Intelligence criteria create segments based on artificial intelligence and machine learning data captured within Mapp Cloud. These criteria use aggregated, predictive, and behavior-based insights derived from past contact behavior.
Prerequisites
Intelligence criteria in the Segmentation Builder are not activated by default. Activation requires a support ticket. For details, contact your Customer Success or Account Manager.
Purchase Insights
Allows you to segment contacts using aggregated transaction insights calculated on the contact level.
Settings (Overview)
Setting Group | Description |
|---|---|
Transaction Status | Buyer and lifecycle-based purchase classification |
Loyalty Status | Purchase frequency–based classification |
Value Status | Revenue-based classification |
Transaction Metrics | Revenue, transactions, order value, discount rate |
Popularity Metrics | Most frequently purchased attributes |
Time-based Metrics | Metrics evaluated within a defined timeframe |
Transaction Status
Selects contacts based on whether and how frequently they purchase products.
Status | Description |
|---|---|
Not a Buyer | Contacts with no recorded transactions |
First Time Buyer | One transaction and not in status Churning or Churned |
Second Time Buyer | Two transactions and not in status Churning or Churned |
Repeat Purchaser | Three or more transactions; Loyalty and Value Status are considered |
Churning | Time since last transaction exceeds the configured churning threshold |
Churned | Time since last transaction exceeds the configured churned threshold |
Loyalty Status
Selects contacts based on how many purchases they finalize per year.
Status | Description |
|---|---|
Low Loyalty | Below the configured threshold |
Medium Loyalty | Within the configured threshold |
High Loyalty | Above the configured threshold |
Value Status
Selects contacts based on how much money they spent over an aggregated time frame.
Status | Description |
|---|---|
Low Value | Below the configured revenue threshold |
Medium Value | Within the configured revenue threshold |
High Value | Above the configured revenue threshold |
Transaction Metrics
Numeric criteria based on transactional data.
Metric | Description |
|---|---|
Total Revenue | Aggregated revenue |
Total Transactions | Number of finalized transactions |
Average Order Value | Average value per transaction |
Average Discount Rate | Mean discount percentage |
Transaction Frequency | How often transactions are finalized |
Popularity Metrics
Identifies dominant purchase attributes.
Metric | Description |
|---|---|
Most Popular Category | Category purchased most frequently |
Most Popular Brand | Brand purchased most frequently |
Most Popular Variant | Variant purchased most frequently |
Most Popular Purchase Source | Most frequent purchase source |
Time-based Metrics
Metrics evaluated within a defined timeframe.
Metric | Description |
|---|---|
Spend (Revenue in timeframe) | Revenue within the selected period |
% of Returned Purchases | Share of returned orders |
More Details
Purchase Insights are based on aggregated historical transaction data.
Insight parameters such as value or loyalty status must be configured in advance.
For setup instructions, see Define Parameters for Value and Loyalty Status.
Engagement Insights
Allows you to segment contacts based on their engagement relative to other contacts in your Engage system.
Settings
Engagement Level | Description |
|---|---|
No Engagement | Contacts that have not opened or clicked any messages in the last 12 months |
Low Engagement | Bottom 30% of contacts |
Medium Engagement | 30%–60% percentile |
High Engagement | 60%–90% percentile |
Very High Engagement | Top 10% of contacts |
More Details
Engagement is calculated based on message interaction data from the last 12 months.
Engagement levels are relative, not absolute, and depend on the overall engagement distribution in your Engage system.
Engagement Insights are derived from contact profile data.
For more information, see Contact Profile.
CI Segments
Customer Intelligence (CI) Segments allow you to use advanced analytics from Mapp Intelligence directly in Mapp Engage.
CI Segments are calculated based on all data collected in Mapp Cloud and reflect the past behavior of your contacts.
Settings
Setting | Description |
|---|---|
CI Segment | Select a predefined segment created in Mapp Intelligence |
More Details
CI Segments are created and maintained in Mapp Intelligence, not in Engage.
Segment calculations are based on aggregated historical data across Mapp Cloud.
CI Segments can be used for personalization, automated workflows (Whiteboards), and triggered messaging.
For step-by-step instructions, see:
ML Attribute
Machine Learning (ML) Attributes use forecasting models to predict optimal communication timing and channels for each contact.
Settings
Setting | Description |
|---|---|
Best Sendout Time | Predicts the optimal time for sending messages |
Best Sendout Channel | Predicts the most effective channel for communication |
More Details
ML Attributes are based on predicted future behavior, not past interactions.
SMS, Push, and In-App channels are available only if mobile channels are activated in your system.
ML models are continuously updated as new data becomes available.
For more information, see:
Topics of Interest
Identifies contacts with specific interests based on the content they interacted with.
This criterion uses content-based analysis to infer topic-level interests from clicked links and visited pages.
Instead of relying on predefined link categories or exact keyword matches, the system evaluates the context of page content to determine which topics a contact engaged with.
Topics of Interest is designed to help you:
identify contacts with specific thematic interests,
target them with more relevant content,
and react to recent engagement signals rather than static profile data.
The feature must be activated in your Mapp Engage account.
Settings
Setting | Description |
|---|---|
ADD | Add one or more topics or keywords to the search. These terms define which interests the system should look for in content interactions. |
Language | Select the language used to analyze page content. Language selection affects how terms and related expressions are interpreted. |
Search Accuracy | Controls how strictly topics must match page content. Choose Precise, Medium, or Broad depending on how narrowly or broadly interests should be detected. |
Search Limit | Limits the number of page interactions per contact that are evaluated for topic detection. Only the most recent interactions up to this limit are considered. |
Matched Links | Displays excerpts of content where the defined topics were detected, providing transparency into why a contact matched the criterion. |
Interested | Defines whether contacts who match the topic criteria (Yes) or do not match (No) are selected. |
In Timeframe | Limits topic detection to interactions within a specific time range, defined using the Engage date picker. The timeframe is evaluated relative to the segment run date. |
More Details
Topic detection is based on content context, including link titles, surrounding text, alternative text, and nested image alternative text.
Search Accuracy determines whether only closely matching terms or also semantically related expressions are considered.
Search Limit and timeframe work together to restrict analysis to recent and relevant interactions.
The criterion evaluates content relevance, not user intent.