In this project, Google Fiber offers fiber optic internet to both individuals and companies. The Fiber customer support team has requested that I create a dashboard with fictitious data as part of this organization. In the customer call center where I work, Fiber monitors and enhances client happiness using business intelligence.
To help management determine if the team can handle customer inquiries the first time, the team must know how frequently customers call customer service again after making their initial request. In order to determine why consumers are contacting more than once and how to enhance the entire customer experience, leaders also wish to investigate patterns in repeat contacts. I'll build a dashboard that will provide information on recurring callers.
The team's ultimate objective is to interact with customers in order to improve operational optimization, lower the number of calls, and raise customer happiness. In addition to giving stakeholders information on the quantities of repeat callers in various markets and the kinds of issues they represent. Primary question:
- How often are customers repeatedly contacting the customer service team?
- What problem types generate the most repeat calls?
- Which market city’s customer service team receives the most repeat calls?
The main goal of this project is to explore trends in repeat callers
The data is fictitious dataset as a representation of real data. As a result, the data has already been authorized and anonymized. Call type, market city, date, number of calls, and number of follow-up calls following initial contact are all included. The datasets use the columns market_1, market_2, and market_3 to indicate the three distinct city service regions that the data reflects in order to anonymize and fictionalize the data. Five problem kinds are also listed in the data:
- Type_1 is account management
- Type_2 is technician troubleshooting
- Type_3 is scheduling
- Type_4 is construction
- Type_5 is internet and wifi
Note: the dataset records repeat calls over seven-day periods. The initial contact date is listed as contacts_n. The other call columns are then contacts_n_number of days since first call. For example, contacts_n_6 indicates six days since first contact.