Text, such as social media posts and customer reviews, is a gold mine waiting to be discovered. We can turn this unstructured data into useful insights, which can help companies better understand how customers like their products or services and more importantly, why, and then make business improvements as quickly as possible.
Super Duper Burgers is one of my favourite burger restaurants. Every time I went there, I would always see customers queueing up for the burgers. One day I was thinking, why people are so obsessed with this burger chain? …
When a user enters an ecommerce website, is he or she just browsing or ultimately will buy something? We can use classification algorithms in machine learning to find and keep the best customers.
As we all know, ecommerce is booming. Large platforms such as Amazon are becoming the primary place for people to find, compare and ultimately purchase products. Especially during the pandemic, more consumers have begun shopping online in greater numbers and frequency. This change in buying behavior will remain even after the COVID.
For the ecommerce platform, one of the most important questions they want to know is…
In my previous article, I showed how we can use Python to do RFM analysis step by step. In the following, I will analyze characteristics of some representative customer segments and give strategic recommendations respectively.
Recently I read the book Python Data Analysis and Data Operation by Tony Song and I was inspired by his analysis of CRM data management. I followed some guidelines in the book and wrote down my own thoughts about how to segment customers in an easy and powerful way.
Customers are heterogeneous and it is important for companies to know who they are and how valuable they are. RFM analysis is a great tool to do customer segmentation by examining recency(R), frequency(F) and monetary value(M) of purchases. This model is very popular and easy to understand.
I will use consumer…
Passionate about product growth, business strategies and data science.