Basics: What Is a Heat Map? Why the Legend Matters

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What is a heat map? A heat map uses color to represent numerical values: in a grid of store orders, one dark Wednesday cell can reveal a rush that disappears in a page of figures. Each colored cell or area ties a measurement to a position, whether that is a calendar day, a geographic location, or a webpage button.

That dark patch is a starting point. Reading it means connecting its position to its value, then asking what produced the difference.

Read the Axes and Legend First

Suppose a store manager sees a dark cell labeled “Sales” and schedules extra packing staff, assuming it means more orders. If the unit is dollars, one expensive purchase could explain the patch. The missing unit has turned revenue into an imaginary workload.

Rows and columns tell you where to look; the legend tells you what you found. Check its endpoints and direction: darker or brighter can mean higher, depending on the scale. Check whether colors change continuously or in bands, too. In a band labeled “50–99,” a store with 50 visitors looks identical to one with 99. Almost twice the traffic. Exactly the same color.

Recognize the Main Types

A matrix compares values at row-column intersections, such as support requests by weekday and hour. Geographic heat maps estimate a density surface from point data. Choropleth maps instead color predefined geographic areas by their values; they are a related visualization, not the same geographic method.

Website maps record behavior. One revealing case is a click hotspot on something that does nothing: in an imagined shop page, visitors repeatedly click a product photograph expecting it to open. The patch could prompt a design fix, not a celebration of engagement. Scroll and pointer maps answer different questions, as the table shows.

Heat map type or related map	What color measures	Best for	Main advantage	Key limitation
Matrix heat map	Cell value, such as monthly revenue ($) by product	Products across months	Shows highs and lows across two categories	Exact values need labels or tooltips
Correlation heat map	Pairwise correlation coefficient; Pearson r ranges from −1 to +1, with 0 at the midpoint	Linear relationships among numeric variables	Summarizes variable pairs	Correlation does not establish causation
Geographic density heat map	Point concentration or weighted density within a chosen radius	Clusters of incidents, stores, or trips	Shows hotspots without administrative boundaries	Radius or bandwidth changes hotspot size and intensity
Choropleth map (related map, not a geographic heat map)	Regional value, such as residents per km²	Rates across counties, states, or countries	Uses meaningful boundaries	Large regions dominate; local differences disappear
Website click heat map	Recorded click count or share by page location	Popular links and noninteractive elements	Shows attempted interactions	Clicks can mean interest or frustration
Website scroll heat map	Percentage of recorded visits reaching each depth	Content or calls to action	Shows declining exposure down a page	Reaching content does not prove reading
Website pointer-movement heat map	Recorded cursor positions or movement density	Desktop mouse-use patterns	Shows activity beyond clicks	Not eye tracking; touch-only visits lack mouse-hover paths, but finger movement can be tracked

Choose Colors That Match the Values

For order counts, a sequential palette such as light-to-dark blue communicates increasing amounts. For gains and losses around zero, use a diverging palette with contrasting ends and a neutral midpoint. That midpoint carries meaning; it is not decoration.

Color can also smuggle in a judgment. Consider a hypothetical executive review where red marks the highest revenue, but a director reads it as a warning and cuts stock at the busiest store. Red-green confusion adds another risk for readers who cannot readily distinguish those hues. Use clear lightness differences and explain whether a color means high, low, favorable, or unfavorable. In a temperature chart, red may simply mean warmer. Keep cell values visible. Shades are not numbers.

Arrange Your Data Before Mapping It

Keep one measure and consistent units in a matrix: revenue in dollars and conversion rates do not belong on the same unadjusted scale. Preserve calendar order for months; for unordered categories, choose the arrangement that serves your comparison.

Data arrangement	Best for	Pros	Cons
Chronological order	Days, months, quarters	Shows seasonality and streaks	Similar periods may be distant; unequal intervals need labels
Natural numeric order	Ages, temperatures, scores	Preserves progression: 18–24, 25–34, 35–44	Unequal band widths can mislead
Alphabetical order	Stores, products, departments	Makes labels easy to find	Neighbors may be unrelated
Ranked by row total	Store purchase totals	Groups high-volume stores	Can hide small-store peaks; period affects ranking
Grouped by category	Stores within regions; products within departments	Supports within-group comparison	Boundaries can obscure similarities
Clustered by value pattern	Similar weekly store patterns	Places similar rows together	Depends on scaling, distance metric, and clustering method; order may change

Ordering brings cells together; missing data can create a false connection between them. A store with no purchases deserves a zero. A store whose reporting system failed needs a distinct neutral fill or “No data” marker explained in the legend. Turning both into zero makes a reporting failure look like a business failure.

Build a Small Example in Excel

Use an imagined bread shop taking preorders during a Wednesday promotion. In Excel for Microsoft 365 on Windows, paste this dataset into A1. All values are orders per day.

Store	Monday	Tuesday	Wednesday	Thursday	Friday
Central	12	18	41	20	15
Riverside	10	14	35	17	13
Market	8	11	29	14	10

Select B2:F4, leaving the headings out. Choose Home > Conditional Formatting > Color Scales and select a two-color scale. Then choose Home > Conditional Formatting > Manage Rules, select the rule and click Edit Rule. Set Format Style to 2-Color Scale. For both endpoints, set Type to Number: use a minimum of 0 with a white fill and a maximum of 50 with a blue fill. Confirm both dialogs. Keep the numbers visible.

For a matching legend, enter “Orders per day” in H1 and 0, 10, 20, 30 and 50 in H2:H6. Apply the same two-color rule, endpoint colors and fixed bounds to H2:H6. Use these bounds for any equivalent grid you want to compare.

Wednesday forms a darker vertical band: every store has its highest count that day. Central’s 41 orders is the grid’s maximum, but not the scale’s upper bound of 50. The promotion is a possible explanation for the shared peak, not something the colors prove.

Check Patterns Before Drawing Conclusions

Suppose the bread shop also stayed open longer on Wednesday. Its higher total now combines extra selling time with the promotion. Orders per opening hour would answer a different question about demand. Geographic incident counts have a similar denominator problem: a busy population center may have more incidents without a higher rate per resident.

Before acting on an unexpected patch, inspect the underlying records. For website maps, compare the same page version and account for mobile versus desktop layouts; the same button may occupy different positions.

Across charts, keep units and scale limits compatible. Otherwise, each chart’s darkest cell can represent a different quantity. Matching colors on mismatched scales create a false comparison.

Key Takeaways

Treat a hotspot as a question worth investigating, not an explanation.
Choose the map type for the measurement, not its appearance.
Make units and color meaning explicit.
Keep missing data visibly separate from zero.
Compare equivalent records on compatible scales before making a decision.

Frequently Asked Questions

Heat maps also turn up in floor plans and warehouse operations. These applications use the same basic encoding, but the measurements differ.

Can you give me some examples of heatmaps?

Examples include a calendar colored by daily exercise minutes and a warehouse grid colored by visits to each storage location. The calendar can reveal routines and gaps, while the warehouse example highlights frequently used areas.

What is another name for a heatmap?

A matrix heat map is also called a color-coded matrix or shaded matrix. “Heatmap” and “heat map” are alternative spellings; names such as correlation matrix and density map refer to particular forms, not interchangeable names for every version.

How do I create a heat map?

Follow the Excel example above, then check the result: Central’s Wednesday cell should show 41 and be darker than its Monday cell showing 12.

What is a Wi-Fi heat map?

A Wi-Fi heat map overlays wireless measurements, such as signal strength, on a floor plan or geographic area to reveal coverage gaps. Survey-based maps use measurements, while predictive maps estimate coverage from access-point placement and building characteristics.

How much does a heat map cost?

The spreadsheet example needs no separate heat-map service if you already have Excel. For website analytics or a Wi-Fi survey, first specify which service you need; they are different purchases.

Start With One Clear Comparison

Test the finished bread-shop heat map with someone who has not read these instructions. Ask: “When does each store receive the most orders, and how many does Central receive that day?” They should identify Wednesday and 41 orders. If they cannot, check the labels, legend and number visibility before adding more data.