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POST
/
api
/
analyze
{
  "sector": "Grocery Retail",
  "decision_summary": {
    "call": "Cautious underweight",
    "severity": "Moderate",
    "most_exposed": "Discount grocery chains with thin margins",
    "near_term_dynamic": "Food-at-home CPI deceleration provides relief but trade-down behaviour persists"
  },
  "time_horizon": "3-6 months",
  "confidence": "medium",
  "key_drivers": [
    {
      "signal": "Food-at-home CPI",
      "role": "PRIMARY",
      "mechanism": "Persistent inflation erodes volume growth despite nominal revenue stability",
      "impact": "Negative margin pressure"
    }
  ],
  "segment_impacts": [
    {
      "segment": "Premium grocery",
      "impact": "weakening",
      "reason": "High-income cohort showing early signs of trade-down"
    },
    {
      "segment": "Value grocery",
      "impact": "improving",
      "reason": "Benefiting from trade-down flows"
    }
  ],
  "contrarian_factors": [
    {
      "factor": "Wage growth acceleration",
      "effect": "Could restore discretionary grocery spend faster than expected"
    }
  ]
}

​
Authentication

Requires a valid JWT token in the Authorization header. 
Authorization: Bearer <your-jwt-token>

​
Rate Limits

10 requests per 60-second window per authenticated user.

​
Request Body

​
sectorName
string
required
Name of the sector to analyse (e.g., “Grocery Retail”, “Auto Finance”).
​
drivers
array
Array of driver objects providing quantitative context.
​
signals
array
Array of signal objects to incorporate.
​
summary
object
Optional summary context for the sector.

​
Response

​
sector
string
The sector name echoed back.
​
decision_summary
object
High-level decision framework.
​
time_horizon
string
Applicable time horizon for the analysis.
​
confidence
string
Confidence level: low, medium, or high.
​
key_drivers
array
Ranked list of key drivers.
​
segment_impacts
array
Impact assessment by sub-segment.
​
contrarian_factors
array
Factors that could challenge the primary thesis.
cURL
curl -X POST "https://api.consumersignals.io/api/analyze" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "sectorName": "Grocery Retail",
    "summary": {
      "score": 62,
      "change": -3.4,
      "classification": "Moderate Pressure"
    }
  }'
Python
import requests

response = requests.post(
    "https://api.consumersignals.io/api/analyze",
    headers={
        "Authorization": "Bearer YOUR_JWT_TOKEN",
        "Content-Type": "application/json"
    },
    json={
        "sectorName": "Grocery Retail",
        "summary": {
            "score": 62,
            "change": -3.4,
            "classification": "Moderate Pressure"
        }
    }
)
data = response.json()
TypeScript
const response = await fetch(
  "https://api.consumersignals.io/api/analyze",
  {
    method: "POST",
    headers: {
      Authorization: "Bearer YOUR_JWT_TOKEN",
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      sectorName: "Grocery Retail",
      summary: {
        score: 62,
        change: -3.4,
        classification: "Moderate Pressure",
      },
    }),
  }
);
const data = await response.json();

{
  "sector": "Grocery Retail",
  "decision_summary": {
    "call": "Cautious underweight",
    "severity": "Moderate",
    "most_exposed": "Discount grocery chains with thin margins",
    "near_term_dynamic": "Food-at-home CPI deceleration provides relief but trade-down behaviour persists"
  },
  "time_horizon": "3-6 months",
  "confidence": "medium",
  "key_drivers": [
    {
      "signal": "Food-at-home CPI",
      "role": "PRIMARY",
      "mechanism": "Persistent inflation erodes volume growth despite nominal revenue stability",
      "impact": "Negative margin pressure"
    }
  ],
  "segment_impacts": [
    {
      "segment": "Premium grocery",
      "impact": "weakening",
      "reason": "High-income cohort showing early signs of trade-down"
    },
    {
      "segment": "Value grocery",
      "impact": "improving",
      "reason": "Benefiting from trade-down flows"
    }
  ],
  "contrarian_factors": [
    {
      "factor": "Wage growth acceleration",
      "effect": "Could restore discretionary grocery spend faster than expected"
    }
  ]
}