Google Analytics remains one of the most effective tools for understanding how your website performs online. It offers a wide range of metrics that allow you to track user demographics, measure landing page conversions, and monitor click-through rates—delivering valuable insights that inform strategic decisions.

However, despite its many advantages, errors in setup are common. Misconfigurations, even minor ones, can lead to inaccurate data and flawed reporting. These issues not only undermine your ability to make data-driven decisions but also waste time and resources.

Understanding and avoiding these common mistakes is essential to ensure your Google Analytics implementation delivers reliable, actionable insights. In this guide, we’ll explore the most common mistakes people make when setting up Google Analytics—and how to avoid them.

Common Mistakes People Make When Setting Up Google Analytics

Google Analytics is a powerful tool for understanding how users interact with your website. However, the value it provides is only as good as its configuration. Poor setup leads to inaccurate tracking, misleading insights, and missed opportunities to optimise your digital strategy. Let’s examine some of the most common mistakes people make when setting up Google Analytics and how to avoid them from the outset.

Not Tracking Code Errors

When websites use multiple content management systems (CMS), it’s easy to mistakenly input incorrect or duplicate tracking code, leading to partial data collection, duplicated pageviews, or no tracking at all. Though Google Analytics provides notifications for missing code, these alerts can be delayed, causing potential data loss due to the slow notification time.

Common Causes Include

• Installing the wrong tracking ID
• Implementing both GA4 and legacy UA code without proper coordination
• Placing code in the wrong part of the site template
• Duplicating the code on multiple templates

Solution

Use tools like Google Tag Assistant or Screaming Frog with custom extraction to audit your site and scan for missing or duplicated GA4 and/or Google Tag Manager (GTM) snippets. Ensure the code is consistently placed on all relevant pages and avoid duplicate implementations.

Choosing the Wrong GA Property

ce “Universal Analytics” sunsetted in July 2023, GA4 is now the default and only supported property for Google Analytics. Some users mistakenly continue to rely on old properties or choose the wrong account structure for their website.

Why it Matters

Using the wrong property can prevent access to essential GA4 features and functionalities that are crucial for your business. These features include event-based tracking, machine learning insights, and future-proof support for privacy compliance.

Solution

Always use GA4 for new implementations. Review the type of property currently in use and transition fully to GA4 if you’ve not already done so. For app-based platforms, opt for “Google Analytics for Firebase” to track application usage and user engagement.

Ignoring Internal Traffic Filters

Accurate session tracking is essential for understanding user behaviour. When internal users, such as your team or developers, visit the site, their sessions can lead to inaccurate session data and distort key metrics such as bounce rate, average session duration, and conversion rate. By default, Google Analytics records all traffic—including yours.

Solution

Set up filters in your GA4 data stream or via GTM to exclude internal IP addresses, eliminate bot traffic, and segment data for clear analysis. In GA4, this can be done using Define Internal Traffic rules in the Admin settings and applying them via a testing parameter or custom dimension. Alternatively, GTM can be used to apply additional filters for internal sessions, ensuring only genuine user data is captured.

Implementing a Referral Exclusion List

Referral exclusions are important when traffic comes from external sources, such as payment gateways or subdomains. Without these exclusions, Google Analytics may count returning users as new sessions, disrupting session continuity and attribution accuracy.

Solution

In GA4, go to Admin > Data Settings > Referral Exclusion List to set up exclusions for sources like payment gateways. Additionally, ensure that the “Cookie Domain” is set to ‘auto’ in your default configuration, which may redirect customers to their payment processors before returning them to your site. This helps maintain session integrity across different domains and prevents misattribution of user sessions.

Separate Sources and Mediums

Referral traffic, especially from platforms like Facebook, can appear under multiple sources due to link shim referrals, which Facebook uses for privacy reasons. This can cause confusion in your analytics, making it difficult to track true performance.

Solution

Use filters in Google Tag Manager to combine and correctly attribute social media traffic. This ensures that Facebook referrals, for example, are grouped under the appropriate source. This will provide a clearer view of your traffic sources and help optimise your marketing efforts.

Ignoring Spam and Bot Traffic Filtering

As your website grows, it’s likely to attract spam referrals and bot traffic, both of which can distort your data and hinder accurate performance analysis. Spam referrals can obscure genuine traffic, while bots can inflate session counts, distort engagement metrics, and make data unreliable.

Solution

In GA4, navigate to Acquisition > All Traffic > Referrals to identify and exclude spammy sources. You can filter these by Campaign Source to block these domains and improve referral accuracy. Additionally, enable Bot Filtering under Admin > Data Settings > Data Filters to exclude known bots and spiders from your reports. This dual approach helps ensure that only real human interactions are counted in your data, leading to more reliable insights.

Failing to Track Conversions

Setting up Google Analytics without configuring conversion tracking is a missed opportunity. In GA4, conversions are not automatically tracked; you must define them manually. Without clear conversion tracking (form submissions, contact clicks, purchases), it’s impossible to measure ROI or evaluate performance effectively.

Solution

Use Google Tag Manager to define events like form submissions, clicks, newsletter signups, and purchases. Then mark these as “Conversions” in GA4’s Admin > Events section. Tailor conversion tracking to align with your key business goals and sales funnel stages.

Not Using Google Tag Manager (GTM)

Many users still implement GA4 directly in the site’s code, limiting flexibility and increasing reliance on developers for updates. Without GTM, making changes to your tracking setup (e.g. adding event tracking, fixing errors, or testing tags) becomes time-consuming and error-prone.

Solution

Install Google Tag Manager and use it as the primary method to deploy GA4 tags, conversion events, remarketing pixels, and more. GTM streamlines management, improves testing, and reduces the need for hardcoded scripts.

Tracking the Incorrect Domain

It is remarkably easy to track the wrong domain within Google Analytics. Implementing preventative measures is essential to ensure you are tracking your own domain and not incorporating hit results from other websites. As your Google Analytics or Google Tag Manager tracking code is visible to anyone who inspects the source code, external entities can readily skew your data.

Solution

To avoid this, implement a view filter in GA4 that includes the hostname in the filter pattern. This ensures that only hits to your domain are tracked, eliminating data pollution from external sources.

Incorrect Configuration of Interaction Events 

Website visitors frequently interact with the diverse content available to them. Interaction events, such as video plays, form submissions, and purchases, are typically set up to prevent a bounce when only one page is viewed. However, if you observe a near-zero bounce rate across your entire site, it suggests that interaction events may be configured incorrectly.

Solution

Ensure that the Non-Interaction Hit setting is configured correctly. For example, if you’re tracking scroll depth or other non-essential interactions, set Non-Interaction Hit = true in Google Tag Manager. Alternatively, adjust the Google Analytics Event Snippet to reflect this setting, which will prevent these interactions from affecting the bounce rate.

Account Setup Mistakes

Setting up Google Analytics accurately is crucial for gathering valuable website data and extracting actionable insights. However, significant errors during the setup phase can hinder your ability to understand user behaviour and make well-informed decisions. Let’s examine some common account setup mistakes and practical solutions to ensure an accurate and insightful analytics experience:

Establishing Multiple Views

A common mistake when setting up Google Analytics is failing to create multiple views. By maintaining the following three distinct views, you can better track data accuracy and resolve potential issues as they arise.

• Master View: This is where you implement all relevant filters and settings for the most accurate data collection.
• Backup View: This view retains the default settings, preserving your raw data for reference in case of mistakes or misconfigurations.
• Testing View: Use this view to experiment with different settings and filters before applying them to your main tracking views.

Solution

Create multiple views to ensure data integrity and facilitate easier troubleshooting. Always keep a backup view to protect your raw data, and use filters in the testing view to fine-tune your settings without affecting your main data.

Not Tracking Personally Identifiable Information

Tracking personally identifiable information (PII), such as email addresses, names, or phone numbers, through Google Analytics is against data privacy regulations like GDPR and CCPA. Failing to adhere to this rule can result in legal complications and damage your business’s reputation.

Solution

Ensure that you do not track PII by using a tool like Dataslayer to verify what data is being collected. Most CMS platforms prevent this by default, but custom-built websites may inadvertently collect sensitive information through online forms or other inputs. Regularly review your analytics setup to confirm that PII is not being captured.

Neglecting Data Security and Privacy

Data security is paramount when handling user data. Failing to implement proper security measures can expose your account to unauthorised access and accidental data loss.

Solution

Implement strong password protection, assign user permissions appropriately, and make sure you follow best practices for data privacy. Familiarise yourself with privacy regulations such as GDPR and CCPA to ensure compliance. Also, enable two-factor authentication (2FA) for an added layer of protection.

Neglecting Data Retention Settings

Data retention settings dictate how long Google Analytics stores your website data. If these settings are incorrect, you may either lose valuable historical data or incur unnecessary data storage costs.

Available Options

• Automatic Deletion: Data is deleted automatically after a specified period (14 months, 26 months, 38 months, or 50 months).
• Manual Deletion: You delete data manually whenever needed.
• Export and delete: Data is exported first before manual deletion.

Solution

Review your industry standards and legal requirements to choose a data retention period that meets your needs. Based on these needs, set up automatic or manual deletion strategies to manage costs and retain necessary data.

Ignoring User Permissions

Properly managing user permissions ensures that only authorised individuals have access to your Google Analytics account, safeguarding your data from accidental or intentional tampering.

Solution

Define clear roles for each user accessing your Analytics account and assign specific permissions based on user needs (e.g., View, Edit, Manage Users). Enable 2FA for enhanced security and ensure that sensitive data is protected.

Remember: Taking the time to set up Google Analytics correctly is an investment in your long-term success. By avoiding these common mistakes and embracing best practices, you ensure access to accurate, actionable data that drives insightful, data-driven decisions.

Data Analysis and Reporting Shortcomings

The true power of Google Analytics lies not just in collecting data but in transforming that data into meaningful insights through effective analysis and reporting. However, common pitfalls can hinder your ability to extract clear takeaways and make data-driven decisions. Let’s explore some shortcomings to avoid and unlock the full potential of your analytics data:

Failing to Create Custom Reports

Relying solely on pre-built reports in Google Analytics without customisation limits the ability to gain deeper insights tailored to your business needs. These default reports provide a general overview but often don’t address specific questions or key performance indicators (KPIs) that matter most to your business.

Solution

Define your KPIs and build custom reports to track progress towards those KPIs. Use filters and segments to isolate relevant data and focus on the metrics that matter most to your business.

Ignoring Data Visualisation Best Practices

Data can quickly become overwhelming when displayed poorly. Cluttered spreadsheets, unreadable charts, or overly complex visualisations obscure key insights and make the data harder to interpret. Clear and effective visual storytelling makes data accessible and impactful.

Solution

Select the most effective chart types for your data (e.g., bar charts for comparisons, line charts for trends). Use colour sparingly to highlight key insights and keep charts clear and concise. Interactive visualisations can engage your audience further and provide deeper insights.

Misinterpreting Data

Data analysis should always be done in context. Without understanding the full context of the data, conclusions can be drawn prematurely, leading to misinterpretations. Misinterpreting data due to a lack of context or jumping to conclusions can lead to misguided business decisions.

For example, ignoring seasonal patterns, comparing different types of data (e.g., website vs. app data), or attributing conversions to the wrong touchpoint can skew your analysis.

Solution

Always consider relevant factors that might influence your data, such as seasonal trends or the impact of specific marketing campaigns. Use historical comparisons or benchmark data to provide context for your analysis. Leverage segmentation and attribution models to understand the full user journey and make more informed decisions.

Overlooking Advanced Features

Google Analytics offers a wealth of powerful features that go beyond basic reporting. By leveraging these advanced functionalities, you can unlock deeper insights and optimise your marketing efforts.

Neglecting User ID Tracking

User ID tracking allows you to connect user behaviour across multiple devices, providing a complete, cross-platform view of the user journey.

Solution

Set up User ID tracking to understand how users interact with your website and app across different platforms. This enables more effective personalised marketing and retargeting strategies that can improve engagement and conversion rates.

Forgetting Remarketing Audiences

Creating and leveraging audience insights for remarketing can significantly boost the effectiveness of your advertising and re-engagement campaigns.

Solution

Create remarketing audiences based on user actions such as page views, purchases, or app usage. Use these audiences for targeted ad campaigns to increase user engagement and drive conversions.

Lack of Custom Dimensions and Metrics

Standard metrics in Google Analytics are useful. However, custom dimensions and metrics allow you to capture specific data points unique to your business, unlocking more tailored insights.

Solution

Identify the specific data that’s not captured by standard metrics. Set up custom dimensions and custom metrics to track unique information relevant to your business. This will provide a deeper understanding of your target audience and website/app performance.

Remember: Data analysis and reporting are iterative processes. Continuously experiment, learn from your mistakes, and refine your approach. By embracing advanced features and avoiding these common shortcomings, you can transform your Google Analytics data into a powerful tool for driving informed decisions and achieving your business goals.

Preventing Common Mistakes People Make When Setting Up Google Analytics

Google Analytics and Google Tag Manager offer powerful capabilities, but they come with complexity. With so many moving parts, including tags, triggers, variables, and configuration settings, it’s easy to make small errors that have a big impact on your data accuracy. Maintaining an organised setup and adopting a structured approach are key to avoiding these issues.

Solutions

• Ensure your tags, triggers, and containers are clearly named and systematically organised within Google Tag Manager.
• Use preview mode in GTM and debug tools like Google Tag Assistant to validate implementations before publishing.
• Perform routine audits using tools such as Screaming Frog or Dataslayer to check for broken tags, duplicate tracking codes, or missing data layers.
• Document your tracking setup and regularly test it following website updates or marketing changes.

By investing time in ongoing testing and maintenance, you’ll reduce errors, maintain clean data, and ensure your analytics platform continues to effectively support your business goals.

Conclusion

Setting up Google Analytics correctly is essential for collecting accurate, meaningful website data. Misconfigurations—whether in goals, channel grouping, domain setup, or event tracking—can lead to misleading analysis and misinformed decisions.

To avoid these issues, take the time to understand best practices and regularly audit your setup. Whether you’re working with GA4 directly or via Google Tag Manager, attention to detail during implementation ensures trustworthy data.

With a correctly configured setup, Google Analytics becomes a powerful tool for understanding user behaviour, optimising marketing strategies, and driving continuous improvement across your digital presence. Monitor key reports and metrics regularly to stay aligned with your business goals.

FAQs

Have questions about setting up Google Analytics for your business? Leave a comment below or get in touch—we’re here to help you get the most out of your analytics setup.