# NFT Impact

## NFTs to disrupt marketing

NFT Impact is a unique mass sender tool developed by CryptoArena that is capable of delivering [**many millions**](https://cryptoarena.org/cryptoarena-delivers-largest-nft-airdrop-in-crypto-history/) of NFTs per day, at a negligible cost. 

#### Other than its unmatched efficiency, our tool can:

* Distinguish individuals from contracts 
* Target specific data attributes (e.g. only wallets with X ETH, wallets that already have NFTs, etc.)
* Update metadata of delivered assets

This provides an alternative, modern and artsy venue to direct marketing efforts such as advertisement, loyalty programs or newsletters, and targets 100% qualified audiences, since they all use wallets already.

But more importantly, NFTs can be transferred by the recipients, allowing your ads and newsletters to be seen by new people, and  if they like it enough, they can be sold! 

This creates the possibility of generating royalties from the sales of your audience, effectively creating a resale market out of publicity, and **turning marketing efforts from a cost into a revenue stream.**

#### **Find out more:**

{% content-ref url="nft-impact" %}
[nft-impact](https://cryptoarena.gitbook.io/docs/nft-impact)
{% endcontent-ref %}

{% content-ref url="nft-impact/problems-solved" %}
[problems-solved](https://cryptoarena.gitbook.io/docs/nft-impact/problems-solved)
{% endcontent-ref %}

{% content-ref url="nft-impact/advantages" %}
[advantages](https://cryptoarena.gitbook.io/docs/nft-impact/advantages)
{% endcontent-ref %}

{% content-ref url="nft-impact/technology" %}
[technology](https://cryptoarena.gitbook.io/docs/nft-impact/technology)
{% endcontent-ref %}


---

# Agent Instructions: 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://cryptoarena.gitbook.io/docs/nft-impact.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.