![]() To resolve this, we need to select the column and then follow these steps ( data > text to columns > Date : MDY > Finish). ![]() Due to this excel don't directly convert all the entries in date format which is required. Next, in call timestamp dates are stored in two formats (mm - dd - yyyy) and (mm / dd / yyyy) format. In csat score column a number of entries are NULL, but it isn't mandatory to change it since we've sentiment column which we can use if we need to perform sentiment analysis. Some of the issues encountered by me are mentioned below: Next we'll review our dataset and do the cleaning and transformation part. Now, we've got a basic understanding of our dataset. Bar chart for the response time- it will inform us whether we're able to resolve the customer queries within the SLA time.Column chart for reason of contact - to know which are the most common reasons for contact.A map for states showing the number of contacts depending upon the region.A bar graph for the call channel which will help us to know which channels are most frequently used by customers.( Columns used are - call timestamp and count_id) Lines chart for call trends - It will tell us how much contacts we receive on a daily bais.We can get different analysis from same dataset and some of the objectives which I've extracted are mentioned below: We need to set a research goal which we have to achieve from the dataset given to us. Response time - Respone time to customer query from our end from time of contact (Above SLA, below SLA or within SLA) (SLA - service level agreement).Channel - Point of contact (Call center, chatbot, email or web).Reason - Contact reason (Billing, Service outage or Payments).csat score - Customer satisfaction score from 1 - 10.Sentiment - Customer sentiment throughout the call ( Neutral, positive ,negative, very negative or very positive).The description of dataset is mentioned below: Our dataset contains 32941 entries and 12 columns. The data is sourced from data.world and I've also added the raw file in the files. Here we'll be performing data analysis on call center data.
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