Question

a data scintist writes a program that applies rules based logic to customer profile data to determine which customer are likely to respond to an advertisemenet how would you categories this type of analysis

Answer 1

A data scientist engages in predictive analytics by using rules-based logic to analyze customer data for marketing purposes.

Step-by-step explanation:

A data scientist who writes a program that applies rules-based logic to customer profile data to determine which customers are likely to respond to an advertisement is conducting a form of predictive analytics within the realm of data science. This type of analysis uses algorithms, statistics, and machine-learning techniques to identify the likelihood of future outcomes based on historical data. The resulting model can inform marketing strategies by identifying target groups that are more likely to engage with the advertisement, allowing for a more efficient allocation of marketing resources. In essence, this program is an application of marketing analytics, which focuses on the evaluation of data to determine marketing strategies.

Answer 2

The type of analysis described is data analytics, which involves examining raw data to draw conclusions and uncover patterns. By analyzing customer profile data and applying rules-based logic, a data scientist can predict which customers are likely to respond to an advertisement. This helps marketing teams identify target customers and personalize advertising campaigns.

Step-by-step explanation:

The type of analysis described, where a data scientist writes a program to apply rules-based logic to customer profile data in order to determine which customers are likely to respond to an advertisement, can be categorized as data analytics.

Data analytics is the science of examining raw data in order to draw conclusions about that information. It involves using specialized software and algorithms to uncover patterns, trends, and insights from the data. In this case, the data scientist is using customer profile data and applying rules-based logic to predict customer response to an advertisement.

This type of analysis is commonly used in marketing to identify target customers and personalize advertising campaigns. By analyzing customer data, the data scientist can determine which customers are more likely to respond to a particular advertisement, allowing the marketing team to focus their efforts and resources on those customers.