網頁和行動互動的Analytics深入分析
Adobe Experience Platform可讓您使用Experience Data Model (XDM)欄位從Adobe Analytics報表套裝擷取資料,以填入資料集。 已修改此分析資料,以符合XDM ExperienceEvent類別。 然後,Query Service可以透過執行SQL查詢來利用此資料,從使用者在數位平台上的行為產生有價值的深入分析。
本檔案提供各種範例SQL查詢,示範根據Web和行動Analytics資料建立深入分析時的常見使用案例。
如需擷取和對應Analytics資料的詳細資訊,請參閱Analytics欄位對應檔案。
快速入門
對於下列每一個使用案例,都會提供引數化SQL查詢範例作為範本供您自訂。 針對您想要評估的資料集、eVar、事件或時間範圍,提供您在SQL範例中看到{ }
的引數。
目標
下列範例顯示用於分析Adobe Analytics資料的常見使用案例的SQL查詢。
產生指定日期每小時的訪客計數
SELECT Substring(from_utc_timestamp(timestamp, 'America/New_York'), 1, 10) AS Day,
Substring(from_utc_timestamp(timestamp, 'America/New_York'), 12, 2) AS Hour,
Count(DISTINCT enduserids._experience.aaid.id) AS Visitor_Count
FROM {TARGET_TABLE}
WHERE TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
GROUP BY Day, Hour
ORDER BY Hour;
識別指定日期檢視次數最多的10個頁面
SELECT web.webpagedetails.name AS Page_Name,
Sum(web.webpagedetails.pageviews.value) AS Page_Views
FROM {TARGET_TABLE}
WHERE TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
GROUP BY web.webpagedetails.name
ORDER BY page_views DESC
LIMIT 10;
識別10位最活躍的使用者
SELECT enduserids._experience.aaid.id AS aaid,
Count(timestamp) AS Count
FROM {TARGET_TABLE}
WHERE TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
GROUP BY enduserids._experience.aaid.id
ORDER BY Count DESC
LIMIT 10;
根據使用者活動識別10個最理想的城市
SELECT concat(placeContext.geo.stateProvince, ' - ', placeContext.geo.city) AS state_city,
Count(timestamp) AS Count
FROM {TARGET_TABLE}
WHERE TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
GROUP BY state_city
ORDER BY Count DESC
LIMIT 10;
識別檢視次數最多的10種產品
SELECT Product_SKU,
Sum(Product_Views) AS Total_Product_Views
FROM (SELECT Explode(productlistitems.sku) AS Product_SKU,
commerce.productviews.value AS Product_Views
FROM {TARGET_TABLE}
WHERE TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
AND commerce.productviews.value IS NOT NULL)
GROUP BY Product_SKU
ORDER BY Total_Product_Views DESC
LIMIT 10;
識別前10名最高訂單收入
SELECT Purchase_ID,
Round(Sum(Product_Items.priceTotal * Product_Items.quantity), 2) AS Total_Order_Revenue
FROM (SELECT commerce.`order`.purchaseid AS Purchase_ID,
Explode(productlistitems) AS Product_Items
FROM {TARGET_TABLE}
WHERE commerce.`order`.purchaseid IS NOT NULL
AND TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
GROUP BY Purchase_ID
ORDER BY total_order_revenue DESC
LIMIT 10;
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