AI search heatmaps: compare brands, models, topics, and countries

Visibility reports tend to give you averages. Your brand appears in 34 percent of tracked answers, say, and that number goes up or down from week to week. It is a fine headline and a poor guide to action, because averages hide the cells where you are strong and the cells where you are invisible.

A heatmap fixes this by laying two dimensions on a grid and coloring each cell. This guide explains how to read one, which pairings answer which questions, and what to look for when comparing tools.

What a heatmap shows

Pick two dimensions, one for the rows and one for the columns. Each cell is the score for that row and column combination, shaded from weak to strong. Your eye finds the pattern before your brain reads a number: a dark stripe across a row, a pale column, one hot spot in a corner.

The power is in the choice of axes. The same data answers different questions depending on what you cross.

Which pairs answer which questions

Brands by topic. Which topics does each competitor own? This is the classic competitive view. A row of pale cells for you against a dark row for a rival tells you where to write.

Brands by model. Does a competitor do well in one AI engine and poorly in another? Engines draw on different sources, so a gap in one model often points to a source problem rather than a content problem.

Models by topic. Where are you strong in ChatGPT but weak in Gemini, or the reverse? This helps you prioritize which engine's sources to work on.

Brands by country. Where do you lead and where are you absent? Useful for a company deciding which market to build next.

Topics by country. The same topic can behave differently across markets, and this shows it.

Do not try to read every pairing at once. Start with the question, then choose the axes.

Reading the grid honestly

A few habits keep a heatmap from misleading you:

1. Check the sample behind each cell. A cell built from three responses is noise. Look for the volume before acting.
2. Hold the period steady. Compare the same date range across views, or you will blame a topic for a seasonal swing.
3. Choose one metric per view. Visibility, sentiment, position, and share of voice tell different stories. Mixing them in your head makes the colors meaningless.
4. Look for the stripe, not the spot. One odd cell is rarely meaningful. A whole row or column that is pale usually is.
5. Follow up with the underlying answers. The heatmap tells you where to look. The responses tell you what to change.

Our guide on prompt visibility heatmaps, brand aliases, and the Brand Book goes deeper on the set-up that keeps the cells accurate, including how brand aliases decide what counts as a mention.

What to ask when comparing tools

• Can I choose both axes, or is the heatmap fixed to brands by prompts?
• Which metrics can color the cells?
• Can I put the heatmap on a shared dashboard and in a PDF report?
• Can it cross in dimensions like country or persona?

Our directory notes that Uberall GEO Studio reports share of voice, citations, and brand traits by persona, location, and competitor, which covers some of the same cuts, though the entry does not call it a heatmap. For the other competitors, the entries do not describe a two-axis heatmap, so treat that as unknown and test in a trial.

Where Promptwatch fits

Promptwatch has a general heatmap, introduced in the October 8, 2026 changelog. Per the changelog, you can put brands, models, topics, or countries on either axis and color the cells by visibility, sentiment, position, or share of voice. You switch the axes with one click, and your choice of axes and metric is remembered.

Where it lives is as useful as what it does. The heatmap is available on monitor pages, as a custom dashboard widget, and in PDF reports. So you can use it for exploration on a monitor, pin it to a dashboard for a monthly review, and include it in a scheduled report. Several related features extend it:

• Personas as an axis. As of the October 23 changelog, personas are a heatmap axis, so you can compare how different buyer types see you. A persona radar is also a dashboard widget and a PDF section. Our post on persona stacking covers how to set the personas up.
• Topics page. Since October 26, Topics has its own page under Trends with Visibility, Citation Share, Avg. Position, Share of Voice, and Sentiment per topic, with By Competitor and By Rank views.
• Clean grids. Heatmaps hide models that no monitor still tracks, so you do not get empty columns.

Why we rank it first for this job: the heatmap is connected to the rest of the platform. When a cell is pale, the next step is to open the responses, check which pages get cited, and look at whether crawlers reach your content. Those steps are in the same product, and the Action Board can turn the finding into a task. The tradeoff is that you need volume for a heatmap to mean much, so a tiny prompt set will give a thin picture on any tool.

A first heatmap routine

1. Start with brands by topic, colored by visibility, over the last 30 days.
2. Find the stripe. Which topic is pale for you and dark for a competitor?
3. Switch the columns to models. Is the gap in every engine or in one?
4. Open the answers behind the cell. Read what the engine says and which sources it cites.
5. Create one task. A page to write, fix, or earn a mention for.
6. Pin the view to a dashboard and check it monthly.

That sequence turns a colorful chart into a short, specific to-do list, which is the only reason to look at a heatmap in the first place.