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

# Personalisation

> Using Omneo profile data to deliver personalised experiences across channels.

Personalisation in Omneo is about using what you know about a customer to make every interaction feel more relevant, at the register, in email, on your website, and via your app.

## What data drives personalisation

Omneo stores several types of profile data that power personalisation:

| Data type        | Examples                                 | Used for                             |
| ---------------- | ---------------------------------------- | ------------------------------------ |
| Identity         | Name, email, phone                       | Greeting, account lookup             |
| Preferences      | Appearance attributes, favourite brands  | Recommendations, product suggestions |
| Behaviour        | Aggregations (spend, frequency, channel) | Segmentation, offer relevance        |
| Incentive status | Tier, reward balance, active benefits    | Personalised offers, VIP treatment   |
| Tags             | Staff-applied labels                     | Staff context in Clienteling         |

## In-store personalisation via Clienteling

When a customer is identified at POS, Clienteling surfaces:

* Their tier and balance at a glance
* Any active benefits or notes
* Recent purchase history and preferences
* Style preferences (size, colour, brand)

This allows staff to give a genuinely personalised experience rather than treating every customer the same way.

## Email personalisation via targets

Omneo's reaction targets use Twig templating to personalise the data sent to your comms platform. Include customer-specific variables in every communication:

```twig theme={null}
Hi {{ first_name }},

You have ${{ reward_balance }} in rewards expiring soon.
Your favourite store is {{ aggregations.most_transacted_location.name }}.
```

## Segmentation with reactions

Use aggregation-based conditions in reactions to target specific customer segments:

* Customers who have spent over \$X in the last 12 months
* Customers who haven't purchased in 90 days
* Customers on a specific tier
* Customers with a birthday this month

## Profile Portal personalisation

Profile Portal automatically personalises the member experience based on their actual incentive data, showing their real balance, tier progress, and available benefits rather than generic content.