Product Analytics in a Nutshell

A Brief Introduction From a Marketing and Business Analytics Perspective

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Customers are valuable assets to the business. Businesses can’t make decisions without putting customers at the center. They must understand customers’ wants and needs and how they interact with their products and services. Ultimately, a good experience is what makes businesses win.

Today, our world is full of products and services with the customer at the epicentre. For every new product, it is almost certain there exists a competitor. Therefore, businesses must do everything possible to acquire and retain customers to sustain. After the internet became the basic utility, a new class of cloud products evolved, making it easier to understand customers using instant analytics. In this post, let’s get into product analytics, understand what it is and how different it is from a marketing and business analytics perspective.

What is Product Analytics?

In simple words, product analytics is a process of collecting and organizing users’ behaviour data. At the same time, they interact with products and answer questions to get valuable insights that lead product teams to enhance user experience. It also helps product teams to develop empathy toward users and quickly implement improvements to the product.

Data for product analytics is generally collected through the product itself. Typically, a piece of code is inserted into the product at the key locations where users’ actions provide meaningful insights. Every time users navigate those locations, data is collected and organized in a format that analytical tools can understand and interpret.

Why Product Analytics?

Implementing product analytics enables product teams to develop a quick feedback loop for collecting valuable insights from users. Knowing how they interact with the product, objectives, and journey will help the product teams quickly identify the weak points and enhance the user experience. It saves businesses significant time and money at the early stage.

It makes it easier to identify power users who can provide great insights and stick around for a long time if their needs are served. Some big companies whose revenue mainly comes from advertising rely heavily on product analytics. They develop effective user interfaces and experiences throughout users’ journeys so that they keep coming back.

Product Analytics vs. Marketing Analytics

Before the 90s, product management was considered a part of marketing. Therefore, a lot of terms are interchangeably used between these two disciplines. For instance, “market” and “marketing” are different. The term market is simply a customer, and marketing refers to the act of reaching out to the customer. In that context, product and marketing analytics are two concepts based on how they deal with the customer, although they look closely related. Here is how product analytics stands out from marketing analytics.

• Product analytics focuses on solving market problems by providing useful customer insights and accordingly improving the products. It is more technical and user-centric. In contrast, marketing analytics focuses on generating revenue for the business with effective messaging and exploring ways to increase conversion rates. It is physiological and sales-centric.
• Product analytics ensures a great user experience by providing useful insights to the product teams on how users interact and navigate various parts of the product. It emphasizes more the user experience than their actions. On the other hand, marketing analytics focuses more on user actions than experience. It relies on diagnostic and predictive analytics, measuring key actionable and exploratory metrics.
• Performing marketing analytics typically leads to developing effective messaging, positioning, and implementing key market strategies. Product analytics leads to new product requirements, code changes, or sometimes pivots.
• While performing product analytics, you may deal with confidential information about the users. The data should be handled carefully as it affects the company’s policies and legal boundaries. On the other side, marketing analytics stays away from user-specific data and can be accessible to others in the company.

Product Analytics vs. Business Analytics

Business analytics is sometimes referred to as Business Intelligence (BI). Some consider it a subcategory of BI. This is just another area of business where the power of analytics is applied.

Unlike product and marketing analytics, business analytics:

• Goes beyond the scope of any particular product. It deals with the organization-level data collected from various sources such as markets, products, services, finance, and human resources to analyze business trends.
• It uses predictive analytical techniques such as data mining, modelling, and machine learning to determine the likelihood of future outcomes to help business leaders as they are always looking for threats and opportunities.
• Provides insights to the business leaders as to whether a company should develop a new product line or prioritize one project over another.
• Focuses on the overall function and day-to-day operation of the business.

Tools for Product Analytics

Collecting and analyzing real-time users’ activities requires specialized tools that constantly interact with products. Google Analytics paved the way for many web-based analytical tools currently available in the market. Like Google Analytics, they all provide useful insights through various functionalities. Each one focuses on different areas of product, marketing, and business analytics as their strength.

Here is a list of the 13 top analytics software to evaluate based on your needs. Although most of these tools focus heavily on marketing and business analytics, you can surely customize them to work for product analytics.

1. Google Analytics

Best Known For

• all types of cloud-based applications
• personal and business websites
• businesses of all sizes to track users’ behaviours and customers interactions
• digital marketing
• Startups

2. Mixpanel

Best Known For

• account level product analytics
• landing page optimization
• SaaS web apps
• temporal analysis of user activities
• integrating segmentation
• A/B Testing

3. Amplitude

Best Known For

• mobile app analytics
• for creating different cohorts based on the custom events tracked and the segments of users
• using heat maps and funnels
• startups (with their great trial version product)
• A/B testing

4. Segment

Best Known For

• developing Customer Data Platforms to support expandability, data enrichment, and multiple devices
• creating chart diagrams, and flowcharts for users
• custom-built websites

5. Heap Analytics

Best Known For

• simplified functionality to track clicks, events, and user journey
• generating heat maps
• user-level product analytics
• segmentation optimization

6. Snowplow

Best Known For

• Big Data processing and distribution with integration to Hadoop
• business intelligence with capabilities for data modelling and transformation
• collecting high-quality event data
• product analytics on multiple platforms and channels (including IoT) with our range of first-party trackers

7. Looker

Best Known For

• Business Intelligence and data visualization
• self-serve user-defined dashboards
• quickly and easily integrating data from across data sources into a single view
• data modelling and blending
• column data filtering
• user-friendly interface for reporting

8. Baremetrics

Best Known For

• simplified SaaS product analytics
• payment, revenue, churn, and cohort analysis
• intuitive dashboards

9. Pendo

Best Known For

• account and user-level product analytics
• click reporting
• feature-based user engagement
• in-app guides and NPS tracking

10. Adobe Analytics

Best Known For

• custom event tracking
• session-based analytics for digital marketing
• tracking user interactions and conversions
• cloud-based solutions
• good reporting tools

11. Profitwell

Best Known For

• customer success monitoring
• SaaS product analytics
• business analytics and improving customer retention
• customer payments tracking

12. Gainsight PX

Best Known For

• simplified integration for both mobile and web apps
• better user engagement and improving conversions
• multi-language support
• integrated surveys and text-bubble walkthroughs

13. Smartlook

Best Known For

• replaying sessions
• replaying mouse movements and click tracking
• ability to create heatmaps with historical data
• segmentation
• analyzing e-commerce sites
• providing insights to the UI/UX designers
• collecting data for qualitative analysis

Closing

Thanks for hanging around. That’s the long list of tools. There are many more. But, I find these are the most popular ones in the market. For product analytics, my top picks are Mixpanel, Heap, Amplitude, and Pendo.

To recap, product analytics exclusively answers product-related questions and user interactions with products. Actions led by product analytics result in improved products and enhanced user experiences. In contrast, marketing and business analytics focus beyond the product, such as user actions, revenue, strategic planning, and day-to-day business operations.

Further Reading

For further reading, I highly recommend visiting the below link to get more information about this topic.

1. 5 Top Analytics Tools That Are Product Managers’ Best Friends — by Donald Fomby
2. Business Intelligence or Business Analytics — By Tableau
3. Product Analytics — By ProductPlan

Thanks for reading! I hope you enjoyed this post. Connect with me on Twitter or visit arjunken.com