Ga4 New Updates and Features

Did you notice that GA4 annotations (finally) arrived? 🙌 (I actually did raise my hands at my desk when they came out.) I've been waiting for this feature since GA4 launched. I bet you can think of a number of times when you've stared at a random traffic spike in GA4 and thought "what the heck happened here?" only to spend 20 minutes digging through emails and Slack to figure out it was from a newsletter mention or campaign launch. Now you can annotate it and save future you from the same waste of time and energy! What I really like about GA4's implementation is that they improved on what Universal Analytics offered. You can now create date ranges (perfect for marking full campaign periods), add annotations in the future, use color coding for instant visual categorization, and export your annotations to CSV. Plus there's centralized management so you can see all annotations in one place instead of hunting through different date ranges. I know it's tempting to just dive in there and annotate away, but hold on! You need a strategy before you start creating annotations. Without clear naming conventions and color coding rules, you'll end up with a chaotic mess that makes things worse for future you (and your co-workers). That's why I put together a complete guide that goes way beyond Google's basic documentation. It includes advanced strategies, best practices, and a free Standard Operating Procedure template you can download and customize for your team. Because let's be honest, the success of annotations isn't in the feature itself but in how consistently your organization uses them. Have you started using GA4 annotations yet? What's the first thing you annotated? #GA4 #GoogleAnalytics #DigitalMarketing

Hold on – spits out coffee! 🤯 Big update for Google Analytics 4 and BigQuery just hit! There’s now a new type of data transfer that loads prepped, analysis-ready tables into BigQuery. Until now, we’ve only had raw event-level data. This new setup adds aggregated tables at different levels. To start it, Go to BigQuery Studio → Data Transfers → Create Transfer → Choose Google Analytics 4. Pick your project, dataset, update frequency – and relax. Next surprise: it supports backfill – you can load historical data. That’s never been possible before. This might seem small, but this could potentially open up much better reporting and data activation options. Compared to the old export, this could be a big deal. But the questions reamins, how granular is it? Does it contain all the data we need to join? Will it match the GA4 interface? But don’t get too excited yet. I tried setting it up and hit a weird error. Google says it’s "as is with limited support". So it might need more work before everything runs smoothly. Setup guide: https://lnkd.in/dmcfgZg5 Table structure: https://lnkd.in/dMZA46NN What do you think? Time to pop the champagne? Will this change how you work in BigQuery with GA4?

Google Analytics 4 #BigQuery export added a few new fields to its schema. The updates took place on 7/11/2024. 3 fields on the root level: - batch_event_index - batch_page_id - batch_ordering_id 3 fields on the collected_traffic_source: - manual_source_platform - manual_creative_format - manual_marketing_tactic These fields are not yet available in the official documentation. The batch fields can finally provide a unique key for each event within a session. In the screenshot attached, you can see events from a single session ordered by the event timestamp ascending. A combination of all three batch fields provides a unique identifier (and order) for each event, even if sent at the exact same timestamp. Example: Rows 5 and 6 in the screenshot have the same user pseudo id, session id and event_timestamp, however, within the same batch page, and batch order one has an event_index 1 and the other one 2. This finally allows us to get deterministic ids for the GA4 events.

The #GA4 Data Transfer in #BigQuery released earlier this year used to fall into the “good for nothing” territory. Well, not anymore. Google has updated it to allow pulling a custom table in a data transfer, with a maximum of 9 dimensions and 10 metrics, instead of the standard tables that were (let’s be honest) rather underwhelming. 💡 Now you can pull data from GA4 that is actually interesting: either a combination of dimensions and metrics that is particularly relevant in your business, or something that helps you troubleshoot things, e.g. allows to cross-check information between this and the GA4 native export (e.g. user counts under specific circumstances), or complementary information e.g. age / demographic breakdown. 🔢 One transfer can only include one custom table, but it’s not a big limitation as you can set up multiple transfers (as many as you want, really). When you set up the transfer, you don’t need to use table filters (and you can’t either): Google is smart enough to realize that if you pull a custom table, chances are that you don’t need any of the default ones. 🔎 The transfer documentation recommends using the GA4 Dimensions & Metrics Explorer website, which I can second from my own experience, as picking the right combination of dimensions and metrics might take a few trials.                                                                             👍 The GA4 Data Transfer may not be the most ground-breaking invention, but they added the exact feature it needed the most: the capability to pull a customized table. Of course there are plenty of other tools out there that do the same thing — 3rd party tools or an n8n workflow recently developed by Ali Izadi — but now it’s suddenly a lot easier to do this, as you don’t even need to step out of the BigQuery environment, and it can be set up within a few minutes. -- Follow me for updates on #digitalanalytics, BigQuery and #digitalmarketing #data solutions, and sign up to GA4BigQuery to get updates in your inbox.

A happy day for 📊4️⃣ analytics, I’ve got a big time saver for you. One of the glaring misses for Google Analytics 4 has finally been fixed. Rolling out this week and going forward, administrators and editors of GA4 properties can now save comparisons within their GA4 property. This means you and your team can easily access and reuse the user segments you frequently analyze without having to recreate them each time. What is a comparison? Is a feature that allows GA4 editors and administrators to compare user segments based on dimensions. The problem was, once you created comparisons, they never could be saved. That meant you had to re-create the comparison every time you went into the report. If you use Google analytics 4 on a regular basis, you know this solves a huge pain point. The old Google Analytics Universal, or GA3 accomplished this through saved segments. These comparisons can be super helpful in looking at various user groups, and comparing their performance. ⭐️For instance, you could compare your paid Facebook campaigns, with your organic search traffic, comparing across the dimensions of default channel group, or source/medium. You can build comparisons like this on any dimension in GA4, and look at various related metrics. Often users get confused around the difference between dimensions and metrics. Just think of them like a spreadsheet, the dimensions are the rows, the metrics are the columns 🔑 Additionally, Google has added the ability to define audience-based conditions through saved comparisons. This feature allows you to create and report on advanced user segmentations, such as defining a comparison as audience name = "OEM referral traffic." 💰 With these new capabilities, you'll be able to: ✅ Save time by reusing previously created comparisons ✅ Ensure consistency in your analysis across your team ✅ Quickly access and report on your key user segments If you're an administrator or editor of a Google Analytics property, be sure to check out these new features and start incorporating them into your analysis process. 📊 Follow George Nenni for more #automotive #automotivemarketing #automotiveindustry #googleanalytics4 tips and strategies to help your dealership

𝑻𝒊𝒓𝒆𝒅 𝒐𝒇 𝒓𝒆𝒄𝒓𝒆𝒂𝒕𝒊𝒏𝒈 𝒔𝒆𝒈𝒎𝒆𝒏𝒕𝒔 𝒊𝒏 𝑮𝒐𝒐𝒈𝒍𝒆 𝑨𝒏𝒂𝒍𝒚𝒕𝒊𝒄𝒔 4? Get ready for a game-changer! Google Analytics 4 has just introduced a new feature that will save you countless hours: 𝐒𝐞𝐠𝐦𝐞𝐧𝐭 𝐒𝐡𝐚𝐫𝐢𝐧𝐠. Now, you can create segments once and share them across your entire team, ensuring everyone is looking at the same data. 𝑲𝒆𝒚 𝒃𝒆𝒏𝒆𝒇𝒊𝒕𝒔: * 𝐼𝑚𝑝𝑟𝑜𝑣𝑒𝑑 𝑐𝑜𝑛𝑠𝑖𝑠𝑡𝑒𝑛𝑐𝑦: No more discrepancies in data analysis due to different segment definitions. * 𝐼𝑛𝑐𝑟𝑒𝑎𝑠𝑒𝑑 𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦: Save time by not having to recreate segments for every report. * 𝐸𝑛ℎ𝑎𝑛𝑐𝑒𝑑 𝑐𝑜𝑙𝑙𝑎𝑏𝑜𝑟𝑎𝑡𝑖𝑜𝑛: Share insights and collaborate more effectively with your team. 𝐇𝐨𝐰 𝐭𝐨 𝐮𝐬𝐞 𝐢𝐭: * 𝑪𝒓𝒆𝒂𝒕𝒆 𝒔𝒆𝒈𝒎𝒆𝒏𝒕𝒔: Easily create custom segments or choose from pre-built options in the shared library. * 𝑺𝒉𝒂𝒓𝒆 𝒘𝒊𝒕𝒉 𝒚𝒐𝒖𝒓 𝒕𝒆𝒂𝒎: Grant access to other users with an Editor or higher permissions. * 𝑳𝒆𝒗𝒆𝒓𝒂𝒈𝒆 𝒏𝒆𝒘 𝒇𝒆𝒂𝒕𝒖𝒓𝒆𝒔: Explore options for applying, editing, duplicating, and removing segments. 𝑰𝒎𝒂𝒈𝒊𝒏𝒆 𝒕𝒉𝒆 𝒑𝒐𝒔𝒔𝒊𝒃𝒊𝒍𝒊𝒕𝒊𝒆𝒔! * 𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐭𝐞𝐚𝐦𝐬: Collaborate seamlessly using shared customer segments. * 𝐀𝐠𝐞𝐧𝐜𝐢𝐞𝐬: Provide consistent reporting and analysis for clients. * 𝐄-𝐜𝐨𝐦𝐦𝐞𝐫𝐜𝐞 𝐬𝐢𝐭𝐞𝐬: Track performance across different customer groups. 𝐴𝑟𝑒 𝑦𝑜𝑢 𝑟𝑒𝑎𝑑𝑦 𝑡𝑜 𝑠𝑡𝑟𝑒𝑎𝑚𝑙𝑖𝑛𝑒 𝑦𝑜𝑢𝑟 𝑑𝑎𝑡𝑎 𝑎𝑛𝑎𝑙𝑦𝑠𝑖𝑠 𝑤𝑖𝑡ℎ 𝐺𝑜𝑜𝑔𝑙𝑒 𝐴𝑛𝑎𝑙𝑦𝑡𝑖𝑐𝑠 4'𝑠 𝑛𝑒𝑤 𝑠𝑒𝑔𝑚𝑒𝑛𝑡 𝑠ℎ𝑎𝑟𝑖𝑛𝑔 𝑓𝑒𝑎𝑡𝑢𝑟𝑒? Let me know in the comments! #GoogleAnalytics4 #DataAnalysis #SEO #Marketing #DigitalAnalytics #ContentMarketing

GA4 now allows you to upload cost data from more data sources including Google Sheets, BigQuery & Snowflake. Importing cost could be valuable in case you want to get a more holistic ROAS in GA4. The update makes doing this more flexible and dynamic. For example, you can now automatically pull Facebook ad costs from BigQuery (since there's a direct connection already). You used to only be able to import from a CSV or SFTP so this is a nice update

🚨 GA4 UPDATE: New Key Events Layout Just Dropped Google just quietly rolled out a UI change (shocker, I know) that could mess with your GA4 workflow if you're not paying attention. Normally, to manage Key Events, you'd go: Admin > Data display > Key events BUT in some properties, this path is gone. Instead, it now lives under: Admin > Data display > Events From there, you’ll click the ⭐️ star next to the event to mark it as a Key Event. What this means: - If you don’t know where to look, you might think your Key Events vanished. - If you're onboarding a new store or QA’ing a vendor setup, this change can throw you. - And if your reporting suddenly looks off? Start here first. Not all properties are impacted (yet), but this feels like a full rollout in progress

Did GA4 just make a massive comeback? In case you missed Google Marketing Live announcements yesterday, here are a few big changes coming: 1. Cross-channel attribution now includes ability to import non-Google campaign data directly into GA4 from Pinterest, Reddit, and Snap. Will Meta be next? 2. Benchmarking. Probably one of the most widely requested feature of Elevar for years! "How do I stack up against ________". Well, there's a new GA4 feature rolling out that will help you understand how your performance compares to businesses similar to you. 3. Open-source MMM Model - Meridian. I'm curious how this will compare to other leaders in the MMM space. Will brands test this to compare against their existing MMM/MTA solution? Will they fully embrace? 4. Forecasting tooling that includes a projections planner and scenario planner. With this update, you’ll be able to track campaign pacing and projected performance across channels—and get recommendations. 5. Data Manager. This has been around for a while behind the scenes (I believe announced 2 years ago?). But it's essentially a pipeline into your Google property to enrich the data that the Google Tag is already collecting. One of the main benefits here will be to help with Enhanced Conversions => Attributed Conversions. Still digesting all of the amazing updates. Unfortunately for those GA4 doomsdayer's, it looks like GA4 is here to stay!

🚀 GA4 Update GA4 announced an update to Cost-Data Import, which essentially allows you to bring in your ad costs for non-Google channels into a single view in GA4 and understand CPA and ROI holistically. The update: GA4 will now provide insights for imported cost data even without perfect matches for required dimensions. This update reduces friction and ensures your imported data is more useful by reporting cost, impressions, and clicks based on any available required dimensions. Here’s why cost-data import is useful: 🎯 Unified ROI Tracking: Now, you can analyze deeper cost-centric KPI's for all paid channels, not just Google Ads. 🎯 Custom Parameters = Better Attribution: By tagging your non-Google ad URLs with UTM parameters (like utm_id or utm_campaign), GA4 can connect campaign performance directly with your imported cost data. 🎯 Dynamic Data Updates: Ad costs fluctuate, so GA4 lets you update data for the same campaigns over time, ensuring your reporting stays accurate and reflects the latest numbers. How to see this: Acquisition > Non-Google Cost Report or the Planning > All Channels Report 💡 Ready to try it? Start by tagging your ad URLs with UTM parameters, creating a CSV of your cost data, and uploading it into GA4. #PPC #GA4 #GoogleAds #DTC #ecommerce #sem #sea ♻️ Repost to share with your network if you found this valuable 💡Follow Jordan Fry for more practical PPC tips, tactics, and updates like this