Hi, I am Abhinav Saha (B Tech) Graduate, currently working as Regional Manager in Customer Service for a leading Automobile Company. Part of my role requires Business development with customer Delight. Post Covid expenditure nature and priorities of customer has changed. Having a large database of customers and improving it further through data mining was the most important thing to have a target set of customers and convert them to bring more revenues for Partners and organizations.
Doing the same was not easy while doing in Excel and to make my seniors and partners to understand the same. I needed something more to make my analysis more interactive and easy for my manager to understand. The problem was a certain class of customers not turning up for service as per the periodicity and don’t want to spend much as they consider it mild/fewer priorities as more local options are at large and with competitive pricing. The problem was affecting our organizational business as the customers who did not turn up proved to be a direct loss of business and retention affected brand loyalty as well.
Going through the learning while DSBA, I applied the Data Mining concepts, predictive modelling/ML and regression techniques for identifying the turn-up probabilities and for identifying the right marketing scheme for clustered customers thru KMeans. For improving satisfaction, Text mining was used where I was using the Word Cloud for the identification of major reasons for dissatisfaction through the voice of customers. With the prediction model, I was successful in improving the turn-ups for the Low or Mild probability customer what I Got from the regression Model & K-Mean clustered customer helped me to classify customers as per the spending nature & float a scheme as per the needs of the cluster customers which helped in not only saving time but also improved the productivity of the callers. I used regression techniques and it helped me in improving the conversion rate of the lost customer by 10% text mining helped in improving the weak area as per the voice of customers to achieve satisfied customers which is most important for repeat business and reducing the dissatisfaction by 3%.
Well, after this I have gained confidence in doing something new with the learning as a data scientist and am quite sure that this will help in improving business with new technologies. Apart from the orthodox approach, we are ready for the transitional shift.
