THE DATA-DRIVEN DECISIONS; WE INCREASED TIME EFFICIENCY IN CUSTOMER RELATIONS DEPARTMENT BY UPDATING CUSTOMER INFO IN OUR DATABASE.
Hi everyone! One of the first steps of data science is collecting true and strategic data in databases. Have you ever asked to update your info while you are using an ATM Probably, most of you say yes! We need the correct and updated data in data-driven decisions about business processes. In this article, I will talk about the importance of updating customer information.
The company that I am working for is teaching how to speak English to Turkish students via Skype for ten years. The company has around 25.000 students. We are caring for our students and trying to make second sales in the customer relations department. In addition to that, the company represents its customer relations consultants for each student as a competitive advantage and the differentiation from its competitors. Getting in touch with the students is vital for the company during their programs or after their programs.
The company manages customer data flow in its customer management (CRM) system. There are many business processes require phone calls to customers. The customer relations consultants have a balanced workload for the customers who are currently taking speaking classes or who have not active programs. Let’s assume the work balance is shared fifty-fifty.
The issue is here increasing the time efficiency for the inactive customer relations. In the database, some phone numbers of old customers are not valid. These students may have canceled or changed their phone numbers since they bought our service. The consultants cannot reach them via phone call. In the system, there were so many tasks to reach these inactive phone numbers. Detecting these inactive phone numbers repetitively is a time-consuming process for the consultants. Therefore, we need a phone number updating system. Before this issue, the consultants have to cope with redundant tasks about inactive students.
In the beginning phase of creating the phone number updating system, the new task scenarios to detect inactive phone numbers were working so slow and inefficiently. It was complex to understand and there was no endpoint for the process. Business intelligence analyst, me , checked the log data of tasks in each step of the new system to update old customers’ data. The numbers did not say what we like to found an efficient updating system. I told the story by data to the data shareholders; this updating system may create a positive effect on inactive student tasks. We computed that we can save %10 of the time that is spent for inactive students with inactive phone numbers. In the overall performance of the consultants in customer relations, it can save %5 of their work time.
After the data work has been done, the business process management and the developers cooperated to upgrade the phone number updating system. In conclusion, the company has made a data-driven development and has been rewarded by %5 time efficiency in the tasks of customer relations management.
