Recommend sending time

POST

https://api.mpc.dev.placewise.com/v2/ml/sending/recommend_time

API Permit:ML:Sending:KPIPrediction

API Context:Loyalty Club

Authorizations:UserToken

Recommends sending date and time in a given time frame. Prediction is made for each hour in the given range, and the best one is also explicitly returned. Version v2, with upgraded models.

Warning: combination of "sms" channel and "open_rate" KPI is not supported.

Text should be as shown to the end user, without any HTML.

Example

When successful, returns:

{
  "predictions": [
    {
      "timestamp": "2025-01-01 01:00:00",
      "prediction": 0.01
    },
    {
      "timestamp": "2025-01-01 02:00:00",
      "prediction": 0.05
    },
    ...
  ],
  "best_prediction": {
    "timestamp": "2025-01-01 05:00:00",
    "prediction": 12,34
  }
}

Request

Header Params

Body Params application/json

Examples

Responses

🟢200Success

application/json

Body

Request Example

Shell

JavaScript

Java

Swift

curl --location --request POST 'https://api.mpc.dev.placewise.com/v2/ml/sending/recommend_time' \
--header 'X-User-Agent: ApiDog' \
--header 'X-Product-Name: default' \
--header 'X-Loyalty-Club-Slug: infinity-mall' \
--header 'X-Customer: 447' \
--header 'Authorization: Bearer ' \
--header 'X-Client-Authorization: ' \
--header 'Content-Type: application/json' \
--data-raw '{
    "channel": "email",
    "kpi": "ctr",
    "community_id": 3433,
    "text": "Canis acervus maxime trepide conculco strues. Calco placeat ipsam tibi.",
    "campaign_window": {
        "start": "2026-04-15T00:00:00",
        "end": "2026-04-29T00:00:00"
    },
    "search_window": {
        "start": "2026-04-13T00:00:00",
        "end": "2026-04-17T00:00:00"
    },
    "daily_sending_window": {
        "start": "08:00:00",
        "end": "21:00:00"
    }
}'

Response Example

{
    "predictions": [
        {
            "timestamp": "2022-11-09T16:25:58.099512Z",
            "prediction": 0
        }
    ],
    "best_prediction": {
        "timestamp": "2022-11-09T16:25:58.099512Z",
        "prediction": 0
    }
}

Explain Sending Popularity Prediction

Detect receipt fraud

Recommend sending time

Example#

Request

Responses

Example