Chat Record Analysis Method

——Learn how to use chat records to analyze the reasons for trans-to-agent through this article

What you can learn from this article

We would like you to understand the following contents through this article:

● How to analyze the reasons for trans-to-agent through chat records

● How to analyze the large fluctuation of Independent Reception %

● How to optimize the knowledge base after determining the reasons for trans-to-agent

How to Analyze Chat Records

You can learn how to analyze the chat records and improve the Independent Reception %:

● How to Get Chat Records

1. The chat records you need to obtain are trans-to-agent chat records, which can be exported through【Trans-to-Agent Statistics - Trans-to-Agent Chat Records】in admin console.

2. After the records of a certain day or period of time are selected, 200-300 chats are selected at random to refine the operation stage. For the first two weeks, they are analyzed and optimized 2-3 times a week.

Figure 1: Trans-to-Agent Chat Record Page

● How to Use Chat Record Analysis

1. Mark the chat record, and mark the reason for trans-to-agent, to improve the Independent Reception %.

Mark method: two dimensions, namely operation dimension and business dimension. The business dimension can be divided according to the actual business scenario of the customer. Please refer to the following introduction

Operation dimension: It can mark the chat as Resolved by Direct Trans-to-Agent, Resolved with Agent Participation, and Independently Resolved by Bot. Among them, Agent Participation can be divided into Guide in Answer, Product Question, Unclear Intention, No Reason and Invalid; Independently Resolved by Bot can be divided into Poor Answer, Unknown Answer, and Guidance Question.

Business dimension: Taking e-commerce as an example, the chat can be marked as pre-sale, in-sale and after-sale, and can also be subdivided.

2. Why it is marked by operation dimension: Solutions can be divided in the operation dimension.

Direct Trans-to-Agent is to trigger the trans-to-agent keyword in the first sentence, without giving the opportunity for bot. It cannot be resolved by operation.

In case of Agent Participation, you can focus on the analysis of answer guidance and product reasons used for business registration for future reference by business departments.

In case of Chat Independently Resolved by Bot, it can be processed using the operation method. If the answer is not good, it can be improved. If it is an unknown answer, you can add it into standardized questions to enrich the knowledge base. If it is a guided answer, you can add it into similar questions or Containing Match.

3. Why to mark from a business perspective: It can be used to analyze what type of business is usually transferred to agent. They are accumulated for business departments to adjust business.

● How to Analyze Independent Reception % with Large Fluctuation

1. It is normal for the Independent Reception % to fluctuate around 5%, and it will change with the cycle. A more accurate comparison method is the period-on-period analysis of different cycles. For example, in the e-commerce industry, the fluctuation of weekend, workday and activity day indicators is inconsistent. It is recommended not to make a mixed analysis of these three indicators.

2. On the date before and after the fluctuation of the Independent Reception %, export the same number of two groups of trans-to-agent chat records with the same conditions, and label and analyze them according to the above analysis method.