> For the complete documentation index, see [llms.txt](https://help.openloyalty.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.openloyalty.io/implementation-guide/integrations-and-data-exchange/imports-exports/imports/sample-import-files/campaign-codes.md).

# Campaign Codes

How to import redemption codes into Open Loyalty campaigns using CSV files.

Redemption codes are unique codes assigned to campaigns. Use this import to pre-load a pool of codes for a campaign.

**File format:** CSV

#### Sample file

{% file src="/files/DL3LJpdyBrs5KsT9JC8D" %}

{% code title="redemption-codes-import-sample.csv" %}

```csv
code
SUMMER2024-ABC123
SUMMER2024-DEF456
SUMMER2024-GHI789
```

{% endcode %}

#### Format rules

* The file **must** include the header row `code`
* Each subsequent row contains one unique redemption code
* Codes must be unique within the tenant
* No extra columns — only `code` is supported

{% hint style="info" %}
**Codes are tied to a specific campaign.** When importing, you will be asked to select the target campaign. Make sure the campaign exists before importing codes.
{% endhint %}

### Common mistakes

| Mistake                         | Fix                                                                                                                              |
| ------------------------------- | -------------------------------------------------------------------------------------------------------------------------------- |
| Missing header row              | The `code` header is required                                                                                                    |
| Duplicate codes within the file | Ensure all codes are unique                                                                                                      |
| Extra columns                   | Only `code` is supported — remove additional columns                                                                             |
| Non-UTF-8 encoding              | Re-save as UTF-8 to avoid corrupted special characters                                                                           |
| Confusing the two import types  | Redemption codes go into **campaigns**, reward coupons go into **rewards** — they are selected separately in the import dropdown |

To find out more, please refer to the article below:

{% content-ref url="/pages/SRo81A5dFHGeogQiRBKA" %}
[Redemption Code](/implementation-guide/campaigns/campaigns/campaigns-and-referral-campaigns/creating-campaigns/trigger-types/redemption-code-campaign.md)
{% endcontent-ref %}


---

# 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 following URL with the `ask` and `goal` query parameters:

```
GET https://help.openloyalty.io/implementation-guide/integrations-and-data-exchange/imports-exports/imports/sample-import-files/campaign-codes.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `build a script that syncs our docs to a CMS` lets GitBook tailor the answer to that use case.

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.