customerSat              package:bayesm              R Documentation

_C_u_s_t_o_m_e_r _S_a_t_i_f_a_c_t_i_o_n _D_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     Responses to a satisfaction survey for a Yellow Pages advertising
     product. All responses are on a 10 point scale from 1 to 10 (10 is
     "Excellent" and 1 is "Poor")

_U_s_a_g_e:

     data(customerSat)

_F_o_r_m_a_t:

     A data frame with 1811 observations on the following 10 variables.

     '_q_1' Overall Satisfaction

     '_q_2' Setting Competitive Prices

     '_q_3' Holding Price Increase to a Minimum

     '_q_4' Appropriate Pricing given Volume

     '_q_5' Demonstrating Effectiveness of Purchase

     '_q_6' Reach a Large # of Customers

     '_q_7' Reach of Advertising

     '_q_8' Long-term Exposure

     '_q_9' Distribution

     '_q_1_0' Distribution to Right Geographic Areas

_S_o_u_r_c_e:

     Rossi et al (2001), "Overcoming Scale Usage Heterogeneity," _JASA_
     96, 20-31.

_R_e_f_e_r_e_n_c_e_s:

     Case Study 3, _Bayesian Statistics and Marketing_ by Rossi et al.
       <URL:
     http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html>

_E_x_a_m_p_l_e_s:

     data(customerSat)
     apply(as.matrix(customerSat),2,table)

