As we respond to inquiries on a daily basis via chat support or AI chat bot, the history accumulates. In Chat Plus, history data is saved for a long time, so you can check it and download it from the administration screen. In addition to just keeping the history, if you classify it, it leads to efficiency increase in response to inquiries.
In this article, we will introduce classification and application method with chat support and AI chat bot history data .
If you read this article,
· Be able to know the type of inquiry and understand the classification method of inquiries.
· As we can classify inquiries well, we will be able to respond to inquiries efficiently.
· If you can respond to inquiries efficiently, you can raise customer satisfaction while reducing the burden on the person in charge.
First let's look at the type of inquiry.
When categorizing inquiries from customers, they can be divided into three broadly.
- 1 1. Basic questions to post on the homepage Q & A
- 2 2．Questions that can be answered with a small survey
- 3 3． Special question which requires individual correspondence
- 4 1．Tag of corresponding tool
- 5 2．Tags by visitor type
- 6 3．Tag by content of inquiry
- 7 4．Troubles and complaint tags
1. Basic questions to post on the homepage Q & A
Actually, inquiries from customers are mostly basic contents such as contents already announced on the homepage. It is important how much you can reduce basic inquiries. You can revise the contents of the homepage to make it easy to see, or use AI chatbots for automatic response.
2．Questions that can be answered with a small survey
Next, there are many inquiries that the person in charge can answer with a little investigation. Since those who respond to inquiries are often serving as other tasks concurrently, manpower will be taken if a small number of investigations are accumulated. If the inquiry history is sufficiently accumulated, try updating the AI chat bot, and try to reduce the response time.
3． Special question which requires individual correspondence
There are some Inquiries that require individual correspondence and that you have not come up to. Let's accumulate new inquiries as knowledge base and be able to answer smoothly the next time the same inquiries come.
Inquiries can be classified effectively by tagging. When tags are attached, it is convenient for chat history search, and even when you look back on it later, the contents of chat become easier to understand.
In addition, classifying by tag, you can maintain AI chatbot and knowledge base efficiently, and can smoothly respond to inquiries from next time onwards.
In Chat Plus, you can add tags to the corresponding chat during chat or after chatting. Since you can add multiple tags, combining tags makes it easier to understand the contents even when other inquiries personnel sees it.
Try tagging from the chat screen
It is also possible to tag automatically by AI chat bot, tag attributes of visitors and so on in cooperation with API.
Try setting up chat bot +
Let's see how to tag.
1．Tag of corresponding tool
Depending on the inquiry, it may be done by chat alone, may require deeper correspondence by e-mail. If it is a highly urgent inquiry, you may respond by phone.
If you complete with chat only, let's tag "chat", e-mail or escalate to the phone, let's tag"email", "phone".
It is convenient to classify the severity of inquiries.
2．Tags by visitor type
Let's attach a tag such as the first visitor, repeater etc. depending on the type of visitor. You can grasp the inquiries often coming from the first visitor and the ones from repeaters. It is useful for maintenance of AI chatbot and knowledge base, etc.
3．Tag by content of inquiry
Let's tag depending on the contents of the inquiry. Product shipment, inventory, how to use the site, stores,
If you decide on tags related to inquiries in advance, it will be easier to grasp the contents while responding to inquiries and after correspondence.
Let's tags such as "troubles" and "complaints" on inquiries that became troubles or complaints.
For better response to inquiries, we should improve by focusing on a response that did not go well, rather than a successful one.
How was it. I hope you can see the type of inquiry and how to classify the received inquiries by this article.
Tagging is useful for categorizing inquiries received by chat support or AI chatbot.
With the hints introduced in this article, it is now possible to classify and organize the inquiries successfully. So you can improve the AI chatbot and knowledge base, respond to inquireies smoothly from the next time, increase customer satisfaction, and also differentiate it from other companies.
If you use Chat Plus, you can share the classified and organized contents in-house on the management screen, so you can share information easily.
Daily inquiries are filled with hints for improving services and hidden needs from visitors. Let's analyze inquiries accumulated every day to improve service.