# Fashion API

Retrieve fashion insights such as browser history, style preferences, recent purchases, and fashion-centric user information with **hushh Fashion API**.

## Style Preferences

<figure><img src="https://3515412604-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5ofdWgtfu1N2tmo5zUB3%2Fuploads%2F5i8nsh3vwYmGqXu4MlUk%2Fnazsharaf_A_woman_dressed_in_high_end_clothing_searching_throug_31c7f493-d849-4570-a08c-179b0d959a37.png?alt=media&#x26;token=25b726f1-a704-4b9f-b3e0-a2c1c253ed25" alt=""><figcaption></figcaption></figure>

Make **Personalized Fashion Recommendations:**

* Valuable **Insights** into Users' **Unique** **Style** **Choices**
* Tailored Fashion Suggestions for **Individual Styles**
* Create a platform that **resonates** with fashion enthusiasts

## User Purchase and browser history

<figure><img src="https://3515412604-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5ofdWgtfu1N2tmo5zUB3%2Fuploads%2FSDBWhQQW22ggkFpXnpQB%2FScreenshot%202023-10-13%20at%207.50.18%E2%80%AFPM.png?alt=media&#x26;token=61a765e7-dde9-4697-85fb-aec8f08596db" alt=""><figcaption></figcaption></figure>

Insights into **Buying Behaviors**:

* Valuable Data on **Preferred Items, Purchase Frequency, Expenditure Habits**
* Develop Personalized, Targeted Product Recommendations
* Build a Customized Shopping Experience that **Fosters Loyalty**

Access to **Online Activities and Interests**:

* Comprehensive View of User Preferences and Behaviors
* Create **Highly Personalized** and Relevant Recommendations
* Tailor Experience to **Align with Individual Interests**

{% hint style="info" %}
To know more about what exact insights we offer, check out our [endpoints](https://hushh.gitbook.io/hushh-docs/api-reference/fashion-api/endpoints) page.
{% endhint %}

## Browse examples

Here are some things **you** can build with **hushh** **Fashion**!

### Digital Closet

<figure><img src="https://3515412604-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5ofdWgtfu1N2tmo5zUB3%2Fuploads%2FQt0yqCCKOWdS4tIDHOT2%2FScreenshot%202023-10-14%20at%201.45.01%E2%80%AFPM.png?alt=media&#x26;token=6942a954-59b4-4294-a69b-d70d00b659f4" alt=""><figcaption><p>Build a digital closet for your customer!</p></figcaption></figure>

**Meet Maria!** She opens your application and is able to see **all** the clothes she owns. With the ability to **virtually** view **accurate representations** of **every single item** she owns, she is able to:

* Share it with friends enabling them to wear **complementary clothing** at **galas and events**&#x20;
* Pass this on to her **personal stylist** for a better understanding of her **clothing style**
* Use her **virtual** closet to check if it is **on par** with **current fashion trends**
* Better **decide** what she needs to buy
* Keep an **inventory** of all her clothing
* Sort by **color, fit, style, and more!**

### Hyper-personalized outfit recommendations

<figure><img src="https://3515412604-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5ofdWgtfu1N2tmo5zUB3%2Fuploads%2FkM6DP7XWKBpaFJy0IBxN%2FScreenshot%202023-10-14%20at%201.50.27%E2%80%AFPM.png?alt=media&#x26;token=33d9439b-8e95-4b5d-a413-bea48b318285" alt=""><figcaption><p>Recommend entire outfits based on your customer's style preferences!</p></figcaption></figure>

**Say hello to Selene!** She opens **your** **clothing** **app** on her phone and **instantly** sees:

* Outfits that **fit** her **clothing style** and **budget**
* **Similar** outfits to the ones she was **trying to buy** on the **internet**
* **Accessories** **and** **shoes** of her size that would **complement** the outfit


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# 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://hushh.gitbook.io/hushh-docs/api-reference/fashion-api.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.