> For the complete documentation index, see [llms.txt](https://documentation.crossengage.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://documentation.crossengage.io/predictions-platform/tutorials/predict-campaign-profit.md).
# Predict Campaign Profit
Click on the Prediction Tab in the top right corner of your screen.
From the dropdown Menu, choose the Model you wish to create a Prediction for.
#### Enter Commercial Data
* Click on the Edit button in the Header.
* Give your Selection a meaningful name.
* Enter Contact Cost. This is the Cost per Customer contact, for example, in a Print Campaign this can be the cost of printing and shipping Marketing Material per Customer.
* Enter Overhead Cost. This is the sum of all One-time costs for the Campaigns, for example, the design cost of the Marketing Material.
* If your Prediction optimizes for Conversion rather than Revenue, enter Average Order Value. This is the mean amount paid by customers for an Order.
* Enter Average Profit Margin. This helps the Predictions Platform understand how much revenue turns into Gross Profit.
* Scroll to the bottom of the Edit Window and click 'Apply' to save the commercial data for the **current** prediction. Alternately, you can click the Save button next to the Commercial Data; This saves the data for **all** predictions.
#### Make a Selection
* To automatically set Optimum Selection Size, click on "Optimize for Profit". YOu can see the number of the customers present in the Optimal Selection.
* Optionally, deselect "Optimize for Profit", and manually enter the preffered number of customers for the Campaign.
* Click Export.
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:
```
GET https://documentation.crossengage.io/predictions-platform/tutorials/predict-campaign-profit.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.