Product Analytics Software

Software Applications for Product Analytics

If you are a product manager or work at a product-based company, then you already know that using guesswork to design and market your products and services will not build better products or drive customer success. You need to know how users are using the product, whether the product is working, what the most important features are, what users like/dislike about the product, and where the customer churn is happening. Answering all these questions will help diagnose issues, develop improved digital experiences for the customer, and understand customer engagement.

Product analytics software helps you find answers to all these questions and understand user behavior and how a customer actually feels about the product. These tools track the customer journey by collecting data on how they interact with the product. Businesses can utilize the insights provided by such tools to understand critical issues such as poor conversion rate and product issues. This can help businesses develop actionable insights and improve customer satisfaction.

Before you dive into every data analytics tool in the market, you need to choose the right tool that will help you get the best results. This guide will help you understand the different factors you must consider when shortlisting a product analytics tool.

Here’s what we'll cover:

• What is product analytics software?
• Common features of product analytics software
• What type of buyer are you?
• Benefits of product analytics software
• Market trends to understand

What is product analytics software?

Product analytics software is a set of tools that allow product managers and product teams to collect user-level data on how customers interact with their products via desktop websites, mobile websites, or applications. These software tools provide insights on user engagement, what features customers use, problems they face, and so on.

Product analytics help businesses understand user behavior by tracking their actions or engagements on the application site. Understanding user behavior will enable product managers to improve the user experience (UX) of their products which will lead to improved conversions, retention of customers, and all around, better products.

Data visualization in Mixpanel (Source)

Common features of product analytics software

Software features vary by product or vendor, but most product analytics platforms have the following features in common:

What type of buyer are you?

Before evaluating software, you should assess the type of buyer you are. The majority of buyers in the insight engines market belong to one of these categories:

• Product managers: The product manager of an organization has to understand their customers’ needs so that they can build useful products. They are mostly involved in conducting customer interviews, surveys, and examining product analytics. They can do so by collecting data from various sources including social media and other third party sources. But a product analytics tool can provide them with timely information on product usage, user engagement, time spent on the app/site and other key performance metrics (KPIs) seamlessly by integrating all data sources into one single organized view.
  A fully-featured product analytics tool with dashboard customization, custom segments, session recording, and automatic data capturing features would be suitable for these buyers. It’ll help them monitor key user behavior with their products such as onboarding, free trial conversions, and new feature launches to increase customer retention and build better products.
• Product designers: The product designer (especially the UX designer) is mostly responsible for UI and UX design of their products to provide end-users with the best possible experiences. Without proper insight into product features, it becomes difficult for developers and designers to innovate, and improve their product performance. They need a product analytics tool that can help them uncover user pain points and what customers like/dislike about the products they use.
  They should opt for a tool that includes features for A/B testing, engagement measuring by feature, user analytics, and to visualize user configuration changes over time. Such data can help them eliminate bugs, fine-tune features, and verify product concepts. It allows developers/designers to test and speed up product design and better prepare for launch.

Benefits of product analytics software

• Improved customer retention: Using product analytics software can help you uncover insights on user returns on your website over a period of time, time spent on the site, number of visits, and churned customers. By examining such key parameters through customer segmentation, engagement tracking, and data visualization, product analytics tools can help create strategies to improve retention over time, implement fixes, and improve product experience.
• Better product marketing: The conversion tracking and customer segmentation capabilities of such software can help product managers and marketers of your organization sell a product to users. By tracking users’ digital footprints to see which marketing programs (emails, social posts, campaigns) bring more visitors, you can create more targeted campaigns and improve customer onboarding.

Market trends to understand

Here’s a recent trend in the global product analytics software market that you should be aware of:

• Growing demand for AI/ML-enabled product analytics software: With the rise in the use of artificial intelligence (AI) and machine learning (ML) technology, product analytics software vendors are integrating AI to their platforms to enable automatic data capture of user level data, and scale personalizing digital experiences. AI-enabled analytics tools or product intelligence platforms with the help of machine learning capabilities can provide self-service, cross-platform analytics that uncovers answers, trends, correlations, and new questions in real-time. This can help product teams to make better and faster decisions by analyzing detailed behavior, user attributes, and channels.

Note: The application selected in this article is an example to show a feature in context and is not intended as an endorsement or recommendation. It has been obtained from sources believed to be reliable at the time of publication.