Count Number of Repeat Customers

[a68tbird]

Hello all -

Having some trouble wrapping my head around this. I would like to count the number of repeat customers in my Orders table. The customer email is the unique value to count. I want to be able to use this calculation to create a table such as the one represented below:

The conditional formatting I should be able to figure out, but I'm not sure how to create the DAX for this. It needs to be able to identify repeat emails, and the number of times it repeats. Filter context for the YEAR should occur in the table - that is, the DAX shouldn't need to consider the year - just the entire Orders table. This way, if I want to look at all years, or drill down to quarters and months, it should still return the relevant results. Will it require five different measures - one for each bin of "# of Orders"?

 

[Herakles]

Hello all -

Having some trouble wrapping my head around this. I would like to count the number of repeat customers in my Orders table. The customer email is the unique value to count. I want to be able to use this calculation to create a table such as the one represented below:

The conditional formatting I should be able to figure out, but I'm not sure how to create the DAX for this. It needs to be able to identify repeat emails, and the number of times it repeats. Filter context for the YEAR should occur in the table - that is, the DAX shouldn't need to consider the year - just the entire Orders table. This way, if I want to look at all years, or drill down to quarters and months, it should still return the relevant results. Will it require five different measures - one for each bin of "# of Orders"?

MrExcel has a tool called “XL2BB” that lets you post samples of your data that will allow us to copy/paste it to our Excel spreadsheets, so we can work with the same copy of data that you are. Instructions on using this tool can be found here: XL2BB Add-in

Note that there is also a "Test Here” forum on this board. This is a place where you can test using this tool (or any other posting techniques that you want to test) before trying to use those tools in your actual posts.

 

[a68tbird]

MrExcel has a tool called “XL2BB” that lets you post samples of your data that will allow us to copy/paste it to our Excel spreadsheets, so we can work with the same copy of data that you are. Instructions on using this tool can be found here: XL2BB Add-in

Note that there is also a "Test Here” forum on this board. This is a place where you can test using this tool (or any other posting techniques that you want to test) before trying to use those tools in your actual posts.

I hope this works for you. This is 6800+ rows of data - all orders from this year - with order date and I used zip code so as to not expose personal emails.

N0P 2L0

Thanks!

 

[Herakles]

I hope this works for you. This is 6800+ rows of data - all orders from this year - with order date and I used zip code so as to not expose personal emails.

N0P 2L0

Thanks!

This is all that I get : N0P 2L0

Did you select the entire range?

 

[a68tbird]

This is all that I get : N0P 2L0

Did you select the entire range?

Apologies - I had not captured the range.

This is now a considerably smaller sample set, which unfortunately doesn't include many duplicates. But hopefully it's something you can work with.

BillingZipPostalCode	DateCompletedGMT
94547-1532	16-Oct-23
T4V 2K3	16-Oct-23
N0P 2L0	16-Oct-23
L7G 5Z1	16-Oct-23
11215-3697	16-Oct-23
B0K 2A0	16-Oct-23
K1Y 3H4	16-Oct-23
19067-5837	16-Oct-23
63146-4916	16-Oct-23
92376-3649	16-Oct-23
E1B 3R6	16-Oct-23
T3H 0S9	16-Oct-23
T3K 5V3	16-Oct-23
V1N 4V1	16-Oct-23
V5Y 0B5	16-Oct-23
V6H 4H4	16-Oct-23
V1M 3A8	16-Oct-23
H2H 2B2	16-Oct-23
60515-1413	16-Oct-23
N4G 2B7	16-Oct-23
L9G 0E4	16-Oct-23
K1C 7G7	16-Oct-23
L9C 4Y8	16-Oct-23
L1N 8M6	16-Oct-23
M4E 2T8	16-Oct-23
K4M 1K2	16-Oct-23
L1X 2R4	16-Oct-23
M6R 2A4	16-Oct-23
15241	16-Oct-23
L8H 5R4	15-Oct-23
M8W 0B6	15-Oct-23
M8W 0B6	15-Oct-23
L2M 7G6	14-Oct-23
N3W 1G5	14-Oct-23
EH4 4GL	14-Oct-23
L6Z 3T3	13-Oct-23
60107	12-Oct-23
60452	12-Oct-23
38464-6540	12-Oct-23
99654	12-Oct-23
94123	12-Oct-23
89048	12-Oct-23
35173-1132	12-Oct-23
16238	12-Oct-23
53548-8838	12-Oct-23
94954	12-Oct-23
77845-5685	12-Oct-23
12404	12-Oct-23
12010	12-Oct-23
89002-8743	12-Oct-23
54022-5915	12-Oct-23
40223	12-Oct-23
63028-4510	12-Oct-23
75229	12-Oct-23
30005	12-Oct-23
7621	12-Oct-23
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K9J 6X7	12-Oct-23
K0G 1L0	12-Oct-23
81543	12-Oct-23
98383	12-Oct-23
AB31 6DY	12-Oct-23
5000	12-Oct-23
T6H 3X9	12-Oct-23
98672	12-Oct-23
8833	12-Oct-23
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BD17 5BN	12-Oct-23
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22942	10-Oct-23
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49412	10-Oct-23
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76049	10-Oct-23
55126	10-Oct-23
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7922	10-Oct-23
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37072	10-Oct-23
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1129	10-Oct-23
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T3C 2Z1	10-Oct-23
T2M 2H8	10-Oct-23
V6L 1A1	10-Oct-23
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J0J 1Y0	10-Oct-23
H7K 3C1	10-Oct-23
L9Y 0A3	10-Oct-23
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M4L 1P4	10-Oct-23
N3B 3L9	10-Oct-23
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M5R 3B2	10-Oct-23
K0C 2J0	10-Oct-23
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45332	10-Oct-23
175	10-Oct-23
624	10-Oct-23
87144	10-Oct-23
1000	10-Oct-23
P0J 1K0	10-Oct-23
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4218	04-Oct-23
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28023	04-Oct-23
T6R 0W3	04-Oct-23
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1067	04-Oct-23
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ME13 8BZ	28-Sep-23
WS9 8RF	28-Sep-23
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3237	26-Sep-23
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233-0013	25-Sep-23
98383	25-Sep-23
ME5 7RU	25-Sep-23
GL6 8JY	25-Sep-23
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3523 RH	25-Sep-23
2750-568	25-Sep-23
R14 AY20	25-Sep-23
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SL2 1TN	22-Sep-23
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L7G 5Z1	21-Sep-23
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76017-6568	16-Sep-23
TN2 5LP	16-Sep-23
32174	15-Sep-23
45011-5592	15-Sep-23
48088	15-Sep-23
78041-1910	15-Sep-23
5353	15-Sep-23
27516	15-Sep-23
33322	14-Sep-23
16238	14-Sep-23
89429	14-Sep-23
92024	14-Sep-23
98605	14-Sep-23
19933	14-Sep-23
55321	14-Sep-23
20770	14-Sep-23
48068	14-Sep-23
49651-8657	14-Sep-23
49038-9304	14-Sep-23
26753-9571	14-Sep-23
22039	14-Sep-23
97756-7533	14-Sep-23
20175	14-Sep-23
22182-1716	14-Sep-23
07755-1113	14-Sep-23
20850-3751	14-Sep-23
46064	14-Sep-23
46581	14-Sep-23
46220-2924	14-Sep-23
46032	14-Sep-23
33444	14-Sep-23
45458-4037	14-Sep-23
46032-8260	14-Sep-23
45066-7401	14-Sep-23
44145-4666	14-Sep-23
46226-4438	14-Sep-23
92866	14-Sep-23
22724-2018	14-Sep-23
22039-1528	14-Sep-23
45159	14-Sep-23
45159	14-Sep-23
45159	14-Sep-23
M1E 5B6	14-Sep-23
G73 3NX	14-Sep-23
22044	14-Sep-23
47460	14-Sep-23
30019	14-Sep-23
48317-3438	14-Sep-23
47960	14-Sep-23
47960	14-Sep-23
78109	13-Sep-23
77619	13-Sep-23
33417-5816	13-Sep-23
44081-9554	13-Sep-23
30606	13-Sep-23
63010	13-Sep-23
59714-4044	13-Sep-23
28462-3332	13-Sep-23
8757	13-Sep-23
06716-2925	13-Sep-23

 

[alansidman]

this Mcode in Power query will tell you how many times the items in Col A appear.

let
Source = Excel.CurrentWorkbook(){[Name="Table2"]}[Content],
#"Changed Type" = Table.TransformColumnTypes(Source,{{"DateCompletedGMT", type date}}),
#"Grouped Rows" = Table.Group(#"Changed Type", {"BillingZipPostalCode"}, {{"Data", each _, type table [BillingZipPostalCode=any, DateCompletedGMT=nullable date]}}),
#"Added Custom" = Table.AddColumn(#"Grouped Rows", "Custom", each Table.AddIndexColumn([Data],"Index",1,1)),
#"Removed Columns" = Table.RemoveColumns(#"Added Custom",{"Data"}),
#"Expanded Custom" = Table.ExpandTableColumn(#"Removed Columns", "Custom", {"DateCompletedGMT", "Index"}, {"DateCompletedGMT", "Index"})
in
#"Expanded Custom"

 

[alansidman]

Here is another solution that shows the items in column A and the number of visits.

let
    Source = Excel.CurrentWorkbook(){[Name="Table1"]}[Content],
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"DateCompletedGMT", type date}, {"BillingZipPostalCode", type text}}),
    #"Grouped Rows" = Table.Group(#"Changed Type", {"BillingZipPostalCode"}, {{"Count", each Table.RowCount(_), Int64.Type}}),
    #"Filtered Rows" = Table.SelectRows(#"Grouped Rows", each ([Count] <> 1))
in
    #"Filtered Rows"

BillingZipPostalCode	Count
L7G 5Z1	5
M8W 0B6	2
94123	2
16238	2
40223	2
98383	2
22942	2
20176	2
92067	2
52761	2
8080	2
10708	2
92544-8478	2
RM16 2RS	2
99403	2
85658	2
92260	2
98029-5705	2
20129	2
L6J 1K4	2
V7R 4B2	2
43701-9056	2
44256	2
47460	2
33704	2
48068	2
46112-8134	2
46074-8741	2
40601	2
45159	3
47960	2

 

[JGordon11]

I'm sure this would be a lot easier with a pivot table and DAX, but I don't know DAX for %$#@.

So here is power query imitating a pivot table.

let
    Source = Excel.CurrentWorkbook(){[Name="Table1"]}[Content],
    tbl = Table.TransformColumnTypes(Source,{{"Date", type date}}),
    tbl1 = Table.TransformColumns(tbl,{{"Date", Date.Year, Int64.Type}}),
    tbl2 = Table.Group(tbl1, {"CustomerID"}, {{"All", each _}}),
    tbl3 = List.Accumulate({ List.Min(tbl1[Date]) .. List.Max(tbl1[Date]) }, tbl2, (s,c)=> 
        Table.AddColumn(s, Text.From(c), each Table.RowCount(Table.SelectRows([All],(x)=> x[Date]=c)))),
    tbl4 = Table.UnpivotOtherColumns(tbl3, {"CustomerID", "All"}, "Year", "Value"),
    tbl5 = Table.RemoveColumns(tbl4,{"CustomerID", "All"}),
    tbl6 = Table.Group(tbl5, {"Year"}, {{"All", each _}}),
    tbl7 = Table.AddColumn(tbl6, "Customers", each Table.RowCount(Table.SelectRows([All], (x)=> x[Value]>0))),
    tbl8 = List.Accumulate({1..4}, tbl7, (s,c)=> Table.AddColumn(s, Text.From(c) & " Orders", each Table.RowCount(Table.SelectRows([All], (x)=> x[Value] =c))/[Customers], Percentage.Type)),
    tbl9 = Table.AddColumn(tbl8, "5+ Orders", each Table.RowCount(Table.SelectRows([All], (x)=> x[Value] >4))/[Customers], Percentage.Type),
    tbl10 = Table.RemoveColumns(tbl9,{"All"}),
    Result = Table.RenameColumns(tbl10,{{"1 Orders", "1 Order"}})
in
    Result

Customers.xlsx
	A	B	C	D	E	F	G	H	I	J	K
1	Table1			Query Output
2	Date	CustomerID		Year	Customers	1 Order	2 Orders	3 Orders	4 Orders	5+ Orders
3	1/31/2021	N		2021	23	30.43%	26.09%	13.04%	17.39%	13.04%
4	2/14/2021	L		2022	25	12.00%	24.00%	24.00%	36.00%	4.00%
5	6/15/2022	Y		2023	22	4.55%	40.91%	31.82%	18.18%	4.55%
6	6/23/2023	A
7	7/30/2021	K
8	11/12/2021	J
9	12/2/2021	P
10	10/16/2021	G
11	3/17/2023	N
12	12/1/2022	A
13	3/8/2023	O
14	9/29/2022	Q
15	2/25/2021	T
16	12/22/2021	K
17	2/23/2023	D
18	9/18/2021	N
19	3/19/2023	Z
20	9/17/2022	B
21	5/13/2022	L
22	12/19/2021	T
23	7/30/2022	E
24	2/15/2022	P
25	8/10/2021	L
26	11/7/2022	A
27	10/8/2021	W
28	3/31/2023	V
29	12/28/2021	R
30	9/2/2023	Z
31	10/6/2022	F
32	4/15/2023	U
33	8/22/2023	W
34	2/5/2021	V
35	7/14/2023	O
36	9/25/2021	Q
37	3/27/2023	Y
38	2/21/2023	V
39	5/4/2021	Z
40	9/14/2022	J
41	8/3/2022	R
42	4/12/2022	A
43	7/3/2023	K
44	2/17/2023	K
45	2/16/2022	E
46	12/27/2022	T
47	5/27/2021	H
48	8/24/2021	E
49	5/24/2021	X
50	5/8/2023	A
51	6/23/2021	M
52	9/27/2023	X
53	4/28/2023	B
54	1/19/2022	J
55	8/21/2021	W
56	4/18/2021	K
57	2/23/2022	W
58	10/8/2022	P
59	12/13/2022	A
60	9/30/2023	D
61	11/20/2021	W
62	1/10/2023	W
63	7/15/2023	N
64	8/19/2022	X
65	1/29/2023	K
66	3/2/2023	P
67	6/3/2023	O
68	5/17/2023	A
69	4/20/2021	E
70	3/21/2021	P
71	7/28/2021	Y
72	8/23/2022	G
73	9/17/2023	I
74	9/22/2022	B
75	7/9/2021	C
76	10/19/2022	P
77	5/31/2022	R
78	7/1/2021	B
79	9/28/2023	V
80	7/2/2023	V
81	10/6/2023	Y
82	10/5/2021	E
83	6/11/2022	X
84	9/17/2021	K
85	5/21/2023	N
86	5/7/2021	E
87	9/15/2023	J
88	2/12/2022	W
89	5/12/2022	M
90	5/6/2021	C
91	2/14/2022	K
92	12/3/2021	J
93	5/27/2022	L
94	1/8/2023	Q
95	6/5/2023	P
96	2/20/2022	D
97	3/22/2022	K
98	1/28/2021	T
99	3/23/2023	F
100	8/29/2021	X
101	1/15/2022	F
102	9/2/2022	R
103	8/18/2023	M
104	2/24/2022	H
105	1/10/2022	C
106	1/29/2021	J
107	11/5/2022	Y
108	5/6/2023	F
109	2/3/2023	F
110	11/1/2022	Q
111	2/3/2022	D
112	10/13/2022	J
113	12/16/2021	N
114	7/3/2022	U
115	4/20/2021	Z
116	4/22/2023	J
117	3/9/2022	T
118	3/5/2022	Y
119	10/19/2022	J
120	2/18/2023	R
121	3/27/2022	I
122	7/27/2022	K
123	2/26/2021	Y
124	4/26/2023	O
125	11/4/2022	C
126	10/21/2021	X
127	9/27/2021	X
128	2/5/2022	W
129	6/14/2023	U
130	7/8/2021	Z
131	10/7/2022	U
132	10/11/2021	Y
133	6/4/2021	L
134	6/11/2022	W
135	6/25/2021	D
136	7/8/2021	G
137	2/13/2021	E
138	8/14/2023	S
139	5/6/2021	U
140	8/9/2021	Z
141	3/10/2022	B
142	7/4/2023	V
143	11/7/2021	A
144	12/14/2022	D
145	5/19/2022	N
146	3/28/2022	F
147	4/17/2023	H
148	8/7/2021	O
149	3/7/2022	A
150	12/4/2021	K
151	8/29/2022	T
152	10/15/2022	A
153	11/2/2022	A
154	9/19/2023	D
155	1/15/2023	I
156	4/8/2023	V
157	2/15/2022	R
158	1/24/2022	S
159	6/28/2023	K
160	3/13/2021	N
161	10/5/2022	Q
162	11/15/2022	N
163	2/4/2022	N
164	3/26/2023	E
165	12/20/2022	B
166	4/22/2023	B
167	1/11/2022	Q
168	1/18/2023	R
169	4/8/2023	N
170	10/16/2022	C
171	11/29/2021	Q
172	4/23/2021	R
173	8/26/2022	O
174	11/25/2022	P
175	2/15/2023	Y
176	12/26/2021	W
177	9/20/2022	H
178	11/7/2021	V
179	10/11/2021	X
180	9/9/2022	V
181	6/10/2023	E
182	8/11/2023	M
183	5/6/2022	N
184	6/14/2023	Z
185	10/31/2022	L
186	4/27/2023	P
187	7/9/2023	H
188	4/9/2023	S
189	3/3/2022	G
190	3/22/2023	Q
191	4/2/2023	B
192	5/24/2022	C
193	8/31/2021	K
194	1/9/2023	W
195	8/10/2023	Y
196	8/20/2022	M
197	1/15/2022	G
198	3/18/2022	I
199	7/31/2021	J
200	10/7/2022	L
201
Sheet2