2024 is another year in which the letters “A” and “I” are on the tips of everyone’s tongues. The emergence of AI is impacting digital analysts as well, but the ultimate course of this revolution is unclear. When discussing changes in the analytics landscape, it’s important to recall the impact of moves by Google, such as the sunset of GA and GA 360, and the retention of third-party data. However, the future might belong to other analytics platforms that often deliver better and more innovative functionalities than the Mountain View giant.
So, if you are wondering if you should stick with GA4, place your trust in AI, or maybe turn to another analytics platform, this article will provide information to help you navigate through changes happening today and those coming in the near future.
About the author: Vincent de Winter is Regional Manager (Benelux) at Piwik PRO, sponsor of the 2024 DDMA Digital Analytics Summit.
Don’t be afraid to embrace new tools
Google Analytics 4 is tailored for technical teams with considerable budgets, and shows minimal resemblance to its predecessor. This new product has caused quite a stir in the analytics community, leaving marketers with the tough task of trying to adapt. Google’s shift away from universal accessibility has prompted users to explore new tools that are more suitable for their use cases and expertise level.
To compete in an increasingly demanding market, marketers need solutions that allow them not only to collect data but to activate it and analyze trends in real time. Analytics platforms like Piwik PRO Analytics Suite offer similar functionalities to GA 3, such as reports, session-based analytics and an intuitive interface. But there is so much more out there! Go explore other options if you’re not satisfied with your current software.
Emerging issues to keep in mind
- Opportunities and risks of the AI wave
Data is the driving force behind analytics platforms and artificial intelligence algorithms. Analytics solutions can leverage AI capabilities to improve efficiency with automated data processing, more precise predictions of consumer behavior, and personalized content tailored for individual users.
However, growing concerns regarding security and privacy are arising from the use of extensive datasets containing confidential information. The risks of possible exploitation and breaches are significant. Generative AI adds another layer of complexity to things by creating synthetic data that, although beneficial, may carry its own privacy risks. In the face of these threats, prioritizing data privacy must be at the forefront of implementation of AI-based solutions.
- Are third-party cookies here to stay after all?
Most major browsers, except Chrome and Opera, have already restricted or blocked third-party cookies, as their use can potentially compromise users’ privacy. Third-party data is not unique, which means that your competitors can purchase the same datasets from brokers. Digital marketers and analysts cannot rely solely on such types of cookies to reach their desired audience. That’s why they must continue developing other data collection strategies to ensure comprehensive reach across platforms.
Win the future with a holistic approach
Adapting to these emerging changes in the digital marketing landscape requires a holistic approach that goes beyond merely switching tools. Here’s how you can prepare your organization for the new era of digital analytics:
- Data strategy
As the shift from third-party to first-party data accelerates, organizations must rethink their data collection strategies. Instead of collecting vast amounts of data with minimal oversight, focus only on the data needed to achieve your business goals. This will not only help you stay compliant with privacy laws but also build trust with your customers. Transparency about what data is collected and how it is used will encourage them to share more information, helping you gain valuable insights.
A solid data strategy should be built on feedback from various stakeholders across your organization. Understanding their needs and challenges will help you define key performance indicators (KPIs) and set clear goals for your analytics efforts. Focusing on first-party data ensures that critical data points remain under your control and free from vendor restrictions.
Overall, user data must help you gain actionable insights to address your business use cases. The data you collect should tell you:
- How to drive profits and sales.
- How to optimize operations.
- How to improve team performance.
In addition, remain open to new channels that might be more cost efficient, or help increase your reach. For example, explore Microsoft Ads, Quora Ads or Amazon instead of relying on Google Ads alone.
- Organizational processes
Ensuring that all departments within your organization understand the value of a data-driven approach is key to growth. Effective collaboration between marketing, HR, sales, and technology teams in implementing data strategies can benefit the entire company.
You should also choose technology stacks not only for their capabilities, but also for their ease of use. The cost of many platforms (especially the free-of-charge ones, but not all) depends on how many hours you need to pour into them to achieve baseline productivity. If your company doesn’t want to spend additional resources to learn a new platform, you should explore other options that might be more sustainable.
- Technology
Evaluating and matching your analytics needs with available tools is a lot of work, but it can pay off in the long run. You don’t need to choose the most popular tool.
The analytics market continues to expand, offering a variety of platforms, from simple to complex solutions suited for sensitive industries to those adaptable for small to medium-sized enterprises (SMEs). When evaluating tools, consider factors such as metrics, reports, customization options, and integration capabilities. Figure out how much time and resources your analytics setup would require in each case.
A well-integrated data stack allows you to connect data from various sources and activate it in other platforms, such as customer relationship management systems (CRMs) or email software. This allows for personalized customer interactions and more effective marketing strategies.
When a copy of your analytics data is needed in your data warehouse for other teams, choose a tool that enables export to data warehouses natively, like Snowplow, or provides a copy like from GA4 to BigQuery or Piwik PRO Analytics Suite to BigQuery, AWS, Azure, or another SFTP. When choosing elements of your data strategy, you should differentiate between using point and broad solutions to their extremes:
- Point solutions, including CRM, analytics, automation, and experimentation, are staying in the marketer’s arsenal.They can be used to:
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- Execute marketing tactics, such as quick personalization or experiments.
- Adjust advertising spend depending on current short-term trends (most popular search terms or most popular pages).
- Approach customers at the right time with the message they expect.
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- Broad solutions like data warehouses are necessary to execute a first-party data strategy. They allow you to:
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- Create funnels across the company – from being a lead to making a return.
- Execute a broader, long-term strategy – like betting on content that attracts customers with the highest lifetime value.
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- Privacy
Incorporating privacy into your data strategy is essential. Regulations like the EU’s Digital Markets Act (DMA) and Digital Services Act (DSA) are in effect, and we can observe how existing laws such as GDPR are being enforced. In the US, federal data privacy laws are in the making, and guidance on HIPAA and the use of tracking technologies is becoming richer.
If your company operates in the EU, follow the data protection authority (DPA) guidelines for each country where you process data. Also, when considering compliance, you might want to check CNIL’s consent exemption program, which shows analytics tools that can work without consent.
It’s crucial to work closely with your legal team as privacy rules continue evolving. They can assist in clarifying your legal responsibilities and ensuring that all teams grasp the legal boundaries and necessary steps for compliance.
Review how you collect and process data. Reduce the amount of data gathered, identify where the data comes from, and understand why each data category is being processed. Obtain only the data needed to achieve your business goals and ensure adequate anonymization if consent is not provided. Mishandling data can lead to fines and loss of trust.
Finally, for EU-based businesses, you should think about where your data is stored and hosted to ensure GDPR compliance. Using European analytics platforms with EU hosting can simplify compliance.
Long-term success in digital analytics
The digital analytics landscape is rapidly changing, and organizations that can adapt to it will thrive. Crafting a solid data strategy, improving organizational processes, and choosing privacy-compliant technology can position your company for long-term success. Solutions offering functionalities like data activation, real-time dashboards and consent management are compelling alternatives to GA4, allowing you to collect and analyze data in a compliant and transparent way.
As you navigate the challenges and opportunities of the years to come, remember that you’re doing more than just changing tools: you’re making a fundamental shift in your approach to digital analytics. By taking a long-term perspective and adapting now, you’ll be better prepared for whatever the future holds.