CLASSIFICATION OF ANALYTICS



Abstract: - Based on the previous article, this article will go deep into each class of Analytics and each will be explained in great depth.

“Data is a precious thing and will last longer than the systems themselves” - Tim Berners-Lee

Since the primitive stages of mankind, we have been in need of the concept of classification. We come about it in various forms of Do’s and Don'ts, Right and Wrong, etc. So how does this concept apply into Analytics that is what we would discuss in the following article.


The types of Analytics

There are multiple classifications, we however, will focus on 6 primary types :-

  1. Customer Analytics

  2. Sales Analytics

  3. Marketing Analytics

  4. Supply Chain Analytics

  5. Risk Management and Analytics

  6. HR Analytics

Watch video below for more detailed explanation:




Customer Analytics:


Customer Analytics is based on customer behavior and transactions made by him/her. Shopping patterns are analysed to give the best possible deals, to attract and retain a customer.


Various factors like Loyalty, Average checkout amount and Frequency play an important role in this process. Customers are segmented into various classes and a lifetime value is determined.


This is most prominently noticed in E-commerce websites. Suppose you search for a product, irrespective of you purchasing the product, time and then you will notice better deals (if available) being advertised in various other websites/notifications.


Sales Analytics:


This kind of Analytics is focused on Product Companies. The process keeps a track of the sales products and representatives and attempts on optimizing resources.


For example, you run a business that sells product “X” on a website. Applying concepts of Sales Analytics you can track the number of visits (organic and inorganic), number of visitors converted to customers, value and revenue, all at once.


Marketing Analytics:


This kind of Analytics is focused on companies that primarily rely on advertisements for the sale of their products. Various Statistics from Marketing and Brand Managers are filed and an extensive report of what is beneficial to the company is given to value each effort and rate the efficiency of each channel.



For Example, when you buy a product, you might often be asked to fill a form asking from where you got to know about the product. These statistics are gathered and the company decides which channel is the best to invest further in (Prescriptive Analytics plays a crucial role here).


Supply Chain Analytics:


Supply Chain is a crucial part of Logistics. The implications of Analytics is vast in this Analytics requires massive computational power if done on a Nationwide or International scale (for companies like Fedex and UPS). This Analytics goes into determining hot zones (areas with maximum business and customers), optimized routes for best delivery of products (like UPS no left turn policy).


For example, the worldwide UPS courier delivery system has been extremely optimized with extensive analysis, resulting in over 300 Million packages being delivered every single day.




Risk Management and Analytics:


The most advanced kind of Analytics resulting in an extensive use of the given product. This is the backbone of every Analytics research, as it can eliminate worst case scenarios. This kind is highly complicated involving input from every single faction of an Enterprise.


For Example, Banks run Risk Analysis before lending a loan based on Credit Scores.


HR Analytics:


Data on performance of various employees are taken into consideration and decision are taken to improve workforce operations. They are also used in recruiting and decisions on retaining or eliminating employee workforces.


For Example, Cisco uses HR analytics to predict attrition of its employees, this helps Cisco HR to take preventive measures which helps in retention of good performing employees.


Thus we conclude this article by explaining six types analytics, in next article we will learn more about first type of Analytics technique : Customer Analytics


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