Google Analytics is a web analytics tool that helps people track and analyze website or app performance

AI-Assisted Setup

When connecting Google Analytics to Scoop, you can choose "Guide me with AI" for an intelligent, guided setup experience. Scoop offers pre-configured analysis templates that automatically select the right dimensions and metrics for common use cases.

Available Analysis Templates

All templates use the GA4 Report object, which provides customizable dimensions and metrics from your Google Analytics 4 property.

Example Questions You Can Answer

Traffic Overview:

• "How has our website traffic trended over the past 6 months?"
• "What's our bounce rate and is it improving?"
• "How many new users are we acquiring each month?"

Traffic Sources:

• "Which channel drives the most engaged users?"
• "Is our organic traffic growing faster than paid?"
• "What percentage of our traffic comes from social media?"

Landing Pages:

• "Which landing pages have the highest bounce rates?"
• "What are our top entry points to the site?"
• "Which pages keep visitors on the site longest?"

Geographic:

• "What countries drive the most traffic?"
• "Are there untapped geographic markets we should target?"
• "How does engagement differ between US and international visitors?"

Campaigns:

• "Which marketing campaign drove the best engagement?"
• "How do our email campaigns compare to paid ads?"
• "What's the session duration for visitors from different campaigns?"

Tip: All templates include the date dimension, enabling time-series analysis. You can ask questions like "show me weekly trends" or "compare this month to last month" with any template.

GA Data Storage

With the upgrade to GA4, Google has limited data storage for both User-Level data and Other Event data to a period of 2 to 14 months, depending on your settings.

Scoop has the ability to store data from Google Analytics for an unlimited time period.

Connecting to Google Analytics

To connect to Google Analytics as a data source, create a new dataset linked to Google Analytics. First, on the datasets page, select applications as a source:

Next, select google analytics:

Selecting an Object and Fields

After selecting Google Analytics, you can select which object you want to extract and which fields you wish to extract.

The most common use case for Google Analytics is website analytics data. Scoop pulls daily web traffic data and pulls it into a database. Unlike the recent up to GA4, which eliminates access to data greater than 14 months, Scoop will store the Google Analytics data for as long as your company needs.

Typical dimensions include event name, full page URL, date, first user campaign, City ID, first user source, date of week, page title, and session medium.

Typical metrics include user engagement, sessions per users, views per session, views, ad source, and date. Be aware that Google Analytics does not support all combinations of dimensions and metrics. The same ones that you can access withing Google Analytics can be extracted into Scoop and blended with other data.

Google Analytics Dataset Configuration Guide

Choosing the Right Properties for Your GA4 Dataset

Google Analytics 4 has specific requirements about which properties can be combined in a single query, making it challenging to know which properties to select when creating your dataset. This guide provides a simple approach to overcome this challenge.

The Challenge

GA4 organizes data into different scopes and categories that don't always play well together. Selecting incompatible properties will result in errors or incomplete data. Rather than guessing which properties work together, you can use AI to help you make informed choices.

Quick Solution: Use AI to Select Compatible Properties

Here's a simple hack to get the right properties for your analysis goals:

Step 1: Define Your Analysis Goal

Start by clearly stating what you want to analyze. For example:

• "I want to analyze campaign data and traffic sources"
• "I need to understand user behavior and engagement metrics"
• "I want to track conversion paths and goal completions"
• "I need to analyze page performance and user interactions"

Step 2: Ask AI for Property Recommendations

Use Claude, ChatGPT, or another AI assistant with this prompt:

I'm creating a Google Analytics dataset in Scoop. My goal is to [insert your analysis goal here]. 

Based on Google Analytics 4 best practices for property pairing and compatibility, please recommend up to 15 GA4 properties that will help me achieve this goal. Make sure to:
- Follow GA4's dimensional compatibility rules
- Avoid mixing incompatible scopes (user vs session vs event)
- Ensure the properties can be queried together without errors
- Prioritize the most relevant metrics and dimensions for my analysis goal

Here's the list of available properties:
[Copy and paste the full list of available properties from below]

Step 3: Apply the Recommendations

Take the 15 properties suggested by the AI and check them off in your Scoop dataset configuration. This ensures you have a focused, compatible set of properties that align with your analysis goals.

Available GA4 Properties

Here's the complete list of properties you can choose from when creating your dataset:

- achievementId
- adClickAdsense
- adDestinationUrl
- adUnitNameAdsense
- adFormatAdsense
- adGroup
- adSourceNameAdsense
- adUnitNameAdsense
- adsenseRevenue
- adsQuery
- age
- appVersion
- audienceId
- audienceName
- bounceRate
- bounces
- brandingInterest
- browser
- browserVersion
- campaign
- campaignId
- channelGroup
- character
- city
- cityId
- cm360AccountId
- cm360AccountName
- cm360AdvertiserId
- cm360AdvertiserName
- cm360CampaignId
- cm360CampaignName
- cm360CreativeFormat
- cm360CreativeId
- cm360CreativeName
- cm360CreativeType
- cm360CreativeTypeId
- cm360CreativeVersion
- cm360Medium
- cm360PlacementCostStructure
- cm360PlacementId
- cm360PlacementName
- cm360RenderingId
- cm360SiteId
- cm360SiteName
- cm360Source
- cm360SourceMedium
- cohort
- cohortActiveUsers
- cohortTotalUsers
- contentGroup
- contentId
- contentType
- continent
- continentId
- conversions
- country
- countryId
- currencyCode
- customEvent
- dataSource
- date
- dateHour
- dateHourMinute
- day
- dayOfWeek
- defaultChannelGroup
- deviceCategory
- deviceModel
- eventCount
- eventName
- eventValue
- exitRate
- exits
- fileExtension
- fileName
- firebaseAppId
- firstSessionDate
- firstUserDefaultChannelGroup
- firstUserMedium
- firstUserSource
- fullPageUrl
- gender
- googleAdsAccountName
- googleAdsAdGroupId
- googleAdsAdGroupName
- googleAdsAdNetworkType
- googleAdsCampaignId
- googleAdsCampaignName
- googleAdsCampaignType
- googleAdsCreativeId
- googleAdsCustomerId
- googleAdsKeyword
- googleAdsQuery
- groupId
- hostName
- hour
- interests
- isConversionEvent
- isoWeek
- isoYear
- isoYearIsoWeek
- itemAffiliation
- itemBrand
- itemCategory
- itemCategory2
- itemCategory3
- itemCategory4
- itemCategory5
- itemId
- itemListId
- itemListName
- itemListPosition
- itemLocationID
- itemName
- itemPromotionCreativeName
- itemPromotionCreativeSlot
- itemPromotionId
- itemPromotionName
- itemVariant
- itemsAddedToCart
- itemsCheckedOut
- itemsClickedInList
- itemsClickedInPromotion
- itemsPurchased
- itemsViewed
- itemsViewedInList
- itemsViewedInPromotion
- landingPage
- language
- languageCode
- level
- linkClasses
- linkDomain
- linkId
- linkText
- linkUrl
- manualAdContent
- manualTerm
- medium
- method
- metro
- metroId
- minute
- mobileDeviceBranding
- mobileDeviceMarketingName
- mobileDeviceModel
- month
- newUsers
- operatingSystem
- operatingSystemVersion
- operatingSystemWithVersion
- orderCoupon
- organicGoogleSearchAvgPos
- organicGoogleSearchClickThroughRate
- organicGoogleSearchClicks
- organicGoogleSearchImpressions
- organicGoogleSearchQuery
- outboundClick
- pageLocation
- pagePath
- pagePathPlusQueryString
- pageReferrer
- pageTitle
- pageviews
- percentScrolled
- platform
- platformDeviceCategory
- publisherAdClicks
- publisherAdImpressions
- quarter
- region
- screenResolution
- scrolledUsers
- searchTerm
- sessionCampaign
- sessionDefaultChannelGroup
- sessionDuration
- sessionEngagedDuration
- sessionMedium
- sessionSource
- sessionSourcePlatform
- sessions
- sessionsPerUser
- source
- sourceMedium
- sourcePlatform
- streamId
- streamName
- testDataFilterId
- testDataFilterName
- totalAdRevenue
- totalRevenue
- totalUsers
- transactionId
- transactions
- unifiedPageScreen
- unifiedScreenClass
- unifiedScreenName
- userAgeBracket
- userEngagement
- userEngagementDuration
- userGender
- users
- videoProvider
- videoTitle
- videoUrl
- virtualCurrencyName
- virtualItemName
- week
- year
- yearWeek

Important Notes

• You don't have to use this method - If you're familiar with GA4's data model, you can select properties manually
• This is a helpful shortcut - Especially useful when you're unsure which properties to choose or want to ensure compatibility
• Start focused - It's better to start with fewer, relevant properties than to select everything
• Iterate as needed - You can always create additional datasets with different property combinations for different analysis needs

Common Property Combinations

Here are some tested combinations that work well together:

Traffic Analysis

• source, medium, campaign, channelGroup, sessions, users, newUsers, bounceRate, sessionDuration, pageviews

Content Performance

• pagePath, pageTitle, pageviews, users, avgTimeOnPage, bounceRate, exitRate, entrances

E-commerce Analysis

• itemName, itemCategory, itemBrand, itemsViewed, itemsAddedToCart, itemsPurchased, itemRevenue, transactionId

User Behavior

• deviceCategory, browser, operatingSystem, country, city, language, userEngagementDuration, sessionsPerUser

Remember: The key is aligning your property selection with your specific analysis goals. When in doubt, use AI assistance to ensure you're choosing compatible properties that will give you the insights you need.