Which of the following retail analytic applications involve(s) the use of search techniques to gain insights into customer's buying patterns?

A. Factor analysis

B. Regression analysis

C. Data mining

D. Data scrapping

E. Data cloning

Choose the most appropriate answer from the options given below:

Retail analytics focuses on providing insights related to sales, inventory, customers, and other important aspects crucial for a merchant's decision-making process. It is used to help make better choices, run a business more efficiently, and deliver improved customer service analytics.

Data mining:

• Data mining is a concept of computer science but has played a significant role in the retail industry as it helps retailers to learn the buying behavior and patterns of their customers.
• Retailers keep on collecting information about seasonal product sales, transactional data, and demographics, etc. the collected data is of no use if it is not converted into useful knowledge and converting data into knowledge requires a proper mechanism.
• Data mining is proved to be one of the most important tools to identify useful information from the large pool of information collected over time.
• It is also used to improve revenue generation and reduce the costs of business.

Therefore, retail analytic applications involve the use of Data mining techniques to gain insights into customer's buying patterns.

Factor analysis:

• Factor analysis is a technique used to reduce a large number of variables into a few factors.
• This technique extracts maximum common variance from all variables and puts them into a common score.
• As an index of all variables, that score can be used for further analysis.

Data scraping:

• Data scraping is a technique in which a computer program extracts data from human-readable output coming from another program.
• It often ignores binary data, display formatting, redundant labels, and other information that is either irrelevant or hinders automated processing.
• It is generally considered as ad-hoc, inelegant techniques used as a last resort when no other mechanism for data interchange is available.

Data cloning:

• Data cloning refers to a complete and separate copy of a database system that includes the business data, the DBMS software, and any other application that makes up the environment.
• Data cloning involves both fully functional and separate in its own right.
• The cloned data can be modified at its inception due to configuration changes or data subsetting.

Regression analysis:

• Regression analysis is a reliable method of identifying which variables have an impact on a topic of interest.
• The process of performing a regression allows you to confidently determine which factors matter most, which factors can be ignored, and how these factors influence each other.