GA4: What Shopify stores should do TODAY to keep up with the new version of Google Analytics
Setting up Google Analytics 4 (GA4) on Shopify is easy with the right tools, but there is a lot of confusion in the marketplace right now. There are apps offering "GA4 setup" that can't actually help you with tracking (getting accurate data into Analytics), and there are agencies offering detailed GTM tag setup guides for GA4 without mentioning that there are automated solutions for GA4 conversion tracking. This is all very exciting...but also not necessary. The truth is that you don't need custom tagging or reporting, just the right Shopify tracking app for GA4. What is GA4? It's Google's answer to the modern data stack, in some ways a complement to it (eg. GA4's BigQuery connection, which used to be reserved for GA 360), and in others a replacement for multiple expensive tools that haven't always worked well together. The move toward GA4 started with Google's interest in offering better cross-device and cross-channel tracking, and has been refined with a focus on user privacy -- in other words a world without third-party cookies. As a result, using the right Shopify and GA4 connection now lets you start capturing data about your Shopify store performance that is by default more complex and dynamic than what you might be currently tracking in Universal Analytics (UA, the current version of GA). GA4 can save you time and money versus a complex analytics setup, while offering visibility into the entire customer lifecycle, from organic and paid channels through complex browsing behavior and -- essentially -- customer lifetime value (LTV) and purchase count. But at the very least you need to start capturing that data. [note]This doesn't only apply to Shopify stores! If you're on BigCommerce you can use our server-side BigCommerce to GA4 integration[/note] Google has also built in data-driven models for both comparative attribution reporting and predictive analytics, such as in-app purchase probability and overall purchase probability. But let's not get ahead of ourselves. First you need to capture the data. We expect some brands to just ignore GA4 until the last minute (I'm expecting some not-so-fun Memorial Day Weekend parties next year in NYC...), but we've also noticed that the top ecommerce managers and data scientists are all doing the same thing: tracking in parallel today, so they will have at least six months of data before making the full switch to GA4. Here's a quick guide to help you make the right moves too. 1. Stop procrastinating Is Google really getting rid of the old version of Google Analytics? The answer is a definitive yes. They are sunsetting the old version of Google Analytics in 2023. You need to be ready, but what does that mean exactly? Is there anything you can do today? Track in parallel today so you will have at least six months of data before making the full switch to GA4 Google formally announced the shift to a new version of Google Analytics back in November 2020, but many DTC brands are still putting off the shift to GA4. While moving to a different version of a tool most online marketers use weekly (if not daily) might sound a bit intimidating, there are two points to remember: Google is one of the most user-friendly companies on the planet and they have already added a bunch of functionality and default reporting templates in GA4 You need to capture data before you can analyze it! As our agency partner CXL writes in their ultimate guide to GA4: "Unlike previous upgrade iterations, GA4 is a brand-new product. This means starting afresh, with a new learning curve to navigate." But at the same time, as they say, "it promises to be the future of analytics, with cross-platform tracking, AI-driven data, and privacy-centric design." We couldn't agree more. Littledata's top 10 reasons to switch to GA4 include both custom funnels and predictive insights. This is especially important for ecommerce brands that want to building shopping funnel reports and LTV cohorts in GA4 that fit their particular business model and customer base. So what should you do today to take advantage of this powerful, free ecommerce reporting? First of all, create a GA4 property! 2. Create a GA4 property Google will not be allowing anybody to import historical data from UA into GA4, so you need to create a Google Analytics 4 (GA4) property today if you are serious about seeing performance over time. Luckily, adding a GA4 property is surprisingly easy. Current GA users (that's most of you) can just head to their Analytics accounts and use the setup assistant. You should add at least one data stream. (Don't worry, you can add more later.) Data Streams in GA4 replace Views in Universal Analytics, but they're a bit different . Data streams can be any website (or blog, microsite, country store, etc) or mobile app (iOS or Android), and they can be viewed in aggregate or individually. Adding a data stream might sound intimidating, but this can be as simple as adding the URL for your website (eg. "littledata.io"). [tip]Whether you're new to Google Analytics or a longtime user, we recommend turning on the Enhanced Measurement settings, which include useful defaults.[/tip] When you add a data stream, you will have the option to enabled Enhanced Measurement settings. This is highly recommended. Here's more info on what Littledata lets you track automatically in GA4 -- examples include product views, product list views, checkout funnel events and purchases -- and which events are tracked with Enhanced Measurement, such as page views, site search and form interactions. Now that you have set up a GA4 property, it's time to set up your ecommerce tracking. [tip] Use our complementary instant order checker for GA4 to check your property [/tip] 3. Track in Parallel Tracking UA and GA4 in parallel means that you can send data to both destinations at the same time. This lets you capture browsing behavior and sales performance in both places, so you can analyze the data, build comparative attribution models and start to get a sense for how Universal Analytics and Google Analytics 4 are different -- as well as where they converge. The most accurate way to do this is to use an ecommerce data platform like Littledata to capture ecommerce events by default, including both sales/conversion tracking and marketing attribution (stitching sessions together). We send data directly to GA4. Because we have a pre-built GTM data layer, you don't need to add tags manually! Use a pre-built data layer for GA4 so you don't have to add tags manually Littledata's tracking schema works out of the box to capture both major and minor touch points in the ecommerce journey. When you install Littledata, we instantly start tracking all of the key ecommerce events for you in both UA and GA4, so you'll have the data you need when you're ready to dive into week-on-week and month-on-month analysis. Here's a quick video on tracking in parallel. To get something similar to Enhanced Ecommerce reporting, you'll need to build reports yourselves, so we've also put together a few videos on building ecommerce reports in GA4. These reports are more flexible and dynamic than anything available in UA. It's like having Google Data Studio within Google Analytics for complete reporting. There's even more free content available for subscribers in the app :) Wait, so GA4 is pretty different? GA4 is based on a different type of tracking called event-based tracking, which is is exactly what it sounds like: a more flexible and comprehensive way of tracking everything so you can build granular reports and predictive models based on the endless flow of events and attached parameters. The UA data model focused on sessions and pageviews. GA4 focuses on events, and sessions are no longer broken by a change in campaign "source" (GA4 continues tracking the same session as well as the change in source). But those sessions will not be stitched together automatically with purchase data and Shopify customer IDs. And many Google Tag Manager solutions for GA4 are missing out on the basics, like purchase events, revenue and conversion tracking. If you aren't capturing purchases, how are you supposed to know if your marketing is working? Using Littledata's solution is quick and easy, with both low-code and no-code options. Our ecommerce tracking is deep and comprehensive. When you start a free trial you can choose to send data to both UA and GA4 at no additional cost, with server-side tracking to guarantee accurate data. [subscribe heading="Top-rated GA4 tracking for $99 a month"] Want to know more? Book a free data audit with one of our Google Analytics experts today!
What's new in Google Analytics 2014
Google has really upped the pace of feature releases on Analytics and Tag Manager in 2014, and we’re betting you may have missed some of the extra functionality that’s been added. In the last 3 months alone we’ve counted 11 major new features. How many have you tried out? Official iPhone app. Monitor your Google Analytics on the go. Set up brand keywords. Separate out branded from non-brand search in reports. Enhanced Ecommerce reporting. Show ecommerce conversion funnels when you tag product and checkout pages. Page Analytics Chrome plugin. Get analytics for a particular page, to replace old in-page analytics. However, it doesn’t work if you are signed into multiple Google Accounts. Notifications about property setup. Troubleshoot common problems like domain mis-matches. Embeded Reports API. So you can build custom dashboards outside of GA quickly. Share tools across GA accounts. Now you can share filters, channel groupings, annotations etc easily between views and properties Tag Assistant Chrome plugin. Easily spot common setup problems on your pages using the Tag Assistant. Built-in user tracking. See our customer tracking guide for the pros and cons. Import historic campaign cost and CRM data (premium only). Previously, imported data would only show up for events added after the data import. Now you can enter a ‘Query Time’ to apply to past events, but only for Premium users. Get unsampled API data (Premium only - developers). Export all your historic data without restrictions Better Management API (for developers). Set up filters, Adwords links and user access programmatically across many accounts. Useful for large companies or agencies with hundreds of web properties.
Pulling Google Analytics into Google Docs - automated template driven reporting
The Google Docs library for the analytics API provides a great tool for managing complex or repetitive reporting requirements, but it can be tricky to use. It would be great if it was a simple as dropping a spreadsheet formula on a page, but Google’s library stops a few steps short of that - it needs some script around it. This sheet closes that gap, providing a framework for template driven analytics reports in Google Docs. With it you can set up a report template, and click a menu to populate it with your analytics results and run your calculations - without needing to write a line of script - the code is there if you want to build on it, but you can get useful reports without writing a line of script. Prerequisites While you don't have to write code to use this, there are some technical requirements. To get the most out of it you'll need to have: your Google analytics tagging and views set up familiarity with Google’s reporting API familiarity with Google Docs spreadsheets - some knowledge of Google apps scripting is an advantage If you are looking for something more user-friendly or tailored to your needs, contact us and book a consultation to discuss - we can help with your analytics setup and bespoke reporting solutions. Getting started Setting this up takes a few steps, but you only need to do this once: Open the shared Google spreadsheet Make a copy Enter a view ID in the settings sheet - get this from the Google Analytics admin page. Authorise the script Authorise the API - in the API console - this is the only time you need to go into the script view using Tools|Script Editor Once in script editor select Resources|Advanced Google services On the bottom of the Advanced Google services dialogue is a link to the Google Developers Console, follow this and ensure that Google analytcs API is set to On You're done. You can go back to the spreadsheet and run the report (on the Analytics menu). From now on all you need to do is tweak any settings on the template and run the report. Setting up your own report template You can explore how the template works using the example. Anywhere you want to retrieve value(s) from Google Analytics, place this spreadsheet function on the template: = templateShowMetric(profile, metric, startdate, enddate, dimensions, segment, filters, sort, maxresults) This works as a custom spreadsheet function, for example =templateShowMetric(Settings!$B$2,$B7,Settings!$B$3,Settings!$B$4,$C7,$D7,$E7,$F7,$G7) Note that in the example, several of the references are to the settings sheet, but they don't have to be, you can use any cell or literal value in the formula - it's just a spreadsheet function. To get the values for the API query, I'd suggest using Google’s query explorer. To set this up for a weekly report, say, you would have all the queries reference a single pair of cells with start and end dates. Each week you would change the date cells run the report again - all queries will be run exactly as before, but for the new dates. Using spreadsheet references for query parameters is key. This opens up use of relative and absolute references - for example if you need to run the same query against 50 segments, you list your segments down a column, set up segment as a relative reference, and copy the formula down spreadsheet style. You can use this to do calculations on the sheet and use results in the analytics API, for example you might calculate start and end dates relative to current date. Future posts will cover setting up templates in more detail. Under the hood The templateShowMetric function generates a JSON string. When you trigger the script, the report generator copies everything on the template to the report sheet and: runs any analytics queries specified by a templateShowMetric function removes any formulas that reference the settings sheet (so you can use the settings sheet to pass values to the template, but your reports are not dependant on the settings staying the same)
Analytics showing wrong numbers for yesterday's visits
We've noticed a few issues with clients using Universal Analytics this last month, when visits for the last day have been double the normal trend. It then corrects itself a few hours later - so seems to be just a blip with the data processing at Google. Others have noticed the same problem. The temporary fix is to only generate reports with time series ending the day before yesterday. i.e. ignore yesterday's data. Now Google have officially acknowledged the problem Looking forward to seeing that one fixed!
Measuring screen resolution versus viewport size
There’s a difference between the ‘screen size’ measured as standard in Google Analytics and the ‘browser size’ or ‘browser viewport’. Especially on mobile devices, there are pitfalls comparing the two. Browser viewport is the actual visible area of the HTML, after the width of scroll bars and height of button, address, plugin and status bars has been allowed for. Desktop computer screens have got much bigger over the last decade, but browser viewports (the visible area within the browser window) are not. The CSS tricks site found only 1% of users have their browser viewing in the full screen. While only 9% of visitors to his site had a monitor less than 1200px wide in 2011, around 21% of users have a browser viewport of less than that width. Simply put, on a huge monitor you don’t browse the web using your full screen. Therefore, 'screen resolution' may be much larger than 'viewport size'. The best solution is to post browser viewport size to GA as a custom dimension. P.S. Google Analytics does have a feature within In Page Analytics (under Behaviour section) to overlay Browser Size, but it doesn’t work for any of the sites I look at.
How many websites use Google Analytics?
Google Analytics is clearly the number one web analytics tool globally. From a meta-analysis of different surveys, we estimate it is currently installed on over 50% of all websites or 80% of operational websites using any kind of analytics tracking. We looked at the following sources for this chart: Datanyze survey of Alexa top 1m sites (04/2014) BuiltWith survey of all websites (04/2014) MetricMail survey of Alexa top 1m sites Pingdom survey of Alexa top 10k sites (07/2012) W3Techs survey of their own sites (04/2014) LeadLedger survey of Fortune 500 sites (04/2014)
What's included in Analytics traffic sources?
The Channel report in Google Analytics (under 'Acquisition' section) splits out into 6 or more types of visit channel: Direct Where a visitor has: typed the URL into the address bar clicked on a link which is NOT in another web page (e.g. in a mobile app) visited a bookmarked link Organic Search All visits from search engines (i.e. Google, Bing, Yahoo) which were not an advertisement. You used to be able to filter out people searching for your brand (which are more like Direct visits), but now the search terms are not provided. Paid Search Visits from search engines where the visitor clicked on an advert. Referral Where a visitor has clicked on a link in another website (not your own domain), but not including search engines or social networks. Social Networks Specifically links from known social network websites (including Facebook, Twitter, LinkedIn etc) Email From links tagged as medium = 'email'. Your email software needs to be configured correctly to add this tag. Display Links tagged as 'display' or 'cpm'. FAQs Can I change the channel groupings? Yes, you can change this under Admin .. (Selected View).. Channel Grouping. But we recommend you don't do this for your default view, as you won't be able to compare the historical data.
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