Product Analytics Essentials

We all know about the number of products available in the market, so to ensure that your product is providing the best possible experience to your customers is really important. Since there are many alternatives present, the customers aren’t bound to use your product. This is where product analytics comes in, as it enables you to comprehend scalability, what works well and what doesn’t on your website or the application. This allows you to improve the user experience, drive retention and engagement and at the end, keep the users satisfied and content.

Product analytics is mainly for product managers, developers and designers but can be used for much more than that. For example, a marketer can understand how people are reacting to a campaign or an analyst could apprehend how to go about next. Basically, if your role asks you to bring or build a digital product to the market, then product analytics is definitely going to be helpful.

When your product’s growth is getting bigger day-by-day, then it isn’t possible to talk or see the users interacting with it. Welcome product analytics! It helps to see at scale how your product is being used on average and notice the patterns and behaviours to further improve the user experience. If we take the top tech giants such as Google, Facebook, Amazon etc., they use all the data sent to them or received by them to just lift up the user experience as much as possible over time. Now to clear a doubt here, don’t confuse product analytics with marketing analytics. Marketing analytics is essentially about how to land new users or customers while product analytics is about how to improve the experience of existing users of the product

P.s. When I say the word ‘product’, I’m talking about digital products and not the ones that are available physically in the offline world.

Product analytics is about defining what the business goals are, identifying the steps to achieve them and then, enhancing the user experience. An example of this could be the auto-play feature on Spotify or Netflix, probably the concerned teams in these companies could tell that the users are binging on songs or movies/shows. So, they improved the experience by not asking the user to manually play the next one.

Product analytics works using a very simple code tracking every user activity. These activities are known as ‘Events’ and in these events, there are details about the users, like where do they belong to, which are called ‘Properties’. Tracking every event and property is similar to aggregating the pieces of puzzles resulting in the overall picture of how different people are using the product. But the main question is what to track and what not to since there are unlimited things which can be tracked yet not every one of them is going to yield insights or results.

The answer is there in your business goals. You can give a framework and structure for the things to be tracked so as to get valuable insights from the product analytics. A few examples of product-focused business goals are user activation, user retention, user referrals, user engagement and so on. While these are some business goals which are product-focused, other business goals can be around marketing, finance or engineering. All of them form the spectrum helping you drive the success of your business.

Now, we’re going to go over how to create a tracking plan or an implementation plan. It’s a document that assists you in mapping your business goals to specific events and properties you wish to track in order to get answers to the questions about these goals. There’s no need to be technical when writing a tracking plan. All you have to do is start with the business goals that are defined in the last step then, break them down into key questions which you want the answers to about your product and identify patterns of behaviour to answer the questions. Once they are identified, all’s left to do is map them to the patterns and voila, that’s your implementation plan. A great thing about the tracking plan is that it provides the structure to ensure that all the data being sent is high quality, highly valuable and understandable to the team running product analytics.

Once you start with the analytics part, it’s important to have a hypothesis beforehand. It’s an educated guess which can be proved or disproved by going through the data, so it gives the frame to look at the right things and run the correct reports resulting in a lot of insights.

To drive impact, I’m going to briefly discuss 3 reports commonly used in analytics of a product -

Segmentation Report:

A powerful tool to answer all the complex questions about behaviour of the users of the product like the types of the users. Another powerful type of segmentation report is comparing multiple events. It identifies the areas to invest the resources in for moving the needle of the business.

Retention:

As it can be guessed from the name, it’s used to understand how sticky the product is for the users. It focuses on the people completing events over time, which is done with a cohort analysis, users are grouped into different cohorts based on their completion of an event. The retention report is structured according to when the users first completed an event.

Funnels:

It’s to analyze a process in the product to comprehend where the users are dropping off from the key points of the conversion steps. It lets you dive into the behaviour patterns that you expect to see in your product.

(We’ve already talked about the processes while discussing the implementation plan or tracking plan.)

It is the funnel analysis that lets you know how effectively people are completing the flows.

I really hope you’ve a basic overview of product analytics and how essential as well as useful it is. After getting the insights from all the collected data, it’s time to take the required action. It could be anything from doing A/B testing to making changes to the product.