A New Era for Marketers: Exploring Different Digital Analytics Tools

If you’re a digital analyst or marketer in 2023, you might still try to wrap your head around all the changes happening in the digital analytics world. The main event is definitely the sunset of Universal Analytics (UA). Google is moving to GA4, which has gathered a fair share of criticisms. 

Many teams and specialists used to UA’s practical features are finding the transition to GA4 challenging. If you’re familiar with digital analytics tools, especially GA4, you’re likely aware of the platform’s limitations. Bugs, cardinality, thresholding issues, a disconnect between the GA4 interface and BigQuery exports, questionable privacy features, an unintuitive UI, data sampling, and API quota limits are just a few of the pain points – the list goes on.

Alternative Digital Analytics Tools: A New Dawn

GA4’s limitations affect how organizations operate, so switching to GA4 might create tension and frustration in the teams, which can take a toll on their efficiency, motivation, and business value. The reality is you don’t have to switch to GA4 – this is the right time to explore what other platforms have to offer.

But the way forward is not just deciding whether your organization should move to GA4 and how to implement this or another platform so it works for you. There is much more you need to factor in. 

Privacy Laws and Data Collection

New privacy laws are popping up from different directions while existing ones are getting modified and strengthened. The US federal law is being developed, the EU introduced DMA and DSA, and we’ve seen clarifications regarding HIPAA and using tracking technologies. 

At the same time, collecting valuable data is more complicated than ever. Deprecation of third-party cookies, browser restrictions, low consent rates, and the increasing popularity of ad blockers are the “new normal” in the world of marketing technology.  

With the shift from third-party to first-party data, organizations need to start relying on data from their own sources. The days when websites didn’t have to think about proper consent and could use data without paying attention to the source are long gone. 

How do you approach all these changes when there is increasing pressure on marketing and data teams to be data-driven?

Beyond the Tool Switch

This is not a simple “tool switch.” Take this moment to re-evaluate the whole data stack and think about analytics long-term, way beyond UA’s sunset. Change must be more profound and focus on a shift in the mindset – you’re now establishing foundations for your organization’s digital analytics and marketing moving forward. 

Piwik PRO was always about the balance – getting information for data-driven decisions without sacrificing privacy. This approach, outlandish when we started because of the uncontrolled and unreflective times, is now at the heart of many digital analytics discussions.

We helped many organizations overhaul their digital analytics and marketing activities, getting them better prepared for what is coming. And now we also have advice for you.

Navigating the changes in digital analytics

When adapting to the ongoing changes in your digital analytics and adopting a data-driven approach, you need to think about a few aspects. 

They include data strategy, privacy, organizational processes, and technology. 

Data strategy

To make your organization data-driven, start by changing your mindset. Here is how:

  • Collect only the data you need, not all the data you can get access to. Less data is better.
  • Understand that data collection is just the beginning. Put your data into action to make it valuable for your company. 
  • Build trust between your brand and clients. Be open and transparent about what data you collect and how. This will also make customers more eager to share their information. 

Reworking your strategy should start with gathering feedback and needs from different organizational stakeholders. Then, map their needs and problems they want to solve using analytics software. 

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.

Once you know the different teams’ data needs, define your KPIs. Only then are you ready to define specific digital analytics needs and tool requirements.

For one, ensure that critical first-party data points are safeguarded and not locked by vendors. You should aim for complete control over your data and how it’s used. 

Remain open to new cost-efficient channels. For example, instead of relying only on Google Ads, explore Microsoft Ads, which may be a cheaper option with several additional benefits, such as less competition.


Follow the changes in the privacy regime in your markets. Complying with the strictest privacy laws should be your global data collection baseline. A good place to start is the CNIL’s consent exemption program for audience measurement. They produced a list of analytics tools that can run without consent. In the EU, follow DPA guidelines for the countries where your company processes data.

Since privacy laws are constantly changing, teams within your organization should cooperate with the legal department, which can help translate complex definitions into simple language. Make sure that everyone understands why there are legal limitations and what steps need to be taken to comply.

If you haven’t done so already, pay attention to how you collect and process user data – map data sources to minimize data collection and understand the purpose of processing each data type. Gather the data needed to fulfill your business goals and process it only until those goals are reached. 

You may be required to collect valid user consent before processing their personal data. Without consent, make sure you only gather properly anonymized data or, better yet, none at all. There is much at stake here, from damaging non-compliance fines to losing customer trust. Don’t try to compromise data privacy to get your hands on more data.

Consider where and how your data is stored – for example, factor in data residency. If you are an EU-based organization, you will be better off considering European analytics platforms that offer EU-based hosting options to comply with GDPR and other local laws.

Organizational processes

Decisions based on data should lead to your business’ growth, whether they are made by marketers, HR, sales, tech teams, and others.

All departments at your organization need to understand the value of a data-driven approach to their work. The key to achieving it is effective cooperation between teams and making efficient use of their resources so they can focus on their dedicated tasks. 

To improve cooperation, make sure your technology stack supports each team’s responsibilities. Some platforms’ cost (especially the free-of-charge ones but not all) is in the number of hours you need to pour into them to achieve baseline productivity. If that’s the case with your company, you should explore your other options to discover more sustainable solutions.


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 market for analytics tools is broad and diverse. You can find a platform of any flavor – simple, complex, suitable for sensitive industries, product or marketing analytics, small- or medium-sized companies, or enterprises.

Explore the features of different tools – such as metrics and reports, customization options, available user authentication, data collection method, and others (like dashboards, integrations, or user management). Figure out your analytics setup in each tool and how much time and resources it would require to maintain it.

Think about integrating your analytics with other tools to do everything you need with your data. For example, adding a customer data platform will give you ways to connect data from many different sources and activate it in other places, such as CRMs or email software. You can personalize relationships with established and new customers in real time.

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 provide a copy like from GA4 to BigQuery or Piwik PRO to BigQuery, AWS, Azure, or other 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:

  • 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.

Broad solutions like data warehouses are necessary to execute a first-party data strategy. 

They allow you to:

  • Create funnels across the company – such as 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.

The bottom line

The changes we’ve gone over will set a new tone for digital analytics in the future. That’s why it’s so important that whatever your next steps are, you act with a long-term perspective. 

Remember that your mindset comes first, then you need to apply it further – to your company’s privacy approach, data strategy, organizational processes, and technology. These changes are challenging, but as you see, the rewards are plenty. Good luck!

About the author


Piotr Korzeniowski
CEO @ Piwik PRO

Piotr is the CEO @ Piwik PRO. An executive with a background in AdTech and MarTech, Piotr successfully ran a software development company until 2021. He has spent the last eight years at Piwik PRO, building one of the best enterprise analytics companies. Piotr is an econometrist and finance person by trade and a lecturer at Kozminsky University in postgraduate courses on internet marketing.

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