Whether due to inertia or fear of disruption, too many companies have chosen to stick with the same web tracking analytics platform, despite privacy concerns and functionality complaints. But not anymore. From European data privacy rulings that find companies using Google Analytics in breach of the General Data Protection Regulation (GDPR) to Google’s decision to end Universal Analytics (UA) in 2023, the excuses are exhausted. There is no choice.
The new version of Google Analytics (GA4) is not backward compatible with UA. Therefore, every company starting out will need to rethink its data model, modify the technical implementation, build historical data from scratch, and train teams to use the new tools. All of the challenges associated with any analytics migration are now inevitable, leading many companies to ask: is it time to switch analytics platforms?
There are a plethora of tools available that offer greater functionality, a demonstrable commitment to data privacy and ethics, and offer a much more sustainable and privacy-focused deployment. As Louis-Marie Guérif, group data protection officer at Piano, explains, today is the perfect opportunity to choose an analytics solution that truly reflects the needs and perspectives of the company.
Improved analysis capabilities
Across Europe, recent data privacy rulings have challenged businesses’ reliance on Google Analytics. By systematically transferring European user data to the United States, Google Analytics – and by association, all companies that use it – violates the GDPR. While the repercussions of these European decisions have yet to be felt in the UK, Google’s additional announcement that it will end UA in 2023 should raise serious concerns. This is not a minor upgrade or version change: GA4 is a completely different product, based on an entirely new data model. Every company has to make a change – either to the new version or to a different platform. The risk of losing data is real. Additionally, given the need to accumulate at least 13 months of data in the new analytics platform to ensure consistent year-over-year reporting, the pressure is high to make the migration decision. right now.
Regardless of which analytics platform an organization adopts, moving to the new event-based data model is a no-brainer. This is how analytics platforms now approach data capture, which means that every deployment will require migrating data streams into an event-driven schema. But not all schemas are created equal – and data quality is a key consideration. The problem with tools that rely on sampled data is that inevitably at some point the business will end up making decisions based on assumed knowledge – which, when incorrect, can quickly undermine the user confidence in the accuracy and relevance of data. Opting instead for an analytics platform that doesn’t sample data and seamlessly connects data across all reporting tools, APIs and interfaces is critical to ensuring a complete view of a customer with the brand and a holistic understanding to build trust across the business.
With consistent, reliable, real-time, and comprehensive data, every individual and every part of the business will use the same consistent information — from the CEO reviewing a KPI to the data scientist running Python with raw datasets. This is the basis that then allows a company to explore the additional functional innovation on offer. Features such as data enrichment, ad hoc data exploration, and the use of interfaces that improve data accessibility and understanding.
For publishers, for example, proactive alerting is an extremely valuable tool that supports a much more nuanced approach to content accessibility and value. Real-time website anomaly tracking will quickly highlight if a piece of content is trending, following an Instagram or TikTok influencer. Rather than discovering the spike in interest the next day when the opportunity was missed, with a real-time approach, the publisher can act immediately and maximize the value of new traffic. A tailored response – such as a subscription offer or opt-in option – is a much more flexible and dynamic approach to value exchange that will increasingly be essential to capturing readership and revenue.
This ability to take a much more nuanced approach is also helping to change attitudes towards data privacy. Ideological positions on customer data and privacy evolve and vary across the world. For organizations evolving their stance on compliance and data privacy, understanding not only how to ensure compliance, but also communicating the strategy to customers through a clearly demonstrated consent policy is critical.
It is also essential to recognize that the concept of data privacy will continue to evolve and legislation will change. Businesses need to distinguish between a vendor that prioritizes data privacy, acts on new legislation, makes proactive changes to ensure compliance, and educates customers, and a vendor that has little or no interest , for country-specific data regulations.
Companies can take steps as part of the initial data design process to facilitate compliance. For example, with a data model that can be flexibly managed, the company can add a flag to all data that is considered personal data. Additionally, a number of countries have tracking exemptions, where specific data can be tracked without obtaining prior consent. The ability to flexibly manage this data, as well as user-sensitive and user-independent information, supports a company’s position on data privacy both today and as we go. that it evolves in the future.
The issues raised by a migration of analytics platforms, whether driven by privacy or functional objectives, underscore the enormous changes that have taken place in recent years. Analytics implementations from three years ago are now obsolete. From the technological shift to an event-driven model described above to the radical change in data privacy laws, analytics deployments require a new approach, a new way of thinking.
But this is a major overhaul, and certainly not one to be repeated every few years. The data analytics process is increasingly business critical – and no data-driven business can afford the disruption associated with repeated changes to the analytics platform. Vendors who are committed to respecting confidentiality and helping companies maximize the value of analytics data within the limits of what is both possible and ethical will provide a much more sustainable long-term solution. Relying on a vendor that doesn’t even pay lip service to data privacy decisions dramatically increases business risk and could lead to another tedious migration within a few years.
Group Data Protection Officer, Piano
Piano’s Digital Experience Cloud enables organizations to understand and influence customer behavior. By unifying customer data, analyzing behavioral metrics, and creating personalized customer journeys, Piano helps brands launch campaigns and products faster, boost customer engagement, and drive personalization at scale from from a single platform. Based in Philadelphia with offices in the Americas, Europe and Asia-Pacific, Piano serves a global clientele including Air France, BBC, CBS, IBM, Kirin Holdings, Jaguar Land Rover, Nielsen, The Wall Street Journal and many more. others. For more information, visit piano.io.