Everything You Need to Know About Product Analytics

You've decided to launch a life-changing product and have dedicated 1 whole year of life working with web developers, app developers, designers, and content writers, to launch your product.

After the successful launch, you're now spending a bucketload of money on marketing your product but wait, your audience is not converting as quickly as you thought it would. What's happening?

What's happening is that you've not spent sufficient time and effort to set up a way to gather and analyze your product analytics. This lack of data is making your whole marketing and product improvement strategy a guessing game and your conversion is consistently dropping.  

To help you with this, we have outlined everything you need to know about product analytics - from what tools to use to which metrics matter the most. So read on, and learn how to make data-driven decisions for your product!

What is product analytics?

Product analytics is collecting data about how your product is being used and then using that data to improve your product.

This data can come from a variety of sources, including:

Web analytics: Tracking how users interact with your website or web app

Mobile analytics: Tracking how users interact with your mobile app

In-app analytics: Tracking how users interact with your app or software

Customer support data: Tracking customer questions, problems, and feedback

You can use several tools to collect this data, including Usermaven, Mixpanel, Heap, and Amplitude.

Once you have this data, you need to make sense of it. This is where product analytics comes in.

Product analytics helps you make sense of your data and then use that information to make decisions about your product.

For example, let's say you have a mobile app, and you're tracking how often users open the app. If you see the number of daily active users decreasing, that's a red flag that something is wrong. Product analytics can help you figure out why this is happening and then take steps to fix the problem.

Why is product analytics important?

Product analytics helps product managers and founders make data-driven decisions about their products.

Without product analytics, it can be challenging to understand how users are interacting with your product and what changes you need to make to improve your product.

Product analytics also helps you track your product's success over time. For example, you can use product analytics to track your product's monthly active users (MAU) or daily active users (DAU).

You can also use product analytics to track engagement metrics, such as how often users use your product or how long they spend using it.

What are the most important product analytics metrics with examples?

There are several different product analytics metrics you can track, but some of the most important ones include:

- Monthly active users (MAU)

- Daily active users (DAU)

- Stickiness metrics (DAU/MAU, WAU/MAU)

- Engagement rate

- Retention rate

- Churn rate

- Conversion rate

Each of these metrics can give you valuable insights into how your product is performing and where you need to make improvements.

For example, if you see that your product's MAU is increasing, but your retention rate is decreasing, that's a sign that you need to keep users engaged.

Here are some examples of product analytics:

1. Customer journey analysis

This is the process of understanding how your customers interact with your product, from first contact to purchase.

This type of analysis can help you identify areas where customers are dropping off and then take steps to improve the customer experience.

Customer journey analysis can:

- Help you understand what's working well and what's not

- Help you create more targeted marketing campaigns

- Help you improve your customer service

-Identify areas where customers are getting stuck

2. Funnel analysis

A funnel is a path a customer takes from first contact with your product to purchase. Funnel analysis helps you understand where customers are dropping off, and what changes you need to make to improve your conversion rate.

Funnel analysis can:

- Help you identify where customers are getting stuck

- Help you understand what's causing customers to drop off

- Help you identify which changes will have the biggest impact on your conversion rate

- Identify areas where you need to make improvements

3. Attribution analysis

This is the process of understanding which marketing channels are most effective at driving conversions. Attribution analysis can help you allocate your marketing budget more effectively and make better decisions about where to invest your resources.

Attribution analysis can:

- Help you understand which marketing channels are most effective at driving conversions

- Allocate your marketing budget more effectively

- Make better decisions about where to invest your resources

- Help you improve your marketing campaigns

4. Cohort analysis

A cohort is a group of customers who share a common characteristic, such as sign-up date, product usage, or purchase history. Cohort analysis helps you track how different groups of customers interact with your product over time.

Cohort analysis can:

- Help you understand how different groups of customers interact with your product

- Help you track customer behavior over time

- Help you identify trends and patterns in customer behavior

- Help you make better decisions about product development and marketing

5. Retention analysis

This is the process of understanding how long users continue using your product after signing up. Retention analysis can help you identify what factors are causing users to drop off and what changes you need to make to improve your retention rate.

Retention analysis can:

- Help you understand why users are leaving your product

- Identify which features are being used the most

- Determine how to keep users engaged with your product

- Help you improve your product's onboarding process

6. Churn analysis

This is the process of understanding why users are leaving your product. Churn analysis can help you identify which features are being used the most and what changes you need to make to keep users engaged with your product.

Churn analysis can:

- Help you understand why users are leaving your product

- Identify which features are being used the most

- Determine how to keep users engaged with your product

- Help you improve your product's onboarding process

Who should be using product analytics?

Product analytics should be used by product managers, founders, and anyone responsible for making decisions about a product.

If you're not using product analytics, you're flying blind.

Product analytics is a critical part of product management, and it can help different departments make better decisions about your product.

Product managers:  Use product analytics to track product usage, engagement, and retention. This data can help you understand what's working well and what needs to be improved.

Founders: Use product analytics to track your product's growth. This data can help you understand whether your product is gaining traction and if it has the potential for long-term success.

Marketing: Use product analytics to track conversion rates and understand how users interact with your product. This data can help you create better marketing campaigns that target the right users.

Sales: Use product analytics to track which features are most used. This data can help you identify upsell and cross-sell opportunities.

Customer success: Use product analytics to track product usage and engagement. This data can help you identify areas where users struggle and need more assistance.

Product analytics is a powerful tool that can help digital businesses in many ways. By understanding what product analytics is, why it is important, and how it can be used, every department can use it to make better decisions about the product and the business.

What can you accomplish with product analytics tools?

Product analytics answer different questions ranging from engagement or trends to analyzing features over time to visualizing intricate experiences and user flow inside or outside the product.

In general, product analytics will give you the following capabilities:

- help you track product engagement and usage

- understand how users interact with your product

- identify areas where users are struggling

- track your product's success over time

- answer different types of questions about your product

- understand what is working well and what needs to be improved

- make data-driven decisions about your product.

To start with product analytics, you only need a good product analytics tool. Some popular options are Usermaven Mixpanel, Amplitude, and Heap.

Once you have chosen a tool, you can start tracking key metrics and generating valuable insights about your product.

How product analytics tools can help with customer lifecycle journey tracking?

Product analytics tools can help you track and understand every stage of the customer lifecycle.

By understanding how users interact with your product at each stage, you can make data-driven decisions that will help you increase product adoption and reduce churn.

The following are some key metrics you should track at each stage of the customer lifecycle:

Awareness:

- Number of website visitors

- Number of people who sign up for a free trial

- Sources of traffic (e.g. referrals, organic search, paid search)

Interest:

- Product engagement (e.g. number of page views, time spent on site)

- Which features are being used the most

Consideration:

- Conversion rates (e.g. free trial to paid, website to app)

- User satisfaction scores

Purchase:

- Revenue

- Average order value

- Payment method

Retention:

- Engagement (e.g. number of page views, time spent on site)

- Churn rate

- Usage of key features

Reactivation:

- Number of reactivated users

- Sources of reactivation (e.g. emails, in-app messages)

The above are just some metrics you can track at each stage of the customer lifecycle. By tracking these metrics and understanding how they change over time, you can make data-driven decisions that will help you improve your product and increase customer retention.

Is product analytics the same as marketing analytics?

No, product analytics is not the same as marketing analytics.

Marketing analytics focuses on understanding how marketing campaigns are performing. This includes metrics such as conversion rates, click-through rates, and cost-per-acquisition.

Product analytics, on the other hand, focuses on understanding how users interact with your product. This includes metrics such as engagement, retention, and satisfaction.

While marketing analytics is important for understanding how your marketing campaigns are performing, product analytics should be the primary focus when making data-driven decisions about your product.

What are some common pitfalls of product analytics?

One of the most common pitfalls of product analytics is tracking too many metrics. It is important to track only the metrics relevant to your business goals.

Another common pitfall is not setting up proper tracking from the start. This can make it difficult to retroactively track important metrics.

Finally, another common mistake is not analyzing or acting on the data. Even if you are tracking the right metrics, it will be useless if you don’t analyze the data and use it to make decisions about your product.

To avoid these pitfalls, it is important to have a clear plan for what you want to track and why. It is also important to set up proper tracking from the beginning and to regularly analyze your data to identify opportunities for improvement.

When should a company invest in product analytics?

There is no one-size-fits-all answer to this question. The decision of when to invest in product analytics depends on factors such as the stage of your product, the size of your company, and your business goals.

If you are just starting with your product, investing in product analytics right away may not be necessary. You can start by tracking basic metrics such as website traffic and conversion rates.

As your product grows and you generate more data, you may want to consider investing in product analytics. This will allow you to track more detailed metrics and generate deeper insights into your product.

Ultimately, deciding when to invest in product analytics should be based on your business goals. If you have a clear plan for how product analytics can help you achieve your goals, then it is probably time to invest.

What type of businesses need to use product analytics?

As the digital world continues to evolve, so does the importance of product analytics. To keep up with the competition, it is becoming increasingly necessary for businesses to track and analyze their product data.

Product analytics can be used by businesses of all types, including e-commerce businesses, SaaS companies, and mobile apps.

E-commerce businesses can use product analytics to track conversion rates, average order value, and basket size metrics. This data can improve the overall customer experience and increase sales.

SaaS companies can use product analytics to track churn rate, customer lifetime value, and engagement metrics. This data can be used to identify areas of improvement in the product and reduce churn.

Mobile app developers can use product analytics to track app downloads, app usage, and in-app purchases. This data can improve the app experience and drive more revenue.

No matter what type of business you have, product analytics can be a valuable tool for understanding your customers and improving your product.

What are the best product analytics tools?

There are several different product analytics tools on the market, each with its features and pricing.

The most popular product analytics tools include Usermaven, Mixpanel, Heap, and Amplitude.

Usermaven:

Usermaven is a powerful analytics tool for websites and SaaS products, including all the essential features a business needs to make data-driven decisions.

Pros:

• Automatically captures all the events making it a no-code tracking tool.
• It has end-to-end customer journey analytics.
• Privacy-friendly and cookieless tracking for website analytics.
• It has the simplest user interface among all analytics tools, and pre-made reports make it easy to get started, even for beginners.
• A generous free plan with all the essential features you need in a product analytics tool.
• Pixel white-labeling allows you to bypass adblockers and get the complete picture from your analytics data.
• It has transparent pricing, and you get more value for money than other tools.

Mixpanel:

Pros:

• Mixpanel is a feature-rich tool that can give you many insights about your website and product usage.
• A/B testing feature is available.
• It has a lot of integrations with other tools.

Cons:

• MixPanel has a steep learning curve and is a difficult tool for starters. It requires some practice and an understanding of how the platform works.
• Although it has a free plan but most of the advanced features are available in the paid plans which can become expensive very quickly.
• Events are not automatically captured. So, a lot of manual work is involved in setting it up.
• Lack of responsive customer support.
• Cookieless (privacy-friendly) tracking is not supported by Mixpanel.

Heap:

Pros:

• Automatic event capturing is a big plus in Heap's feature set.
• It allows retroactive event tracking, which is good for ever-evolving products.

Cons:

• Heap's free plan is very limited, and paid plans start from $3600/year which can be expensive for small businesses. If you have a lot of traffic, users, and events, it can become an expensive tool even for big companies.
• UX is not so great, making it a bit difficult to get started.
• Cookieless tracking is not possible with Heap.

Amplitude:

Pros:

• Predictive analytics powered by machine learning to estimate future outcomes.
• A generous free plan (10M events per month) but premium features are not available in this plan.

Cons:

• Complex interface, which makes getting started difficult for new users.
• Pricing is non-transparent and not available on the website.
• Amplitude becomes expensive as your business grows. Although it has a generous free plan most of the premium features are excluded.
• It doesn't provide cookieless tracking.

Why is Usermaven the best product analytics solution?

Usermaven uniquely approaches product analytics, beginning with an inquisitive mentality. Product-market fit, we believe, is the ultimate measure of success for firms of all sizes.

You can test any hypothesis with Usermaven at any point in the feature development process, and you'll be able to analyze the results to see if it's working as intended.

Unlike other solutions, Usermaven is simple to set up and provides comprehensive access to your past data.

With Usermaven, you must install a single script to record every click, swipe, touch, pageview, and other action for all your users without invading their privacy.

The data ingested may answer every question you may have, including ones you haven't considered yet. There is no need for manual tracking, planning, or engineering time.

Usermaven is also the most cost-effective solution. It provides a forever-free trial that includes all of our essential features, and you can upgrade anytime you want with transparent pricing (without any surprises) on the website.

We hope this article has helped to shed some light on product analytics and given you a better understanding of what it is and how it can help your business.