I need to query a 12, 24, 36 and 48 month total for each customer
I've got a dataset that includes customer information (customer_id, products, spend, qty, purchase_date, etc) I need to display the totals for the different periods per customer
SELECT customer_id, MIN(purchase_date) AS first_purchase,
SUM(CASE WHEN purchase_date BETWEEN MIN(purchase_date) AND DATETIME_ADD(MIN(purchase_date), INTERVAL 1 YEAR THEN spend END) AS 12_mnth_total,
SUM(CASE WHEN purchase_date BETWEEN MIN(purchase_date) AND DATETIME_ADD(MIN(purchase_date), INTERVAL 2 YEAR THEN spend END) AS 24_mnth_total,
SUM(CASE WHEN purchase_date BETWEEN MIN(purchase_date) AND DATETIME_ADD(MIN(purchase_date), INTERVAL 3 YEAR THEN spend END) AS 36_mnth_total,
SUM(CASE WHEN purchase_date BETWEEN MIN(purchase_date) AND DATETIME_ADD(MIN(purchase_date), INTERVAL 4 YEAR THEN spend END) AS 48_mnth_total
FROM SalesTable
GROUP BY customer_id, purchase_date
ORDER BY purchase_date
My query shows me the following error: Syntax error: Expected ")" but got keyword THEN
You seem to want to count from the first purchase. You cannot nest aggregation functions the way that you are doing it. Instead, use a window function to get the minimum date for each customer and then aggregate:
SELECT customer_id, MIN(purchase_date) AS first_purchase,
SUM(CASE WHEN purchase_date BETWEEN min_purchase_date AND DATETIME_ADD(min_purchase_date, INTERVAL 1 YEAR) THEN spend
END) AS 12_mnth_total,
SUM(CASE WHEN purchase_date BETWEEN min_purchase_date AND DATETIME_ADD(min_purchase_date, INTERVAL 2 YEAR) THEN spend
END) AS 24_mnth_total,
SUM(CASE WHEN purchase_date BETWEEN min_purchase_date AND DATETIME_ADD(min_purchase_date, INTERVAL 3 YEAR) THEN spend
END) AS 36_mnth_total,
SUM(CASE WHEN purchase_date BETWEEN min_purchase_date AND DATETIME_ADD(min_purchase_date, INTERVAL 4 YEAR) THEN spend
END) AS 48_mnth_total,
FROM (SELECT s.*,
MIN(purchase_date) OVER (PARTITION BY customer_id) as min_purchase_date
FROM SalesTable s
) t
GROUP BY customer_id
ORDER BY first_purchase;
You ca simplify the logic by removing the first comparison in the case:
SELECT customer_id, MIN(purchase_date) AS first_purchase,
SUM(CASE WHEN purchase_date <= DATETIME_ADD(min_purchase_date, INTERVAL 1 YEAR) THEN spend
END) AS 12_mnth_total,
SUM(CASE WHEN purchase_date <= DATETIME_ADD(min_purchase_date, INTERVAL 2 YEAR) THEN spend
END) AS 24_mnth_total,
SUM(CASE WHEN purchase_date <= DATETIME_ADD(min_purchase_date, INTERVAL 3 YEAR) THEN spend
END) AS 36_mnth_total,
SUM(CASE WHEN purchase_date <= DATETIME_ADD(min_purchase_date, INTERVAL 4 YEAR) THEN spend
END) AS 48_mnth_total,
FROM (SELECT s.*,
MIN(purchase_date) OVER (PARTITION BY customer_id) as min_purchase_date
FROM SalesTable s
) t
GROUP BY customer_id
ORDER BY first_purchase;
Any purchase is logically on or after the first one.
The function DATETIME_ADD is not closed. I put it here INTERVAL 1 YEAR")".
Wouldnt know the exact sintax but its a good guess.
SELECT customer_id, MIN(purchase_date) AS first_purchase,
SUM(CASE WHEN purchase_date BETWEEN MIN(purchase_date) AND DATETIME_ADD(MIN(purchase_date), INTERVAL 1 YEAR) THEN spend END) AS 12_mnth_total,
SUM(CASE WHEN purchase_date BETWEEN MIN(purchase_date) AND DATETIME_ADD(MIN(purchase_date), INTERVAL 2 YEAR) THEN spend END) AS 24_mnth_total,
SUM(CASE WHEN purchase_date BETWEEN MIN(purchase_date) AND DATETIME_ADD(MIN(purchase_date), INTERVAL 3 YEAR) THEN spend END) AS 36_mnth_total,
SUM(CASE WHEN purchase_date BETWEEN MIN(purchase_date) AND DATETIME_ADD(MIN(purchase_date), INTERVAL 4 YEAR) THEN spend END) AS 48_mnth_total
FROM SalesTable
GROUP BY customer_id, purchase_date
ORDER BY purchase_date
Related
I have a table with columns sales_date, sales_id, sales_region and I am looking to display the count of sales for the past 7 days, 20 days and YTD.
I have this query below that returns the correct count for 7 and 20 days but the YTD shows the count minus the 7 and 20 days. How can I tweak this query to show the YTD correctly? Thank you
select region,
case when current_date- sales_date <=7 then 'Past7'
when current_date- sales_date <=28 then 'Past20'
else 'YTD'
end as "trendsales",
count(*) as salescount
from sales_table
where sales_date >= '2022-01-01'
group by 1
you could pivot it a bit. 4 columns Region, YTD, Past7, and Past20 would be columns.
select region,
sum(case when current_date- sales_date <=7 then 1 else 0 end) as Past7,
sum(case when current_date- sales_date <=28 then 1 else 0 end) as Past20,
count(*) as YTD
from sales_table
where sales_date >= '2022-01-01'
group by 1
So I'm running this query to get the name of the customer, total amount ordered, and number of orders they've submitted. With this query, I get their entire history from March to July, what I want is the name, march amount total/# of orders, april amount total/# of orders, may amount total/# of orders, ..... etc.
SELECT customer_name,MONTH(created_on), SUM(amount), COUNT(order_id)
FROM customer_orders
WHERE created_on BETWEEN '2020-03-01' AND '2020-08-01'
GROUP BY customer_name, MONTH(created_on)
If you want the values in separate columns, then use conditional aggregation:
SELECT customer_name,
SUM(CASE WHEN MONTH(created_on) = 3 THEN amount END) as march_amount,
SUM(CASE WHEN MONTH(created_on) = 3 THEN 1 ELSE 0 END) as march_count,
SUM(CASE WHEN MONTH(created_on) = 4 THEN amount END) as april_amount,
SUM(CASE WHEN MONTH(created_on) = 4 THEN 1 ELSE 0 END) as april_count,
. . .
FROM customer_orders
WHERE created_on >= '2020-03-01' AND
created_on < '2020-08-01'
GROUP BY customer_name;
Notice that I changed the date filter so it does not include 2020-08-01.
I am trying to find the customer's repurchase rates from their first order date. For example, for 2016, how many customer purchased 1X in days 1-365 from their initial purchase, how many purchased twice etc.
I have a transaction_detail table which looks like below:
txn_date Customer_ID Transaction_Number Sales
1/2/2019 1 12345 $10
4/3/2018 1 65890 $20
3/22/2019 3 64453 $30
4/3/2019 4 88567 $20
5/21/2019 4 85446 $15
1/23/2018 5 89464 $40
4/3/2019 5 99674 $30
4/3/2019 6 32224 $20
1/23/2018 6 46466 $30
1/20/2018 7 56558 $30
I am able to find the customers who have shopped in 2016 and how many times have they repurchased in 2016, but I need to find the customer who have shopped in 2016 and how many times have they come back from their first purchase date.
I need a starting point for the query, I am not sure how to build this logic in my SQL code.
Any help would be appreciated.
I am using the below query:
WITH by_year
AS (SELECT
Customer_ID,
to_char(txn_date, 'YYYY') AS visit_year
FROM table
GROUP BY Customer_ID, to_char(txn_date, 'YYYY')),
with_first_year
AS (SELECT
Customer_ID,
visit_year,
FIRST_VALUE(visit_year) OVER (PARTITION BY Customer_ID ORDER BY visit_year) AS first_year
FROM by_year),
with_year_number
AS (SELECT
Customer_ID,
visit_year,
first_year,
(visit_year - first_year) AS year_number
FROM with_first_year)
SELECT
first_year AS first_year,
SUM(CASE WHEN year_number = 0 THEN 1 ELSE 0 END) AS year_0,
SUM(CASE WHEN year_number = 1 THEN 1 ELSE 0 END) AS year_1,
SUM(CASE WHEN year_number = 2 THEN 1 ELSE 0 END) AS year_2,
SUM(CASE WHEN year_number = 3 THEN 1 ELSE 0 END) AS year_3,
SUM(CASE WHEN year_number = 4 THEN 1 ELSE 0 END) AS year_4,
SUM(CASE WHEN year_number = 5 THEN 1 ELSE 0 END) AS year_5,
SUM(CASE WHEN year_number = 6 THEN 1 ELSE 0 END) AS year_6,
SUM(CASE WHEN year_number = 7 THEN 1 ELSE 0 END) AS year_7,
SUM(CASE WHEN year_number = 8 THEN 1 ELSE 0 END) AS year_8,
SUM(CASE WHEN year_number = 9 THEN 1 ELSE 0 END) AS year_9
FROM with_year_number
GROUP BY first_year
ORDER BY first_year
Use window functions and aggregation:
select cnt, count(*), min(customer_id), max(customer_id)
from (select customer_id, count(*) as cnt
from (select td.*,
min(txn_date) over (partition by Customer_ID) as min_txn_date
from transaction_detail td
) td
where txn_date >= min_txn_date and txn_date < min_txn_date + interval '365' day
group by customer_id
) c
group by cnt
order by cnt;
So as per my understanding, you want to know the count of the distinct person who first purchased in 2016 and repurchased after one year or more from date of purchase.
Select * from
(
Select customer_id,
Floor(months_between(txn_date, lead_txn_date)/12) as num_years
From
(
Select customer_id,
txn_date,
row_number() over (partition by Customer_ID order by txn_date) as rn,
lead(txn_date) over (partition by Customer_ID order by txn_date) as lead_txn_date
From your_table
)
Where txn_date >= date '2016-01-01'
and txn_date < date '2017-01-01'
and rn = 1
And months_between(txn_date, lead_txn_date) >= 12
)
Pivot
(
Count(1) for num_year in (1,2,3,4)
)
Ultimately, we are finding the number of years between first and second purchase of the customer. And first purchase must be in 2016.
Cheers!!
I am trying to write a SQL query that show the distribution of customers seniority since 2015/01/31:
Up to one month
Between one and six months
Between six months and one year
Over a year
I succeeded to split and group the number of months of the customers.
SELECT Seniority, COUNT(Customer_ID) [Number of Customers]
FROM
(SELECT Customer_ID,
DATEDIFF(MONTH, MIN(CONVERT(datetime, Order_Date)), '2015/01/31') Seniority
FROM Orders
GROUP BY Customer_ID) t
GROUP BY Seniority
How can I split by given ranges?
Expected:
Seniorty | Number of Customers
Up to one month | 0
Between one and six months | 14
Between six months and one year | 1
Over a year | 0
Use conditional aggregation:
WITH cte AS (
SELECT
'Up to one month' AS Seniority,
COUNT(CASE WHEN DATEDIFF(MONTH, Order_Date, '2015-01-31') < 1 THEN 1 END) AS [Number of Customers],
1 AS position
FROM Orders
UNION ALL
SELECT
'Between one and six months',
COUNT(CASE WHEN DATEDIFF(MONTH, Order_Date, '2015-01-31') >= 1 AND
DATEDIFF(MONTH, Order_Date, '2015-01-31') < 6 THEN 1 END),
2
FROM Orders
UNION ALL
SELECT
'Between six months and one year',
COUNT( CASE WHEN DATEDIFF(MONTH, Order_Date, '2015-01-31') >= 6 AND
DATEDIFF(MONTH, Order_Date, '2015-01-31') < 12 THEN 1 END),
3
FROM Orders
UNION ALL
SELECT
'Over a year',
COUNT(CASE WHEN DATEDIFF(MONTH, Order_Date, '2015-01-31') > 12 THEN 1 END),
4
FROM Orders
)
SELECT
Seniority,
[Number of Customers]
FROM cte
ORDER BY
position;
This answer assumes that the Order_Date column is already date or datetime. If not, then the first thing you should do is to convert this column to an actual date type.
WITH CTE AS (
SELECT CUSTOMER_ID,
CASE WHEN DATEDIFF(MONTH,'2015-01-31',ORDER_DATE)=1 THEN 'Up to one month'
WHEN DATEDIFF(MONTH,'2015-01-31',ORDER_DATE) BETWEEN 1 AND 6 THEN 'Between one and six months'
WHEN DATEDIFF(MONTH,'2015-01-31',ORDER_DATE) BETWEEN 6 AND 12 THEN 'Between six months and one year'
WHEN DATEDIFF(MONTH,'2015-01-31',ORDER_DATE)>12 THEN 'Over a year'
END AS SENIORITY
FROM ORDERS
)
SELECT SENIORITY AS 'Seniority', COUNT(CUSTOMER_ID) AS 'Number of Customers'
FROM CTE
WHERE SENIORITY IS NOT NULL
GROUP BY SENIORITY
SELECT SKU, SUM(CASE WHEN EXTRACT(MONTH FROM SALEDATE)=6 AND STYPE='P'
THEN AMT
END) AS VALUEJUNE,
SUM(CASE WHEN EXTRACT(MONTH FROM SALEDATE)=7 AND STYPE='P'
THEN AMT
END) AS VALUEJULY,
SUM(CASE WHEN EXTRACT(MONTH FROM SALEDATE)=8 AND STYPE='P'
THEN AMT
END) AS VALUEAUGUST
,(VALUEJUNE+VALUEJULY+VALUEAUGUST) AS totalsales
FROM TRNSACT
GROUP BY SKU
ORDER BY totalsales DESC ;
Put most of your query in a derived table, including the GROUP BY. Calculate totalsales on its result:
select sku, VALUEJUNE, VALUEJULY, VALUEAUGUST, (VALUEJUNE+VALUEJULY+VALUEAUGUST) AS totalsales
from
(
SELECT SKU,
SUM(CASE WHEN EXTRACT(MONTH FROM SALEDATE)=6 AND STYPE='P'
THEN AMT
END) AS VALUEJUNE,
SUM(CASE WHEN EXTRACT(MONTH FROM SALEDATE)=7 AND STYPE='P'
THEN AMT
END) AS VALUEJULY,
SUM(CASE WHEN EXTRACT(MONTH FROM SALEDATE)=8 AND STYPE='P'
THEN AMT
END) AS VALUEAUGUST
FROM TRNSACT
GROUP BY SKU
) dt
ORDER BY totalsales DESC ;