Filtering Data

Scout's filtering options provide a comprehensive suite of filtering features for users to efficiently manage and analyze vast amounts of data. These features enhance the platform's capability to deliver relevant, actionable intelligence tailored to specific user needs and scenarios.

Boolean Search

Functionality: Boolean search allows users to create complex search queries using Boolean operators (AND, OR, NOT) to combine or exclude specific keywords.

Application: This is essential for precise searches, especially when dealing with large datasets. It helps in narrowing down results to the most pertinent information based on specific criteria.

Word Lists

Functionality: Word lists in Scout are customizable lists of words or phrases used to filter search results. They can include specific keywords, industry jargon, brand names, or any relevant terms.

Use Cases: Word lists are instrumental in refining search results to include only the most relevant information. They are particularly useful in brand monitoring, threat detection, and competitive intelligence gathering.

User-Defined Tags

Purpose: User-defined tags are customizable labels that users can create and assign to various data points or results in Scout.

Advantages: These tags facilitate better organization, categorization, and retrieval of data. They are particularly useful in team collaborations, where standardized tags can streamline communication and data analysis.

System Tags

Description: System tags are predefined tags in Scout used to automatically categorize data based on certain criteria or rules.

Usage: System tags help in the automatic sorting and prioritization of data. They play a crucial role in alerting users to specific types of content, such as potential threats, mentions of a brand, or compliance-related information.