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Question

Chatbot does not resolve the conversations as per the customer's command.

  • Jul 21, 2022 4:46 PM UTC
  • 1 reply
  • 62 views
Andressa.Megiolaro
Apprentice

Hi!

We use freddy self service in freshchat and it is not filtering the conversations that are attributed to analysts. All customers contacted via chat are assigned directly to analysts by IntelliAssign.We need the conversations to be filtered by the chatbot and for it to assign to agents only conversations where the customer points out that it has not been resolved and that it resolves the conversations that the customer points out that it has been resolved.Can someone who uses the chatbot in the support team help me, please?
We would also like to know if there is a way to measure thethe amount of conversations that freddy resolved and the amount he needed to transfer to an agent.

 

 

 

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1 reply

Community Debut
  • rahul999
  • Community Debut
  • Jul 20, 2023 10:46 AM UTC

It seems like you are facing some challenges with the Freddy self-service in Freshchat and its interaction with the analysts. I'll try to address your concerns and provide some possible solutions.

  1. Filtering Conversations: To ensure that conversations are filtered by the chatbot before being assigned to analysts, you'll need to adjust the configuration settings of Freddy self-service. Within Freshchat, there should be options to customize the chatbot's behavior and criteria for transferring conversations to agents. You may need to fine-tune the chatbot's responses and triggers to only escalate conversations that require human assistance.

  2. Intelligent Assignment: You mentioned using IntelliAssign to directly assign customers to analysts. If you want the chatbot to handle certain conversations before reaching the analysts, make sure the integration between Freddy and IntelliAssign is properly set up. You may need to define specific rules for when the chatbot should take action versus when it should be passed to an analyst.

  3. Customer Feedback for Resolution Status: To better manage conversations and identify which ones are resolved or unresolved, you can train the chatbot to ask customers for feedback at the end of each interaction. If the customer indicates that the issue has been resolved, the chatbot can mark the conversation as such. Similarly, if the customer states that the problem persists, the chatbot can escalate the conversation to an agent.

  4. Tracking Freddy's Performance: To measure the effectiveness of Freddy's resolutions and transfers, you can use analytics and reporting tools within Freshchat app. These tools should provide insights into the number of conversations resolved by the chatbot and those that were transferred to agents. By monitoring this data, you can optimize the chatbot's performance over time.

  5. Seek Support from Your Team: If you're part of a support team, it's best to collaborate with your team members who have experience with the chatbot and its configurations. They may have encountered similar issues or found effective solutions to optimize Freddy's performance.

  6. Contact Freshchat Support: If you're still facing challenges after trying the above steps, don't hesitate to reach out to Freshchat's customer support. They should be able to provide you with specific guidance and troubleshoot any technical issues related to Freddy and its integration with IntelliAssign.

Remember that the effectiveness of the chatbot relies on continuous monitoring, adjustment, and improvement. Regularly gather feedback from customers and your support team to enhance the chatbot's capabilities and provide a better user experience.

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