Valuation Predict

Generate market accurate predictions for vehicles.

Overview

The Valuation API can be used to determine new vehicles' present retail and trade values and their residual values. Read more about our valuation methodology or how we use confidence score on our responses.

Value a vehicle using an AutoGrab ID

post

Value a vehicle using an AutoGrab ID

Authorizations

ApiKeystringRequired

Body

regionstring · enumOptionalPossible values:

vehicle_idstringRequired

The AutoGrab Vehicle ID which corresponds to the vehicle that should be valued

kmsnumberOptional

The odometer reading of the vehicle. If no reading is provided, the average value will be subsituted

rrp_overwritenumberOptional

rrp_adjustmentnumberOptional

condition_scorenumberOptional

regostringOptional

The registration plate of the vehicle, for reference purposes only

state_for_pricingstringOptional

state to be used for state based valuations instead of national

statestringOptional

The registration state of the vehicle, if applicable

vinstringOptional

The VIN of the vehicle, for reference purposes only

Responses

200

Success

application/json

successbooleanOptionalDefault: true

400

Bad Request

application/json

401

Unauthorized

application/json

post/v2/valuations/predict

POST /v2/valuations/predict HTTP/1.1
Host: api.autograb.com.au
ApiKey: YOUR_API_KEY
Content-Type: application/json
Accept: */*
Content-Length: 169

{
  "region": "au",
  "vehicle_id": "text",
  "kms": 1,
  "rrp_overwrite": 1,
  "rrp_adjustment": 1,
  "condition_score": 1,
  "rego": "text",
  "state_for_pricing": "text",
  "state": "text",
  "vin": "text"
}

{
  "success": true,
  "prediction": {
    "id": "text",
    "vehicle_id": "text",
    "created_at": "text",
    "kms": 1,
    "price": 1,
    "score": 1,
    "retail_price": 1,
    "trade_price": 1,
    "adjustment": {
      "vehicle_id": "text",
      "type": "account",
      "enabled": true,
      "trade_adjustment": {
        "amount": 1,
        "type": "fixed"
      },
      "retail_adjustment": {
        "amount": 1,
        "type": "fixed"
      },
      "overrides": [
        {
          "id": "text",
          "min_kms": 1,
          "max_kms": 1,
          "trade_price": 1,
          "retail_price": 1
        }
      ]
    }
  },
  "bounds": {
    "retail": {
      "lower": 1,
      "upper": 1
    },
    "trade": {
      "lower": 1,
      "upper": 1
    }
  },
  "max_offer": {
    "reconditioning": 1,
    "profit_margin": 1,
    "lot": 1,
    "transport": 1,
    "admin": 1,
    "price": 1
  }
}

Pricing ID

The payload returned by price prediction requests will include an ID, which you can use to refer to the pricing request in the future. The /v2/valuations/history/{PRICING_ID} method will return the response from a previous pricing request, and you can also use the Pricing ID to track price changes with the Price Changes API.

To get a paginated list of all your previous price predictions, you can use the /v2/valuations/history endpoint.

Condition Score

You can manipulate the valuation returned by the prediction endpoint by supplying a condition score. The condition score can be between 1 and 5. A condition of 1 is poor, and 5 is excellent.

Supplying any other numbers will return the default trade_price, which assumes excellent condition.

If you're building a user interface that allows the user to choose a condition, it is recommended that you follow the industry standard in the table below.

Condition	Condition Score
Poor	1
Fair	2
Average	3
Good	4
Excellent	5

Features

Positive Equity

The positive equity feature identifies if the vehicle is in positive equity and the current equity position. To add an equity calculation to the Predict call, use features=equity

{
    "success": true,
    "prediction": {
        "id": "599aff94-7c79-4b9c-a976-ff39c3892190",
        "vehicle_id": "4825547834130432",
        "kms": 20000,
        "price": 32669,
        "score": 0.8515,
        "retail_price": 32669,
        "trade_price": 27769,
        "adjustment": null
    },
    "equity": {
        "positive_equity": true,
        "equity_position": 15769
    }
}

Valuation Bounds

If you require the upper and lower bounds used to calculate a prediction, you can use features=bounds.

Example request body including the features array.

curl --location 'https://api.autograb.com.au/v2/valuations/predict' \
--header 'Content-Type: application/json' \
--header 'ApiKey: YOURKEY' \
--data '{
    "region": "au",
    "vehicle_id": "5804870883868672",
    "kms": 30000,
    "features":["bounds"]
}'

Example response with the bounds for the valuation included.

{
    "success": true,
    "prediction": {
        "id": "e2813b16-1012-41b5-9ea3-3b65675c50fd",
        "vehicle_id": "5804870883868672",
        "kms": 57306,
        "price": 20622,
        "score": 0.9239,
        "retail_price": 20622,
        "trade_price": 17122,
        "adjustment": null
    },
    "bounds": {
        "retail": {
            "lower": 19622,
            "upper": 21872
        },
        "trade": {
            "lower": 16122,
            "upper": 18372
        }
    }
}