Tracksuit measures how real people think and feel about brands. Every month, thousands of consumers across multiple markets answer short surveys about the brands they know, would consider, use, and prefer. Respondents are nationally representative, matched to each market's population by age, gender, and region, so the data reflects the real world, not just a narrow slice of it.

Responses are cleaned and weighted, then turned into the metrics you see in the API: simple percentages (e.g. “68% of people in this category are aware of your brand”). Data refreshes monthly.

Tracksuit measures brand health through a funnel of consumer sentiment. Every metric is a percentage of people in the category, returned as a decimal between 0 and 1 (0.68 = 68%).

API value: UNPROMPTED_AWARENESS

The share of people who can name your brand without prompting.

Survey question: “Thinking about different [category brands], which ones come to mind?” Respondents see an open text field and type in any brands in the category they can think of.

Not every tracker includes this. It's a paid add-on, so if your subscription doesn't have it, it won't appear in the API response.

API value: PROMPTED_AWARENESS

The share of people who recognise your brand when shown its name and logo. This is the top of the standard funnel.

Survey question: "Which of the following [category brands] have you heard of?" Respondents see a list of brands with logos and select all they've heard of.

API value: CONSIDERATION

Of the people aware of your brand, how many would consider buying or using it?

Survey question: "Which of the following [category brands] would you consider buying?" Multiple select.

API value: INVESTIGATION

Whether someone has actively looked into your brand. Only used in service or high-involvement categories (insurance, banking, automotive) where the purchase journey involves research. If your tracker doesn't include it, it won't appear in the API.

Survey question: "Which of the following [category brands] have you actively looked into or researched?" Multiple select.

API value: USAGE

The share of people who've recently bought or used your brand. This is claimed usage, not sales data.

Survey question: "Which of the following [category brands] have you used in the last week?" Multiple select.

API value: PREFERENCE

Your brand's share of first-choice picks. The only single-select question in the survey, making it a strong signal of loyalty.

Survey question: "Which is your preferred brand?" Single select.

Endpoint: /v2/category-views/{id}/media-consumption

Where people in your category spend their media time. Returns a ranked list of channels with percentage of respondents who selected each one. Unlike the funnel, this isn't a timeline. You get one aggregated data point per channel for the period you request.

Each channel in the response includes a rank field (its position by consumption within the category) and a value object with the same percent, weight, and base_weight structure as the funnel.

Survey question: "In the past month, which of the following media channels have you used, read, seen, or listened to?" Multiple select.

Percent (value.percent): the metric value as a decimal (0–1). Multiply by 100 for display, or format as a percentage in your BI tool.

Weight (value.weight): weighted count of positive responses (numerator). Adjusted for demographic imbalances in the sample.

Base Weight (value.base_weight): total weighted base (denominator). Percent = weight ÷ base_weight. Useful for aggregating over time: sum the weights and base_weights, then divide. Don't average percentages directly. Sample sizes vary by month.

Sample (sample): every data point includes a sample object with two fields:

The funnel endpoint accepts a minimum_indicator query parameter (default: DIRECTIONAL). This filters out data points below the specified quality threshold before they reach your response. Set it to RELIABLE for only high-confidence data, or INSUFFICIENT if you want everything and will handle quality filtering yourself.

Also known as “rolling averages” in the dashboard.

​API parameter: smoothing

Controls the rolling average window. Any value from "1mo" to "12mo" / "1y".

Don't compare 1mo data as though it has the same precision as 3mo.

Slice data by age, gender, region, income, household status, etc. Available filters depend on your category view and geography. Call GET /v2/category-views/{id} to check.

Combining filters: Selecting across types (age 18–24 + Female) gives the intersection. Selecting within a type (18–24 and 25–34) expands the group.

A specific Category × Geography combination (e.g. "Beer in Australia"). Equivalent to the account picker in the dashboard.

A category view also includes your account's configuration: which competitor brands are tracked, what statements are available, which extra demographics are enabled, and so on.

Call GET /v2/category-views/{id} to see the full metadata for a given view.

Start with GET /v2/category-views to list your available views. The id from that response is used in every other endpoint.

Token-based. Each response includes a next_token field.

If next_token is not null, pass it as next_token in your next request to fetch the next page. When next_token is null, you've reached the last page.

All dates use ISO 8601 format (e.g. 2026-03-01). Always use the first day of the month. Tracksuit data is collected monthly, so mid-month dates will be snapped to the nearest period boundary.

start_period is inclusive. end_period is inclusive.

An individual brand tracked within a category view (e.g. "Corona" within "Beer in Australia"). This includes your own brand(s) and the competitors in your tracker. Funnel metrics are calculated per brand, per category view.

A period of data collection, aggregated monthly. Tracksuit surveys continuously, and data is rolled up into monthly waves. When you request data with smoothing=3mo, each data point pools three consecutive waves.