For the last few years, we’ve been promised a simpler way to “get answers” from our analytics data. We often just look at a chart, ask a question, and let the tool explain it to you. Actually, that’s what Google Analytics Advisor is supposed to do. And to be fair, it does explain things. It tells you what you’re looking at. It points out trends too, and it seems to help non-analysts feel a little less lost in GA4. But if you’re looking for a deeper explanation to actually make a decision, you’ve probably felt something is missing or there’s a gap. Knowing that “traffic is down” isn’t the same as knowing why it’s down, whether you should worry, and what you should do next. Real analytics work lives in that gap, in those missing (crucial) information. And we think that’s exactly where most AI assistants in analytics stop being helpful.
The Promise (and Limits) of Google Analytics Advisor
Like most marketers, we’ve been excited about Google Analytics Advisor, thinking it was built to make GA4 easier to live with. For teams that do not spend much time inside reports, this already helps. Instead of guessing what a spike or dip means, you get a short explanation in plain language.
But then the limit starts to show up as soon as you try to use it for decisions. Most of the time, the Advisor stays very close to the obvious. If traffic drops, it tells you traffic dropped. If one channel grows, it tells you what channel that was. It does not usually tell you whether the change is real, whether there could be a problem with your tracking , or if any of it is worth acting on. We feel like it’s avoiding making those calls and stays in safe territory. We think a simple way to think about it is - the Advisor explains data. It does not analyze it.
What People Actually Do Instead
This was or could still be the way we do things today when we hit the limits of built-in explanations, we usually do something very simple- that is to export data from GA4, upload it into ChatGPT, Gemini, or Claude, and start asking real questions there. We’ve actually prepared a separate blog post on how that works, and you can find it here. That is before the Google Analytics Advisor or The Helm came into picture. The process is not the most refined, but it is direct. First, export the data from your Analytics property. Second, upload it to the AI tool you prefer. Third, ask questions that go beyond “what happened” and move into “why might this be happening” and “where should I look next.” Pretty simple, but really tedious and not the most efficient way to do things.
The Real-World Alternatives (And Their Trade-Offs)
Let’s leave Google Analytics Advisor for a bit and let’s take a closer look at what's happening, and the real problem in using external tools is that it does not know your property. It does not remember how your tracking is set up. It cannot notice when something breaks tomorrow because it only sees what you paste in today. There is no auditing and no monitoring. Each session starts from zero.
Let’s take for example Google Gemini and Claude. Gemini knows the Google ecosystem well, which helps when questions drift into how GA4 or related tools work. It still stays generic and still has no access to your actual configuration. Claude is very good at reading large exports and long documents, which makes it useful when you have a lot of rows to review. It runs into the same wall as the others. None of them actually understands how your GA4 property is set up. They do not know which events are critical, or which reports you trust and which ones you already ignore. They also do not know your business model, so they cannot tell whether a change is normal for you or a problem. When something feels off, you still have to do the first round of checking yourself.
In short, these are smart tools that help you think, but they do not take responsibility for the health of your measurement. They can work for some teams, and for a while we used them too. When Google released Google Analytics Advisor, we tried it. It helped with explanations, but it still did not match how we work. That gap is what led us to build The Helm.
Why We Built The Helm
The Helm started from a very practical frustration. We did not want to build another chatbot that sits next to a chart and repeats what the chart already shows. We also did not want another feature that explains reports in a slightly nicer language. That category of tools already exists, and it already stops at the same place. What we kept needing in real work was something that could look at the property itself and tell us whether the setup made sense before we even talked about performance.
So the goal was different. The Helm connects directly to GA4 and reads the actual configuration. It looks at events, conversions, filters, and structure. It runs audits. It flags problems. When something is inconsistent or broken, that comes up first. Only after that does it move into questions about trends and results. The system is also allowed to take positions. It can say that something does not matter, that a report is misleading, or that a drop is probably a tracking issue. That is the difference. The Helm is built for analytics work, not for generic conversations. It is not a general purpose language model, and it is not limited to explaining what is already on the screen.
Where Google Analytics Advisor and The Helm part ways
Google Analytics Advisor and The Helm start from different assumptions about what the problem is. The Advisor assumes the problem is that people do not understand the charts. So it stays close to the report and explains what is already visible. If a line goes down, it tells you it went down. If one channel changes more than another, it points that out.
The Helm starts from a different place. It assumes the problem is that you do not know whether the data and the setup can be trusted in the first place. So it looks at the configuration before it looks at performance. It checks events, conversions, filters, and structure. It looks for things that are missing, duplicated, or broken. Only after that does it move into questions about trends and results.
This leads to two very different kinds of output. The Advisor explains what you are looking at. The Helm tries to decide whether what you are looking at is even the right thing to look at, and what deserves attention first. Let’s put it to a test and ask this very simple question and see how they respond:
Why did conversions drop this week?
Here’s how Google Analytics Advisor responded - and we think it explains the decline but it does not analyze the situation.
Here’s how The Helm gave us the answer:
Want to see how this works on your own GA4 property?
The Helm is currently in open beta. If you are curious how this kind of analysis looks on your own GA4 property, you can try it directly here: https://app.analyticsmates.com
You will be able to connect a property, ask the same kind of questions shown here, and see how the system approaches diagnosis, not just description. It is still a work in progress, and that is the point of the beta.
FAQs
1. Do I still need an analyst if I use tools like The Helm?
Yes. The Helm is designed to augment analysts and teams, not replace your entire team.
2. Is Google Analytics Advisor bad or useless?
No. It’s helpful for basic explanations and learning. It’s just not designed for real decision-making.
3. Can The Helm replace Looker Studio or dashboards?
Not exactly. Dashboards show you data. The Helm helps you interpret and audit what’s behind that data.
4. What makes The Helm different from just connecting GA4 to an AI model?
The Helm understands your setup, monitors it, audits it, and keeps improving context over time. A generic AI tool doesn’t.
5. Will The Helm tell me what to fix first if multiple things are wrong?
That’s one of the main goals: help prioritize, not just list problems.
6. Is this useful for small teams or only big companies?
It’s especially useful for small teams who don’t have time to manually audit and sanity-check everything.
7. Does The Helm work only for GA4?
Today the focus is GA4, but the philosophy is broader: opinionated, system-level analytics, not just explanations.
8. Will it help catch tracking issues I don’t notice?
That’s a core use case: catching silent failures and configuration problems before they ruin your data.
Final Words
Most analytics tools try very hard to stay neutral. They describe what changed and stop there. The Helm was built to do something different. It is meant to say when something is broken, when a metric is not worth paying attention to, and when one area deserves attention more than the rest. Those statements are not always comfortable, but they are the kind of calls analysts make in real work when time is limited and not everything can be investigated at once.
So, if you’re serious about using GA4 to run your business better, you eventually need more than descriptions. You need judgment. You need priorities. You need a system that watches your setup, challenges your assumptions, and tells you when something is off. That’s the gap The Helm is built to fill. And if you’re ready to stop translating charts into decisions by hand, this is the direction analytics is heading.
Thank you for reading!
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