Behavioural analytics examines the “what’s” and “how’s” of customer behavioural data to inform the “why’s” of customer behaviour. These critical day to day insights allow us to further optimize for conversion, engagement, and retention.
Data is the new currency of modern business. Everyone, in any industry, should be able to use behavioral analytics to drive their business. Marketers, product managers, and data analysts can begin to see their customers as people, not just data points when they begin to use behavioral analysis tools.
Behavioural analytics is crucial in optimizing your company’s conversion, engagement, and retention. With the right behavioural analytics tool, every member of your team should be able to gain the actionable insights they need to answer their own questions and leverage data in ways that didn’t seem possible before.
There are three main behavioral analysis tools involved in building a complete picture of your customer journey: segmentation analysis, funnel analysis, and cohort analysis. Each of these tools serves its own importance when examining users conversion, engagement and retention.
The segmentation helps you build out key KPIs and metrics, create custom calculations, and identify behavioural trends. For example, if you’re interested in tracking your user interactions or subscriptions, you can monitor each marketing source to track the number of subscriptions they bring in over time. This allows you to optimize your marketing channels by enhancing the ones that work and improving or removing ones that are less effective.
The Funnel tool is used to analyze conversion funnels, visualize multidimensional user journeys, and see what’s working and what’s not. Funnel analysis is a great way to examine user drop-off. For example, you could explore users who create an account, but then never go one to visit your blog page. This could help you optimize your site so that users are more clearly directed to your blog page.
Cohort analysis is used to analyze user retention over time to see what keeps users coming back. For example, you could analyze and group users who purchased items from one category and then came back to purchase a product from a different category. This allows you to build more accurate profiles of your users and their interests and needs.
Data analysts can use behavioral data to gain complex analytics without having to build complex SQL queries and analysis capabilities that are not available using SQL. This allows business users to devote more time to other projects and streamline their workflows. For example, if you’re looking to build a report on conversion time vs. new features, you can use create a conversion over time funnel and flag the dates when new features were rolled out.