Building a product requires organizations to make some critical decisions about the product’s features, updates, and UI. A few years ago, all these decisions were taken manually either by interacting with the customers and taking their feedback or considering the most important requirements. With the advent of data analysis technologies, the data collected from product experience is now analyzed and data-driven insights are derived from the results of analysis and observing trends. Extracting complex data from different data sources can be a tedious  task and this is where No code ETL tool Hevo Data comes in to the play!  

One such analysis that focuses on the product features and experiences is Product Analysis. This analysis will help you make decisions to build the best product completely based on real-time user and product data. A product is a centerpiece of revenue. The thoughts put into building and maintaining the product will determine your organization’s market value and importance. A great product speaks for itself and always attracts more customers So, in this article, we will discuss in-depth Product Analysis, its concepts, and best practices an organization must follow to get the best results.

Understanding Product Analytics

product analytics

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Product Analysis in general deals with providing you the required information that answers any questions you may have relating to your product. Some very general questions that are answered using Product Analysis are:

  1. Which features are most liked by the customers?
  2. Which feature is least used by a customer? Is this feature the least used because of its lack of robustness or that this feature is generally less required by the customers?
  3. Are your customers happy with the functionalities of the product?
  4. In the next update, what features need to be worked on, what features must be kept the same, and what features are of no value and can be removed?
  5. What was the reason that an existing customer stopped using your product? 

All the answers to the above questions are essential in making accurate decisions. The company’s future revenue and profits extremely rely on these decisions. So, it is important to make the best product decisions. These decisions help in overcoming the underlying problems, creating a better experience for your user, and keeping up with the market competition.   

There are a lot of product analytics platforms like Amplitude, Pendo, Heap, etc. that you can use to perform Product Analytics. These platforms help in tracking user actions, deploying Funnel analysis, creating interactive Dashboards, and a lot of other things. 

Understanding the Need for Product Analytics

To understand the importance of Product Analysis you must first understand its need. Product Analysis is needed for:

  1. Building a new product on basis of a previous version of a product.
  2. Analyzing the best features and strong points.
  3. Finding the lacking functionalities and errors.
  4. Creating the best product experiences.
  5. Understanding the customers’ needs.
  6. Identify the functionalities that are hard to use.
  7. Retaining existing customers.
  8. Converting new leads into customers.

Concepts of Product Analytics

SInce Product Analysis is all about creating the best product experience for the customer, it analyzes all the user’s actions performed or not performed. Let’s talk about a few basic concepts of Product Analytics:

1. Journey Analysis

Journey Analysis deals with the flow of interactivity in the product by users. It helps you identify how the user navigated your product to use a particular feature. Sometimes it is the same for some users or it is different. This way you will know what particular flow is most convenient to your customers.

2. Cohort Analysis

Cohort Analysis answers the question about what feature/features have maximum impact on the retention of your customers. This analysis gives you an idea about your best assets that contribute to long-term market value.

3. Funnel Analysis

Funnel Analysis gives you a quantitative measure of the number of customers that engage in a particular workflow. For example, assume you have a sign-in page and for the customer to sign-up for your product, he/she needs to enter a series of information to complete the sign-up process. Funnel analysis will help you determine where your leads have fallen off during the whole process. So, now you will understand that you have to shorten the process if the users are dropping off midway, or probably you are asking for information that they do not want to share.

4. Feature Performance

With Product Analytics you can observe the feature performance of all features and understand your product’s best and worst features. This way you can make changes to the features that are less preferred by your customers.

Best Practices of Product Analytics

The following are some of the best practices to be observed while performing Product Analytics:

1. Gathering the Right Data For Analysis

This is true not just for Product Analysis but also for any data analysis in general. To get accurate results from your analysis it is important that the analysis is performed on the right data. Make sure that the data that you are analyzing will give answers to your questions while making decisions.

2. Maintaining  Data Integrity 

Product Analytics is an ever-continuing process and will need the proper Data Integrity. Make sure that the product data is accurate, near real-time, and in the right formats. 

3. Identifying the Right Product Analytics Solution

There are many tools that deliver Product Analysis. Choose the right tool that fits your organization’s needs or a tool that answers all your questions.

4. Making Data-Driven Decisions

Product Analysis is just a means to decision making. Once you have performed analysis, it is important to observe trends and derive insights. It is more important to act upon these insights and make business decisions that have a positive impact on your product experience.


Product Analysis is a smart means to analyze and make the right product decisions to keep up with the cut-throat market competition. In this article, you learned about Product Analysis in depth. 

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