Are you a startup founder or product manager looking to make data-driven decisions for your product development? Do you want to understand how your customers are using your product and where to focus your efforts?
Look no further than product analytics. Every business aspires to be customer-centric, and product analytics help you do just that in no time.
From Instagram to Netflix to Uber, the most successful businesses use product analytics to understand customer behavior, develop new products, and improve current products. In this blog post, we'll dive into the world of product analytics, explaining what it is, why it's important, and how it can benefit your business.
What is product analytics?
Product analytics is the process of collecting, analyzing, and interpreting data about your product and its usage. This information can help you figure out how customers use your product, find ways to make it better, and make decisions about product development that are well-informed.
For example, if you're a SaaS company, product analytics can help you track user engagement, identify which features are most popular, and understand how customers are using your software. With this information, you can make informed decisions about which features to prioritize and deprioritize and where to focus your development efforts. Essentially, product analytics allows you to gain valuable insights into your customers and optimize your product strategy accordingly.
What does data collection or tracking mean?
In product analytics, "tracking" refers to the process of gathering data about how customers interact with your product. This data can include things like how often a feature is used, how long a user engages with it, who the user is, and more.
You can use two different types of tracking with product analytics tools:
Event tracking is the process of keeping track of particular actions users take while using a product, such as button clicks, form submissions, or page views.
Tracking user demographics involves keeping tabs on details about users, such as their location, device, and browser.
As simple as the word "tracking" sounds, it's not as easy as you might think. To get good data to analyze and figure out, you have to do it the right way. If you set up tracking incorrectly, it will cost you money, the time of your engineers, and poor decisions.
In summary, tracking in product analytics refers to the collection of data about how customers interact with a product, and it is the first step in the process of product analytics to use that data for deeper analysis, visualization, and insights.
How is the tracking data different from my product database?
Before we move on to the analysis and interpretation of tracked data for product analytics, let's talk about how the collected or tracked data differs from your app's or site’s database data.
Tracking data and data in your app's database are different in terms of their purpose, structure, and usage.
Tracking data is typically unstructured and is collected in real-time as users interact with the app. Product analytics use this information to learn how users interact with the app, such as what features they use, how often they use them, and where they run into problems. This data is usually collected through tracking scripts or analytics tools, and it focuses on product usage data, customer behavior, and app performance.
On the other hand, data in your app's database is typically structured and is used to store information about the app's users, products, and other business-related information. This data is used to support the operational and transactional aspects of the app, such as user authentication, data storage, and data retrieval specific to your app's functionality. This data is usually stored in a relational database and focuses on user information, transactions, and app states.
What types of insights can product analytics offer?
By analyzing and interpreting tracking data, you can gain a wide range of insights into customer behavior, including:
User engagement: You can see how often users are interacting with your product, which features they are using most frequently, and how long they are spending in the app. This can help you decide which ones to focus on and which ones to put on the back burner.
Cohort Analysis: You can see how the engagement differs among different cohorts of users and tailor your product features to the specific needs of cohorts that matters the most. You can also go in-depth about understanding the behavior of a cohort of users by combining qualitative forms of product analytics such as user interviews, surveys, etc and optimize feature efforts for that cohort.
User behavior: You can see how users are interacting with your product, such as the number of sessions, time spent in the app, and features used.
Funnel analysis: You can see how users move through different stages of your product, such as sign-up or any key flow. This can help you identify where users are dropping off and areas where you can improve the user experience. You can even look at the funnels to understand where the users are spending their most time and optimize for a particular step of the funnel.
Retention and Churn: You can see how many users are coming back to your product each and every day (or week or months) and how many are leaving. This can help you identify if your product is retaining users, and if not, what are the reasons. You can also look at the patterns of usage of retained users and double down your product development efforts on these areas.
Benefits of product analytics for businesses
The insights gained from product analytics can benefit your business in a number of ways.
Product development: By understanding how customers are using your product, you can make informed decisions about which features to prioritize and which ones to deprioritize, and where to focus development efforts. This can help you create a better product that meets the needs of your customers and improves their experience.
User acquisition and retention: By understanding your users' demographics, behavior and engagement patterns, you can tailor your product features to target specific groups of users, and increase user acquisition and retention.
Optimizing revenue: By understanding which features are most popular and how users are interacting with your product, you can identify opportunities to increase revenue, such as upselling or cross-selling additional features or services.
Improve user experience: By understanding where users are facing problems and where they are dropping off, you can identify gaps and solve problems that are affecting the user experience, and improve overall user satisfaction.
Making data-driven decisions: Product analytics will help you escape the build trap. Around 86% of the product managers build features that nobody wants. By having a deep understanding of how users interact with your product, you can make data-driven decisions that are based on evidence and not assumptions.
The wrap
In conclusion, product analytics is a powerful tool that allows businesses to gain valuable insights into how customers interact with their products. Product analytics can be applied to a wide range of products, including mobile apps, software applications, and websites. It's an essential tool for any business that wants to stay competitive and make data-driven decisions that can help them reach their business goals. By understanding customer behavior, identifying pain points, and optimizing the product strategy, businesses can improve customer satisfaction and increase revenue. With the increasing competition, product analytics is becoming more important than ever.