Predict all potential values across many conditions for a vehicle.
If you wish to predict valuations at all available conditions of the vehicle. That is those between 1 and 5,with 1 being poor and 5 being excellent condition. You can utilise the conditions in the same way you would use the standard /v2/valuations/predict/ endpoint.
In this endpoint, we will return all available conditions in an array. This can power great user experiences where you may wish to show a large range depending on the condition of the vehicle.
Generate upper and lower bounds on each valuation.
If you require the upper and lower bounds used to calculate a prediction you can use features=bounds.
This will yield the bounds on the retail and trade prices.
/v2/valuations/registrations/BMT038?features=bounds
If you have a max offer profile setup via API or via the AutoGrab web app you can opt to receive the same results via API. Use features=max_offer to receive them in your response.
/v2/valuations/predict?features=max_offer
If you want to set or update your Max Offer configuration over API view the guide here.
Generate market accurate predictions for vehicles.
The Valuation API can be used to determine the present retail & trade values, as well as the residual values of new vehicles.
This API requires and an appropriate license attached to it.
To use the API, a Vehicle ID returned from the Vehicle Search API or Vehicle Facet API is required.
Request
To retrieve a Vehicle ID, use the .
Starting with a vehicle ID post it to /v2/valuations/predict
The is optional and can be used to further refine your pricing prediction.
Payload
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, if licenced.
To get a paginated list of all your previous price predictions, you can use the /v2/valuations/history endpoint.
By supplying a condition score, you can manipulate the trade_price returned by the prediction endpoint. The condition score can be between 1 and 5. A condition of 1 being poor condition and a condition of 5 excellent condition.
Supplying any other numbers will return the default trade_price which assumes excellent condition.
If you're building a user interface where you allow the user to choose a condition it is recommended you follow the industry standard in the table below.
| Condition | Condition Score |
|---|
Poor |
|
Fair |
|
Average |
|
Good |
|
Excellent |
|
Adjust valuations we send you based on a rule set.
Both the Residual Value and Used Value APIs support pricing adjustments. These can be used to retrieve a more accurate price prediction of a vehicle if the AutoGrab price is not already accurate enough.
To adjust the stored Recommended Retail Price you can supply a rrp_adjustment value in the payload which accepts a number — positive or negative.
This is useful when a car is fitted with factory extras, the Price When New can be increased for each of the options to get a better price prediction.
To overwrite the stored Recommended Retail Price with your own, use the rrp_overwrite value in the payload which accepts a number.
The Pricing Adjustments API (/v2/valuations/adjustments) allows you to configure fixed or percentage adjustments for specific Vehicle IDs.
Per-vehicle pricing adjustments will apply to price predictions that you perform using the same API Key and for the same Vehicle ID.
If you set a Retail Price Adjustment for a vehicle, the trade price will also be affected because the trade price is derived from the retail price. If you set an adjustment for both the retail price and the trade price, both adjustments will be applied to the trade price while the retail price is only affected by the retail price adjustment.
When you perform a price prediction, you will receive a summary of the price adjustments that were applied, if any.
Predicted Retail/Trade Adjustments do not apply to residual valuations.
Example
Below is an example price prediction payload with predicted trade and retail adjustments applied.
As well as Price Adjustments, you also have the option to override Retail and Trade prices for specific Vehicle IDs where the odometer reading falls within a set range. Price overrides are configured using the Price Override API at /v2/valuations/adjustments/{VEHICLE_ID}/overrides.
If you have configured a retail or trade price override that applies to a price prediction, the overridden price will be returned instead of the AutoGrab valuation. This will bypass any price adjustments that you may have configured, and the response payload will indicate this with the {overridden: true} flag.
Retail price overrides will impact the predicted trade price in the same way that retail price adjustments impact the trade price - unless you have configured a trade price override. In the case where you have both a trade override and a retail override, the two overridden prices will be returned without any pre-processing (except to calculate condition scores, if applicable - see below).
As with Predicted Retail/Trade Adjustments, price overrides do not apply to residual valuations
Example
Below is an example price prediction paylaod where both price adjustments and price overrides have been configured. In this example, the retail price adjustment has been overridden by the retail price override, and the trade price adjustment has been applied.