Bayesian network considering the clustering of the customers in a hair salon

Figures & data

Figure 1. The distribution of the recency (R) of the customer visits.

Figure 2. The distribution of the frequency (F) of the customer’s visits.

Figure 3. The distribution of the money (M) of the customer monetary.

Table 1. Basic statistical values

	R	F	M
Maximum	731	69	1,139,008
Minimum	1	1	0
Middle	147	2	22,140
Mean	246.44	4.94	56,888.74
SD	233.85	5.73	79,538.14

Table 2. The results of the RFMD analysis

Latent Class	R	F	M	D	Probability of Belonging
$z_1$	356.52	1.15	10,147.91	16.44	41.73%
$z_2$	53.5	7.02	77,517.12	5.53	17.21%
$z_3$	310.96	2.94	31,438.19	28.09	14.68%
$z_4$	26.85	13.53	171,437.1	5.13	9.79%
$z_5$	319.23	5.93	73,093.54	463.99	3.48%
$z_6$	72.97	5.63	61,193.69	299.41	2.62%
$z_7$	15.55	22.82	334,396.2	324.61	2.57%
$z_8$	378.82	1.01	8644.68	1332.59	1.86%
$z_9$	38.27	10.29	132,496.8	30.08	1.75%
$z_{10}$	364.8	2.02	20,973.12	8.35	1.20%
$z_{11}$	17.25	18.23	255,180	33.13	0.74%
$z_{12}$	220.22	13.14	181,443.2	53.89	0.68%
$z_{13}$	363.72	6.59	86,611.33	447.47	0.57%
$z_{14}$	97.56	4.32	47,684.14	108.69	0.27%
$z_{15}$	97.33	7.81	114,141.6	7.05	0.20%
$z_{16}$	475.62	2.06	26,031.55	6.46	0.19%
$z_{17}$	104.74	18.46	287,318.4	223.78	0.17%
$z_{18}$	41.49	7.95	145,688.1	29.78	0.15%
$z_{19}$	32.35	17.21	362,370.8	3.83	0.12%
$z_{20}$	6.57	49.03	712,508.9	7.87	0.11%
$z_{21}$	34.99	16.51	155,987.6	5.01	0.02%

Table 3. Effects of coupon 1 on a good cluster

Menu	Probability	Difference	Lift value
Hair dyeing	0.342	0.278	5.35
Treatment	0.103	0.076	3.832
Blow	0.381	0.275	3.581
Haircut4	0.773	0.529	3.169
Permanent	0.167	0.114	3.162
Straight perm	0.071	0.022	1.446
Fix it again	0.003	0	1
Treatment item	0.02	−0.017	0.542
Haircut2	0.011	−0.255	0.04
Haircut3	0.005	−0.134	0.038
Haircut1	0.005	−0.173	0.029

Table 4. Effects of coupon 2 on a good cluster

Menu	Probability	Difference	Lift value
Treatment	0.522	0.495	19.451
Hair dyeing	0.425	0.361	6.64
Haircut4	0.93	0.686	3.815
Straight perm	0.167	0.118	3.422
Permanent	0.121	0.068	2.29
Fix it again	0.003	0	1
Blow	0.046	−0.061	0.429
Treatment item	0.01	−0.027	0.278
Haircut3	0.01	−0.129	0.071
Haircut1	0.01	−0.169	0.056
Haircut2	0.01	−0.255	0.037

Table 5. Effects of coupon 1 on a bad cluster

Menu	Probability	Difference	Lift value
Permanent	0.148	0.067	1.826
Hair dyeing	0.387	0.163	1.724
haircut4	0.779	0.297	1.617
Blow	0.355	0.114	1.474
Straight perm	0.136	0.039	1.398
Treatment	0.108	0.029	1.361
Fix it again	1	0	1
Haircut1	0.013	−0.035	0.263
Haircut2	0.007	−0.085	0.081
Treatment item	0.001	−0.034	0.042
Haircut3	0.001	−0.075	0.015

Table 6. Effects of coupon 2 on a bad cluster

Menu	Probability	Difference	Lift value
Treatment	0.41	0.331	5.151
Straight perm	0.237	0.139	2.426
Haircut4	0.914	0.432	1.897
Permanent	0.123	0.042	1.514
Hair dyeing	0.335	0.111	1.492
Treatment item	0.04	0.005	1.135
Fix it again	1	0	1
Blow	0.183	−0.057	0.761
Haircut1	0.019	−0.029	0.391
Haircut3	0.019	−0.058	0.245
Haircut2	0.019	−0.074	0.203

Table 7. Effects of coupon 1 on “good customers’ willingness to travel a long distance” cluster

Menu	Probability	Difference	Lift value
Straight perm	0.501	0.479	23.41
Treatment	0.484	0.452	15.317
Hair dyeing	0.352	0.258	3.735
Permanent	0.199	0.141	3.469
Haircut4	0.319	0.104	1.483
Treatment item	0.121	0.038	1.452
Blow	0.348	0.101	1.407
Fix it again	0.001	0	1
Haircut3	0.029	−0.037	0.437
Haircut1	0.08	−0.121	0.399
Haircut2	0.12	−0.185	0.393

Table 8. Effects of coupon 2 on “good customers’ willingness to travel a long distance” cluster

Menu	Probability	Difference	Lift value
Treatment	0.831	0.8	26.317
Straight perm	0.291	0.27	13.597
Hair dyeing	0.55	0.455	5.836
Permanent	0.251	0.194	4.392
Haircut4	0.519	0.304	2.415
Blow	0.328	0.08	1.324
Fix it again	0.001	0	1
Treatment item	0.079	−0.004	0.953
Haircut3	0.011	−0.054	0.171
Haircut1	0.023	−0.178	0.114
Haircut2	0.032	−0.273	0.105

Figure 4. Good customers.

Figure 5. The results of the bad customers.

Figure 6. Good customers travel long distances to reach the salon.