昤
昤
昤
<3-1>...43 <3-2>...45 <3-3>...45 <4-1>...59 <4-2> (1-)...63 <4-3> (1-)...63 <4-4>...68 <4-5> (1)...71
[2-1] CRM... 11 [2-2] CRM...20 [2-3]...39 [3-1]...46 [3-2]...47 [3-3]...48 [3-4]...49 [3-5]...49 [3-6]...50 [3-7]...51 [3-8]...51 [3-9]...52 [4-1]...58 [4-2]...60 [4-3] (TERM)(1)...64 [4-4] (TERM)(1-)...65 [4-5] (TERM)(1-)...65 [4-6] (TERM)(1)...66 [4-7] (TERM)(1-)...67 [4-8] (TERM)(1-)...67 [4-9]...68
[4-10] ()...70 [4-11]...71 [4-12]...73 [4-13]...74 [4-14] (A, B, C )...76 [4-15] (1)...77 [4-16] (1)...78 [4-17] (1)...79 [4-18] (1)...80 [4-19] (1)...81 [4-20] (1)...82
I 1
2
3
II 1 (Market Segmentation) 1.
2.
2 (CRM) 1.
2.
3. CRM 18
4. (1)
(2)
(3)
(1).,
(2) CRM
3 1.
2. 35
3.
4.
5. CRM
4 CRM 1.
2.
III 1 1.
2. (Data Cleaning) (Data Transformation)
(1) (2)
(3) (4) (5) (6)
(7)(term)
3.
2
1. 2. (sale effect)
(1), FR ti = Freq ti days t Freq ti termt days t termt
AV ti = Amounti Freq ti Amoun ti termt Freq ti termt (2) AFR( FR = Average ( ) ) ( )
= ( ) ) Average AAV ( ) AV( AFR( FR = Average ( ) ) ( ) AAV( AV = Average ( ) ) ( ) D AFR = AFR ) AFR ( ) ( - D AAV = AAV ) AAV ( ) ( - D D
D D Score Score AFR( AAV = * ( ) ) ( ) AFR( AAV = * ( ) ) ( ) SE Score Score( = - ( ) )
IV 1 1.
2. (trend analysis)
2 () 1.
2. (1)
(2)
(3)
(4)
(5) (6)
(7)
(8)
(9)
3 1.
2. q360 (1 2%) qse = -7,140() q. q. q125. q36. q,
q512 (1 3%) qse = 8,449() q. q. q q5. q60% 6. q,. q. q133 (1 1%) qse = 43,062() q. q30, 40~50. q3~6 q,. q. q686 (1 4%) qse = 18,726() q. q. q. q60%6. q.
q1,388 (1 8%) qse = -2,151() q. q1,748 (1 10%) qse = 4,613() q30. q. q1,052 (6%), SE=4,557, q3050~60. q. q6,791 (41%), SE=-74 q 4,090 (24%), SE=398
V 1
2
[] (1997), -, (1999),, /, (1993),?,, 8, 2, pp.81~108, (1993),, (2000), CRM : Buyculture.com, (2001), CRM() :, () (1997),, -, (2000), CRM, (2001), e-crm, (2001), CRM,, September (1999),,
(2001), CRM,, 138, pp45~47 (1998),, (1999), : O (2000), CRM :, (1995),, (1995),, pp.119~120 (2001),, (1992),, (1998),, (2001), VALUE CONFIGUATIONCRMSCM :,,, (1999),, (1996),, (1986),, (2001), CRM, (1997),, :, p.11
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