Undeniably, data in today’s enterprise ecosystem is everything. From decoding customer preferences, understanding user behavior or making crucial business decisions, data controls it all. It is why enterprises invest in leading analytics tools to ensure continuous excellence and innovation.
When it comes to data analytics, Google Analytics and Adobe Analytics are both popular tools, well-known for their respective capabilities. Depending on the level of analysis you wish to perform, you might employ either of these tools or any other data analytics system.
Here, we compare Google Analytics vs Adobe Analytics, how to migrate from Google Analytics to Adobe Analytics, and the mid-size and enterprise-level use cases that Adobe Analytics solves.
Google Analytics vs Adobe Analytics: An overview
Google Analytics 4 (GA4) is one of the most popular analytics tools leveraged by enterprises to gain insights about their conversions, traffic, and visitors. Its latest version, Google Analytics 4 (replacing its predecessor Universal Analytics, know more here) takes a more detailed approach to allow for:
- Event-based tracking: Focussing more on user interactions and events tracking rather than page-views, event-based analytics allows to gain insights into clicks, views, downloads, form submissions, and more along with page views. This results in more granular understanding of user behavior and engagement.
- Cross-platform tracking: GA4 allows data gathering across all your websites and/or apps in a single property. This results in a more holistic view of how users interact across different platforms, regardless of their device.
- Enhanced privacy: GA4 complies with GDPR and CCPA regulations to focus more on user privacy and data protection. This covers built-in features for user consent, data retention/deletion, and aggregated/anonymized data reporting.
- Lifecycle reporting: GA4 covers all four key stages of acquisition, engagement, monetization, and retention. This allows enterprises to track and analyze users across their entire journey, resulting in optimized marketing campaigns and overall improvement in user experience.
- ML and AI integration: GA4 offers a more predictive and actionable approach to data analytics. ML and AI features help identify trends, predict user behavior, automate audience segmentation, and more.
- Enhanced analytics tools: GA4 offers new analytics tools and reports like the Exploration tool for ad-hoc analysis, the Funnel Analysis tool for visualizing conversion funnels, and the Path Analysis tool for understanding user navigation paths on your site or app.
And more.
Adobe Analytics, an offering from Adobe, is a more advanced analytics tool that empowers marketers to track visitors across devices while also allowing for detailed segmentation and real-time analytics. Its powerful capabilities of Analysis Workspaces, Report Builder, Ad Hoc Analysis, reports & analytics have made it an enterprise choice across industrial verticals. Some of its state-of-the-art features include:
- Data collection and tracking: Adobe Analytics allows you to aggregate data across touchpoints – website, apps, IoT devices, and offline sources; use tags and SDKs to track user interactions and events like pageviews, clicks, conversions, views, and custom actions.
- Real-time reporting: With Adobe Analytics, you get to monitor user activity in real-time, resulting in optimized marketing campaigns, identifying issues and addressing them.
- Advanced segmentation: You can segment your audiences based on several criteria – demographics, behaviors, location, etc. This results in more targeted campaigns based on the analyzed behavior patterns.
- Customizable dashboards and reports: Visualize and analyze user data as you want with customizable dashboards and reports. Adobe Analytics also makes it easy to create custom reports and dashboards to help visualize and track KPIs as required to monitor campaign effectiveness.
- Path analysis and conversion funnels: These tools result in a complete view of the user journey from acquisition to conversion. Path analysis helps identify common user paths and navigation patterns. Conversion funnels help identify drop-off in the conversion process, empowering enterprises to solve the friction for enhanced conversions.
- Predictive analytics: Adobe Analytics leverages AI and ML algorithms to forecast future trends and behaviors based on historical data. This helps enterprises pinpoint customer needs, identify opportunities for growth, and optimize campaigns accordingly.
- Integration with other Adobe solutions: Adobe Analytics seamlessly integrates with other AEC solutions like Adobe Experience Manager, Adobe Target, Adobe Campaign, Adobe Audience Manager. For enterprises leveraging any of the Adobe solutions, it results in cohesive digital experiences across channels.
- Data privacy and security: Complying with GDPR and CCPA, Adobe Analytics promises data privacy and security.
Google Analytics vs Adobe Analytics: Key differences
Here’s a breakdown of Google Analytics and Adobe Analytics based on some key attributes
| Attributes | Adobe Analytics | Google Analytics 4 |
| Cost | Paid subscription | Free subscription |
| Data capture | Up to 1000 custom dimensions and events | Up to 25 custom dimension and events |
| Data retention | Up to 25 months and extendable | 2 months extendable to 14 months |
| Cross-platform tracking | Available with integrations | Native cross-platform tracking available |
| Predictive analytics | Yes with advanced machine learning predictions and forecasts | Basic predictive capabilities available |
| Reporting & data visualization | Comprehensive and highly customizable reports and dashboards features available | Moderate customizable reports and dashboards |
| Ease of use | Technical expertise required | Basic, can be easily setup , hence a more user-friendly interface |
| eCommerce tracking | Advanced features available | Basic tracking can be done not advanced |
| Integrations | Seamlessly integrate with Adobe Experience Cloud suite | Can be easily integrated with other Google products like Adwords, BigQuery |
| Cohort analysis | Advanced audience segmentation and analysis available | Basic segmentation available |
| Data Studio integration | Seamlessly integrated | Additional set up required |
| Anomaly detection | AI-powered alerts available | Basic detection available |
| Customer journey analysis | Adobe Journey Optimizer available for detailed analysis along with path analysis and conversion funnels | Path analysis and conversion funnels |
| Data privacy | Compliance with privacy regulations | More emphasis on cookie-based tracking |
| API access | Yes | Yes |
Migrating from Google Analytics to Adobe Analytics: Key considerations
Migrating from Google Analytics to Adobe Analytics is not as easy as it seems, considering that both platforms use varied terminologies and marketers are then challenged to find an equivalent functionality between the two. A quick terminology comparison between the two is below:
| Activity description | Adobe Analytics | Google Analytics |
| An event metric that represents a page (or screen on an app) has been viewed | Page View | Views |
| A metric that represents a group of interactions on your website or app that take place in the same time frame | Visit | Session |
| A metric that defines an identified device (based on multiple criteria including cookies and other behavior patterns to stitch user information) | Unique visitor | User |
The following are some points that must be considered when migrating from Google Analytics to Adobe Analytics.
- Reviewing tracking codes, analytics variables, tag management, and opportunities for cleanup, including marketing pixels, and documenting as necessary.
- Planning for accessing historical data and migrating dashboards, segments, and reporting configurations, while also considering data governance measures for analytics maturity and privacy compliance (e.g., GDPR).
- Understanding marketing attribution models and devising a clean migration strategy for campaigns.
- Reassessing organizational initiatives, KPIs (Key Performance Indicators), and reporting needs to align with the capabilities of Adobe Analytics.
- Considering additional marketing and optimization tools that integrate effectively with Adobe Analytics during the migration process.
- Implementing best practices for data layer setup and tagging optimization to maximize the effectiveness of analytics tracking.
- Architecting solutions and preparing a comprehensive migration plan with contingency plans (backout plans) as necessary.
- Developing quality assurance test plans and validation procedures to ensure the accuracy and reliability of data post-migration.
- Providing training sessions for analysts, report builders, and end-users of the analytics dashboards to familiarize them with the new platform.
- Periodically reassessing the analytics implementation for potential improvements and adjustments based on evolving objectives and changes in the digital landscape.
- Involving stakeholders from different departments and ensuring clear communication throughout the migration process to mitigate any potential challenges or disruptions.
Google Analytics to Adobe Analytics migration strategy
Refer to the following migration strategy when transitioning from Google Analytics to Adobe Analytics.
#1: Document requirements and catalog current implementation
Review the current documentations for tag implementation and conduct a thorough audit of the website. Document all tagging functionalities, KPIs (Key Performance Indicators), reporting structures, tools, and external integrations. Ensure comprehensive documentation to facilitate a smooth transition.
#2: Historical data and data governance measures
Evaluate the usage of historical data and develop a plan for migrating dashboards, segments, and reporting configurations. Consider data governance measures to ensure compliance with analytics maturity standards, as well as privacy regulations such as GDPR. Implement strategies for securely handling sensitive data during the migration process.
#3: Re-assess organization’s initiatives, KPIs, and reporting needs
Beyond reviewing current functionalities, take the opportunity to reassess the organization’s initiatives, KPIs, and reporting requirements. Align these with the capabilities of Adobe Analytics to optimize performance and insights generation.
#4: Marketing campaign tracking & attribution models
Gain a deep understanding of marketing attribution models and devise a clean migration strategy for campaigns. Analyze the similarities and differences between attribution models in Google Analytics and Adobe Analytics, ensuring a seamless transition without compromising on data accuracy or campaign performance tracking.
#5: Integrated tools
Recognize that each analytics platform integrates with specific tool sets more effectively. Evaluate additional marketing and optimization tools that can enhance the capabilities of Adobe Analytics and consider migrating them during the switch. Ensure compatibility and seamless integration to maintain continuity in data analysis and reporting workflows.
#6: Technical implementation and tag migration
Develop a detailed technical implementation plan for migrating tags, ensuring accuracy and consistency throughout the process. Employ best practices for tag management and optimization to maximize the effectiveness of analytics tracking in Adobe Analytics. Conduct thorough testing and validation to verify the functionality of migrated tags and ensure data integrity post-migration.
#7: User training and adoption
Provide comprehensive training sessions for analysts, report builders, and other stakeholders involved in using Adobe Analytics. Familiarize them with the new platform’s features, functionalities, and reporting capabilities to facilitate smooth adoption and maximize utilization of its potential.
#8: Continuous monitoring and optimization
Establish protocols for continuous monitoring and optimization of Adobe Analytics implementation post-migration. Regularly review analytics performance, identify areas for improvement, and implement necessary adjustments to align with evolving business objectives and changing market dynamics. Stay updated on platform updates, best practices, and emerging trends to leverage Adobe Analytics effectively for informed decision-making and strategic planning.
10 steps to seamless Google Analytics to Adobe Analytics migration
Refer to the following steps to ensure a seamless data migration from Google Analytics to Adobe Analytics.
#1: Adobe Analytics design documentation
- Create Solution Design Reference (SDR) document outlining analytics architecture.
- Develop a KPI Handbook detailing key performance indicators for measurement.
- Map Google Analytics variables to Adobe Analytics for seamless transition.
- Define marketing channel models and related documentation for tracking.
#2: Tagging guide
- Develop a comprehensive tagging guide for website development teams.
- Include instructions for implementing tag management code snippets.
- Outline data layer and events architecture for efficient data tracking.
#3: Reporting and insights design
- Define KPIs and reporting hierarchy for analytics insights.
- Set up reporting configurations for users and admin access.
- Plan for historical data usage to maintain continuity in reporting.
#4: Marketing tags, product management, and design
- Design and document marketing tags and integrations for tracking.
- Outline usage of other products and their integration with Adobe Analytics.
#5: Backout plan
- Architect measures for backing out in case of unexpected incidents.
- Maintain active Google Analytics free version as a backup system.
#6: Develop
- Guide website development team in implementing functionalities as per tagging guide.
- Implement analytics tags using tag management systems and conduct unit testing.
- Prepare analytics quality assurance test plans for thorough testing.
#7: Quality assurance
- Conduct functional testing of tags to ensure accuracy.
- Set up data dashboards for QA and go-live readiness.
- Perform functional testing of websites to validate analytics implementation.
#8: Go live
- Publish tags and website changes to production environment.
- Conduct post-production tags and functionality testing to ensure smooth transition.
#9: Training and knowledge transfer
- Provide training to analysts, report builders, and dashboard end-users.
- Assist in building dashboards and analyzing data to derive insights.
#10: Usage and sustainability
- Periodically reassess analytics implementation for improvements and alignment with objectives.
- Adapt analytics strategies based on changes in objectives or business landscape.
Migrate from Google Analytics to Adobe Analytics with Ranosys
We understand how challenging it can be to migrate data from one platform to the another that too when their terminologies don’t match. As an award-winning Adobe Solution Partner with strategic expertise in Adobe Analytics, our certified experts simplify this entire process. We ensure seamless and worry-free data migration with zero data loss while gathering all the insights about your users in real-time. We even prepare custom dashboards and reports, customize the interface, and train your teams on Adobe Analytics.
Contact us if you’re looking to seamlessly migrate from GA to Adobe Analytics.
