Bu örnek sorgularda SQL ve BigQuery hakkında bilgi sahibi olduğunuz varsayılır. BigQuery'deki SQL hakkında daha fazla bilgi edinin.
Campaign Manager 360 Veri Aktarımı sorguları
Floodlight değişkenlerini geçici tablolarla eşleştirme
Etkinlik tablosunda user_id ile özel Floodlight değişkenleri arasında bir eşleştirme oluşturun. Bu eşleştirme, daha sonra birinci taraf verilerini Campaign Manager 360 verileriyle birleştirmek için kullanılabilir.
/* Creating the match temp table. This can be a separate query and the
temporary table will persist for 72 hours. */
CREATE TABLE
temp_table AS (
SELECT
user_id,
REGEXP_EXTRACT(event.other_data, 'u1=([^;]*)') AS u1_val
FROM
adh.cm_dt_activities_attributed
GROUP BY
1,
2 )
/* Matching to Campaign Manager 360 impression data */
SELECT
imp.event.campaign_id,
temp.u1_val,
COUNT(*) AS cnt
FROM
adh.cm_dt_impressions AS imp
JOIN
tmp.temp_table AS temp USING (user_id)
GROUP BY
1,
2
Gösterim yayını
Gösterim yönetimi için uygun olan bu örnek, sıklık sınırları dışında sunulan gösterimlerin sayısını gösterir veya belirli potansiyel müşterilere reklamların yeterince gösterilip gösterilmediğini belirtir. Sitelerinizi ve taktiklerinizi optimize etmek için bu bilgilerden yararlanarak seçtiğiniz bir kitleye doğru sayıda gösterim yayınlayın.
/* For this query to run, @advertiser_ids and @campaigns_ids
must be replaced with actual IDs. For example [12345] */
WITH filtered_uniques AS (
SELECT
user_id,
COUNT(event.placement_id) AS frequency
FROM adh.cm_dt_impressions
WHERE user_id != '0'
AND event.advertiser_id IN UNNEST(@advertiser_ids)
AND event.campaign_id IN UNNEST(@campaign_ids)
AND event.country_domain_name = 'US'
GROUP BY user_id
)
SELECT
frequency,
COUNT(*) AS uniques
FROM filtered_uniques
GROUP BY frequency
ORDER BY frequency
;
Toplam tekil çerez sayısı/sıklığı
Bu örnek, benzersiz çerez sayısı veya sıklığında artışa ya da düşüşe neden olan taktikleri ve reklam biçimlerini belirlemeye yardımcı olur.
/* For this query to run, @advertiser_ids and @campaigns_ids and @placement_ids
must be replaced with actual IDs. For example [12345] */
SELECT
COUNT(DISTINCT user_id) AS total_users,
COUNT(DISTINCT event.site_id) AS total_sites,
COUNT(DISTINCT device_id_md5) AS total_devices,
COUNT(event.placement_id) AS impressions
FROM adh.cm_dt_impressions
WHERE user_id != '0'
AND event.advertiser_id IN UNNEST(@advertiser_ids)
AND event.campaign_id IN UNNEST(@campaign_ids)
AND event.placement_id IN UNNEST(@placement_ids)
AND event.country_domain_name = 'US'
;
Sorgunuzu daraltmak için WHERE yan tümcesine site veya yerleşim kimlikleri de ekleyebilirsiniz.
Durum bazında toplam tekil çerez sayısı ve ortalama sıklığı
Bu örnek, cm_dt_impressions
tablosu ile cm_dt_state
meta veri tablosunu birleştirerek toplam gösterim sayısını, duruma göre çerez sayısını ve kullanıcı bazında ortalama gösterimi, Kuzey Amerika'daki coğrafi eyaletlere veya bölgelere göre gruplandırarak gösterir.
WITH impression_stats AS (
SELECT
event.country_domain_name AS country,
CONCAT(event.country_domain_name, '-', event.state) AS state,
COUNT(DISTINCT user_id) AS users,
COUNT(*) AS impressions
FROM adh.cm_dt_impressions
WHERE event.country_domain_name = 'US'
OR event.country_domain_name = 'CA'
GROUP BY 1, 2
)
SELECT
country,
IFNULL(state_name, state) AS state_name,
users,
impressions,
FORMAT(
'%0.2f',
IF(
IFNULL(impressions, 0) = 0,
0,
impressions / users
)
) AS avg_imps_per_user
FROM impression_stats
LEFT JOIN adh.cm_dt_state USING (state)
;
Display & Video 360 kitleleri
Bu örnek, Display & Video 360 kitlelerinin nasıl analiz edileceğini gösterir. Gösterimlerin hangi kitlelere ulaştığını öğrenin ve bazı kitlelerin diğerlerinden daha iyi performans gösterip göstermediğini belirleyin. Bu bilgi, hedeflerinize bağlı olarak tekil çerez sayısını (reklamları çok sayıda kullanıcıya gösterme) ve kalitesini (dar hedefleme ve görüntülenebilir gösterimler) dengelemenize yardımcı olabilir.
/* For this query to run, @advertiser_ids and @campaigns_ids and @placement_ids
must be replaced with actual IDs. For example [12345] */
WITH filtered_impressions AS (
SELECT
event.event_time as date,
CASE
WHEN (event.browser_enum IN ('29', '30', '31')
OR event.os_id IN
(501012, 501013, 501017, 501018,
501019, 501020, 501021, 501022,
501023, 501024, 501025, 501027))
THEN 'Mobile'
ELSE 'Desktop'
END AS device,
event.dv360_matching_targeted_segments,
event.active_view_viewable_impressions,
event.active_view_measurable_impressions,
user_id
FROM adh.cm_dt_impressions
WHERE event.dv360_matching_targeted_segments != ''
AND event.advertiser_id in UNNEST(@advertiser_ids)
AND event.campaign_id IN UNNEST(@campaign_ids)
AND event.dv360_country_code = 'US'
)
SELECT
audience_id,
device,
COUNT(*) AS impressions,
COUNT(DISTINCT user_id) AS uniques,
ROUND(COUNT(*) / COUNT(DISTINCT user_id), 1) AS frequency,
SUM(active_view_viewable_impressions) AS viewable_impressions,
SUM(active_view_measurable_impressions) AS measurable_impressions
FROM filtered_impressions
JOIN UNNEST(SPLIT(dv360_matching_targeted_segments, ' ')) AS audience_id
GROUP BY 1, 2
;
Görüntülenebilirlik
Bu örnek, Aktif Görüntüleme Plus görüntülenebilirlik metriklerinin nasıl ölçüleceğini gösterir.
WITH T AS (
SELECT cm_dt_impressions.event.impression_id AS Impression,
cm_dt_impressions.event.active_view_measurable_impressions AS AV_Measurable,
SUM(cm_dt_active_view_plus.event.active_view_plus_measurable_count) AS AVP_Measurable
FROM adh.cm_dt_impressions
FULL JOIN adh.cm_dt_active_view_plus
ON (cm_dt_impressions.event.impression_id =
cm_dt_active_view_plus.event.impression_id)
GROUP BY Impression, AV_Measurable
)
SELECT COUNT(Impression), SUM(AV_Measurable), SUM(AVP_Measurable)
FROM T
;
WITH Raw AS (
SELECT
event.ad_id AS Ad_Id,
SUM(event.active_view_plus_measurable_count) AS avp_total,
SUM(event.active_view_first_quartile_viewable_impressions) AS avp_1st_quartile,
SUM(event.active_view_midpoint_viewable_impressions) AS avp_2nd_quartile,
SUM(event.active_view_third_quartile_viewable_impressions) AS avp_3rd_quartile,
SUM(event.active_view_complete_viewable_impressions) AS avp_complete
FROM
adh.cm_dt_active_view_plus
GROUP BY
1
)
SELECT
Ad_Id,
avp_1st_quartile / avp_total AS Viewable_Rate_1st_Quartile,
avp_2nd_quartile / avp_total AS Viewable_Rate_2nd_Quartile,
avp_3rd_quartile / avp_total AS Viewable_Rate_3rd_Quartile,
avp_complete / avp_total AS Viewable_Rate_Completion_Quartile
FROM
Raw
WHERE
avp_total > 0
ORDER BY
Viewable_Rate_1st_Quartile DESC
;
Campaign Manager 360 Veri Aktarımı'ndaki dinamik veriler
Dinamik profil ve feed başına gösterim sayısı
SELECT
event.dynamic_profile,
feed_name,
COUNT(*) as impressions
FROM adh.cm_dt_impressions
JOIN UNNEST (event.feed) as feed_name
GROUP BY 1, 2;
Feed 1'deki dinamik raporlama etiketi başına gösterim sayısı
SELECT
event.feed_reporting_label[SAFE_ORDINAL(1)] feed1_reporting_label,,
COUNT(*) as impressions
FROM adh.cm_dt_impressions
WHERE event.feed_reporting_label[SAFE_ORDINAL(1)] <> “” # where you have at least one reporting label set
GROUP BY 1;
Feed 2'de raporlama etiketinin "red" olduğu gösterimlerin sayısı
SELECT
event.feed_reporting_label[SAFE_ORDINAL(2)] AS feed1_reporting_label,
COUNT(*) as impressions
FROM adh.cm_dt_impressions
WHERE event.feed_reporting_label[SAFE_ORDINAL(2)] = “red”
GROUP BY 1;
Feed 1'de reporting_dimension_1 değerinin "red" ve reporting_dimension_2 değerinin "car" olduğu gösterimlerin sayısı
SELECT
event.feed_reporting_label[SAFE_ORDINAL(1)] AS feed1_reporting_label,
event.feed_reporting_dimension1[SAFE_ORDINAL(1)] AS feed1_reporting_dimension1,
event.feed_reporting_dimension2[SAFE_ORDINAL(1)] AS feed2_reporting_dimension1,
event.feed_reporting_dimension3[SAFE_ORDINAL(1)] AS feed3_reporting_dimension1,
event.feed_reporting_dimension4[SAFE_ORDINAL(1)] AS feed4_reporting_dimension1,
event.feed_reporting_dimension5[SAFE_ORDINAL(1)] AS feed5_reporting_dimension1,
event.feed_reporting_dimension6[SAFE_ORDINAL(1)] AS feed6_reporting_dimension1,
COUNT(*) as impressions
FROM adh.cm_dt_impressions
WHERE event.feed_reporting_dimension1[SAFE_ORDINAL(1)] = “red”
AND event.feed_reporting_dimension2[SAFE_ORDINAL(1)] = “car”
GROUP BY 1,2,3,4,5,6,7;
Campaign Manager 360 Veri Aktarımı'ndaki reklam biçimleri
Bu örnekler, tekil çerez sayısını veya gösterim sıklığını en üst düzeye çıkaran reklam biçimlerinin nasıl belirleneceğini gösterir. Toplam tekil çerez sayısı ile kullanıcılara reklamların gösterilme sayısını dengelemek için bu bilgilerden yararlanabilirsiniz.
Gösterim yayını
/* For this query to run, @advertiser_ids and @campaigns_ids
must be replaced with actual IDs. For example [12345]. YOUR_BQ_DATASET must be
replaced with the actual name of your dataset.*/
WITH filtered_uniques AS (
SELECT
user_id,
CASE
WHEN creative_type LIKE '%Video%' THEN 'Video'
WHEN creative_type IS NULL THEN 'Unknown'
ELSE 'Display'
END AS creative_format,
COUNT(*) AS impressions
FROM adh.cm_dt_impressions impression
LEFT JOIN YOUR_BQ_DATASET.campaigns creative
ON creative.rendering_id = impression.event.rendering_id
WHERE user_id != '0'
AND event.advertiser_id IN UNNEST(@advertiser_ids)
AND event.campaign_id IN UNNEST(@campaign_ids)
AND event.country_domain_name = 'US'
GROUP BY user_id, creative_format
)
SELECT
impressions AS frequency,
creative_format,
COUNT(DISTINCT user_id) AS uniques,
SUM(impressions) AS impressions
FROM filtered_uniques
GROUP BY frequency, creative_format
ORDER BY frequency
;
Tekil çerez sayısı ve sıklığı
/* For this query to run, @advertiser_ids and @campaigns_ids
must be replaced with actual IDs. For example [12345]. YOUR_BQ_DATASET must be
replaced with the actual name of your dataset. */
WITH filtered_impressions AS (
SELECT
event.campaign_id AS campaign_id,
event.rendering_id AS rendering_id,
user_id
FROM adh.cm_dt_impressions
WHERE user_id != '0'
AND event.advertiser_id IN UNNEST(@advertiser_ids)
AND event.campaign_id IN UNNEST(@campaign_ids)
AND event.country_domain_name = 'US'
)
SELECT
Campaign,
CASE
WHEN creative_type LIKE '%Video%' THEN 'Video'
WHEN creative_type IS NULL THEN 'Unknown'
ELSE 'Display'
END AS creative_format,
COUNT(DISTINCT user_id) AS users,
COUNT(*) AS impressions
FROM filtered_impressions
LEFT JOIN YOUR_BQ_DATASET.campaigns USING (campaign_id)
LEFT JOIN YOUR_BQ_DATASET.creatives USING (rendering_id)
GROUP BY 1, 2
;
Google Ads
_rdid tabloları içeren mobil uygulama gösterimleri
Sorgu 1:
SELECT
campaign_id,
COUNT(*) AS imp,
COUNT(DISTINCT user_id) AS users
FROM adh.google_ads_impressions
WHERE is_app_traffic
GROUP BY 1
;
Sorgu 2:
SELECT
campaign_id,
COUNT(DISTINCT device_id_md5) AS device_ids
FROM adh.google_ads_impressions_rdid
GROUP BY 1
;
Sonuçlar campaign_id kullanılarak birleştirilebilir.
Demografik gruba yayınlama
Bu örnek, belirli bir demografik gruba hangi kampanyaların ulaştığını nasıl belirleyeceğinizi gösterir.
/* For this query to run, @customer_id
must be replaced with an actual ID. For example [12345] */
WITH impression_stats AS (
SELECT
campaign_id,
demographics.gender AS gender_id,
demographics.age_group AS age_group_id,
COUNT(DISTINCT user_id) AS users,
COUNT(*) AS impressions
FROM adh.google_ads_impressions
WHERE customer_id = @customer_id
GROUP BY 1, 2, 3
)
SELECT
campaign_name,
gender_name,
age_group_name,
users,
impressions
FROM impression_stats
LEFT JOIN adh.google_ads_campaign USING (campaign_id)
LEFT JOIN adh.gender USING (gender_id)
LEFT JOIN adh.age_group USING (age_group_id)
ORDER BY 1, 2, 3
;
Görüntülenebilirlik
Sorgu örnekleriyle görüntülenebilirliğe genel bakış için Gelişmiş Aktif Görüntüleme metrikleri bölümüne bakın.
Google Ads reklamvereninin saat dilimi ayarları
SELECT
customer_id,
customer_timezone,
count(1) as impressions
FROM adh.google_ads_impressions i
INNER JOIN adh.google_ads_customer c
ON c.customer_id = i.customer_id
WHERE TIMESTAMP_MICROS(i.query_id.time_usec) >= CAST(DATETIME(@date, c.customer_timezone) AS TIMESTAMP)
AND TIMESTAMP_MICROS(i.query_id.time_usec) < CAST(DATETIME_ADD(DATETIME(@date, c.customer_timezone), INTERVAL 1 DAY) AS TIMESTAMP)
GROUP BY customer_id, customer_timezone
Envanter türü
Bu örnek sorguda, envanter türü kavramı gösterilmektedir. Reklamlarınızın hangi envanterde (ör. Gmail veya YouTube Music) sunulduğunu belirlemek için inventory_type
alanını kullanabilirsiniz. Muhtemel değerler: YOUTUBE
, YOUTUBE_TV
,
YOUTUBE_MUSIC
, SEARCH
, GMAIL
, OTHER
. Diğeri, Google Görüntülü Reklam veya Video Ağı anlamına gelir.
SELECT
i.campaign_id,
cmp.campaign_name,
i.inventory_type,
COUNT(i.query_id.time_usec) AS impressions
FROM adh.google_ads_impressions i
LEFT JOIN adh.google_ads_campaign cmp ON (i.campaign_id = cmp.campaign_id)
WHERE
TIMESTAMP_MICROS(i.query_id.time_usec)
BETWEEN @local_start_date
AND TIMESTAMP_ADD(@local_start_date,INTERVAL @number_days*24 HOUR)
GROUP BY 1, 2, 3
ORDER BY 4 DESC
YouTube reklam kapsülü sorguları
Reklam kapsülleri, daha uzun YouTube izleme oturumlarında 2 reklamı tek bir reklam arasında gruplandırır. (Yalnızca 2 reklamla sınırlandırılmış bir reklam arası düşünün.) Reklam kapsüllerinde sunulan reklamlar atlanabilir olarak kalır. Ancak kullanıcı ilk reklamı atlarsa ikinci reklam da atlanır.
Google Ads TrueView yayın içi kampanya gösterimi ve TrueView görüntüleme sayısı
SELECT
cmp.campaign_name,
imp.is_app_traffic,
COUNT(*) AS total_impressions,
COUNTIF(clk.click_id IS NOT NULL) AS total_trueview_views
FROM adh.google_ads_impressions imp
JOIN adh.google_ads_campaign cmp USING (campaign_id)
JOIN adh.google_ads_adgroup adg USING (adgroup_id)
LEFT JOIN adh.google_ads_clicks clk ON
imp.impression_id = clk.impression_id
WHERE
imp.customer_id IN UNNEST(@customer_ids)
AND adg.adgroup_type = 'VIDEO_TRUE_VIEW_IN_STREAM'
AND cmp.advertising_channel_type = 'VIDEO'
GROUP BY 1, 2
Satır öğelerine göre Display & Video 360 görüntülenebilirlik metrikleri
WITH
imp_stats AS (
SELECT
imp.line_item_id,
count(*) as total_imp,
SUM(num_active_view_measurable_impression) AS num_measurable_impressions,
SUM(num_active_view_eligible_impression) AS num_enabled_impressions
FROM adh.dv360_youtube_impressions imp
WHERE
imp.line_item_id IN UNNEST(@line_item_ids)
GROUP BY 1
),
av_stats AS (
SELECT
imp.line_item_id,
SUM(num_active_view_viewable_impression) AS num_viewable_impressions
FROM adh.dv360_youtube_impressions imp
LEFT JOIN
adh.dv360_youtube_active_views av
ON imp.impression_id = av.impression_id
WHERE
imp.line_item_id IN UNNEST(@line_item_ids)
GROUP BY 1
)
SELECT
li.line_item_name,
SUM(imp.total_imp) as num_impressions,
SUM(imp.num_measurable_impressions) AS num_measurable_impressions,
SUM(imp.num_enabled_impressions) AS num_enabled_impressions,
SUM(IFNULL(av.num_viewable_impressions, 0)) AS num_viewable_impressions
FROM imp_stats as imp
LEFT JOIN av_stats AS av USING (line_item_id)
JOIN adh.dv360_youtube_lineitem li ON (imp.line_item_id = li.line_item_id)
GROUP BY 1
YouTube Reserve sorguları
Reklamverene göre gösterim yayını
Bu sorgu, reklamveren başına gösterim ve farklı kullanıcı sayısını ölçer. Bu sayıları kullanarak kullanıcı başına ortalama gösterim sayısını (veya "reklam sıklığını") hesaplayabilirsiniz.
SELECT
advertiser_name,
COUNT(*) AS imp,
COUNT(DISTINCT user_id) AS users
FROM adh.yt_reserve_impressions AS impressions
JOIN adh.yt_reserve_order order ON impressions.order_id = order.order_id
GROUP BY 1
;
Reklam atlama sayısı
Bu sorgu müşteri, kampanya, reklam grubu ve reklam öğesi başına reklam atlama sayısını ölçer.
SELECT
impression_data.customer_id,
impression_data.campaign_id,
impression_data.adgroup_id,
impression_data.ad_group_creative_id,
COUNTIF(label = "videoskipped") AS num_skips
FROM
adh.google_ads_conversions
GROUP BY 1, 2, 3, 4;
Genel sorgular
Bir kullanıcı grubunu başka bir gruptan çıkarma
Bu örnek, bir kullanıcı grubunun başka bir gruptan nasıl çıkarılacağını gösterir. Bu tekniğin dönüşüm gerçekleştirmeyen, görüntülenebilir gösterimi olmayan ve tıklama yapmayan kullanıcıları sayma gibi çok çeşitli uygulama alanları bulunur.
WITH exclude AS (
SELECT DISTINCT user_id
FROM adh.google_ads_impressions
WHERE campaign_id = 123
)
SELECT
COUNT(DISTINCT imp.user_id) -
COUNT(DISTINCT exclude.user_id) AS users
FROM adh.google_ads_impressions imp
LEFT JOIN exclude
USING (user_id)
WHERE imp.campaign_id = 876
;
Özel çakışma
Bu sorgu, 2 veya daha fazla kampanyanın çakışmasını ölçer. Çakışmayı, isteğe bağlı ölçütlere göre ölçmek için özelleştirilebilir.
/* For this query to run, @campaign_1 and @campaign_2 must be replaced with
actual campaign IDs. */
WITH flagged_impressions AS (
SELECT
user_ID,
SUM(IF(campaign_ID in UNNEST(@campaign_1), 1, 0)) AS C1_impressions,
SUM(IF(campaign_ID in UNNEST(@campaign_2), 1, 0)) AS C2_impressions
FROM adh.cm_dt_impressions
GROUP BY user_ID
SELECT COUNTIF(C1_impressions > 0) as C1_cookie_count,
COUNTIF(C2_impressions > 0) as C2_cookie_count,
COUNTIF(C1_impressions > 0 and C2_impressions > 0) as overlap_cookie_count
FROM flagged_impressions
;
İş Ortağı Tarafından Satılan - Çapraz Satış
Bu sorgu, iş ortağı tarafından satılan envanterin gösterimlerini ve tıklamalarını ölçer.
SELECT
a.record_date AS record_date,
a.line_item_id AS line_item_id,
a.creative_id AS creative_id,
a.ad_id AS ad_id,
a.impressions AS impressions,
a.click_through AS click_through,
a.video_skipped AS video_skipped,
b.pixel_url AS pixel_url
FROM
(
SELECT
FORMAT_TIMESTAMP('%D', TIMESTAMP_MICROS(i.query_id.time_usec), 'Etc/UTC') AS record_date,
i.line_item_id as line_item_id,
i.creative_id as creative_id,
i.ad_id as ad_id,
COUNT(i.query_id) as impressions,
COUNTIF(c.label='video_click_to_advertiser_site') AS click_through,
COUNTIF(c.label='videoskipped') AS video_skipped
FROM
adh.partner_sold_cross_sell_impressions AS i
LEFT JOIN adh.partner_sold_cross_sell_conversions AS c
ON i.impression_id = c.impression_id
GROUP BY
1, 2, 3, 4
) AS a
JOIN adh.partner_sold_cross_sell_creative_pixels AS b
ON (a.ad_id = b.ad_id)
;
Uygulama mağazası gösterim sayısı
Aşağıdaki sorgu, uygulama mağazasına ve uygulamaya göre gruplandırılmış toplam gösterim sayısını gösterir.
SELECT app_store_name, app_name, COUNT(*) AS number
FROM adh.google_ads_impressions AS imp
JOIN adh.mobile_app_info
USING (app_store_id, app_id)
WHERE imp.app_id IS NOT NULL
GROUP BY 1,2
ORDER BY 3 DESC