In today's fast-paced world, efficient customer support is paramount for businesses. Tiledesk, a popular customer engagement platform, offers a wide range of features to help businesses deliver top-notch support to their users. One way to enhance the user experience is by creating customized templates that streamline conversations and improve efficiency. In this article, we'll explore how to create a personalized Tiledesk user template using Large Language Models (LLM), specifically, a LLM like GPT-4.0, to categorize user responses, create different conversation branches, and generate new blocks for better engagement.
You can get started by watching this video tutorial or, if you prefer, keep reading the rest of this article and watch it later.
1. Categorization of User Answers with Larg Language Models
The first step in creating a customized Tiledesk user template is to categorize user responses efficiently. This categorization helps in routing users to appropriate conversation flows. To achieve this, we can leverage the power of LLM, such as GPT-4.0.
How it works:
Initial Question: Start by asking an initial question, such as, "Have you ever used Tiledesk before?" Users' responses can be quite diverse, but a Language Model can help categorize these responses into predefined categories. For instance, responses can be categorized into "New Users," "Experienced Users," or "Not Sure."
Language Model Assistance: Utilize the Language Model's capabilities to analyze and categorize user responses. The model can understand the context of the responses and assign them to the relevant categories.
Routing: Depending on the category, you can set up different conversation flows. For instance, new users can be guided through onboarding, while experienced users may need advanced support or product feature information.
2. Creation of Different Branches for Conversation Flows
Once you've categorized user responses, it's time to create different conversation branches to guide users through their unique journeys. Each branch can be tailored to address the specific needs of users in a particular category.
How it works:
Branches: Set up different conversation branches for each user category. For instance, for "New Users," you might have a branch that covers the basics of using Tiledesk. For "Experienced Users," you could create a branch that delves into advanced features and troubleshooting.
Conditional Logic: Use conditional logic within Tiledesk to route users to the appropriate branch based on their categorization. Language Models can assist in making dynamic decisions by analyzing user responses.
3. Creation of New Blocks with Language Models
Engaging users effectively often requires asking questions and seeking feedback. Language Models can assist in generating relevant questions and responses to user feedback, enhancing the conversational experience.
How it works:
Generating Questions: Use the Language Model to generate questions that solicit user feedback. For instance, "What features of Tiledesk do you find most valuable?" or "Is there anything you'd like to see improved in Tiledesk?"
Handling Feedback: When users provide feedback, use the Language Model to generate appropriate responses. It can help in acknowledging their feedback, providing solutions, or passing feedback to relevant teams.
Iterative Improvements: Continuously refine the questions and responses based on the feedback received. Over time, this can lead to a more personalized and effective user template.
By incorporating Language Models into your Tiledesk template, you can achieve a higher level of personalization and efficiency in your customer support interactions. This approach not only streamlines user conversations but also enhances the overall user experience.
In conclusion, creating a customized user template with LLM for Tiledesk empowers businesses to categorize user responses, create tailored conversation flows, and generate engaging questions and responses. This not only improves support efficiency but also helps in delivering a better customer experience.
If you're looking to take your Tiledesk support to the next level, consider integrating Large Language Models to create a more personalized and efficient template for your users.
