Kueri lanjutan

Kueri lanjutan di halaman ini berlaku untuk data ekspor peristiwa BigQuery untuk di Google Analytics. Lihat Cookbook BigQuery untuk Universal Analytics jika Anda mencari referensi yang sama untuk Universal Analytics. Coba kueri dasar terlebih dahulu sebelum mencoba kueri lanjutan.

Produk yang dibeli oleh pelanggan yang membeli produk tertentu

Kueri berikut menunjukkan apa saja produk lainnya yang dibeli oleh pelanggan yang membeli produk tertentu. Contoh ini tidak mengasumsikan bahwa produk dibeli dalam pesanan yang sama.

Contoh yang dioptimalkan bergantung pada fitur skrip BigQuery untuk menentukan variabel yang mendeklarasikan item yang akan difilter. Meskipun jika tidak meningkatkan performa, hal ini adalah pendekatan yang lebih mudah dibaca untuk menentukan variabel dibandingkan membuat satu tabel nilai menggunakan klausa WITH. Kueri yang disederhanakan akan menggunakan pendekatan terakhir dengan klausa WITH.

Kueri yang disederhanakan akan membuat daftar "Pembeli Produk A" yang terpisah dan menggabungkan data tersebut. Kueri yang dioptimalkan akan membuat daftar semua item yang telah dibeli pengguna di seluruh pesanan menggunakan fungsi ARRAY_AGG. Selanjutnya, menggunakan klausa WHERE luar, daftar pembelian dari semua pengguna difilter untuk target_item dan hanya item yang relevan yang ditampilkan.

Sederhana

-- Example: Products purchased by customers who purchased a specific product.
--
-- `Params` is used to hold the value of the selected product and is referenced
-- throughout the query.

WITH
  Params AS (
    -- Replace with selected item_name or item_id.
    SELECT 'Google Navy Speckled Tee' AS selected_product
  ),
  PurchaseEvents AS (
    SELECT
      user_pseudo_id,
      items
    FROM
      -- Replace table name.
      `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_*`
    WHERE
      -- Replace date range.
      _TABLE_SUFFIX BETWEEN '20201101' AND '20210131'
      AND event_name = 'purchase'
  ),
  ProductABuyers AS (
    SELECT DISTINCT
      user_pseudo_id
    FROM
      Params,
      PurchaseEvents,
      UNNEST(items) AS items
    WHERE
      -- item.item_id can be used instead of items.item_name.
      items.item_name = selected_product
  )
SELECT
  items.item_name AS item_name,
  SUM(items.quantity) AS item_quantity
FROM
  Params,
  PurchaseEvents,
  UNNEST(items) AS items
WHERE
  user_pseudo_id IN (SELECT user_pseudo_id FROM ProductABuyers)
  -- item.item_id can be used instead of items.item_name
  AND items.item_name != selected_product
GROUP BY 1
ORDER BY item_quantity DESC;

Dioptimalkan

-- Optimized Example: Products purchased by customers who purchased a specific product.

-- Replace item name
DECLARE target_item STRING DEFAULT 'Google Navy Speckled Tee';

SELECT
  IL.item_name AS item_name,
  SUM(IL.quantity) AS quantity
FROM
  (
    SELECT
      user_pseudo_id,
      ARRAY_AGG(STRUCT(item_name, quantity)) AS item_list
    FROM
      -- Replace table
      `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_*`, UNNEST(items)
    WHERE
      -- Replace date range
      _TABLE_SUFFIX BETWEEN '20201201' AND '20201210'
      AND event_name = 'purchase'
    GROUP BY
      1
  ),
  UNNEST(item_list) AS IL
WHERE
  target_item IN (SELECT item_name FROM UNNEST(item_list))
  -- Remove the following line if you want the target_item to appear in the results
  AND target_item != IL.item_name
GROUP BY
  item_name
ORDER BY
  quantity DESC;

Jumlah rata-rata uang yang dibelanjakan per sesi pembelian oleh pengguna

Kueri berikut menunjukkan jumlah rata-rata uang yang dibelanjakan per sesi oleh setiap pengguna. Ini hanya memperhitungkan sesi tempat pengguna melakukan pembelian.

-- Example: Average amount of money spent per purchase session by user.

WITH
  events AS (
    SELECT
      session.value.int_value AS session_id,
      COALESCE(spend.value.int_value, spend.value.float_value, spend.value.double_value, 0.0)
        AS spend_value,
      event.*

    -- Replace table name
    FROM `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_*` AS event
    LEFT JOIN UNNEST(event.event_params) AS session
      ON session.key = 'ga_session_id'
    LEFT JOIN UNNEST(event.event_params) AS spend
      ON spend.key = 'value'

    -- Replace date range
    WHERE _TABLE_SUFFIX BETWEEN '20201101' AND '20210131'
  )
SELECT
  user_pseudo_id,
  COUNT(DISTINCT session_id) AS session_count,
  SUM(spend_value) / COUNT(DISTINCT session_id) AS avg_spend_per_session_by_user
FROM events
WHERE event_name = 'purchase' and session_id IS NOT NULL
GROUP BY user_pseudo_id

ID Sesi dan Nomor Sesi terbaru untuk pengguna

Kueri berikut memberikan daftar ga_session_id dan ga_session_number terbaru dari 4 hari terakhir untuk satu daftar pengguna. Anda dapat memberikan daftar user_pseudo_id atau daftar user_id.

user_pseudo_id

-- Get the latest ga_session_id and ga_session_number for specific users during last 4 days.

-- Replace timezone. List at https://en.wikipedia.org/wiki/List_of_tz_database_time_zones.
DECLARE REPORTING_TIMEZONE STRING DEFAULT 'America/Los_Angeles';

-- Replace list of user_pseudo_id's with ones you want to query.
DECLARE USER_PSEUDO_ID_LIST ARRAY<STRING> DEFAULT
  [
    '1005355938.1632145814', '979622592.1632496588', '1101478530.1632831095'];

CREATE TEMP FUNCTION GetParamValue(params ANY TYPE, target_key STRING)
AS (
  (SELECT `value` FROM UNNEST(params) WHERE key = target_key LIMIT 1)
);

CREATE TEMP FUNCTION GetDateSuffix(date_shift INT64, timezone STRING)
AS (
  (SELECT FORMAT_DATE('%Y%m%d', DATE_ADD(CURRENT_DATE(timezone), INTERVAL date_shift DAY)))
);

SELECT DISTINCT
  user_pseudo_id,
  FIRST_VALUE(GetParamValue(event_params, 'ga_session_id').int_value)
    OVER (UserWindow) AS ga_session_id,
  FIRST_VALUE(GetParamValue(event_params, 'ga_session_number').int_value)
    OVER (UserWindow) AS ga_session_number
FROM
  -- Replace table name.
  `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_*`
WHERE
  user_pseudo_id IN UNNEST(USER_PSEUDO_ID_LIST)
  AND RIGHT(_TABLE_SUFFIX, 8)
    BETWEEN GetDateSuffix(-3, REPORTING_TIMEZONE)
    AND GetDateSuffix(0, REPORTING_TIMEZONE)
WINDOW UserWindow AS (PARTITION BY user_pseudo_id ORDER BY event_timestamp DESC);

user_id

-- Get the latest ga_session_id and ga_session_number for specific users during last 4 days.

-- Replace timezone. List at https://en.wikipedia.org/wiki/List_of_tz_database_time_zones.
DECLARE REPORTING_TIMEZONE STRING DEFAULT 'America/Los_Angeles';

-- Replace list of user_id's with ones you want to query.
DECLARE USER_ID_LIST ARRAY<STRING> DEFAULT ['<user_id_1>', '<user_id_2>', '<user_id_n>'];

CREATE TEMP FUNCTION GetParamValue(params ANY TYPE, target_key STRING)
AS (
  (SELECT `value` FROM UNNEST(params) WHERE key = target_key LIMIT 1)
);

CREATE TEMP FUNCTION GetDateSuffix(date_shift INT64, timezone STRING)
AS (
  (SELECT FORMAT_DATE('%Y%m%d', DATE_ADD(CURRENT_DATE(timezone), INTERVAL date_shift DAY)))
);

SELECT DISTINCT
  user_pseudo_id,
  FIRST_VALUE(GetParamValue(event_params, 'ga_session_id').int_value)
    OVER (UserWindow) AS ga_session_id,
  FIRST_VALUE(GetParamValue(event_params, 'ga_session_number').int_value)
    OVER (UserWindow) AS ga_session_number
FROM
  -- Replace table name.
  `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_*`
WHERE
  user_id IN UNNEST(USER_ID_LIST)
  AND RIGHT(_TABLE_SUFFIX, 8)
    BETWEEN GetDateSuffix(-3, REPORTING_TIMEZONE)
    AND GetDateSuffix(0, REPORTING_TIMEZONE)
WINDOW UserWindow AS (PARTITION BY user_pseudo_id ORDER BY event_timestamp DESC);