Analysis of paying subscribers

_sql/analytics/tts/tts_models.sql

@@ -48,11 +48,14 @@ select
     m.ietf_language_tag,
     m.title,
     u.username,
-    r.use_count
+    r.use_count,
+    m.created_at,
+    m.user_deleted_at,
+    m.mod_deleted_at
 from (
     select model_token, count(*) as use_count
     from tts_results
-    where created_at > ( CURDATE() - INTERVAL 5 DAY )
+    where created_at > ( CURDATE() - INTERVAL 12 HOUR )
     group by model_token
 ) as r
     join tts_models as m

_sql/analytics/users/paying_user_interests.sql

@@ -0,0 +1,38 @@
+-- noinspection SqlDialectInspectionForFile
+-- noinspection SqlNoDataSourceInspectionForFile
+-- noinspection SqlResolveForFile
+
+-- The most popular models amongst paying subscribers.
+-- This should give us insight as to which models subscribers pay us for.
+SELECT *
+FROM (
+         SELECT
+             t.token,
+             t.title,
+             count(*) as use_count,
+             t.text_pipeline_type,
+             t.ietf_language_tag,
+             t.created_at,
+             t.user_deleted_at,
+             t.mod_deleted_at
+         FROM
+             tts_inference_jobs as j
+                 JOIN
+             tts_models as t
+             ON
+                     t.token = j.model_token
+         WHERE j.maybe_creator_user_token IN
+               (
+                   select distinct user_token
+                   from user_subscriptions
+               )
+           AND
+                 j.created_at > ( CURDATE() - INTERVAL 1 MONTH )
+         GROUP BY t.token
+         ORDER BY use_count DESC
+     ) as x
+     WHERE
+        x.use_count > 10;
+
+
+