User behavior analytics has the ability to provide real-time insights about the tendencies and inclinations of users navigating through any website or application. This helps businesses pinpoint and understand their target audience, learn what they want and why; and enables them to establish the best ways in which to offer their products/services. You can learn more about the basics of UBA here.

With the easy and rapid collection of raw data, a business, or anyone using UBA, is made aware of very intricate details about their users. These may include things like where a user swiped right or left, scrolled up or down, where they stopped to look for something, how long did they stay on that page, what was the exact step that made them log off, etc. This kind of information is termed “behavioral data”, and is largely used around the world today in strategies relating to product development and marketing, as well as website or application design. What should be noted, however, is that a user’s personal data is kept secure and most companies have specific policies to make sure that no harm can come to the user from a possible breach.

In this article, you will learn about all of the different ways you can benefit by incorporating user behavior analytics and its quantitative and qualitative results into the various areas of your company.

Tracking user behavior as they go through a company’s online spaces can have a big influence on the future developmental prospects of existing products, along with any potential new products or services that they may benefit from launching to their customer base. Studying the aggregated actions that users take, as well as the possible motivations behind them, can help you know about the demand of each service, and decide whether it is worth expanding on. Moreover, it takes into account every user’s experience with a product or service, and notes the step where most of them drop off, so the app or website can be made better and more user friendly.

Collecting behavioral data in this manner saves a company the hassle of asking their users for their individual feedbacks- which may be tainted or inaccurate, and the number of users willing to go through with it will be way lower than their total. Long story short, user behavior analytics is popular and efficient because it saves both time and money.

The use of UBA in creating better marketing strategies to target specific users and build customer loyalty, is of undeniable importance. With ever-evolving social trends dictating consumer behavior, companies can track any alterations in what their users will respond to, or like to see from a brand, without having to spend months researching and interviewing customers. It can also aid in attracting new customers, as well as gaining more trust and loyalty from the existing ones.

As people now prefer more personalized advertisements and marketing approaches, UBA is put in place to keep track of every user and suggest exactly what recommendations should be made to them when they visit any page on your website of software. It can also help in creating advertisement campaigns on social media, even on the same apps that provided user behavioral data in the first place.

In many ways, the incorporation of UBA has created harmony between the producers/developers and their users, with both parties benefitting in the end.

For companies starting out in the web or app development area, or for those looking to upgrade their online spaces to more modern, accessible ones- user behavior analysis is the way to go. Companies can track their own users’ interaction with their online spaces, or take big data from competitors, to analyze and draw conclusions about what users might want, think, or do.

The product team gets to create the entire mobile application or website around what the target audience needs or desires. The landing page, the drop-down menus, the side bars and the pop-ups; everything can be altered and adjusted according to the findings and insights of the UBA system. This gives a huge edge to businesses and drives more and more customers to the spaces they have created.

It has been established by now that a user behavior analytics system provides valuable information relating to user engagement, their value and retention, and the demographic and other details. Collectively, these help a company or business add or remove products, policies, designs, and features from their website or applications. The question then, is how exactly does UBA achieve this, and what are the methods of analysis being used by thousands of companies today?

This method is based on a linear progression of predetermined user actions; and present the number of users at each step of the ‘funnel’, with, for instance, the visiting page at the top and the purchase page at the bottom level. In this way, it depicts the exact weak area where the number of users drops off at the highest rate, and also allows the company to observe conversion paths of users to clients, every time they change something in their product or software.

User flow is a flow chart associated with every user, that depicts not just their identity, but every event that they cause to occur, or every step they take. It documents the whole journey taken by a user- to arrive at, or leave- a particular page or service feature. In other words, it observes the in and out flow of each user and provides a more detailed and personalized map to the company. In the designing or development phase, making user flows can help determine what actions the future target user is going to take. This shows a company how best to create the space needed for the user to perform those actions without the presence of hesitation or confusion at any step, in order to improve their experience.

Cohort or Segmental analysis is the ability of UBA to separate the user databases into segments or subsets, according to different parameters that group them together and set them apart. These can be demographic, for e.g. ‘users who are women over 20 years of age’, social, for e.g. ‘users who have graduated college’, or behavioral, for e.g. ‘users who immediately clicked on a pop-up product recommendation’, etc. The most commonly used cohort, though, is time specific. This is the type that deals with studying the number and characteristics of new sign ups and retained users, for whatever window of time we specify.

In separating and analyzing each cohort and observing the users present in it, a company can get valuable information about their clients and can profile them to adjust future strategies around their audience.

Clustering is the process of analyzing and finding patterns and repetitions in a large amount of unstructured data, to provide random and often overlooked user statistics using an artificially intelligent system. An example of this can be the discovery that a certain percentage of users regularly purchasing skincare products reported having parents or siblings who had gone through teenage acne. This method of analysis provides the company with an even more detailed picture of users or customers because we do not label the data before putting it through an AI-driven user behavior analysis system; and therefore the system is free to look for anything and everything that it deems to be part of a cluster.

An application of cluster analysis related to user experience and interface, is when the system is able to define and categorize users. From previously studied data and patterns, a clustering system can tell which users are about to be lost and which ones have been retained, for the time being.

These are only a few of the ways user behavior analytics is working to benefit companies and increasing their profits and user satisfaction rates. That is why, so many companies, big or small, call UBA their “secret weapon” for their products or services to do exceptionally well in the market.