A Detailed Guide To Data Science For Any Business
Data science refers to the art of using data with statistical methods for the benefit of your business. Wherever there is data involved, you can apply data science and analytics techniques. Making decisions for a lucrative business needs data to predict the correct choice. Given that the “thin-line” of separation is thinning out, there is essentially only one correct choice amongst the pool of options. So, to make the right decision, you need data science solutions to help you stay ahead of any contingency.
The management team of any business has to ensure that all their resources — whether human or machine — are well utilized. They can strategize all these business decisions with the help of data. Let’s look at some of the data science systems which come to rescue and deliver a sigh of relief to business management.
It refers to the division of customer data into segments based on their purchasing behavior. There are many different customer segments possible. Segmentation is done based on the purpose of decision making.
The most common segmentation is the RFM model. It refers to the Recency-Frequency-Monetary aspects of a customer to decide the segment to which customers will be assigned.
Recency is calculated based on the number of days since the customer’s last purchase and the next-to-last day of the purchase. Frequency refers to the number of orders of the customer. Monetary value refers to the sum of the number of orders placed by the customer. Recency and Frequency can also be calculated based on the website visits made by customers.
Other types of segmentation include dividing the customer base based on their device used while making the purchase. We can also segment the customer based on where the user made the purchase and many more parameters for segmenting customers.
Nowadays, websites have a facility for customers to leave their comments about the brand/product.
Customer Review Sentiment Analysis refers to the systematic analysis of customer reviews. We segregate reviews into positive and negative. The Analysis uncovers topics about which customers are talking about the most. We can also assess the location of customers and find their preferences.
This analysis helps senior management to track the glitches in the departments for which grievances have been reported. It is beneficial to senior management to know what customers think about their business and formulate strategies to address their concerns. It also helps them to design products in the future, keeping in mind what customers want.
It refers to the calculation of customer lifetime value and predicting the customer’s future purchase based on their past purchase.
Customer lifetime value is calculated as
This prediction analysis informs businesses about how much revenue customers are going to generate. Higher the revenue generated per customer highlights higher customer satisfaction. If there is a decline in average revenue/order, companies need to take steps to raise it.
Subscription-based businesses segment their customers into two categories: active and churned. Active customers are the ones who continue their subscription renewal. Churned customers are those who canceled their subscriptions.
Customer Churn Prediction refers to the system that predicts which customers will churn and what traits they possess. This can be age, gender, location, etc., of customers.
Subscription-based businesses need to know what customers are going to churn soon. This helps them prepare for the future and devise plans to retain these customers.
For Example, Video content service loses more of its subscribers in Tamil Nadu because subscribers love watching more local language content. So, to attract more audience, any Company should start showing regional content as well to ensure maintaining subscribers.
Retention rate refers to calculating the number of customers who have been making multiple purchases on your website.
