Strategy
- Optimize pricing plan
- New core features
History
Month | Average Monthly Revenue Per Customer |
June 2023 | ₩10,325 |
May 2023 | ₩9,739 |
Apr 2023 | ₩8,746 |
Mar 2023 | ₩7,865 |
Feb 2023 | ₩7,600 |
Jan 2023 | ₩7,419 |
Dec 2022 | ₩7,307 |
Nov 2022 | ₩7,206 |
Oct 2022 | ₩7,361 |
Sep 2022 | ₩7,249 |
Aug 2022 | ₩7,271 |
July 2022 | ₩7,315 |
Jun 2022 | ₩7,404 |
May 2022 | ₩7,393 |
Apr 2022 | ₩7,373 |
Mar 2022 | ₩7,415 |
Feb 2022 | ₩7,161 |
Jan 2022 | ₩7,122 |
Calculation
Total Average
SET @target_month = '2023-05-01';
SELECT AVG(
CASE
WHEN lang = 'en' THEN ROUND(amount_remaining*1200/ROUND(DATEDIFF(end_date, start_date)/30))
WHEN payment_key LIKE '%premium_12%' AND lang = 'ko' THEN 17491
ELSE ROUND(amount_remaining/ROUND(DATEDIFF(end_date, start_date)/30))
END
)
FROM payment
WHERE amount_remaining > 0
AND (lang = 'ko' OR lang = 'en')
AND start_date < DATE_ADD(@target_month, INTERVAL 1 MONTH)
AND end_date > DATE_ADD(@target_month, INTERVAL 1 MONTH)
AND is_pending != 1
AND payment_key NOT LIKE '%daypass%'
AND payment_key NOT LIKE '%indian%';
SQL
복사