Group respondents based on their preferences and behaviors to identify distinct segments within the customer base.

R STUDIO REQUIRED! You have to analyze the attached data. Run an analysis on R studio and explain which methods you used.
A little about the project: “The Impact of Advertising Techniques on Consumer Preferences for High-Speed Internet Packages: A Comparative Analysis of Cost and Perceived Value”
– The first set of data was to understand consumer preference when it comes to speed, reliability, price, etc. You have run an analysis for this set of data on R studio.

– Secondly, I attached two Verizon Internet Ads (Option 1 – 300/300 mbps, Option 2 – 1000/1000 mbps). The goal was to test if consumers would go for a cheaper package with more perks and benefits or would they go for a more reliable service but more pricey with less perks. You have to run this analysis and at the end write an analysis and see how the two sets of data compare to each other and if the behavior is matched.
All data and the Ads are attached below.
DATA COLLECTION:For the research project, a choice-based survey design will be used, implemented through Qualtrics. This method will present participants two different internet package options which help understand customers’’ preferences. Data collection will target current and potential internet service users aged 18 and above, ensuring diverse demographic representation.
Use mean, median, mode, and standard deviation to summarize responses.
B. Regression Analysis:
Apply multiple regression to identify which factors (speed, price, advertising) most significantly influence customer preferences.
C. Factor Analysis:
Use factor analysis to identify underlying variables (factors) that explain the pattern of correlations within a set of observed variables (e.g., different aspects of advertising).
D. Cluster Analysis:
Group respondents based on their preferences and behaviors to identify distinct segments within the customer base.
E. Structural Equation Modeling (SEM):
Use SEM to test complex relationships between observed and latent variables (e.g., how advertising influences perceived value, which in turn affects choice).

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