Grouping by financial year and applying these groups as filters

Question

I am looking to set up 6 groups into which customers would fall into:

Non-purchaser (never bought from us)
New purchaser (purchased for the first time within the current financial year)
Reactivated purchaser (purchased in the current financial year, and also in the 2nd most recent year)
Lapsed purchaser (purchased in the prior financial year but not the current one)
2 yr Consecutive purchaser (has purchased in the current financial year and the most recent one)
3-4 yr consecutive purchaser (has purchased in every year for the last 3 or 4 financial years)
5+ year consecutive purchaser (has purchased in every financial year for a minimum of 5 years)

The financial year I would be using would be from 1st april to 31st march, and would use the following tables:

purchaser (including id (primary key))

purchases (date_purchased, purchases_purchaser_id)

Where the tables are joined on purchaser_id = purchases_purchaser_id and each purchaser can have multiple purchases withn any financial year (so could presumably be grouped by year as well)

It's been driving me mad so any help would be majorly appreciated!!!

Thanks, Davin

Answer 1

Here is dynamic version

Declare @currentYear int
Declare @OlderThan5yrs datetime 

Set @currentYear  = Year(GetDate()) - Case When month(GetDate())<4 then 1 else 0 end
Set @OlderThan5yrs = cast(cast( @currentYear-5 as varchar(4))+'/04/01' as datetime)

Select p.pName,
       p.purchaser_id,
       isNull(a.[5+YrAgo],0) as [5+YrAgo],
       isNull(a.[4YrAgo], 0)  as [4YrAgo],
       isNull(a.[3YrAgo], 0)  as [3YrAgo],
       isNull(a.[2YrAgo], 0)  as [2YrAgo],
       isNull(a.[1YrAgo], 0)  as [1YrAgo],
       isNull(a.[CurYr],  0)   as [CurYr],
       isNull(a.Category, 'Non-purchaser (ever)') as Category
From purchasers p
Left Join 
(        
   Select purchases_purchaser_id, 
          [5] as [5+YrAgo],
          [4] as [4YrAgo],
          [3] as [3YrAgo],
          [2] as [2YrAgo],
          [1] as [1YrAgo],
          [0]  as [CurYr],
         Case When [4]+[3]+[2]+[1]+[0] = 5     Then '5+ year consecutive'
              When [2]+[1]+[0] = 3             Then '3-4 yr consecutive'
              When [1]+[0] = 2                 Then '2 yr Consecutive'
              When [1]=1 and [0]=0             Then 'Lapsed'
              When [2]=1 and [1]=0 and [0]=1   Then 'Reactivated'
              When [4]+[3]+[2]+[1]=0 and [0]=1 Then 'New'
              When [4]+[3]+[2]+[1]+[0] = 0     Then 'Non-purchaser (last 5 yrs)'
              Else 'non categorized'
         End as Category     
   From (
            Select purchases_purchaser_id, 
                   Case When date_purchased < @OlderThan5yrs Then 5 
                        Else @currentYear - Year(date_purchased)+ Case When month(date_purchased)<4 Then 1 else 0 end 
                     end as fiscalYear, count(*) as nPurchases
            From purchases 
            Group by purchases_purchaser_id,
                   Case When date_purchased < @OlderThan5yrs Then 5 
                        Else @currentYear - Year(date_purchased)+ Case When month(date_purchased)<4 Then 1 else 0 end 
                     end
         ) as AggData
   PIVOT ( count(nPurchases) for fiscalYear in ([5],[4],[3],[2],[1],[0]) ) pvt
) as a
on p.purchaser_id=a.purchases_purchaser_id

UPDATED:

Here is result with data I inserted in previous query (You will have to add # to table names in the query).

pName                purchaser_id 5+YrAgo 4YrAgo 3YrAgo 2YrAgo 1YrAgo CurYr Category
-------------------- ------------ ------- ------ ------ ------ ------ ----- --------------------------
Non-purchaser                   0       0      0      0      0      0     0 Non-purchaser (ever)
New purchaser                   1       0      0      0      0      0     1 New
Reactivated                     2       0      0      1      1      0     1 Reactivated
Lapsed                          3       0      0      0      1      1     0 Lapsed
2 yr Consecutive                4       0      0      0      0      1     1 2 yr Consecutive
3 yr consecutive                5       0      0      0      1      1     1 3-4 yr consecutive
4 yr consecutive                6       0      0      1      1      1     1 3-4 yr consecutive
5+ year consecutive             7       1      1      1      1      1     1 5+ year consecutive
Uncategorized                   8       0      0      1      0      0     0 non categorized
old one                         9       1      0      0      0      0     0 Non-purchaser (last 5 yrs)

You also don't need columns [5+YrAgo], [4YrAgo], [3YrAgo], [2YrAgo], [1YrAgo] and [CurYr]. I added them to be easier to check query logic.

UPDATE 2

Below is query you asked in comment. Note table structures I've used in query are:

Table purchasers ( purchaser_id int, pName varchar(20))
Table purchases (purchases_purchaser_id int, date_purchased datetime)

and there is Foreign key on purchases (purchases_purchaser_id) referencing purchases (purchaser_id).

;With AggData as (
Select   purchases_purchaser_id, 
         Case When [4]+[3]+[2]+[1]+[0] = 5     Then 1 end as [Consec5],
         Case When [4]=0 and [2]+[1]+[0] = 3   Then 1 end as [Consec34],
         Case When [2]=0 and [1]+[0] = 2       Then 1 end as [Consec2],
         Case When [1]=1 and [0]=0             Then 1 end as [Lapsed],
         Case When [2]=1 and [1]=0 and [0]=1   Then 1 end as [Reactivated],
         Case When [4]+[3]+[2]+[1]=0 and [0]=1 Then 1 end as [New],
         Case When [4]+[3]+[2]>0 and [1]+[0]=0 Then 1 end as [Uncateg]
   From  (
            Select purchases_purchaser_id, 
                   @currentYear - Year(date_purchased) + Case When month(date_purchased)<4 Then 1 else 0 end as fiscalYear, 
                   count(*) as nPurchases
              From purchases      
             Where date_purchased >= @OlderThan5yrs  
             Group by purchases_purchaser_id,
                      @currentYear - Year(date_purchased) + Case When month(date_purchased)<4 Then 1 else 0 end
         ) as AggData
   PIVOT ( count(nPurchases) for fiscalYear in ([4],[3],[2],[1],[0]) ) pvt
)
Select count([Consec5])     as [Consec5],
       count([Consec34])    as [Consec34],
       count([Consec2])     as [Consec2],
       count([Lapsed])      as [Lapsed],
       count([Reactivated]) as [Reactivated],
       count([New])         as [New],
       count(*)-count(a.purchases_purchaser_id) as [Non],
       count([Uncateg])     as [Uncateg]
  From purchasers p
 Left Join AggData as a
  on p.purchaser_id=a.purchases_purchaser_id              

Result (With test data from previous post)

Consec5 Consec34 Consec2 Lapsed Reactivated New Non Uncateg
------- -------- ------- ------ ----------- --- --- -------
      1        2       1      1           1   1   2       1

Answer 2

Although it COULD be done a bit easier with another table of date ranges showing the 5 fiscal years, I have hard-coded the from/to date references for your query and appears to be working...

The INNER Select will pre-gather a "flag" based on any 1 or more purchase within the given date range... ex: Apr 1, 2010 = "20100401" for date conversion to Mar 31, 2011 = "20110331", and cycle through last 5 years... Additionally, a flag to count for ANY with a date purchase within the actual purchases table to confirm a "never purchased" vs someone purchasing 6, 7 or older years history...

That queries' basis will basically create a cross-tab of possible individual years where activity has occurred. I can then query with the most detailed criteria for some caption of their classification down to the least...

I converted from another SQL language as best as possible to comply with SQL-Server syntax (mostly about the date conversion), but otherwise, the principle and queries do work... The final classification column is character, but can be whatever you want to supercede.

SELECT
      id,
      CASE 
         WHEN year1 + year2 + year3 + year4 + year5 = 5 THEN "5+yrs "
         WHEN year1 + year2 + year3 + year4 >= 3 THEN "3-4yrs"
         WHEN year1 + year2 = 2, "2yrs  "
         WHEN year1 = 1 AND year2 = 0 AND year3 = 1 THEN "Reacti"
         WHEN year1 = 1 THEN "New   "
         WHEN year1 = 0 AND year2 = 1 THEN "Lapsed"
         WHEN AnyPurchase = 1, "over5"
         ELSE "never" BuyerClassification
      END
   FROM
      ( SELECT
            id,
            MAX( CASE WHEN date_purchased >= CONVERT( Date, "20100401", 112 ) 
                       AND date_purchased <= CONVERT( Date, "20110331", 112 ) 
                 THEN 1 ELSE 0 END ) Year1,
            MAX( CASE WHEN date_purchased >= CONVERT( Date, "20090401", 112 ) 
                       AND date_purchased <= CONVERT( Date, "20100331", 112 )
                 THEN 1 ELSE 0 END ) Year2,
            MAX( CASE WEHEN date_purchased >= CONVERT( Date, "20080401", 112 ) 
                       AND date_purchased <= CONVERT( Date, "20090331", 112 )
                 THEN 1 ELSE 0 END ) Year3,
            MAX( CASE WHEN date_purchased >= CONVERT( Date, "20070401", 112 ) 
                       AND date_purchased <= CONVERT( Date, "20080331", 112 )
                 THEN 1 ELSE 0 END ) Year4,
            MAX( CASE WHEN date_purchased >= CONVERT( Date, "20060401", 112 ) 
                       AND date_purchased <= CONVERT( Date, "20070331", 112 )
                 THEN 1 ELSE 0 END ) Year5,
            MAX( CASE WHEN date_purchased <= CONVERT( Date, "20100401", 112 )
                 THEN 1 ELSE 0 END ) AnyPurchase
         FROM
            purchaser LEFT OUTER JOIN purchases
               ON purchaser.id = purchases.purchases_purchaser_id
         GROUP BY 
            1 ) PreGroup1

EDIT -- fixed parens via syntax conversion and missed it...

The "Group By 1" refers to doing a group by the first column in the query which is the purchaser's ID from the purchaser. By doing a left-outer join will guarantee all possible people in the purchasers table regardless of having any actual purchases. The "PreGroup1" is the "alias" of the select statement just in case you wanted to do other joins subsequent in the outer most select where detecting the year values for classification.

Although it will work, but may not be as efficient as others have chimed-in on by doing analysis of the query, it may open your mind to some querying and aggregating techniques. This process is basically creating a sort-of cross-tab by utilization of case/when construct on the inner SQL-Select, and final classification in the OUTER most SQL-Select.

Answer 3

MS SQL Server (works on 2000, 2005, 2008)

SET NOCOUNT ON

CREATE TABLE #purchasers (purchaser_id int, pName varchar(20))

Insert Into #purchasers values (0, 'Non-purchaser')
Insert Into #purchasers values (1, 'New purchaser')
Insert Into #purchasers values (2, 'Reactivated')
Insert Into #purchasers values (3, 'Lapsed')
Insert Into #purchasers values (4, '2 yr Consecutive')
Insert Into #purchasers values (5, '3 yr consecutive')
Insert Into #purchasers values (6, '4 yr consecutive')
Insert Into #purchasers values (7, '5+ year consecutive')
Insert Into #purchasers values (8, 'Uncategorized')
Insert Into #purchasers values (9, 'old one')


CREATE TABLE #purchases (date_purchased datetime, purchases_purchaser_id int)

Insert Into #purchases values ('2010/05/03', 1)

Insert Into #purchases values ('2007/05/03', 2)
Insert Into #purchases values ('2008/05/03', 2)
Insert Into #purchases values ('2010/05/03', 2)

Insert Into #purchases values ('2008/05/03', 3)
Insert Into #purchases values ('2009/05/03', 3)


Insert Into #purchases values ('2009/05/03', 4)
Insert Into #purchases values ('2010/05/03', 4)

Insert Into #purchases values ('2008/05/03', 5)
Insert Into #purchases values ('2009/05/03', 5)
Insert Into #purchases values ('2010/05/03', 5)

Insert Into #purchases values ('2007/05/03', 6)
Insert Into #purchases values ('2008/05/03', 6)
Insert Into #purchases values ('2009/05/03', 6)
Insert Into #purchases values ('2010/05/03', 6)

Insert Into #purchases values ('2004/05/03', 7)
Insert Into #purchases values ('2005/05/03', 7)
Insert Into #purchases values ('2006/05/03', 7)
Insert Into #purchases values ('2007/05/03', 7)
Insert Into #purchases values ('2008/05/03', 7)
Insert Into #purchases values ('2009/05/03', 7)
Insert Into #purchases values ('2009/05/03', 7)
Insert Into #purchases values ('2009/05/03', 7)
Insert Into #purchases values ('2010/05/03', 7)

Insert Into #purchases values ('2007/05/03', 8)

Insert Into #purchases values ('2000/05/03', 9)

Select p.pName,
       p.purchaser_id,
       isNull(a.[2005],0) as [Bef.2006],
       isNull(a.[2006],0) as [2006],
       isNull(a.[2007],0) as [2007],
       isNull(a.[2008],0) as [2008],
       isNull(a.[2009],0) as [2009],
       isNull(a.[2010],0) as [2010],
       isNull(a.Category, 'Non-purchaser') as Category
From #purchasers p
Left Join 
(        
   Select purchases_purchaser_id, [2005],[2006],[2007],[2008],[2009],[2010],
         Case When [2006]+[2007]+[2008]+[2009]+[2010] = 5 Then '5+ year consecutive'
              When [2008]+[2009]+[2010] = 3               Then '3-4 yr consecutive'
              When [2009]+[2010] = 2                      Then '2 yr Consecutive'
              When [2009]=1 and [2010]=0                  Then 'Lapsed'
              When [2008]=1 and [2009]=0 and [2010]=1     Then 'Reactivated'
              When [2006]+[2007]+[2008]+[2009]=0 and [2010]=1 Then 'New'
              When [2006]+[2007]+[2008]+[2009]+[2010] = 0 Then 'Non-purchaser in last 5 yrs'
              Else 'non categorized'
         End as Category     
   From (
            Select purchases_purchaser_id, 
                   Case When date_purchased < '2006/04/01' Then 2005 
                        Else Year(date_purchased)- Case When month(date_purchased)<4 Then -1 else 0 end 
                     end as fiscalYear, count(*) as nPurchases
            From #purchases 
            Group by purchases_purchaser_id,
                     Case When date_purchased < '2006/04/01' Then 2005 
                        Else Year(date_purchased)- Case When month(date_purchased)<4 Then -1 else 0 end 
                     end
         ) as AggData
   PIVOT ( count(nPurchases) for fiscalYear in ([2005],[2006],[2007],[2008],[2009],[2010]) ) pvt
) as a
on p.purchaser_id=a.purchases_purchaser_id