What other Digital Analytics tools are available?

There are many Digital Analytics Tools that are alternatives to Google Analytics 4 (GA4) on the market today. These existed before GA4, but have come to the forefront because of the consensus that standard GA4 can be limited for many basic use cases. In this article I’m going to explore these analytics options within the context of why these changes are occurring in the industry.

First of all, marketers have been spoilt with a very good free tool for a long time (in GA3) and it had a very large market share. Essentially, the market is now becoming increasingly monetised by other digital analytics tools for access to better features. Those businesses who don’t want to pay in some way for analytics data are stuck with the limitations of the GA4 interface.

Where is the industry heading towards?

• Warehouse Native and owned data
• AI and self-serve
• Privacy first analytics
• Event tracking schemas and user first reporting
• Analytics as a specialism in marketing

Warehouse Native & Owned data

If you don’t want your GA4 data disappearing after 14 months, you need to be storing it in a data warehouse. This means having GA4 send data to BigQuery, Google’s own data warehouse, where you pay small amounts for storage and querying.

The above system is the process of having a third-party tool collect data and post it to the data warehouse. But warehouse native analytics means the warehouse itself is the analytics interface, so there is no need to transfer data from one location to another.

Mostly, interacting with data warehouses directly is the task of data analysts who know structured Query Language (SQL) to query data and produce insights. However, some of the tools I’ll mention have attempted to have a basic level of functionality against a user interface overlayed on the warehouse. This will become a more common and sophisticated practice for analytics tools.

In general, Digital Analytics tools will be seen as a contributor to a data ecosystem, and enrichment factor to your customer database. This may form just one part of a Composable Customer Data Platform (CDP) This is what Apex Digital specialises in providing; services to ensure clients thrive in the future. I see it as an essential step that will make warehouse native very relevant.

AI and self-serve Digital Analytics

This buzzword in analytics ultimately aims to simplify the process of analytics by being able to ask questions of the data directly. Say we have a data warehouse, with some capability on its front end, but not much. There might be in future, an AI that could receive natural language questions from the user, then go and query the data and return some results.

In a perfect world, this would remove the need for any user interface, replacing it with a simple search box. Naturally this may be appealing, but there could be huge limitations to this, including lack of transparency, lack of trust, lack of contextual guidance, poor prompt quality and it ultimately risks users simply not understanding their own data. Moreover, non-technical marketers or senior leaders within businesses may still want data presented to them by analysts who know the contexts of their individual businesses.

Despite these drawbacks, the bandwagon of AI will continue to generate pace, and the Digital Analytics tools will jump onto it in order to appear relevant, so don’t be surprised to see more of these AI interfaces in future.

Privacy First Analytics

Privacy from two fronts:

GDPR and further regulation

This is in the playbook of many GA4 alternatives. The fact that Google’s servers are in the USA technically contradicts GDPR, and there are a few headlines that have appeared suggesting that it is likely that GA4 will be banned in the EU, and already is in some countries.

However, because so many websites have GA4 installed, the reality of regulating this is a challenge, so for now the industry is just carrying on as normal until it is pushed in another direction. This is the biggest risk and weakness of GA4.

Cookies and 1^st party data

In response to cookie lifetime limitation, the trend will be to move web analytics to a self-hosted platform with enriched first party data to ensure the visibility of customers does not diminish as cookies worsen. This to an extent has already happened, and most companies are just dealing with poorer data quality (wrongly). See my article on sessions and cookies to read more.

Event tracking schemas and user-first reporting

This is what GA moved towards when it changed to GA4. Previously it tracked sessions, pageviews and events, but now al of these are derived from events that get sent to it. For me it makes sense, it is a far better measurement schema because ultimately it is simpler and allows for higher quality and better enriched data to be collected in each event, but it is a big change.

Even if cookies lasted forever on devices, the idea of session based analytics…is such a limiting way of conducting web analytics

This has largely already happened, and it is due to the fact notwithstanding the cookie quality issue, that user behaviour is just different to what it was 10 or 15 years ago, with multiple devices and multi session purchase journeys. Even if cookies lasted forever on devices, the idea of session based analytics just focusses in so much on the small picture, it is just such a limiting way of conducting web analytics.

This is why the change to event tracking schemas is merited, and any analytics tools trying to work in legacy ways are simply burying their heads in the sand.

Digital Analytics as a specialism in marketing

With the added complexities that are emerging in marketing and product analytics, more often now it falls to a specialist role within a marketing team to be responsible for tagging, analytics and insight. More often, people in these roles or generalist marketers, are putting up with the old way of thinking about web analytics, which is yielding poorer results with tools like GA4 in a standard implementation.

More often now, data roles within marketing teams need to be focussed on data analytics as a starting point, understanding the complexities of warehouses and clouds, but also understand the requirements of tagging and marketing analytics. Essentially, the skill is to marry up the marketing requirement and address the challenges, but also have the skills of a data scientist to some degree.

I discuss this in my article benefits of hiring a contractor or agency instead of full-time roles in Digital Analytics.

Conclusion:

The industry has changed a lot due to one single change by one analytics provider in 2023. I think this has been a good thing, because it has shaken up processes and allowed marketing and data professionals to think outside the box, and realise that there is (and always was) other ways to achieve goals, potentially even without GA4.

GA4 has a very important role to play within the Digital Analytics landscape over the next decade, but it will need to adapt to challenges from other Digital Analytics tools and adopt the new capabilities to maintain it’s market position in the analytics space.

In part 2 of this article, I go through the specific tools that are challenging Google in the analytics space, and outline pros, cons and use cases for all the prominent challengers, including:

Product Analytics

• PwikPro
• GA4
• Matomo
• Posthog
• Snowplow
• Amplitude

Specialist Marketing Analytics & Attribution

• Ruler Analytics

Read part 2 >> (Coming soon)

---

Want to chat about your analytics stack?

Contact me today or book a call

Connect with me on LinkedIn

---

Read more posts