As companies continue to compete in a rapidly changing IT industry, making data-driven decisions has become essential for success. This is because using data to inform decisions enables companies to make more accurate and effective choices that are better aligned with their goals and the needs of their customers.

As a part of our BRO Recommends rubric, we asked Denys Hlazkov, Platform Product Manager to share his insight on product analytics and the vital role it plays in the development of companies in this ever-expanding market.

Product analytics provide a wealth of information that can be used to inform decisions about product development, marketing, and other important aspects of a company’s operations. The first step in making data-driven decisions is to define one’s goals clearly. This could include objectives like increasing revenue, improving customer satisfaction, or reducing costs.

Companies can then begin collecting and analyzing data, which is the key step in making data-driven decisions. This data can come from various sources, such as tracking customer behavior on a company’s website, analyzing sales data, or conducting surveys to gather feedback from customers.

A technique that companies use for this is A/B testing, which allows them to test different versions of a product or marketing campaign to see which one performs better.  This might involve identifying patterns and trends in customer behavior, testing different product features or marketing strategies to see what works best. Another way of using data is by data mining, discovering insights, and identifying customer segments, behavior patterns, and trends. This information can be used to increase the efficiency of marketing campaigns, reduce costs, and identify new revenue streams.

It is also important to note that data-driven decisions are an ongoing process and companies must be prepared to continuously monitor the data and adapt their decisions accordingly. This is because data will constantly be changing based on the company as well as external factors like market demand and the general environment.

It is also important to note that companies need to make significant investments in data infrastructure and technology. This includes investing in data storage and processing capabilities, as well as hiring data scientists and analysts who are skilled in working with data.

Here is a list of best tools for product analytics that can be used depending on a company’s specific needs. Each tool has its own particular features and price range so it is a good idea to see which one fits best for your company.

User research and behaviour tracking:

  • Mixpanel - is used for tracking user behaviour and engagement, as well as revenue, sign-ups, and other key metrics on your website.
  • Amplitude - this helps you understand how customers interact with your product and provides insights on how to improve it.
  • Heap - automatically captures all user interactions on your website, allowing you to analyze and segment data without having to manually set up tracking.
  • Google Analytics - provides insights into website traffic, user behaviour, and conversion rates.
  • Smartlook - a website and mobile app, analytics tool that allows you to track user behaviour and understand how users interact with your product.
  • Hotjar - allows you to see how users interact with your web application through heatmaps, session recordings, and form analytics.

Data visualisation and reporting:

  • Tableau - a data visualisation and business intelligence tool that allows you to connect to, visualise and analyse data from a wide variety of sources.
  • Power BI - provides advanced data visualisation and business intelligence capabilities.
  • Grafana - An open-source platform for creating interactive visualisations and dashboards for monitoring and analysing data.
  • Kibana - An open-source data visualisation and exploration tool that allows you to perform advanced data analysis and visualise large volumes of data.

Market Intelligence and Competitive Analysis:

  • SimilarWeb - a website analytics and market intelligence platform that provides information on website traffic, engagement, referral sources and more.
  • SEMrush - a digital marketing tool that provides insights into website performance, search engine optimization, pay-per-click advertising, and content marketing.
  • App Annie - a mobile app analytics and market intelligence platform that provides insights into app performance, including downloads, revenue, and user ratings.
  • Sensor Tower - a mobile app analytics and market intelligence platform that provides detailed information on app performance, including downloads, revenue, and more

Data Warehousing and Storage:

  • Google BigQuery - a cloud-based data warehousing service provided by Google Cloud Platform. It allows you to store and query large amounts of data using SQL, and it also supports advanced analytics such as machine learning.
  • Snowflake - a cloud-based data warehousing service that provides a SQL-based relational database.
  • ClickHouse - an open-source column-oriented database management system that allows for the real-time generation of analytical data reports using SQL.

In conclusion, data-driven decisions in product analytics is a powerful approach for driving growth and improving decision-making. By using data to inform decisions, companies can reap the benefits.