Greenscreens.ai
Enabling the Greenscreens App
If you have a Greenscreens.ai account, you can connect it to your Chaine account to sync the Greenscreens' Lane Rate Prediction data into Chaine. This allows your team to see the Greenscreens predicted lane rates on all available posts in side of Chaine.
To get started, in you Chaine account:
- Click your Avatar on the top right which will open a menu
- Select
Settings - In the Settings menu, select
Apps - Find the Greenscreens app, and click
Enable, and then again on the confirmation pop-up - You will asked to add your Greenscreens
client idandclient secret. If you don't have this available, ask your Greenscreens account manager for this information. - Click 'Enable' and thats it
Depending in your plan, your loads will start to sync inside of Chaine.
Enabling Chaine as "Capacity on Tap" in Greenscreens
To enable Chaine as a Capacity on Tap option inside of Greenscreens, you will need to generate an API Key in Chaine and provide it to your Greenscreens support rep. Once this is done, you will be able to see Chaine as an option in the Capacity on Tap section of Greenscreens. Here are instructions on how to generate an API Key in Chaine:
- Click your Avatar on the top right which will open a menu
- Select
Settings - In the Settings menu, select
Developers - Click
Create key - Make sure to select
capacity:readpermissions underAPI Permissions - Click
Create key - Copy the key and provide it to your Greenscreens support rep
Greenscreens + Revenova
If you have both Greenscreens and the Revenova app enabled, you can utilize both of these apps together to sync Greenscreens' Lane Rate Prediction data into Revenova as well. When both of these apps are enabled, you will see the following fields in Revenova:
Note, the "total" fields are determined by the "per mile" rate multiplied by the distance from Revenova. i.e. gs_Target_Buy_Ratec = gs_Target_Buy_Per_Mile_Ratec * gs_Distance__c
| Data | Description | Revenova API Field Name |
|---|---|---|
| Target buy rate total | Total Target buy rate (fuel included). | gs_Target_Buy_Rate__c |
| Start buy rate total | Total Suggested starting buy rate for negotiations with the carrier (fuel included) | gs_Start_Buy_Rate__c |
| Low buy rate total | Total Low boundry of the buy rate (fuel included) | gs_Low_Buy_Rate__c |
| High buy rate total | Total High boundry of the buy rate (fuel included) | gs_High_Buy_Rate__c |
| Fuel rate total | Total Fuel surcharge | gs_Fuel_Rate__c |
| Target buy per mile rate | Target buy rate (per mile, fuel included). | gs_Target_Buy_Per_Mile_Rate__c |
| Start buy per mile rate | Suggested starting buy rate for negotiations with the carrier (per mile, fuel included) | gs_Start_Buy_Per_Mile_Rate__c |
| Low buy per mile rate | Low boundry of the buy rate (per mile, fuel included) | gs_Low_Buy_Per_Mile_Rate__c |
| High buy per mile rate | High boundry of the buy rate (per mile, fuel included) | gs_High_Buy_Per_Mile_Rate__c |
| Fuel per mile rate | Fuel surcharge (per mile) | gs_Fuel_Per_Mile_Rate__c |
| Confidence level | How confident the system is in the prediction it is making. From 0 (lowest) to 100 (highest) possible confidence | gs_Confidence_Level__c |
| Currency | The currency that the prediction values are in (ISO 4217 format) | gs_Currency__c |
| Distance | Total distance of the trip (in miles). | gs_Distance__c |