Policy Impact Preview

POST /api/v1/contact-policies/impact-preview

Previews the customer impact of a proposed contact policy configuration. Samples customers from recent interaction history and simulates how many would be affected by the proposed frequency cap.

Request Body

Field	Type	Required	Description
`policyType`	string	Yes	Policy type identifier
`scope`	string	No	Scope: `global`, `offer`, `category`, or `channel` (default: `global`)
`scopeId`	string	No	ID of the scoped entity (required when scope is `offer`, `category`, or `channel`)
`config.maxFrequency`	integer	Yes	Maximum allowed contacts per period (minimum: 1)
`config.periodDays`	integer	Yes	Lookback period in days (1-365)
`config.outcomeType`	string	Yes	Interaction type to count (e.g., `impression`, `click`, `convert`)
`sampleSize`	integer	No	Max customers to analyze (100-10000, default: 1000)

Example

curl -X POST https://playground.kaireonai.com/api/v1/contact-policies/impact-preview \
  -H "Content-Type: application/json" \
  -H "X-Tenant-Id: my-tenant" \
  -d '{
    "policyType": "frequency_cap",
    "scope": "channel",
    "scopeId": "ch_email",
    "config": {
      "maxFrequency": 3,
      "periodDays": 7,
      "outcome": "impression"
    },
    "sampleSize": 2000
  }'

Response

{
  "totalCustomersAnalyzed": 2000,
  "customersAffected": 420,
  "affectedPercent": 21.0,
  "offersSuppressed": {
    "Platinum Card Upgrade": 85,
    "Auto Loan Refinance": 62,
    "Savings Account Promo": 45
  },
  "avgOffersBeforePolicy": 4.2,
  "avgOffersAfterPolicy": 2.8,
  "topAffectedSegments": [
    { "segment": "High Value", "affected": 180, "total": 500 },
    { "segment": "Active Traders", "affected": 95, "total": 320 }
  ]
}

Response Fields

Field	Type	Description
`totalCustomersAnalyzed`	integer	Number of customers in the sample
`customersAffected`	integer	Customers who would hit the frequency cap
`affectedPercent`	number	Percentage of analyzed customers affected
`offersSuppressed`	object	Map of offer names to suppression counts
`avgOffersBeforePolicy`	number	Average contacts per customer before the policy
`avgOffersAfterPolicy`	number	Average contacts per customer after the policy
`topAffectedSegments`	array	Segments most impacted (sorted by affected count)

Use this endpoint before creating a contact policy to understand which customers and offers will be impacted. High affectedPercent values may indicate the policy is too restrictive.

Roles

admin, editor See also: Contact Policies | Policy Conflicts

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Policy Impact Preview

POST /api/v1/contact-policies/impact-preview

Request Body

Example

Response

Response Fields

Roles

​POST /api/v1/contact-policies/impact-preview

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POST /api/v1/contact-policies/impact-preview

Request Body

Example

Response

Response Fields

Roles