We are one of the fastest growing startups in the logistics and delivery domain. We work with several partners and make on-demand delivery to our customers. During the COVID-19 pandemic, we are facing several different challenges and everyday we are trying to address these challenges.
We thrive on making our customers happy. As a growing startup, with a global expansion strategy we know that we need to make our customers happy and the only way to do that is to measure how happy each customer is. If we can predict what makes our customers happy or unhappy, we can then take necessary actions.
Getting feedback from customers is not easy either, but we do our best to get constant feedback from our customers. This is a crucial function to improve our operations across all levels.
We recently did a survey to a select customer cohort. You are presented with a subset of this data. We will be using the remaining data as a private test set.
Y = target attribute (Y) with values indicating 0 (unhappy) and 1 (happy) customers
X1 = my order was delivered on time
X2 = contents of my order was as I expected
X3 = I ordered everything I wanted to order
X4 = I paid a good price for my order
X5 = I am satisfied with my courier
X6 = the app makes ordering easy for me
Attributes X1 to X6 indicate the responses for each question and have values from 1 to 5 where the smaller number indicates less and the higher number indicates more towards the answer.
https://drive.google.com/open?id=1KWE3J0uU_sFIJnZ74Id3FDBcejELI7FD
Predict if a customer is happy or not based on the answers they give to questions asked.
Reach 73% accuracy score or above, or convince us why your solution is superior. We are definitely interested in every solution and insight you can provide us.
Try to submit your working solution as soon as possible. The sooner the better.
We are very interested in finding which questions/features are more important when predicting a customer’s happiness. Using a feature selection approach show us understand what is the minimal set of attributes/features that would preserve the most information about the problem while increasing predictability of the data we have. Is there any question that we can remove in our next survey?