this query performs aggregations to find Power Users on GA4 sample data from Google Merchandise Score

bq_standard_page_power_user_agg.sql

-- pulling user page views from GA4 events
WITH base_table AS (
  SELECT
    event_name,
    event_date,
    event_timestamp,
    user_pseudo_id,
    user_id,
    device,
    geo,
    traffic_source,
    event_params,
    user_properties
  FROM
    `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_*`
  WHERE
    _table_suffix >= '20210101'
  AND event_name IN ('page_view')
)
, unnested_events AS (
  SELECT
    event_date AS date,
    event_timestamp AS event_timestamp_microseconds,
    user_pseudo_id,
    MAX(CASE WHEN c.key = 'ga_session_id' THEN c.value.int_value END) AS visitID,
    MAX(CASE WHEN c.key = 'ga_session_number' THEN c.value.int_value END) AS visitNumber,
    MAX(CASE WHEN c.key = 'page_title' THEN c.value.string_value END) AS page_title,
    MAX(CASE WHEN c.key = 'page_location' THEN c.value.string_value END) AS page_location
  FROM 
    base_table,
    UNNEST (event_params) c
  GROUP BY 1,2,3
)

, unnested_events_categorised AS (
  SELECT
  *,
  CASE WHEN ARRAY_LENGTH(SPLIT(page_location, '/')) >= 5 
            AND
            CONTAINS_SUBSTR(ARRAY_REVERSE(SPLIT(page_location, '/'))[SAFE_OFFSET(0)], '+')
            AND (LOWER(SPLIT(page_location, '/')[SAFE_OFFSET(4)]) IN 
                                        ('accessories','apparel','brands','campus+collection','drinkware',
                                          'electronics','google+redesign',
                                          'lifestyle','nest','new+2015+logo','notebooks+journals',
                                          'office','shop+by+brand','small+goods','stationery','wearables'
                                          )
                  OR
                  LOWER(SPLIT(page_location, '/')[SAFE_OFFSET(3)]) IN 
                                        ('accessories','apparel','brands','campus+collection','drinkware',
                                          'electronics','google+redesign',
                                          'lifestyle','nest','new+2015+logo','notebooks+journals',
                                          'office','shop+by+brand','small+goods','stationery','wearables'
                                          )
            )
            THEN 'PDP'
            WHEN NOT(CONTAINS_SUBSTR(ARRAY_REVERSE(SPLIT(page_location, '/'))[SAFE_OFFSET(0)], '+'))
            AND (LOWER(SPLIT(page_location, '/')[SAFE_OFFSET(4)]) IN 
                                        ('accessories','apparel','brands','campus+collection','drinkware',
                                          'electronics','google+redesign',
                                          'lifestyle','nest','new+2015+logo','notebooks+journals',
                                          'office','shop+by+brand','small+goods','stationery','wearables'
                                          )
                  OR 
                  LOWER(SPLIT(page_location, '/')[SAFE_OFFSET(3)]) IN 
                                          ('accessories','apparel','brands','campus+collection','drinkware',
                                            'electronics','google+redesign',
                                            'lifestyle','nest','new+2015+logo','notebooks+journals',
                                            'office','shop+by+brand','small+goods','stationery','wearables'
                                            )
            )
            THEN 'PLP'
        ELSE page_title
        END AS page_title_adjusted 

  FROM 
    unnested_events
)

, user_aggregations AS (
-- power users can be based on the distribution of users across the number of days they interacted with the feature on a monthly basis, but it does not work as well in this case
-- another approach is to see user distribution per action count
  SELECT
    page_title_adjusted,
    user_pseudo_id,
    COUNT(*) AS views,
    COUNT(DISTINCT date) days
  FROM 
    unnested_events_categorised
  WHERE page_title_adjusted IN ('PDP', 'PLP', 'Store search results', 'The Google Merchandise Store - Log In', 'Frequently Asked Questions', 'Page Unavailable')
  GROUP BY 1,2
)
SELECT
  page_title_adjusted,
  views,
  COUNT(DISTINCT user_pseudo_id) users
FROM 
  user_aggregations
GROUP BY 1,2