Behavioral data: what they are, their meaning, types and examples

The use of Behavioral data enables diverse teams of marketers, developers and engineers to create engaging content, interesting products and unique customer experiences that directly address customers' purchasing needs.

Companies use the proven method of observing customer behavior to gain insights into consumer purchasing behavior. Understanding your target audience is crucial to increasing conversion rates, engagement, and customer retention in your business.

In this article we explain what behavioral data is, how important it is and what examples there are.

What is behavioral data?

Behavioral data paints a clear picture of your business by describing interactions with customers, partners, and their applications and systems.

This information can come from your digital and physical assets, including your website, applications, IoT devices, infrastructure, applications, CRM, and more.

For each customer encounter, a customer journey is created by linking entities and properties together. Beyond the “what” and “how,” you need to leverage these to improve conversion, engagement, and retention for your business. This is about how a customer interacts with your company.

When you have access to data about customer behavior, you can examine the “why” of customer activity.

For example, why does a customer look longingly at a certain product but not buy it?

A “customer” in behavioral data can be an individual buyer, a company, or someone buying on behalf of the company. Here's the important information: Whether it's a known or unknown person, it's always connected to a single end user.

The importance of behavioral data

Your behavioral data will become more valuable as your organization moves to digital. They are generated through website visits, product views, purchases, content downloads, newsletter subscriptions and other user interactions.

Websites, mobile applications, CRM platforms, marketing automation platforms and help desks are the main sources of behavioral data in digital businesses.

Better data

Behavioral data helps you understand individual customers, which strengthens your business. By combining data from your website, apps and devices with company data, you can transform your marketing efforts and personalized suggestions. Here's how you can use this data to personalize visitors' and customers' experiences.

Better analytics

Using a survey tool like QuestionPro for in-depth analysis and feedback is the first step to providing your customers with a personalized experience. This tool allows analysts to collect raw data in dashboards, charts, and visualizations through surveys to further explore your data and insights.

Better Choices

With behavioral data in a pipeline, decision making can be improved. Based on business rules, some brands try to identify a target audience of visitors who will add a specific item to their shopping cart.

Big data helps these companies assess each individual's interests and intentions. The previous behavior of website visitors serves as the basis for their forecasts. This is how a global technology company creates models that predict which visitors would buy a specific product and adds them to a targeted campaign.

Better actions

Enabling these options for your customers at the right stage of their journey based on the types of items they are looking at, in what order, and which products they want to purchase is the ultimate value of behavioral data.

Types and examples of behavioral data

Companies can only use data extracted from existing SaaS solutions to leverage customer behavior for data and analytics applications. Find out how:

Extracting behavioral data

Data from various SaaS products is extracted to uncover behavioral data. Therefore, they contain different levels of aggregation, unique SaaS logic, and varying levels of quality and integrity.

The result is that when this data is extracted from its source, it is used in ways that were not intended.

An example would be combining Salesforce data with Google Analytics pageview data, which is primarily intended for visualization in the Google interface to provide a complete picture of reader behavior. It is necessary to separate the logic and internal structures of the two data sets before combining them.

Creation of behavioral data

You wouldn't use generic prose to explain your product to your customers, so why would you use generic data to describe the user journey? One size does not fit all.

Data creation is the future. It's about intentionally creating behavioral data for any data product. Your company can customize each metric. Predefined session lengths and naming conventions are not included in the data. Contextual entities/properties of your event can be included in the data.

Conclusion

Behavioral data is a valuable resource that shows the connections between actions, interactions, engagement, intentions and outcomes. They can be very broad or general, but also analyse increasingly specific characteristics of users and events.

Companies and organizations should be cautious about drawing few conclusions from their behavioral data or making too many claims. When the data is used to train systems such as ML models, user characteristics must be carefully examined to avoid discrimination and other forms of bias.

The functions of QuestionPro go far beyond those of a simple survey program. We have a solution for every area of ​​the economy and every problem. We also offer tools for data management, such as Insights Hub, our research repository.

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KEYWORDS OF THIS BLOG POST

Customer Experience Mapping | Customer Experience  | Mapping