Product Analytics – A first glimpse of a new area of analytics
on 22.03.2022 by Daria L., Christian Spannbauer, David Berger
We at FELD M have been active in the field of digital analytics for many years now, consulting a multitude of clients from various industries. Over this time, we witnessed a dynamic development. It started with rudimentary native analytics implementations with only very limited reporting possibilities and data access only restricted to few persons within an organization. Meanwhile, we have dynamic, complex, tag management-based analytics implementations with advanced reporting functionalities and possibilities for data access for everyone within an organization.
Along the way, we built up expertise for various tools within the Digital Analytics space. We know the in-and-outs of the two predominant Digital Analytics tools, Adobe Analytics and Google Analytics. We successfully implemented analytics solutions with various Tag Management Systems and helped clients setting up holistic architectures including other tool categories, such as testing tools, DMPs, and lately, also CDPs.
And even though the MarTech area seems rather crowded already, we have been seeing a new tool category and analytics approach gaining more and more attention lately: Product Analytics.
Seeing this development, we have been asking ourselves: Is Product Analytics something we should take a closer look at? – Yes, it is! And here is why:
- Although becoming evermore sophisticated, Digital Analytics tools are often still struggling to provide easy, fast and actionable insights for product teams
- Mobile-first strategies are getting more and more relevant for companies, as users are increasingly interacting with brands via smartphones. This is especially true for mobile apps. However, Analytics for mobile apps is less centered around questions like marketing channel effectiveness or attribution, but more about product usage, retention and user experience.
- Adam Greco, longtime Web Analytics Evangelist for Adobe Analytics and a luminary in the field of Digital Analytics, joined the Product Analytics tool Amplitude at the beginning of 2021, lending additional weight to this development.
- Getting started with Amplitude ourselves, we think that Product Analytics lives up to its promise. Clients who already use Amplitude are satisfied with its usage and the results it delivers.
This is why we worked hard to become one of the first Amplitude partners in the DACH region and started to build up our expertise.
To get started, it might make sense to define what “Product Analytics” is. Is it just another term from the Digital Analytics universe or is it a completely different approach to analyse one’s data? What is hiding behind this term? Assuming that it is a different approach, do I necessarily need it as an enterprise? And if so, should I combine a Product Analytics tool with other Digital Analytics tools or should I be loyal to my one and only Digital Analytics tool and perform Product Analytics with what I already have in place? If those questions came to your mind, congrats, you are not alone!
Let’s try to demystify Product Analytics and its distinctive features together in this blog post.
Puzzle number 1: What is Product Analytics?
According to one of the leading Product Analytics tools Amplitude, Product Analytics can be identified as “the process used to understand how customers engage with digital products. It is a framework for putting customers at the core of a business by analysing behavioural data, identifying opportunities for conversion, and creating impactful digital experiences that bring about high customer lifetime value.” Thus far, this does not sound too different from things that have also been said about other areas of Digital Analytics. So, what makes Product Analytics unique?
One of the most important differentiating factors of Product Analytics is the fact that rather your product itself – web or mobile apps, websites or smart hardware – is the focus of your analyses. Not the ways of reaching your website or app and the acquisition of users and customers. With the help of Product Analytics, it is possible to evaluate the feature performance, calculate error rates, adjust it based on customers’ needs and improve the whole user experience within your product.
Hence, Product Analytics can be seen as a part of overall Digital Analytics, but with a clear focus on digital products and services aiming to understand how users interact with product, which incentives make them perform better, who are the most valuable customer, what are the pain-points in the user experience and how your product can be developed and improved.
Puzzle number 2: How do Product Analytics and Digital Analytics differ?
While Product Analytics is only one part of Digital Analytics, most of the existing Digital Analytics tools aim at Marketing Analytics by measuring attribution, optimising marketing channels and delivering insights for distribution of advertising and media budget. In these cases, Digital Analytics tools will be mostly used by Marketing teams and Channel or Campaign managers. The general approach of these tools – especially since relying on cookie-based user IDs has become more difficult during the last two years – is to use session-based data. This inevitably leads to the challenge of stitching sessions from multiple devices (or even interactions between two different sessions) together. This does not mean, however, that companies are not trying to use existing Digital Analytics tools to also perform Product Analytics. But in comparison to a Product Analytics tool, this is just not as efficient and effective and will not lead to the same results.
Meanwhile Product Analytics gives an opportunity to evaluate the product performance and provides a data base for product development and optimization. These types of analyses are of interest to a range of people, such as Product Owners, Product Development Teams, UX/UI Designers and Researchers, Customer Success Leaders and Sales Leaders. Several Product Analytics tools are present on the market now. Among them Amplitude, Heap, Mixpanel and others. Moreover, big analytics vendors such as Adobe Analytics and Google Analytics are moving towards features available in other Product Analytics tools.
Looking at Marketing Analytics and Product Analytics and the purpose they fulfill, it seems that both approaches are important for companies to have them in place. Which leads us to:
Puzzle number 3: Do companies have to decide for either a Digital Analytics or a dedicated Product Analytics tool, or can both systems run in parallel?
This question is harder to answer, as there are different opinions by experts on this one. On the one hand, few companies are willing to pay twice and live with a two-pronged approach. Some analytics experts like Adam Greco claim that the approach to have both tools is not sustainable anymore. Some tools can cover the needs of both teams. However, when using already existing tools for Product Analytics, a company should be willing to face the shortcomings, such as pre-processed data or less functionalities as in the dedicated tools.
In reality, a lot of companies decide in favour of a parallel solution. This solution lets you build the most useful data base for both marketing and product team within the company. This approach can look like this: using Digital Analytics tools such as Google Analytics or Adobe Analytics to evaluate everything before the registration within the product, including referral parameters, the registration funnel, and landing page performance. Product Analytics tools can then be used to analyse the performance after registration to evaluate user behaviour, core experience, retention and perform more in-depth product and event analytics.
This leads to the conclusion that the key question is rather not which tool is better and what approach should be used, but – as most of the time – to first gain clarity about what a company’s individual goal is. What lies at the core of the business model? How does the overall customer journey look like? Where is the most value created? Based on that, we can evaluate which data and analyses are most relevant for different user groups and provide them with the right tool(s) and approach to reach these goals.
The aim of this blog post was to introduce readers to Product Analytics in general and provide a first idea on the main differences between Digital Analytics and Product Analytics. For readers who are currently thinking about taking first steps towards Product Analytics, or have already done so, we want to provide more detailed information and insights in future blog posts.
So, stay tuned if you want to dig deeper into things like
- Should you integrate Product Analytics into your existing tool landscape? And if so, how?
- What do companies need to consider when setting up a Product Analytics tool such as Amplitude?
- Which use cases can be realized with Product Analytics, and is eCommerce one of them?
- A more detailed comparison of tools: Amplitude vs. Adobe Analytics vs. Google Analytics
You don’t want to wait any longer and are curious to talk to us regarding about possibilities and potentials of product analytics for your company? Feel free to contact us via email to firstname.lastname@example.org. We’re looking forward to an exciting exchange with you!