> For the complete documentation index, see [llms.txt](https://marketing-trailhead.gitbook.io/home/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://marketing-trailhead.gitbook.io/home/the-marketing-playbook/marketing-channels/referrals/referral-systems.md).

# Designing Referral Systems

## Referral systems are of two types:

1. **Forward-only reward:** If a prospect referred by your customer takes a desired action

   (an actual sale or signing for a trial), then only the prospect gets a reward for the transaction. The reward for the customer could be intangible - "positive feeling of doing good".
2. **Both-way reward:** If a prospect referred by your client takes a desired action (an actual sale or signing for a trial), then your customer as well as the propect - both get rewarded for the transaction. 

Rewards in case of referrals could be in multiple forms - digital or physical or even intangible such as social recognition:

* Discount on the normal price.
* More of a product at the same price - subscription period, more storage space, premium features unlocked, etc.
* Free complimentary product along with the core product at the same price.
* Digital vouchers along with the main product at the same price.

## Reference material:

{% embed url="<https://www.referralcandy.com/blog/47-referral-programs/>" %}


---

# 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:

```
GET https://marketing-trailhead.gitbook.io/home/the-marketing-playbook/marketing-channels/referrals/referral-systems.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.