Introduction
Topic classification for post-conversation analytics helps identify and categorize the key issues or themes discussed during customer interactions. This allows contact centers to gain insights into common problems, identify trends and products, and optimize agent training and business processes.
In Ender Turing, the Topic is called Category to highlight that it can be used for much broader purposes than just a topic of conversation. For example, If you need to categorize Product-123 related conversation and analytics, you can use this categorization.
Categorization Approaches
This guide will walk you through creating topics in the Ender Turing application, covering three distinct categorization approaches that can be mixed depending on your tasks and goals:
Generative Categorization (using Generative AI): This option leverages AI models to automatically generate and categorize topics based on the call's content. The AI identifies and categorizes key themes without predefined rules, adapting to new topics over time. It’s highly flexible and works well in dynamic environments where new trends emerge frequently. Generative categorization is a fast and efficient way to categorize new or evolving topics but can't be used to categorize through historical conversation.
Rule-Based (based on Filters and Tags): This approach categorizes topics using predefined rules, such as specific keywords, tags, or filters. It’s ideal for contact centers with well-established categories where certain phrases or terms reliably indicate specific topics (e.g., “refund request” or “technical issue”). Rule-based categorization is a fast and efficient way to categorize new and historical topics but is less adaptable to new or evolving topics.
Manual (Human Categorization): In some cases, you need to manually link the Category to the conversation, either for further training or an internal process. Using manual category, the user can select an appropriate Category from a predefined list.
Creating Category
1. Go to Analytics Configuration
2. Click "Categories"
Navigate to the Categories section.
3. Click "Create"
Initiate the Category creation process.
4. Fill in the Category name
Creating Generative Categorization
5. Select "Use Gen AI"
Enable the use of Gen AI.
6. Fill in a detailed category description
Add details to describe the category precisely, e.g.:
Name: ATM,
Description: Customer asks or tells information regarding ATM locations, issues, etc.
7. Click "Create" to save the Category
Finalize and create the category.
Creating Rule-bases Categorization
Definition
Rule-bases Categories are advanced constructs that group multiple tags into broader topics or themes. They provide higher-level logic by consolidating various tags under a single umbrella, allowing for the identification of complex topics within conversations and simplifying advanced logic operators on Filtering, Analytics, and Reporting steps.
Think of Rule-bases Categories as Logical constructors (AND, OR, NOT), e.g.:
Category Name: Verification Succesful (Compliance)
Category Logical Rule: Tag1 (Agent started verification) AND Tag2 (Client provided asked data) AND Tag3 (Agent confirmed identity)
5. Select "Use Rules"
Opt for using rules.
6. Define rules
You can apply filters as necessary.
7. Select Tags to match the Category
Navigate to the desired section.
8. Click "Add"
Add a new element.
9. Click "Create" to save Category
Finalize and create the category.
Creating Manual Category
5. Select "Manual Only"
Select the manual category type.
6. Click "Create" to save the Category
Finalize and create the category.