At the end of July, I started involving in a big project of our team with which we hope to build a customer journey to create a more systematic service and leverage customer satisfaction for both users and drivers. As AhaMove is a technological logistics start-up that aims to create a cyber marketplace with equivalent stakeholders from supply and demand sides, this project plays a vital role in increasing the engagement of customers and fostering the development of the company in a long term.
With its important and wide-reaching impacts, customer journey mapping is considered a powerful tool that reflects customers’ experience and interaction with the company. However, it is hard to find a stable and applicable approach for an effective customer journey because it depends on several demographic and behavioral factors, which makes it challenging to design a suitable journey and generate automated treatments accordingly for all customers. Thus, I am trying to define segments of the customer journey in more details to make sure they target the right audiences.
In general, working with data can be ambiguous sometimes, especially when the ideas behind requested tasks are too broad or impractical to do. Hence, data analysts are required to spend a lot of time researching and digging into data to find patterns and untangle knots in response to requested tasks. In the last month of my internship, I am going to deepen my own research of our customers and keep on developing my models further.
Working on the project, I have understood more deeply about the databases and had a chance to apply the knowledge from Dickinson math classes to a professional setting. Indeed, the statistical models and interpolation methods learned from Probability and Statistics as well as Numerical Methods have helped me visualize data and analyze findings more easily. Although I have learned about SQL and R through some online courses, using these programming languages to solve real problems certainly speeds up my learning process and enables me to remember syntax much faster than merely watching online tutorials and writing codes for virtual cases. Therefore, this project is an amazing opportunity for me to sharpen my analytical skills and accumulate hands-on experiences that will give me a competitive edge in my future career in data analytics.