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Introducing the Business and Consumer Confidence Endpoints

FXMacroData now exposes business and consumer confidence endpoints with country-specific handling, so traders can compare survey tone without flattening the real differences in methodology, frequency, and units across markets.

Introducing the Business and Consumer Confidence Endpoints

By FXMacroData Team
Published on June 6, 2026

FXMacroData now includes dedicated endpoints for business confidence and consumer confidence, giving traders and analysts a cleaner way to track how firms and households are responding to the macro cycle. These series are useful because confidence often moves before harder data such as spending, hiring, or capital expenditure, especially when markets are trying to decide whether a slowdown is temporary or becoming broad-based.

The important point, though, is that confidence data is not globally standardized. A confidence print in the euro area is not measured the same way as one in Canada or Japan, and in some countries the nearest equivalent does not even use the same endpoint slug. That is exactly why these new endpoints matter: they preserve the country-specific structure instead of pretending every survey can be read on a single universal scale.

What changed
FXMacroData now exposes country-level confidence series where official or stable survey coverage exists, with metadata that keeps the local reporting standard intact: frequency, unit, source, and availability all remain market-specific.

What’s New

The new release adds confidence-series coverage in a way that is actually useful for macro work:

  • Separate household and business lenses: consumer and business surveys can diverge sharply around growth shocks, inflation squeezes, and credit slowdowns.
  • Country-specific metadata: the endpoint keeps the local unit and frequency rather than forcing everything into an artificial composite score.
  • Cleaner release monitoring: traders can track confidence alongside the release calendar and link soft-data shifts to upcoming central-bank decisions.
  • Natural integration with pair analysis: confidence data can sit next to hard data when you are framing moves in EUR/USD, USD/CAD, or USD/JPY.

Why Reporting Standards Matter

This is the main interpretive trap with confidence data. In the euro area, both series are monthly balance indicators published by the European Commission and are best read as diffusion-style sentiment gauges. In Canada, the comparable business and consumer series are quarterly balance surveys, which makes them slower-moving and more strategic. In Japan, the current confidence coverage is consumer-focused and reported as an index, while the business side is better captured through other survey structures rather than the same standardized endpoint family.

That means a move from -14 to -11 in a euro-area balance series is not directly comparable to a quarterly shift in a Canadian balance survey, and neither should be read the same way as a Japanese index level. The data still belongs in the same research stack, but not in the same mental spreadsheet cell.

The same point applies to the United States. The US macro conversation is often framed through consumer sentiment and business sentiment rather than the exact business-confidence or consumer-confidence labels used elsewhere. That is not a gap in meaning so much as a difference in survey architecture and publishing convention.

Why It Matters for Traders

Soft data matters most when price is trying to anticipate the next hard-data turn. If euro-area consumers are stabilizing while firms remain cautious, that can imply a different growth mix than a broad rebound in both surveys. If Canadian business confidence deteriorates while the Bank of Canada is already leaning dovish, the survey can help explain why rate expectations are shifting before GDP confirms it. If Japanese households weaken again while the Bank of Japan is navigating a fragile normalization path, the confidence story can matter for domestic demand expectations even when headline inflation remains the bigger market driver.

For FX, that means confidence data is usually not a trade trigger by itself. It is a regime-confirmation tool. It helps answer whether a surprise in retail sales, inflation, or employment fits a broader macro tone or looks isolated.

Practical Example 1: Comparing Euro-Area Consumer and Business Confidence

Suppose you want to know whether a softer euro move reflects a genuine deterioration in internal demand or only a temporary headline shock. The first step is to inspect both household and corporate survey tone together rather than relying on one print.

curl "https://fxmacrodata.com/api/v1/announcements/eur/consumer_confidence?api_key=YOUR_API_KEY"
curl "https://fxmacrodata.com/api/v1/announcements/eur/business_confidence?api_key=YOUR_API_KEY"

A representative response snapshot could look like this:

{
  "consumer_confidence": {
    "currency": "EUR",
    "indicator": "consumer_confidence",
    "data": [
      {
        "date": "2026-03-01",
        "val": -13.8,
        "announcement_datetime": 1774000800,
        "announcement_datetime_local": "2026-03-20T11:00:00+01:00"
      },
      {
        "date": "2026-04-01",
        "val": -13.1,
        "announcement_datetime": 1776938400,
        "announcement_datetime_local": "2026-04-23T12:00:00+02:00"
      },
      {
        "date": "2026-05-01",
        "val": -12.4,
        "announcement_datetime": 1779444000,
        "announcement_datetime_local": "2026-05-22T12:00:00+02:00"
      }
    ]
  },
  "business_confidence": {
    "currency": "EUR",
    "indicator": "business_confidence",
    "data": [
      {
        "date": "2026-03-01",
        "val": -10.0,
        "announcement_datetime": 1774000800,
        "announcement_datetime_local": "2026-03-20T11:00:00+01:00"
      },
      {
        "date": "2026-04-01",
        "val": -9.0,
        "announcement_datetime": 1776938400,
        "announcement_datetime_local": "2026-04-23T12:00:00+02:00"
      },
      {
        "date": "2026-05-01",
        "val": -8.0,
        "announcement_datetime": 1779444000,
        "announcement_datetime_local": "2026-05-22T12:00:00+02:00"
      }
    ]
  }
}

The interpretation is not that both values are “low” in some absolute global sense. The interpretation is that both balance measures are becoming less negative at the same time. For a trader watching the European Central Bank, that can matter because improving sentiment breadth may reduce pressure for an aggressively dovish read, even before the harder activity data turns.

Practical Example 2: Reading Canada and Japan on Their Own Terms

Now imagine you are comparing North American and Asian demand signals. Canada currently offers a business-confidence series that reflects the slower quarterly survey cadence of the local reporting framework, while Japan’s current endpoint coverage is cleaner on the consumer side.

curl "https://fxmacrodata.com/api/v1/announcements/cad/business_confidence?api_key=YOUR_API_KEY"
curl "https://fxmacrodata.com/api/v1/announcements/jpy/consumer_confidence?api_key=YOUR_API_KEY"

A plausible normalized response might look like this:

{
  "cad_business_confidence": {
    "currency": "CAD",
    "indicator": "business_confidence",
    "data": [
      {
        "date": "2025-10-01",
        "val": -1.8,
        "announcement_datetime": 1760452200,
        "announcement_datetime_local": "2025-10-14T10:30:00-04:00"
      },
      {
        "date": "2026-01-01",
        "val": -3.1,
        "announcement_datetime": 1768923000,
        "announcement_datetime_local": "2026-01-20T10:30:00-05:00"
      },
      {
        "date": "2026-04-01",
        "val": -2.4,
        "announcement_datetime": 1776177000,
        "announcement_datetime_local": "2026-04-14T10:30:00-04:00"
      }
    ]
  },
  "jpy_consumer_confidence": {
    "currency": "JPY",
    "indicator": "consumer_confidence",
    "data": [
      {
        "date": "2026-03-01",
        "val": 38.7,
        "announcement_datetime": 1775624400,
        "announcement_datetime_local": "2026-04-08T14:00:00+09:00"
      },
      {
        "date": "2026-04-01",
        "val": 37.9,
        "announcement_datetime": 1778302800,
        "announcement_datetime_local": "2026-05-09T14:00:00+09:00"
      },
      {
        "date": "2026-05-01",
        "val": 38.2,
        "announcement_datetime": 1781067600,
        "announcement_datetime_local": "2026-06-10T14:00:00+09:00"
      }
    ]
  }
}

The trader takeaway is straightforward. Canada’s quarterly business survey is better for judging broader corporate caution around investment and hiring. Japan’s monthly consumer index is better for tracking household pulse and whether domestic demand is recovering or stalling. Both matter, but they answer different questions on different clocks.

What These Endpoints Actually Improve

  • Less false comparability: the API preserves whether a series is an index or a balance measure.
  • Better timing awareness: monthly and quarterly confidence surveys should not be mixed without context.
  • Cleaner central-bank framing: confidence moves can be assessed alongside communication from the Federal Reserve, the ECB, the BoC, and the BoJ.
  • Faster cross-country research: you can query what exists market by market instead of guessing whether a local survey maps to a global label.
Bottom line
Confidence data is most useful when it keeps its local meaning. The new endpoint family is designed to expose that information cleanly, not flatten it.

Get Started

You can start with the documentation for EUR consumer confidence, EUR business confidence, CAD business confidence, and JPY consumer confidence. If you work across markets, pair those with the relevant dashboard view and central-bank press-release page before drawing any cross-country conclusion.

The new coverage is built for comparative macro work, but it is built with a strict rule: comparable does not mean identical. That is the right way to read confidence data, and now it is the way the API exposes it too.

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Introducing Business And Consumer Confidence Endpoints
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Last Updated
2026-06-10 14:15 UTC

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