> ## Documentation Index
> Fetch the complete documentation index at: https://docs.scentxp.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

## Powering the fragrance discovery journey

Choosing a fragrance online is inherently complex. Preferences are sensory, emotional, and often difficult to articulate. Most e-commerce catalogs classify perfumes only by brand, gender, or price — leaving customers confused, uncertain, and more likely to abandon or return a purchase.

WikiParfum transforms this complexity into a **clear, guided and personalized discovery experience**. Built on a curated database of **31,000+ perfumes** and **1,500+ ingredients** — classified by fragrance experts in partnership with [Fragrances of the World](https://fragrancesoftheworld.com/) — it provides the olfactive intelligence that brands and retailers need to help their customers discover, understand, and choose fragrances with confidence.

### What WikiParfum enables

* **Expert olfactive classification** — every fragrance classified by family, subfamily, ingredients, and intensity
* **Intuitive fragrance exploration** without requiring prior knowledge
* **Enriched product experiences** with visual ingredient breakdowns, perfumer profiles, and olfactive data
* **Personalized recommendations** grounded in real olfactive affinities, not popularity
* **Persistent preference understanding** across sessions, channels, and CRM

### The business impact

WikiParfum addresses the core barriers to online fragrance purchase:

| Challenge                                       | How WikiParfum helps                                                                   |
| ----------------------------------------------- | -------------------------------------------------------------------------------------- |
| Customers don't know what a perfume smells like | Visual ingredient breakdowns and olfactive profiles make each fragrance understandable |
| Catalogs are poorly classified and confusing    | Expert olfactive classification standardizes and enriches every product                |
| Generic recommendations don't drive trust       | Olfactive-affinity-based recommendations feel authentic and accurate                   |
| High return rates on fragrance purchases        | Better understanding before purchase increases confidence and reduces returns          |
| No insight into customer scent preferences      | Olfactive preference data enables targeted CRM and lifecycle campaigns                 |

### What WikiParfum is — and is not

WikiParfum is **not** a static perfume database or a generic recommendation rules engine.\
It is a **fragrance-native intelligence layer**, designed specifically for how people explore, evaluate and choose perfumes.

## Technical foundations

All API interactions are performed through GraphQL.

* **Endpoint**: `https://api.wikiparfum.com/graphql`
* **Authentication**: `Authorization` header with API key
* **Execution model**: Server-side only
* **Multi-language**: All content available in multiple languages via the `lang` parameter

The API is designed for real-time usage and flexible data access at every step of the journey. See [Authentication & Security](/wikiparfum-api/getting-started/authentication) for setup details.

## The fragrance discovery journey

A typical integration powered by WikiParfum follows these steps:

| Step              | Description                                                                            | Guide                                                                       |
| ----------------- | -------------------------------------------------------------------------------------- | --------------------------------------------------------------------------- |
| **1. Connect**    | Map your product catalog to WikiParfum via EAN codes                                   | [Catalog Integration](/catalog-integration/product-feed)                    |
| **2. Initialize** | Establish a user session for personalization and analytics                             | [Sessions & User Identity](/wikiparfum-api/getting-started/sessions)        |
| **3. Classify**   | Enrich your catalog with expert olfactive classification                               | [Olfactive Classification](/wikiparfum-api/guides/olfactive-classification) |
| **4. Explore**    | Let users discover fragrances by name, ingredient, family, or guided questionnaire     | [Fragrance Exploration](/wikiparfum-api/guides/exploration)                 |
| **5. Enrich**     | Enhance product pages with olfactive profiles, ingredients, perfumer data, and visuals | [Fragrance Library](/wikiparfum-api/guides/product-enrichment)              |
| **6. Recommend**  | Generate personalized recommendations based on olfactive affinity                      | [Recommendations](/wikiparfum-api/guides/recommendations)                   |
| **7. Persist**    | Reuse preference data across sessions, channels, and CRM                               | [CRM & Personalization](/wikiparfum-api/guides/crm-personalization)         |

Each step can be implemented independently or combined into a continuous experience.

## Next steps

<CardGroup cols={2}>
  <Card title="Authentication & Security" icon="key" href="/wikiparfum-api/getting-started/authentication">
    Set up your API key and understand the server-side execution model.
  </Card>

  <Card title="Catalog Integration" icon="barcode" href="/catalog-integration/product-feed">
    Connect your product catalog to WikiParfum.
  </Card>

  <Card title="Fragrance Library" icon="book" href="/wikiparfum-api/guides/product-enrichment">
    Enrich your product pages with olfactive data and visuals.
  </Card>

  <Card title="Exploring the Schema" icon="magnifying-glass" href="/wikiparfum-api/getting-started/exploring-the-schema">
    Use GraphQL introspection to discover all available queries and types.
  </Card>
</CardGroup>