Creating conditional fields based upon previous month values

Question

I'm currently doing some work on a dataset that contains monthly data about the subscription status of users, where a given row shows whether a user is subscribed on a given month(shown as truncated date) in the following format:

+------------+------+---------------------+
|   month    | user | subscription_status |
+------------+------+---------------------+
| 2022-02-01 | 2345 | true                |
| 2022-01-01 | 2345 | false               |
| 2021-12-01 | 2345 | false               |
| 2022-02-01 | 4578 | true                |
| 2022-02-01 | 9548 | false               |
| 2022-02-01 | 1212 | true                |
|......                                   |
+------------+------+---------------------+

What I would like to do is query this data, but also generate a number of extra boolean fields whose values are conditional on the previous monthly subscription data for a given user, e.g:

• never_subscribed_ever(subscription_status is false for each month for a user)
• never_subscribed_last_6_months (subscription_status is false for the last 6 months only)
• first_subscribed (subscription_status is true for the first time)
• resubscribed (subscription_status is true after being false last month)

to give a table such as :

+------------+------+---------------------+-----------------------+--------------------------------+------------------+--------------+
|   month    | user | subscription_status | never_subscribed_ever | never_subscribed_last_6_months | first_subscribed | resubscribed |
+------------+------+---------------------+-----------------------+--------------------------------+------------------+--------------+

However I'm afraid that I am quite lost on how best to implement the logic which I plan to do using the lag function along with conditionals such as if/case when needed.

Can anyone help me get started on the best way to implement lag logic on a user level looking at various past timeframes per field?