Dynamically compare week to week by cohorts - sql

Question

Objective:
Get Id logins in week 1. Then how many of those Ids logged in in Week 2.
Restart the same logic for Week 2 to Week 3.
Then week 3 and week 4 and so on... This exercise needs to be done every week.
The Ids need to be segmented by cohorts which are the month and year they subscribed.
Story:
First table (member) has the email and its creation date. The 2nd table (login table) is the login activity. First, I need to group emails by creation date(month-year) to create the cohorts.
Then, the login activity comparing week to week for each cohort. Is it possible
for this query to be dynamic each week?
Output:
The result should look like this:
+--------+--------+--------+--------+---------+
| Cohort | 2019-1 | 2019-2 | 2019-3 | 2019-4 |...
+--------+--------+--------+--------+---------+
| 2018-3 | 7000 | 6800 | 7400| 7100 |...
| 2018-4 | 6800 | 6500 | 8400| 8000 |...
| 2018-5 | 9500 | 8000 | 6400| 6200 |...
| 2018-6 | 9100 | 8500 | 8000| 7800 |...
| 2018-7 | 10000 | 8000 | 7000| 6800 |...
+--------+--------+--------+--------+---------+
What I tried:
SELECT CONCAT(DATEPART(YEAR,m.date_created),'-',DATEPART(MONTH,m.date_created)) AS Cohort
,CONCAT(subquery.[YYYY],'-',subquery.[ISO]) AS YYYY_ISO
,m.email
FROM member as m
INNER JOIN (SELECT DATEPART(YEAR,log.login_time) AS [YYYY]
,DATEPART(ISO_WEEK,log.login_time) AS [ISO]
,log.email
,ROW_NUMBER()
OVER(PARTITION BY
DATEPART(YEAR,log.login_time),
DATEPART(ISO_WEEK,log.login_time),
log.email
ORDER BY log.login_time ASC) AS Log_Rank
FROM login AS log
WHERE CAST(log.login_time AS DATE) >= '2019-01-01'
) AS subquery ON m.email=subquery.email AND Log_Rank = 1
ORDER BY cohort
Sample Data:
CREATE TABLE member
([email] varchar(50), [date_created] Datetime)
CREATE TABLE login
([email] varchar(50), [login_time] Datetime)
INSERT INTO member
VALUES
('player123#google.com', '2018-03-01 05:00:00'),
('player999#google.com', '2018-04-12 12:00:00'),
('player555#google.com', '2018-04-25 20:15:00')
INSERT INTO login
VALUES
('player123#google.com', '2019-01-07 05:30:00'),
('player123#google.com', '2019-01-08 08:30:00'),
('player123#google.com', '2019-01-15 06:30:00'),
('player999#google.com', '2019-01-08 11:30:00'),
('player999#google.com', '2019-01-10 07:30:00'),
('player555#google.com', '2019-01-08 04:30:00')