What Is Product Analytics?

Product analytics is concerned with using data to understand how people actually use a product. This is to be distinguished from how a company intends for customers to use a product, or how (or why) a customer thinks they might use a product. Instead, it is a data-driven analysis of how a product is used by customers in the real world. Companies apply product analytics for many reasons, including new product development, profitability analysis, product recalls, supply chain optimization, product portfolio analysis, and competitive product analysis.

Data sources used in product analytics can vary. For example, software product would typically include programming code that generates data on user behavior, application performance, and so forth. Meanwhile, many machines—everything from fitness trackers to vehicles to appliances—are embedded with sensors than can similarly transmit data for product analytics purposes. Such data-driven marketing insights help with planning new products and with devising new campaign messaging to encourage perviously unpredicted product uses.

Product analytics helps ensure a data-driven approach to product development and product management. Without product analytics, it would be much more difficult to understand how people actually interact with a product. Rather than relying on purely anecdotal evidence or assumptions, product analytics brings the disciplines of big data and data-driven decision-making to product management. This enables product managers to conduct ongoing evaluation and optimization of a product portfolio, including SWOT analysis and competitive product analysis.