
Google Analytics 360
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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:
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.
Software features vary by product or vendor, but most product analytics platforms have the following features in common:
Data visualization | See and understand trends, outliers, and patterns in data in graphical representations using visual elements such as charts, graphs, and maps. |
Product data management | Capture, organize and track product-specific data and information in a centralized location. This data includes product usage, features, design data, user feedback, and configurations. |
Cohort analysis | Categorize and divide data into groups with common characteristics before analysis. |
Conversion tracking | Analyze what happens after a customer interacts with your ads - whether they purchased the product, signed up for a free trial, downloaded your app. This helps you understand how your products are selling and at what rate you are converting leads. |
Customer segmentation | Segment your customers into groups with similar characteristics or parameters such as demographics, gender, and buying behavior. This can improve your marketing analytics through targeted marketing messages to establish customer relationships. |
Engagement tracking | Monitor customer interactions and which interactions bring about the most value. This includes, number of visits, total logins, number of tasks performed, files stored and deleted, and other parameters. |
Funnel analysis | Analyze a series of events that lead towards an outcome on a website and how many users get through each of those steps. Example: the flow that starts with an advertisement-to-purchase journey in online advertising. |
Alerts/notification | Trigger notifications or alerts via email to keep up with important and time-sensitive information. |
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:
Here’s a recent trend in the global product analytics software market that you should be aware of:
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.