How Google Analytics 4 helps you make smarter decisions and why do you need it now

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Ever since Google announced the launch of Google Analytics 4, the data analysis world was divided into two — those who support an immediate migration and those who disapprove.

I hear many companies out there trying to better understand how the changes would affect them, but mainly, they ask whether they should migrate to Google Analytics 4 now?

Here’s a spoiler:

The short answer is YES.

The long answer: IT’S COMPLICATED (it always is…)

Yes — because Google Analytics4 is the future, whether you like it or not, and like any other scenario, those who get in early will have an advantage.

But not less important, some of the premium features (only available in the 360 version, priced at $150,000/year) are now open to free Google Analytics 4 users — and they’re real game-changers! Particularly for marketing teams.

It’s complicated — Google Analytics 4 is not yet ready to fully replace Universal Analytics. It’s still buggy and doesn’t support some essential functionalities (don’t worry, they’re on the road map).

So the best advice I have for you at the moment is to use both.

Keep using your Universal Google Analytics, and simultaneously start experimenting with Google Analytics 4 (read more about how to do it with minimal effort).

Now, let’s drill down into some of those Google Analytics game-changing features I mentioned.

𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿-𝗰𝗲𝗻𝘁𝗿𝗶𝗰 𝗱𝗮𝘁𝗮 — It’s all about the complete user journey

The new event and user-based tracking allows you to collect data from various devices and touchpoints and consolidate them into a single view.

This basically means that a user can be identified and reported as the same user even if they used a different platform (Mobile-Web to Mobile-App) or a different device (Web to Mobile). If until now companies had to track their web and mobile app data separately, brands can now not only analyze App and Web performance side by side; they can also use multiple identification techniques: Device, internal User ID, and even Google Signals to get a consolidated view of web and app performance.

Why is this so important? marketing teams can now analyze the full user journey cross-platform and cross-device and know which channels and campaigns show the highest ROAS and LTV.

*Apple’s iOS 14 and IDFA depreciation will affect this ability, no doubt, but that’s for a different post.

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Source: Google

No more aggregated data only. Access user-level data with BigQuery

Many fail to mention how revolutionary this new ability is, but from my perspective, this is the #1 reason to begin using Google Analytics 4 ASAP.

Formerly a 360 feature only, Google Analytics 4 now supports raw data export to Big Query for free accounts as well.

Up to now, free Google Analytics users had access to aggregated data only and couldn’t analyze or use data and signals at the single-user level.

Raw data export changes that.

The Google Analytics Big Query export scheme includes a unique ID per user (the default GA CID) and also your internal UID if captured and sent to Google Analytics.

Now you’ll have more control over your data, and that’s a big thing!

User-level raw data allows brands to create advanced analysis and research, build custom attribution models, and enrich their data from other sources such as marketing platforms or internal DB.

User-level raw data availability also opens the gateway for brands to a much-desired capability, which until now was reserved only to the biggest and most advanced. It integrates AI-driven predictions into their workflow.

This integration of smart models can empower brands to level up their UA and growth capabilities by leveraging user-level predictive models for LTV evaluation and UA optimization.

( If you’d like to read more about Predictive LTV Optimization, I would humbly suggest this article I wrote as a starting point.)

The Big Query integration supports hit-level data export. This can be done in real-time or as a daily batch process. The integration is easy and doesn’t require any in-depth technical knowledge (learn how to set up your Big Query integration here).

See YouTube engagement, cross-device, for the first time with better integration to Google’s Marketing Products

Google Analytics’ integration with its marketing platforms has always presented meaningful insights for the marketeer, but not without limitations.

While conversions and goals on the marketing platforms were calculated and presented across the user journey (using Google signals), Google Analytics’ reporting did not match the same abilities, due to cookie-centric processing and modeling (relating to each _ga cookie as a separate user).

With new and advanced integrations across Google’s marketing products, it should become easier to improve the ROI of your marketing (if a significant percentage of your budget is invested in Google Marketing Platform).

Deeper integration with Google Ads, for example, enables marketers for the first time to create audiences that can reach their customers with more relevant, helpful experiences, wherever they choose to engage with their business.

The new Google Analytics 4 approach also makes it possible to make real long time advertiser requests — a better understanding of YouTube performance (WOW to that clapping hand’s emoji).

Because the new Analytics can measure app and web interactions together, it can include conversions from YouTube engaged views that occur in-app and on the web in reports. Seeing conversions from YouTube video views alongside conversions from Google and non-Google paid channels, organic channels, social, and email helps brands understand the combined impact of marketing efforts.

*Apple OS 14 and IDFA depreciation will no doubt affect this ability as well, but even if not applied for all users, this will still shed light on multi-touch attribution.

Powerful analysis capabilities at your fingertips. Answer your questions at the New Analysis Hub

Likely to become the analyst’s favorite feature, the new Analysis Hub is the center of custom reporting and analysis. Google Analytics 4 now has this feature available to ALL users, and it comes with new, insightful analysis types.

Funnel analysis allows you to visualize progress and abandonment through a flow of up to 10 steps. Marketers can now build funnels and easily detect drops from different channels or campaigns, and generate audiences for remarketing of users who dropped from the funnel with just one click (well, maybe two or three clicks)

Segment overlap helps you better understand the overlap between different user segments. Marketing teams can understand how many of their users interact with their brand across different devices, or how many reach their site from multiple channels (and which channels convert well together).

Exploration empowers you to quickly create custom reports, using the drag-and-drop interface to add and remove dimensions, metrics, segments, and filters. Analysts can now slice and dice their data for answers like never before.

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Is it time to start your journey with Google Analytics 4?

There are many more new capabilities and features worth tuning into Google Analytics 4 for. I won’t expand on them now, but they are worth a mention: improved UI, ML insights built into the product and the reports, better data control (opt-out for users) and faster performance (those of you who use Google Analytics often know how significant that is).

It might sound all too perfect, but trust me, it’s not. As mentioned before, there are still some unresolved bugs and missing functionalities (such as filters and views). But as they say, practice makes perfect — and we should all begin practicing our Google Analytics 4 skills.

If you wish to share your own Google Analytics 4 experiences, ask about a specific feature, or if you need help in modeling your users LTV with Google Analytics 4, feel free to reach out.

Co-Founder & CEO at Voyantis — Super powers for growth and UA teams. Before Voyantis I co-founded Tvinci (acquired by Kaltura). Mentor @Techstars.

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