when you want to compare a team or segment with the full sales pattern. It also requires care when explaining the map. The visible pins and the heat surface may now represent different sets of records.
Test the behavior before presenting the view. Apply a filter that gives you a clearly different marker set, then inspect whether the heat changes as intended. Keep the scope of the surface clear alongside the filtered pins.
You can create more heat maps by repeating the build. Use the eye icon to hide a surface and the trash icon to remove it. When comparing surfaces, keep the measure, date window, radius, and other settings consistent unless the difference itself is what you want to study.
Check what the sales pattern says
Inspect at least one strong patch against the source records. Confirm the locations, sales values, and selected group behind it. Check an area with little heat too. It may have few sales, missing location records, or customers outside the sample you've selected.
A raw sales surface describes where your recorded sales occurred. It doesn't establish untapped demand or a conversion rate. An area with little heat needs more market evidence before it becomes an expansion recommendation. If you need a rate, prepare a properly defined rate column with a suitable denominator before mapping that measure.
Use boundary fill when the question needs an exact regional total. Open Geographic Boundary, select a numerical fill and the sales column in Fill Data, choose Sum, and click Load Boundaries. Average, Max Value, and Min Value answer other numerical questions. Keep the reconciled source measure, selected group, and display settings together with the final heat-map view.
