Analyze customer satisfaction data to understand how customers feel about the application and discover trends and insights for the business and marketing team.
This dataset collects information about calls from the seller's side to report difficulties with the application.
Assuming that the person who is collecting data, in this case, is the owner of a shopping app, this dataset contains additional details about complaint records, successfully resolved cases, and customer satisfaction from the seller and customer.
Power Bi for data visualization
After reviewing the dataset, I took the choice to create a dashboard from Power Bi to help gain a deep understanding. I split the results into two parts: the first part is about comparing data from the customer and seller sides, which showed an overview of the situation on both sides. The second is about a seller's insight that reported behavior and other recommendations in my opinion.
From the dashboard, notice the score card on the right-hand side, Average of CSAT score, found that the customer's side has an average satisfaction percentage of 89.8%, which is higher than the seller's side. This is due to the higher number of cases solved and the number of incoming calls on the customer's side.
There is additional information obtained from the analysis, which can be observed from the line chart below, found that on the seller's side (It's the light purple line) there was a percentage of satisfaction approaching the 50% average for two periods, which was a notable peak because on that day There might be an error on the operation side and it should be checked. For example, there might be an event/campaign special that makes the operation side unable to receive a large enough number of incoming calls due to insufficient staff
The solution may use this information to solve problems by recruiting more employees in a special case to deal with this event.
From this dashboard, there are four highlights.
💡 1. It was found that investigating the problem took too long, as can be observed from the pie chart data below the middle. It shows that it takes 6-10 days to fix the problem, followed by 10-20 days, which shows that it takes quite a long time. Which may affect the satisfaction of the seller side. Therefore, more expedited action may be needed to reduce the investigation time and to increase satisfaction scores as well.
💡 2. It was found that there were more than 24.6% of sellers who contacted the company to inquire about training or wanted a guideline to recommend various methods for customers. Noticed from the pie chart contact reason, which in this section is recommended. that There should be a guideline introducing various methods of use for customers, as well as having a special course to increase the use of various skills for customers because in this issue there is one special interest that is beneficial to both sides, for example, if the customers have more knowledge and understanding of use at a good level will reduce the amount of work on the complaint side and has a positive effect on application usage scores that are more positive as well.
💡 3. It was found that the chat channel is the channel that the customer contacts the company the most. In this section, we may find a way to use that is more convenient for customers, such as making a chatbot to divide discussion topics into application usage problems or popular questions in the chat box for users to read automatically. To reduce the working time of employees and to add more convenience to the customer's side.
💡 last point, in the pie chart on the bottom right-hand side, found that INBOUND MARKETING marketing benefits the company and is more effective than other methods. It can be seen from the percentage in the pie chart that is 67% in this section. It may be suggested that in making content should adhere to the principle of creating content using the needs of customers as the main theme. Including two-way communication according to the form of Inbound marketing.