Building and sustaining a successful product in the market requires meeting user expectations and needs. Ensuring this requires a strong understanding of end users and leveraging that understanding to meet their expectations.
Enter product analytics, which is all about collating and analyzing different product-related data to understand user behavior and use it to ideate and improve products for success.
The importance given to product analytics is growing at speed. From a mere $9.6 billion in 2021, its market size is expected to reach $25.3 million by 2026. This indicates more product managers are taking analytics very seriously to remain competitive.
In this guide I’ll help you learn how to leverage product analytics to your advantage in your PM work.
Table of contents:
- What is product analytics
- Decoding the user behavior puzzle: How does product analytics work
- What to track as a product analyst
- What are the different analyses product analysts perform
- Is data analytics and product analytics the same?
- Is product analytics only for product managers
- How will product analytics help you in the future?
1. What is product analytics
Product analytics studies product and user data to understand user requirements and track product performance. The information gathered helps you stay on top of what users want and identify gaps.
Leveraging it, you can make informed product decisions to enhance user experience and product lifecycle while boosting revenues.
While these metrics are used by a wide variety of product professionals across the spectrum, the dedicated role of product analyst has emerged in recent years, blending product management and data analytics expertise.
2. Decoding the user behavior puzzle: How does product analytics work
Product analytics works by granularly studying user behavior patterns to identify their needs, desires, and expectations. User behavior includes users’ different actions and interactions while using a product.
Gathering information on how users interact with a product and identifying patterns and trends helps decode their experience and identify any problems they face. The more you focus on behavior data and iterate, the better you can ensure that your product is driven by user experience and not mere guesswork.
How can you do this?
Product analytics makes decoding user behavior possible with its processes involving
- Collecting and analyzing qualitative and quantitative data on user behavior, product performance, product features, and overall product-related trends.
- Generating insights on how people interact and engage with a product.
- Exploring product improvement opportunities to enhance user experience and satisfaction.
How do you implement this? Let’s start by looking at some essential data you can track.
3. What to track as a product analyst
As a product manager, you must keep track of various Key Performance Indicators (KPIs) concerning different aspects of a product, its users, and the technical and business side.
Tracking these can help you improve the product and user experience. While there are umpteen metrics to track, the most important ones can be classified into two main groups:
- User behavior metrics: These help understand what’s wrong with the product and where it can be improved.
- Business metrics: These help understand your product’s performance in the market and identify potential improvement areas.
Important user behavior metrics to track as a product analyst
- Feature usage: Not all features are equal, and some may be unnecessary. Feature usage information helps you study how users interact with different product features and identify what features are unused or require modification.
- Stickiness: There may be certain product aspects that your users genuinely love. This is demonstrated by repeated actions in that area, such as clicking and other forms of interaction. As a product analyst, it’s your job to identify these, ensure sticky features and regions get special attention, and that there aren’t any bottlenecks within the UX.
- Sessions per user: The number of times a user uses a product indicates engagement levels. If the sessions per user metrics aren’t impressive, it’s a clue for you to conduct a complete product audit to find out where things are going wrong.
- Adoption rate: This helps you understand the percentage of users who’ve adopted a new feature in the product. Tracking this is particularly helpful when you’ve changed or added new features.
- Activation rate: This is the rate at which new users perform their first actions in the product. A low activation rate may indicate problems with the registration interface or the product’s UX/UI.
Important business metrics to track as a product analyst
- Referral rate: Knowing how frequently users recommend your product to others can help you gauge its success and ascertain whether your overall product management strategy is successful.
- Churn rate: This tracks the rate at which you lose users. A high churn rate can indicate something amiss. You must track it regularly to minimize it by tying it with other parallel and co-occurring metrics and analyses. For example, collect and analyze user feedback to identify areas of dissatisfaction.
- Revenue rates: Annual Revenue Rate (ARR) and Monthly Revenue Rate (MRR) help you understand how well-received your product is in the marketplace. Deviations from the normal ARR or MRR indicate your product isn’t performing well. That’s when you need to go back and check other metrics and insights to understand where things are going wrong.
In addition to tracking these metrics, other popular ways exist to gather information on how users interact with a product.
Additional ways to track user behavior and product adoption:
- Heatmaps and session recordings: These help you identify why users cannot complete specific tasks. Popular heatmap tools include Hotjar, Smartlook, and Crazy Egg. These tools also support session recording tools.
- In-app surveys: These help understand the needs and desires of engaged users. Tools like Survicate, GetFeedback, and Pendo can help you collect responses from the app.
- A/B testing: This helps you test and tweak various feature updates and additions before they go live. AB Tasty, Convertize, and Zoho PageSense are popular tools for performing A/B tests.
While collecting information and identifying patterns is one part, performing different kinds of analyses is integral to product analysis.
4. What are the different analyses product analysts perform?
Regarding analyzing the information collected, several analysis methods are popular among product analysts. Some of these include:
- Segment analysis to identify patterns of behavior among users with similar attributes.
- Cohort analysis to understand user behavior from the perspective of a specific period.
- Funnel analysis to understand how users proceed through the product lifecycle journey and identify bottlenecks.
- Customer journey analysis to understand engagement and user experience.
- Conversion analysis to identify successful features and make further improvements to drive conversions.
There are several dedicated product analytics software tools available. These can enable you to bring in a variety of metric tracking and analytics under a single interface. You can watch out for features that help understand customer journeys, behavior-based user segmentation, product usage tracking, and the ability to integrate with third-party tools.
Examples of tools product analysts use include Quantum Metric, UXCam, and MixPanel.
At this point, you might be wondering if data analytics and product analytics are the same.
5. Is data analytics and product analytics the same?
While data and product analytics may appear similar, they are distinct concepts.
I’ve broken some of the major ones down in this handy table:
6. Is product analytics only for product managers?
As you can see, product managers use product analytics to track different metrics to improve the product experience and market success. But they aren’t the only ones doing so.
The process is also sometimes used by associate product managers, data analysts, and marketing and sales teams seeking to understand user behavior. Developer teams use it to gain tech-related insights about a product. It’s a versatile discipline with applications for anyone managing a product or its development.
7. How will product analytics help you in the future?
If you’re a PM, product analytics is essential for navigating current and future product landscapes. Current trends make it clear that the demand for PMs with specialized knowledge is set to increase—which means it’s something you must start engaging in.
Furthermore, the insights offered by product analytics tools will likely get even more refined as artificial intelligence (AI) and machine learning (ML) make inroads into the space. Far from being just for AI product managers, knowing how to access and interpret these will lend you an edge in understanding users and enhancing product features quickly and seamlessly.
Having said this, you’ll need to be careful about complying with data privacy and security-related aspects.
8. Bottom line—Product analytics is the backbone of successful products
Engaging in product analytics is essential in the competitive product world to improve user experience, extend a product’s lifecycle, and spell market success. As user requirements and expectations change and evolve continuously, you must watch out for the different trends to make sense of the data and leverage it when planning your sprints.
To explore product analytics in more detail, check out our 5-day data analytics short course. Conversely, if product roles in general interest you, CareerFoundry also have free product management short course should help you get started on your awareness about building and launching products.
Some additional resources you might want to explore: