What is Not the Function of Google Analytics?
Google Analytics is exceptionally good at telling you what groups of anonymous visitors do on your website - which pages they view, where they come from, and which paths they take. But understanding what it doesn't do is just as important as knowing what it does. This article clarifies the common misconceptions about Google Analytics' functions so you can use it for its intended purpose and know when to reach for a different tool.
It Doesn't Tell You Who Your Users Are Personally
One of the biggest lines Google Analytics draws in the sand is around user privacy. It is fundamentally designed to collect anonymous, aggregated data. This means that while you can see patterns in user behavior, you can't tie that behavior back to a specific individual's personal information.
According to its terms of service, collecting Personally Identifiable Information (PII) is strictly forbidden. This includes data such as:
- Names
- Email Addresses
- Phone Numbers
- Precise Physical Addresses
GA works by assigning a randomly generated string of numbers, called a Client ID, to a user's browser via a cookie. This lets GA recognize the same browser returning to your site. However, that ID is pseudonymous, meaning it isn't linked to a real person's identity in GA's analytics reports.
What This Looks Like in Practice
Imagine your sales team closes a deal with someone named "Jane Doe." You cannot go into Google Analytics, search for Jane Doe, and see her entire browsing history on your website - the pages she visited, the buttons she clicked, or how she found you. GA can tell you that a user from San Francisco, using a Chrome browser on a Mac, visited your pricing page three times before converting, but it won't tell you if that user was Jane.
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What to Use Instead
For tracking individual user journeys, you need tools that are explicitly built for managing customer relationships and identity.
- Customer Relationship Management (CRM) Systems: Tools like Salesforce and HubSpot are the classic examples. When a lead fills out a form, their on-site activity (tracked via the CRM's own code) is connected directly to their unique contact record - email, name, company, and all.
- Email Marketing Platforms: A service like Klaviyo or Mailchimp can track exactly how a known subscriber interacts with your marketing emails and the subsequent behavior when they click through to your site.
It Doesn’t Explain the "Why" Behind User Behavior
Google Analytics is a master of quantitative data. It excels at answering questions that start with "what," "how many," "when," and "where."
- What is my most popular landing page?
- How many users converted from the last email campaign?
- When do most users abandon their carts?
What it can't tell you is why. It reports the symptom, not the cause. GA can show you a high bounce rate on a key landing page, but it offers zero insight into whether users left because the page's design was confusing, the content didn't match their expectations, the price was too high, or a technical glitch prevented the page from loading correctly.
What This Looks Like in Practice
You launch a new feature and create a beautiful landing page for it. In Google Analytics, you see that traffic is high, but the conversion rate is near zero, and the average time on page is only a few seconds. The data screams that something is wrong, but it doesn't give you a diagnosis. Is your call-to-action button not working on mobile? Did the ad you ran promise something the page doesn't deliver? You won't find the answers in GA's pageview reports.
What to Use Instead
To understand the "why," you need qualitative feedback directly from your users.
- Session Replay & Heatmap Tools: Solutions like Hotjar, FullStory, and Microsoft Clarity record anonymous user sessions, letting you watch videos of how people move their mouse, where they click, and how far they scroll. Heatmaps give an aggregated view of clicks, so you can see if users are clicking on non-clickable elements in frustration.
- On-Site Surveys: Tools like Hotjar or SurveyMonkey can trigger short, contextual surveys. For example, you can launch a poll that asks "What's stopping you from signing up today?" just as a user is about to leave the checkout page.
- User Testing Platforms: A service like UserTesting.com allows you to pay people in your target demographic to perform specific tasks on your site and speak their thoughts aloud. This provides direct feedback on what they find confusing or useful.
It's Not a Full Cross-Device Customer Journey Tracker
The modern customer journey is fragmented. A person might see your advertisement on Instagram while on their phone, do some research on their work laptop a day later, and finally make a purchase on their personal tablet that evening. To them, it's one continuous buying journey. But to traditional, out-of-the-box Google Analytics, it looks like three different users from three different devices and potentially three different marketing channels.
Google works to stitch these sessions together with features like Google Signals and User-ID, but these have limitations. User-ID, for example, only works if a user is logged into your site across all those devices, which is common for SaaS products and e-commerce stores with customer accounts but not for many other types of websites.
Furthermore, GA fundamentally cannot track offline interactions. If a user researches online then places an order over the phone or visits your brick-and-mortar store, GA has no way of connecting that final conversion back to the initial digital touchpoints.
What This Looks Like in Practice
Your team runs a brilliant Google Ads campaign. A user clicks an ad on their laptop and browses your products but doesn't buy. Later that day, they remember your brand, directly type your URL into their phone's browser, and complete the purchase. In default GA reporting, the revenue from that sale would likely be attributed to "Direct" traffic, making your Google Ads campaign look less effective than it actually was. GA couldn't connect the initial ad click on the laptop to the final sale on the phone.
What to Use Instead
Getting a unified customer view requires tools that centralize data from many sources.
- Customer Relationship Management (CRM): A powerful CRM like HubSpot is purpose-built to solve this. It can track a lead's interactions from different web devices and even incorporate offline data, such as notes from a sales call logged by a team member.
- Dedicated Attribution Platforms: For businesses running complex campaigns, advanced B2B attribution tools that connect to CRMs can provide a much more accurate picture of a channel's true influence on revenue.
It's Not Your Financial Source of Truth
Google Analytics provides fantastic Ecommerce tracking that helps marketers understand which campaigns are driving revenue on the website. You can see transaction IDs, revenue per user, product performance, and conversion rates. However, this is marketing data, not accounting-grade financial data.
The revenue figures in a digital marketplace might not match your company's actual bank deposits for several reasons:
- Refunds and Returns: GA records a sale when it happens. If a customer returns the product a week later, GA's reported revenue will be higher than your actual revenue.
- Exclusions (Taxes and Shipping): Depending on your setup, the platform might show gross revenue, while your business financials often focus on net revenue after excluding taxes and shipping costs.
- Tracking Errors: Adblockers might prevent tracking code from executing, or browsers can stop the ecommerce tracking pixel from firing, causing GA to miss a valid transaction.
- Offline Transactions: It doesn't track offline transactions, which would be recorded in your accounting software for phone sales.
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What This Looks Like in Practice
Your weekly marketing report, pulled from GA, proudly shows $50,000 in revenue. Meanwhile, the finance team's report from Stripe or Shopify shows $47,000. The discrepancy is likely due to $3,000 in customer refunds processed that week. Both reports are "correct" for their purpose - GA is measuring marketing-driven sales, and Stripe or Quickbooks is measuring actual cash flow.
What to Use Instead
There's no substitute for proper financial and platform-specific reporting.
- Ecommerce Platforms: Your official sales data source should always be your e-commerce platform back-end, whether that's Shopify, WooCommerce, or another alternative of your choice.
- Payment Gateways: Tools like Stripe and PayPal are the gatekeepers of your actual transaction volume.
- Accounting Software: A software platform such as QuickBooks or something new (e.g., Xero, NetSuite) is where you reconcile all revenue alongside the cost of goods sold (COGS), operating expenses, and taxes.
Final Thoughts
Leveraging Google Analytics effectively means embracing both its strengths and limitations. It serves as an essential tool for understanding the aggregated, anonymous "what" of on-site user behavior, revealing trends and analyzing how people interact with a website. Once you recognize that it doesn't function as a CRM, a user-testing tool, or an accounting ledger, you can pair it with other specialized tools to build a comprehensive view of your business performance.
The real issue is that each of these tools - your ad platforms, your Shopify store, your HubSpot analytics, GA - holds just one part of the story. Stitching it all together often takes tedious, manual work with hours of reporting and human intervention. We believe getting data answers shouldn’t be so hard, so we created Graphed to connect to all your marketing and sales tools instantly. This way, you can finally use simple, natural language to build real-time dashboards that show the full customer journey, answering questions a single analytics program such as Google Analytics never could - saving you countless hours normally spent on manual report production each week.
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