ChatBot
Visual AI chatbot builder for customer support & engagement
What is ChatBot?
Try ChatBotChatBot by Text helps you build AI chatbots, then gives you reporting to measure how your chatbot is performing. With ChatBot reports, you can track activity across chats and users, spot the busiest times, and review which topics come up most often. You can also use chat archives to analyze past conversations, capture context, and improve your chatbot stories over time.
What kind of analytics and reports does ChatBot provide?
ChatBot reports help you track and optimize performance with insights like the total number of chats, your busiest periods (via a heatmap), the number of user messages and average engagement, and trends in typical chat length. You can also see popular interactions and how many users are chatting with your bot.
How can I use ChatBot analytics to improve customer engagement?
You can monitor engagement by looking at message counts and average chat length to understand how users interact with your chatbot. Reviewing popular interactions and repeating topics helps you identify what users care about most, so you can adjust your chatbot’s responses and stories accordingly.
Does ChatBot save user information for later review?
Yes. ChatBot automatically saves each user to a Users database, where you can view collected details about the user and their chats. You can also assign users to segments (custom groups) to support targeting in your next marketing campaign.
What are chat archives, and how do they help?
Chat archives store information from past conversations so you can learn from what happened during each chat, including collected data and any failed actions. Archives are linked to Users, which lets you review full chat context, understand weak spots in your chatbot stories, and improve customer experience.
Can I use past chats to refine my chatbot stories?
Yes. By analyzing what occurred in prior chats and learning from mistakes, you can discover weaknesses in your chatbot’s stories and make improvements. With archive context tied to individual users, you can better understand what to change to improve satisfaction.