Best Practices for Maintaining Data Accuracy in Google Analytics

Best practices for maintaining data accuracy in Google Analytics include:

• Set up conversions properly by defining recommended or custom events and marking key ones as conversions to track meaningful actions accurately.

• Remove unwanted referrals and filter bot traffic to prevent inflated or misleading metrics. This can be done via Google Tag Manager or GA4 settings.

• Fix cardinality issues to avoid excessive "(not set)" or "others" categories in reports, which indicate incomplete or aggregated data.

• Activate Google Signals to enhance data collection and enable deduplication of user data across devices.

• Link GA4 to Google Search Console and BigQuery to enrich data quality and enable advanced analysis and data backup.

• Assign unique transaction IDs for e-commerce events to avoid duplicate transaction counting.

• Regularly audit your Google Analytics setup to ensure tracking codes are correctly implemented on all pages, especially critical ones like checkout confirmation pages.

• Filter out known bot traffic and cross-reference Google Analytics data with other sources such as server logs or sales reports to validate accuracy.

• Minimize the use of VPNs or proxies and avoid altering IP addresses in tracking setups to improve the accuracy of geographic and language data.

• Implement data governance practices by standardizing data entry, validation, and storage procedures across teams to reduce discrepancies.

• Automate data integration and monitoring to reduce human error, maintain a single source of truth, and keep data up to date.

• Define clear data ownership within your organisation to ensure accountability for data quality and accuracy.

These combined practices help ensure that Google Analytics data is reliable, actionable, and reflective of true user behaviour. Regular maintenance and validation are key to sustaining data accuracy over time.