Are you building digital products but have a lot of questions such as which features users want? Will they interact with the product easily? Will users like this product? The answers to all these questions and more are offered by ‘Product Analytics’!
This tool is useful to improve product engagement and drive business success. Tracking user behavior towards the product is easy with this tool.
Let’s dive in and learn how product analytics help businesses and which tools can help analyze product performance efficiently.
What Exactly is Product Analytics?
Product analytics is a collection of powerful tools that help product managers and teams evaluate the performance of the digital experiences they produce. It provides crucial data for optimizing performance, diagnosing problems, and correlating customer engagement with long-term value (LTV).
If you are in charge of producing an excellent website or digital product, product analytics will help answer the who, when, how, and where of your product.
Product analytics software allows you to monitor users’ digital experiences, optimize product utilization performance, and discover which features your consumers use and which they disregard, how to effectively reduce churn, what are the major challenges. and how you can personalize user engagement.
Product Analytics Metrics: Uncover Hidden Insights
Product analytics can answer a variety of use cases, from analyzing feature adoption or user engagement over time to visualizing detailed experiences and user flows within and outside of the product.
Here are the five most critical forms of analysis you must employ to maximize the benefits of product analytics.
1. Trends Analysis
One of the most prevalent types of reporting in product analytics, it enables businesses to see whether feature adoption is increasing or decreasing over time.
A trend analysis focuses on one or more specific user journey touchpoints by slicing and dicing them and then zooming in on their performance over time.
UX designers, for instance, can zoom in on specific features and see changes in user configuration over time. Product teams can determine the most and least used product features, and also how the utilization of each feature compares to the past.
2. Journey Analysis
The journey analysis identifies bottlenecks in the user’s journey and allows you to fine-tune the user experience even further.
It’s vital to visualize the user’s journey to each goal and where they can get lost along the way. A Customer Success Manager, for example, can visualize a user’s journey to resolving an issue.
3. Attribution Analysis
Customers who succeed can provide you with meaningful insights. Attribution analysis can assist you in identifying the touchpoints that are pivotal to your success.
Attribution analysis, like journey analysis, relies on user flow data to accurately identify users who have completed their journey and retrace their steps.
A product manager, for instance, can segment revenue based on the most recent premium feature usage attempts before conversion. Based on this, companies can assign a monetary value to each premium feature and emphasize the highest-converting prospects.
4. Cohort Analysis
Product messaging, website design, documentation, onboarding experience, brand recognition, product complexity, and many other aspects evolve as a company grows. These changes have a significant impact on how each cohort sees the product or service. As a result, product measurements should be broken down by cohort to demonstrate how consumer impression changes over time.
A cohort can be identified based on when they first visited the website, signed up for the service, spoke with a salesperson for the first time, or upgraded to a paid subscription.
The cohort definition should be dynamic and precise for each cohort analysis. This analysis allows product managers to see user submissions broken down by when they registered for the product.
5. Retention Analysis
Churn occurs in the majority of successful businesses. Companies must examine the rate of churn. The Retention Analysis assists your company in analyzing the rate at which users continue to engage with a product or feature over time.
A retention analysis, as compared to a cohort analysis, normalizes cohorts under the ‘initial period’ and provides the aggregate retention rate for the subsequent periods. The cohort units can differ depending on the use case. They range from days to weeks to months to quarters.
Every retention analysis also necessitates a cohort definition (an action that defines the cohort, such as signing up) and a repeat action (an action that will be analyzed over time, such as logging in).
Top 5 Product Analytics Tools
Here’s a detailed description of each product analytics tool with a focus on its best use case and standout features.
1. Quantum Metric
Best for automatically detecting faults with user experience, Quantum Metric identifies product flaws that could be costing you money.
It is powered by big data and machine intelligence and provides organizations with a complete overview of client behavior. This is conducted through the use of interactive customer experience journeys. These trips assist product managers in understanding the demands and challenges of their consumers.
Quantum Metric automatically records user sessions and creates step-by-step logs of user behavior to be viewed as video replays. Heat maps highlight areas where users struggle as well as the scope for improvement.
This application works with popular platforms like Salesforce, Google Cloud, Slack, and Google Analytics.
2. Google Analytics
Google Analytics is a free service that gives detailed information on user behavior. It is the industry standard for tracking and analyzing user activity and behavior on websites and mobile apps.
It has evolved into a robust tool that delivers detailed information on user behavior, customer location, and per-click quotas over time. You can use this data to boost conversions, decrease bounce rates, and improve engagement with your digital products or services.
Google Analytics interfaces with numerous relevant services and products due to its widespread popularity. GitHub, Stack Overflow, Twitter, and YouTube are a few examples.
3. UXCam
The feature session recordings from UXCam can track how people interact with the product, such as mouse movement, time on the page, and button or link clicks.
UXCam is specifically designed to understand mobile-focused user behavior. It gathers, processes, analyzes, and visualizes user behavior data automatically, making it simple to see the motivations and behaviors behind the user experience.
To understand the how and why of the client experience, teams can comment on session recordings and heatmaps, and follow journeys across funnels. UXCam works with a variety of systems, including Firebase, Google Analytics, and Segment.
4. Mixpanel
Mixpanel is a vital tool that focuses on getting detailed information about user activity. It enables organizations of any size to do cost-effective user behavior analysis.
It gives interactive reports, identifies popular new features and functionalities, and highlights power users. Instead of analyzing page views, it measures the actions or steps made by people who enter the monitored application. A single action can range from uploading an image to streaming a video.
Mixpanel interfaces with a variety of systems, including Google Cloud, Optimizely, Zoho, and Slack.
5. Pendo
Pendo is a product management tool for customer-centric industries such as healthcare, educational technology, and financial services.
It helps increase client retention by providing insights into user behavior throughout their product experience. Improve onboarding and feature uptake with targeted walkthroughs and messaging within the app. It enables data analysts to track product features and usage across web and mobile applications.
Pendo connects with various third-party systems such as Algolia, Figma, HubSpot, Jira, Microsoft Teams, Slack, Salesforce, and Tableau.
To Put it Briefly
Product analytics is an essential tool for making data-driven decisions and facilitating product-led growth. It involves the use of various types of data and methods to gain insights into customer needs, product performance, and market trends.
It is a dynamic field that is continually evolving with advancements in technology and approaches to analysis. A product analytics strategy requires skills in data analysis and interpretation, an understanding of user behavior, and knowledge of the product and market.
When done correctly, product analytics can help you improve product engagement, increase customer retention, and drive your business’ success.
