You have just joined a team of Consulting Psychologists. The team has a client organization that markets a range of products and services, including a chain of Health Clubs. Your supervisor has given you a dataset obtained for the client relating to the marketing and consumer response to the clubs and she wants you to investigate the dataset with the aim of producing a report for the client highlighting what it suggests.
The data were obtained by interview and questionnaire from 263 club members after the first three months of membership.
SPSS Variable name Description Possible values
ID Case number
Gender 1 – Female
2 – Male
FirstContact Point of first contact
for membership
1 – Visit to a Club
2 – Television
3 – Facebook
NVisits Number of visits in the first three months of membership 1 (low) – 7 (high)
Big5_ E 1 – 10
Big5_ N 1 – 10
Big5_ O 1 – 10
Big5_ C 1 – 10
Big5_ A 1 – 10
Internet Estimated hours of internet use per week
BRAND_L Brand loyalty Scores (0 – 100)
CUST_S Customer satisfaction score Scores (0 – 100)
Age Age in years
Task
The data file was set up by a temporary member of staff who had no specific knowledge of the variables and you have been warned that the file may contain some input errors. So the first task is to screen the data to identify any possible input errors and decide how you want to deal with these.
You should then provide a statistical summary of each of the key variables.
The client would like to know what influenced how much members used the club, their overall satisfaction and their loyalty to other products and services marketed by the organisation.
The questions you have been asked to investigate are therefore as follows:
1. Are there any differences between male and female customers on variables that might to be of importance to the organisation and future marketing campaigns?
2. Does the number of visits made, brand loyalty or customer satisfaction vary with the initial point of contact or gender of the customer?
3. Are those customers whose first point of contact was Facebook greater internet users.
4. Are the personality variables useful in predicting number of visits, customer satisfaction or brand loyalty?
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