What is user analytics?
User analytics is the practice of measuring, analyzing, and reporting user data to improve the usability of a digital product. User analytics can be used to answer questions about how users interact with a product, what features they use most often, what errors they encounter, and more.
There are two common ways a product manager, customer success manager, or digital marketer can view user analytics data to start making decisions and taking action:
Segments: Segmenting the input data by user or account characteristics within a product analytics view that groups usage data into trends, funnels, and paths provide a more actionable set of insights than by features and pages alone. Segments can be defined by the user, usage events, and survey data.
Retention: By grouping user and usage data, companies can understand which cohorts find the product to be sticky—and which don’t.
What’s the value of user analytics?
User analytics is an essential tool for product managers. It helps them understand how people are using their product and identify areas for improvement. Additionally, user analytics can inform decisions about what features to build and where to focus your team’s efforts.
User analytics provide two main types of value for businesses: business insights and the opportunity to take action. Here’s a closer look at each:
User analytics has allowed companies to gain a deeper understanding of their customer base and segment it effectively. By creating dashboards that group and filter product interaction data, product teams can get a clear picture of how users interact with their products.
User analytics also provide the opportunity to further engage with specific user cohorts. By drawing from the web and mobile app interactions, businesses can send notifications, tutorials, offers, and guides to users to encourage them to keep using the product.
What are the use cases for user analytics?
User analytics refers to a company’s understanding and observation of its customer base to guide them to successful outcomes. Segmenting the customer base and user behaviors is an effective way to answer important questions that can help improve business results, such as:
-What early behaviors are likely signals that a customer will churn?
-Which profile characteristics contribute to feature retention?
-Why does a feature variation cause different user behaviors?
-How does customer vertical, device type, or referral channel affect outcomes?
-When did the most valuable cohorts of customers become users?
How did user analytics evolve?
User analytics have come a long way over the years. In the past, companies only had two basic ways of dividing their target market – broad-stroke demographic/firmographic data that gave a general overview of the target buyer, and surveys that are often biased and not very reliable.
Nowadays, user analytics have evolved to become much more sophisticated and accurate. Companies can now track user behavior data to get a clear picture of their target market, and they can also use AI-powered tools to segment their audiences more accurately. This has made it easier for companies to tailor their products and marketing campaigns to meet the needs of their target market, and it has also made it easier to track the performance of those campaigns.