Running 3 Month Count - sql

Question

I get a list of new accounts twice a month. Majority of my accounts have either gone through the funnel or can be categorized as a bad lead by the end of the third month. So I am working on sql query that will tell me the number of accounts in my funnel at each date when I received a new list.
Here is what I have been working with (Yes I joined table1 on itself):
select t.receiveddate, count(*)
from table1 t
join table1 t2 on t2.number = t.number
and (t2.receiveddate > Dateadd(month , -3, t.received) AND t2.receiveddate<=
t.receiveddate)
group by t.receiveddate
What I am hoping to end up with is a list of the dates that I receive new business, with a count of how many accounts are in the funnel (accounts that I received no more than 3 months ago). The count should include the new accounts received on that date as well.
Here is an example, lets assume the business started on 1/1/2000, there is no one in the funnel for the first count. Lets also assume that I get 100 new accounts every time, just to make things simple for this example.
receiveddate Count
1/1/2000 100
1/15/2000 200
2/1/2000 300
2/15/2000 300
3/1/2000 300
3/15/2000 300

Answer 1

Welcome to Stack Overflow!
I see where you were going with that, but I would use a correlated sub-query, instead. I've included my sample data, which I randomized to make it similar to the real world - you can use an Update statement to change them all to 100 to validate the query):
create table Pipeline
(
ID int identity
, Received_Date Date
, Received_Count Int
)
Insert Into Pipeline
select '01/01/2018', 75 + (RAND() * 50)
union all select '01/15/2018', 75 + (RAND() * 50)
union all select '02/01/2018', 75 + (RAND() * 50)
union all select '02/15/2018', 75 + (RAND() * 50)
union all select '03/01/2018', 75 + (RAND() * 50)
union all select '03/15/2018', 75 + (RAND() * 50)
union all select '04/01/2018', 75 + (RAND() * 50)
union all select '04/15/2018', 75 + (RAND() * 50)
union all select '05/01/2018', 75 + (RAND() * 50)
union all select '05/15/2018', 75 + (RAND() * 50)
union all select '06/01/2018', 75 + (RAND() * 50)
union all select '06/15/2018', 75 + (RAND() * 50)
select * from Pipeline -- so you can see the values you got
select
P1.Received_Date
, (Select Sum(P2.Received_Count)
from Pipeline as P2
Where P2.Received_Date > DateAdd(MONTH, -3, P1.Received_Date)
and P2.Received_Date <= P1.Received_Date
) As Pipeline_Total
from Pipeline as P1

Answer 2

Your question is not entirely clear. I assume that you have a table of accounts, and for each account you have the received-date.
-- One record per account, each with a received-date
create table Account ( AccountID int identity(1,1),
ReceivedDate date )
-- Populate with 1000 random received-dates.
-- DateAdd(month,... gives a range of 60 months
-- DateAdd(day,... forces either 1st or 15th of the month
-- Of course, the query below will work regardless of the
-- distribution of dates
declare #k int
set #k = 0
while #k < 1000
begin
insert into Account ( ReceivedDate ) values
( DateAdd ( day, 14*cast( 2*rand()as int),
DateAdd ( month, cast(60*rand()as int), '2000-01-01' ) ) )
set #k = #k + 1
end
-- Let's see the list of dates
select * from Account
-- T1 is the list of DISTINCT received-dates
-- Other than that this query almost matches your own attempt
select T1.ReceivedDate, count(*) as InFunnel
from
(select distinct ReceivedDate from Account) T1,
Account T2
where T2.ReceivedDate > DateAdd ( month, -3, T1.ReceivedDate )
and T2.ReceivedDate <= T1.ReceivedDate
group by T1.ReceivedDate
order by T1.ReceivedDate