Export Google Analytics data

Get your Google Analytics data everywhere

The cheapest option to get access to the click-stream / hit-level data

Available Destinations

No strings attached – it’s just a trial

See a sample of how the data looks inside Google BigQuery

The screenshot show a few of the available columns in the dataset

See a sample of how the data looks inside Microsoft Power BI

The screenshot show a few of the available columns in the dataset

Features and Benefits

Export ALL your data

Collect  your  data anywhere and tear down the Google Analytics data silo. 

Clickstream 

Gain insight to the exact human behaviour order with clickstream data.

More Custom Dimensions

Get 100+ Custom Dimensions with SCITYLANA.

Distinct Count

Get Distinct Count and link your Google Analytics data with multible datasets in a datalake.

Client ID

Get Client ID retrospectively with SCITYLANA’s unique back-filling algorithm.

Unsampled hit-level data

Escape the issues with aggregated data and start using hit-level data.

Increased Volume

Overcome the limitation of 1 million hits per day.

The Schema

The Scitylana Data extraction consists of the following dimesions and metrics

The data is delivered in 1 table. Each dimension or metric is represented by a single column. Each row is equal to a hit. A hit is either a Page View, Screen view, Event, Transaction or Other.
The schema is designed to be fact only. This means it is trimmed for deducted/filtered dimensions. But there are some filtered metrics (bounces, goals) which we added for your convenience – but we recommend bulding these metrics  in SQL or favorite query language. Google Analytics metrics are very broad-purposed and typically not what your business needs.

Scitylana Hit Level
sl:ident
sl:sessionid
sl:hitorder
sl:pagevieworder
sl:hittype
sl:timeStamp
sl:propertyId
sl:viewId

User
ga:userType
ga:clientId
ga:sessionCount
ga:userBucket

Session 
ga:bounces
ga:sessionDuration

Traffic Sources
ga:fullReferrer
ga:campaign
ga:source
ga:medium
ga:keyword
ga:adContent
ga:campaignCode

Adwords
ga:adwordsCreativeID

Goal Conversions
ga:goalXXCompletions (XX = 1-20)

Platform or Device
ga:browser
ga:browserVersion
ga:operatingSystem
ga:operatingSystemVersion
ga:deviceCategory
ga:browserSize

Geo Network
ga:continent
ga:subContinent
ga:country
ga:region
ga:metro
ga:city
ga:latitude
ga:longitude
ga:networkLocation
ga:countryIsoCode
ga:regionIsoCode
ga:subContinentCode

System
ga:language
ga:screenResolution

Page Tracking
ga:hostname
ga:pagePath
ga:pageTitle
ga:landingPagePath
ga:secondPagePath
ga:exitPagePath
ga:previousPagePath
ga:timeOnPage

Event
ga:eventCategory
ga:eventAction
ga:eventLabel
ga:eventValue
ga:totalEvents

Ecommerce
ga:productSku
ga:productName
ga:currencyCode
ga:transactionRevenue

Custom Dimensions
ga:dimensionXX (XX = 1-20)

Channel Grouping
ga:channelGrouping

App Tracking
ga:screenName
ga:appName
ga:appId
ga:appVersion
ga:appInstallerId
ga:timeOnScreen

The unique extraction algorithm​

We provide you with ALL your data at hit-level granularity

“Why is data important?”

The following dashboards are made in collaboration with Miild – a Scitylana premium partner. Miild decided to start using SCITYLANA in order to perform necessary calculations to gain important  insights and become data driven.

The following dashboards originates from this client case.

Case 1: Miild Uses hit-level data to calculate their funnel attribution 

Click here to learn more about attribution 

Case 2: Miild uses hit-level data and our Facebook Ads Power BI connector to calculate the real ad cost per user. Note the data from the last four columns are a combination of at least two sources

Get historical data now and break the barriers to faster insights

Receive fresh data every day    and ensure continuous insights

Back-fill hit-level data now

Parallel Tracking
vs
Scitylana

Google Analytics in BigQuery

Google Analytics 360
vs
Scitylana

// Type writer effect