---
title: "Preference Filters"
slug: "preference-filters"
tags: ["Filters", "Scope", "Page", "Preference", "Visitor", "Filter", "Visit"]
updated: 2025-06-05T15:04:22Z
published: 2025-06-05T15:04:22Z
canonical: "docs.mapp.com/preference-filters"
---

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

# Preference Filters

## 1 Introduction

The *Visitors Preference* scope allows you to identify users who show a repeated interest in specific content — not just one-time interactions.

Instead of simply checking whether an event occurred, preference filters evaluate how frequently certain behaviors happen over time. This enables a deeper understanding of user affinities and supports more precise segmentation.

---

## 2 How to Set It Up

To use a preference filter in Mapp Intelligence:

1. Create a new filter.
2. Select **Visitors Preference** as the scope.
3. Choose a dimension that is available for this scope (see table below).

![Example: Preference Filter for Running Shoes](https://cdn.document360.io/554b9b98-6720-4d8b-9919-c7b203d72648/Images/Documentation/2025-06 Filterengine 7.gif)

Example: Preference Filter for Running Shoes

Not all dimensions are supported — only those that represent repeatable user interactions. The available list is shown in the next section.

---

## 3 Supported Dimensions (by Classification)

The following dimensions are supported by the Visitors Preference scope. They are grouped by classification:

| **Classification** | **Supported Dimensions** |
| --- | --- |
| **Pages** | Pages, Content Groups, Page Parameters |
| **Marketing** | Campaigns, Campaign Categories, Campaign Parameters |
| **E-Commerce** | Viewed Products, Viewed Product Categories, E-Commerce Parameters |
| **Media** | Media, Media Categories |

---

## 4 Rules for Combining Filters

When using the *Visitors Preference* scope, certain restrictions apply to how filters can be combined:

- **Within a single container**:

All selected dimensions must share the **same standard scope**.

Example: *Pages* and *Marketing* can be used together (Page scope), but not *Pages* and *E-Commerce*.
- **Across multiple containers**:

You can use more than one container with the *Visitors Preference* scope, but containers must be combined using AND.

---

## 5 How Interest Is Calculated

Whether a user is considered interested is determined by **one of two rules**. The system applies the logic automatically, based on the selected dimension. Each classification uses a specific metric as the basis for evaluation:

| **Classification** | **Metric used** |
| --- | --- |
| **Pages** | Page Impressions |
| **Marketing** | Campaign Clicks |
| **E-Commerce** | Viewed Products |
| **Media** | Media Views |

### Rule A: Frequency and Share

A visitor is considered interested if:

- The event occurred **more than once**, and
- It accounts for **more than 20%** of all relevant events by that visitor

**Example**:

A visitor generated **100 Page Impressions** in total. Of those, **60** were from the Content Group *Sport*.

→ Since the value exceeds 20%, **Rule A is fulfilled**.

### Rule B: Dominance within a set of values

Alternatively, a preference is recognized if:

- Events from **at least two different categories** occurred, and
- One value occurred **more frequently than the average** of all other values in the same dimension

**Example**:

A visitor triggered Page Impressions in the following Content Groups:

- *Sport*: 40
- *News*: 20
- *Travel*: 10

→ Average of other Content Groups = (20 + 10) / 2 = 15

→ *Sport* (40) > 15 → **Rule B is fulfilled**

> [!NOTE]
> You don’t need to configure or calculate anything manually — Mapp Intelligence applies the logic in the background.

---

## 6 Use Case Examples

Here are three practical ways to use preference filters in your daily work:

- **Identify content affinities for better targeting**

Segment users who regularly consume content from specific content groups. For example, users who frequently access sections such as *Sustainability*, *Health* or *Travel*.
- **Personalize product experiences**

Use product-related preference filters to show tailored offers. For example, visitors with a high interest in *running shoes*, *outdoor gear* or specific *brands*.
- **Optimize campaign messaging**

Target users who have clicked on specific types of campaigns multiple times. For example, users who often click on *promotional banners* or *newsletter campaigns* can be addressed with tailored visuals or messaging frequency.