Short answer: a heat map shows a value across two categorical dimensions as a grid of coloured cells, so patterns leap out — the busy Friday-evening cell in taproom sales, the summer band in style seasonality, the account-SKU gaps in distribution. It’s the chart for “where are the hot and cold spots across these two dimensions.” Its honesty lives entirely in the colour scale: choose a sequential scale for magnitude, keep it consistent, show a legend, and never let a rainbow distort the story.
This closes The Brewer’s Chart Field Guide. The heat map is the chart for two categorical dimensions at once — where a bar handles one.
When to reach for it
Reach for a heat map when a value lives at the intersection of two categories and the pattern across the grid is the message. Colour encodes magnitude per cell, so clusters, bands and gaps emerge that a table of numbers would bury.
Use case 1 — Taproom sales by hour × day
The canonical heat map: day of week across, hour down, sales as colour. The Friday-and-Saturday-evening hot block tells you exactly when to staff and run events — the actionable core of a taproom view that a daily total hides.
Use case 2 — Style demand by month (seasonality)
Styles down, months across, volume as colour. Seasonal bands appear instantly — the summer wheat-and-lager heat, the winter stout warmth — guiding brew scheduling and forecasting far faster than twelve separate lines.
Use case 3 — Account × SKU distribution gaps
Accounts down, SKUs across, with colour for volume (or a flag for “stocked / not”). The cold cells are your distribution white space — accounts not buying SKUs they should — a concrete sales intelligence target list.
Where this breaks
The colour scale is everything — use a sequential single-hue scale for magnitude; reserve diverging scales for a real midpoint (above/below target); avoid rainbow, which distorts. No legend, no meaning — always show the scale. Too fine a grid — hundreds of tiny cells overwhelm; aggregate sensibly. Exact values lost — colour is approximate; if readers need numbers, colour the table cells and keep the figures. Accessibility — choose colourblind-safe palettes.
The bottom line
The heat map reveals patterns across two categorical dimensions — hour × day, style × month, account × SKU — by encoding value as colour, surfacing hot spots and gaps a table buries. Choose the colour scale honestly, always show a legend, and aggregate to a readable grid. That completes the field guide; for the charts not covered here — radar, CUSUM, trajectories and Sankey — see the Seeing Your Beer series, and the full index ties them all together.
Frequently asked questions
When should a brewery use a heat map? When you want to see a value across two categorical dimensions at once and spot patterns — taproom sales by hour and day of week, style demand by month (seasonality), or account-by-SKU purchasing. Each cell’s colour shows the value, so hot spots and cold spots emerge from the grid in a way rows of numbers never would.
What makes a heat map misleading? The colour scale. A poorly chosen scale can hide real differences or invent dramatic ones, and rainbow scales distort because colour isn’t perceived evenly. Use a single-hue sequential scale for magnitude (light to dark), a diverging scale only when there’s a meaningful midpoint (above/below target), keep the scale consistent, and always show a legend.
What is the difference between a heat map and a table? A heat map is a table where the cell values are encoded as colour, so patterns across the whole grid are visible at a glance rather than read cell by cell. Use a heat map when the pattern across two dimensions is the message; keep a plain table when readers need exact values. Many tools let you do both — colour the table cells and keep the numbers.