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Behavioral Analytics

An accurate understanding of how users engage with your product is critical to improve the product experience. Behavioral analytics is an approach to study user behaviors and leverage behavioral data to drive business benefits.  

What is behavioral analytics?

Behavioral analytics studies user behavior within an app or a website. It is a remote research method, facilitated by software that captures user interactions. These can be everything your users do or the specific actions they take within your digital product. They include creating an account, clicking the ‘Help’ button, filtering products, specific page views, and others.

Importance of behavioral analytics

Recording and analyzing user activity generates important insights for SaaS product managers and marketing managers. If users aren’t using a particular feature of your app, it’s likely that they perceive it to be less useful to them. The product team can dig deeper to determine whether the feature can be improved upon or removed. The product marketing team can evaluate whether there is a need to improve user onboarding to provide greater clarity on the feature’s usefulness.

The data points can reveal user patterns that lead to churn or signal an opportune time for driving upsells or expansion MRR rate. You can categorize positive and negative user patterns along user journeys to improve the overall user experience.

How does behavioral analytics work?

You track user actions in web or app sessions over a period of time, and use the data to inform your app/website usage metrics. For this, you can use one of several behavioral analytics tools that capture customer experiences within digital products. The quantitative data from multiple users can be analyzed alongside the qualitative experiences, that is, what users did on screen.

Some popular behavioral analytics solutions are Mixpanel, Heap, Amplitude, Toplyne, and Userpilot. Features you can leverage include real-time user tracking, machine-learning driven quantitative and qualitative data analytics, ability to set up custom events and user segments, and reporting and analysis.

Types of behavioral analyses

Behavioral analytics is of three types: funnel, segmentation, and A/B testing.

Funnel analysis helps identify bottlenecks in the customer journey so they can be solved to improve conversions. A behavioral analytics platform offering segmentation analytics allows you to capture the behaviors of various user segments. In A/B testing you record how users interact with different versions of the same thing, such as your landing page or home page, and see which changes lead to the best outcomes.

Use behavioral analytics to hit your metrics

User or customer data can be put to use in improving engagement, conversion rates, customer lifetime value, retention, and revenue. A great user experience with your app, for example, can help shorten the lengthy SaaS sales cycle and create loyal customers. The user data may indicate that your customers will be well-served by new features or integrations, which can also help attract more subscribers or upgrades.

An aggregation of website sessions data can be combined with other insights to identify where and why potential customers drop-off. This real-world data can also help optimize experiences at various touchpoints, and inform your other KPIs and marketing campaigns.

User behavior analytics is a growth driver for SaaS and eCommerce businesses alike. The choice of tool is key to maximizing benefits from user behaviors. If you’re aiming for product-led growth, use Toplyne’s behavioral AI engine, which combines product analytics, CRM, and billing with third-party enrichment data to find the right account to target. eCommerce businesses should look at A/B experimentation tools like Google Optimize and AB Tasty.