Graphic Of Product Analysis

A Guide To Product Analytics: Tools, Benefits & Why It Matters

A Guide to Product Analytics

In every business, there is an invisible boss who determines whether employees get paid or not, whether the business can pay its suppliers, and if the business will remain sustainable, going into the future. That boss is called the customer. Therefore, any business that fails to understand how customers interact with its products will find it hard to succeed, particularly at this time when customers have the digital power to share their opinions. 

Successful companies, that want to understand their clients, are progressively turning to product analytics software to understand how their current and potential customers are interacting with their products and services. However, software tools are not created equal.

This guide will help you answer some of the leading questions in the product analytics area. In the end, we will identify the 10 top product analytics software we can find, and explain the criteria we have used to identify these tools.

Product Analytics FAQs

Before we reveal our top product analytics software, let us address some questions that product managers frequently ask about product analytics.

What is Product Analytics?

Photo of Customer satisfaction survey

Product analytics is the process of understanding and answering questions related to customers’ behaviors when they interact with your products. For the product manager and their team, product analytics provides useful data from which insights can be made. It provides a range of information, from basic details, such as who uses the products, to more complex insights into the personalized penchants of these users.

Product analytics software tools use embedded sensors within digital products to track user actions. Information gathered about user behavior is then used to identify shortcomings, optimize the product, and improve the user experience. 

Product analytics is user-centric. Rather than focusing on what a product was designed to do, it is concerned with how users interact with the product. This helps the product manager to draw precise insights on what aspects of the product need improvement, rather than relying on guesswork and instinct alone. 

Traditionally, product managers relied on questionnaires and customer interviews to determine the perceptions of customers and users of their products. Even though these methods allowed brands to understand how users interacted with their products, these techniques were expensive and time-consuming. Today, companies can discern these user interactions using a range of product analytics software tools available in the market.   

Is Product Analytics the Same as Marketing Analytics?

Even though the phrases ‘product analytics’ and ‘marketing analytics’ are sometimes used as synonyms, this is not always the case. However, the two concepts are closely interlinked. Below are the main differences between the two concepts:

  • Product analytics focuses on user engagement with specific portions of the product environment to understand the entire customer journey so that parts, where users are getting stuck, can be corrected, and parts working well can be identified. Thus, product analytics’ success is determined by understanding user interactions and determining how these interactions can constantly be improved to create the best experience. On the other hand, marketing analytics focuses on the user actions that result in a conversion, meaning that success is determined by the user taking the desired action.  
  • While marketing analytics focuses on how to turn visitors into paying customers, product analytics seek to find ways that these customers can be engaged so that they will keep coming back to buy the product.
  • While marketing analytics seek to determine how the various parts of the customer journey can be tailored to lead to a conversion, product analytics focuses on how this could be done through the way the product is designed. 
  • Product analytics relies on more confidential information obtained from customers who have already ordered the product. This includes information such as where the product was purchased from, the gender of the person purchasing the products, and credit card information.  Marketing analytics, on the other hand, depends mostly on the information in the public domain.

Why is Product Analytics Important?

One of the seminal speakers often used to explain why product analytics is important is John Wanamaker, the 19th Century American merchant. He is often seen as a pioneer of marketing. Wanamaker is widely quoted saying, “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.” This seems to be the challenge that product analytics, and the software tools available today, seek to alleviate. 

Product analytics ensures that brands do not just shoot into the dark, hoping that they will hit something. Rather than expend money and other valuable resources on speculative advertising, product analytics ensures you have the right insights on what your customers are doing with your product. This can help your company develop better ways to reward and reinforce desirable behaviors, and keep customers coming back.

Product analytics helps in product design abstraction. With the level of insight brought about by tracking user events, it is easier to know what customers use, and what they don’t. Your product can be made leaner, lighter, and faster by removing features that no one is using while retaining its most relevant ones.

Who Benefits Most From Product Analytics?

Everybody involved in the creation process, marketing, and use of products, benefits from product analytics.

The Product Manager:  Uses data produced by product analytics to evaluate the experience of the users when using the product. Product managers also identify the product’s weaknesses, and determine what needs to be done to improve the user experience.

Developers and UX Designers:  Are better able to find and resolve design and implementation flaws when they are aware of users’ experiences with the product. Designers can also learn which features confuse users and address them accordingly.

Marketers:  Are better able to sell a product to users if they know exactly what the users are doing with the product. Added to this, they can also determine what the users do with the marketing information they receive.

Customers: Are always looking for products that are easy to use as it may not always be possible for customers to get their views across in the way their actions do. Thus, by knowing what behaviors customers exhibit when dealing with products, brands can discern what customers are looking for. This improves the customer experience.    

When Should a Company Invest in a Product Analytics Tool?

As long as you have a product to sell, you need to determine how the users are interacting with your product. Of course, small companies require different tools when compared to large companies. Therefore, it is vital to start by determining what you need to track to have an idea of the scale of the tools you need.

We often see advice that product teams should only start using product analytics tools when they have reached a certain number of users. However, there is a dichotomy in this advice. You will only reach a certain number of users if you can scale, through ensuring a desirable experience when users interact with your product.

The Best Product Analytics Software

Here is a list of the 10 best product analytics software we have come across: 

1. Amplitude

Screenshot Of Amplitude

Amplitude offers what it calls “The gold standard for product analytics.” The software guarantees interfaces that are easy to use, ensuring that teams work collaboratively. It also solves one of the most significant challenges faced by product teams: data governance, security, and compliance.   

2. Mixpanel 

Screenshot Of Mixpanel

The developers of Mixpanel indicate that they are driven by the realization that “great products are built by teams who know their users.” The software allows users to see top user flows, build funnels, and create cohorts, among many others.

Mixpanel also promises a simple data model and APIs (application programming interface) to enable you to “load data from your internal pipeline, a customer data platform (CDP), and [Mixpanel’s] SDKs.” This data is then transformed into insights.    

3. Google Analytics

Screenshot Of Google Analytics

Considering the company’s pedigree, it is no surprise that Google Analytics is one of the first product analytics software. What makes this software one of the best is that it provides many free features that better understand the users of your site. 

You also benefit from the machine learning capabilities of a company such as Google. The analytics are built to “work with Google’s advertising and publisher products so you can use your analytics insights to reach the right customers.” 

4. Segment

Screenshot Of Segment

Segment promises a unique feature that enables you to have a “single view of the customer.” The software is also designed to gather data from different sources, including the web, warehouse, and mobile applications. This data is then organized for use by different teams, including the engineers and marketing. The tool also promises data privacy through compliance with privacy regulations such as GDPR, CCPA, etc.

5. Snowplow

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Snowplow says that its software “is ideal for data teams who want to manage the collection and warehousing of data across all their platforms and channels, in real-time.” In reality, this means that data is collected from several event sources, such as the web, mobile applications, email, and others, before it is validated, enriched, and placed in a warehouse from which different teams can access it.

6. Heap Analytics

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Heap promises to assist product teams to “use behavioral data to build extraordinary products.” The company says that it accomplishes this through assisting teams to “understand how people interact with your product, increase acquisition and retention, reduce your engineering burden, and create a powerful product experience.” 

Some of the product’s most powerful features include: 

  • Automatically uniting visits from various channels and devices to create a single user profile. 
  • Analyzing the behavior of customers to determine trends that can assist product teams in personalizing the customer experience.
  • Ensuring that everyone in the organization who wants to use analytics can.

7. Looker

Screenshot Of Looker

Looker attempts to ensure that users get the most value from the data they collect. Some of the software’s leading features include: 

  • Allowing users to create dashboards in real-time for conducting in-depth analysis later.
  • Enabling team collaboration so that data-informed decisions are made across the board. 

8. Pendo 

Screenshot Of Pendo

The Pendo product cloud promises to guide users through the whole product journey. This is accomplished by providing the ability to communicate with clients as they interact with the product, instead of through the inbox.

Pendo also ensures customer retention by encouraging feedback and engagement. User onboarding is also done in-product to ensure that the customer experience is optimal.

9. Smartlook

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Smartlook is designed to comply with the General Data Protection Regulation (GDPR) specifications. It is easy to install on websites with only a snippet of code, and in mobile applications. Some of the software’s features include: 

  • Automatic event tracking 
  • Gathering event statistics 
  • Creating funnels connected to recordings 
  • Production of retroactive data
  • Creating retention tables 

10. Gainsight PX

Screenshot Of Gainsight

Gainsight calls itself “The most customer-centric user analytics and product engagement platform.” The analytics produced from this software enables product teams to: 

  • Visualize the journey taken by cohorts of users as they move through a product.
  • Determine areas where customers drop off from engaging. 
  • Know the features associated with high user satisfaction and long-term retention. 
  • Place users into groups based on their behaviors. 

Criteria for Selecting Product Analytics Software

Product analytics platforms provide a plethora of features. These include tracking, segmentation, establishing user profiles based on your preferred criteria, notifications, dashboards, funnels, and measurement tools. These are some of the elements we looked at when we selected the best software in our list above. 

The above list was also compiled based on a set of parameters that we think are the essential features that any product analytics software should possess. These include A/B testing, user tracking, and user segmentation. 

Because of the sensitivity of the data required by product analytics, we also looked for product analytic platforms that provide vital data security services. We are also generally attracted to software tools that provide free demos. This tells us that the tool has the confidence that it will impress most users to want to pay for it.