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If you've ever wanted to know what consumers were thinking when they visited your website or interacted with your digital products, you're not alone.
The reasons why people visit or leave a website and make purchases vary significantly from one person to the next. As a result, it can be challenging to understand how your efforts impact your customers’ actions.
Luckily, there’s a way to glean valuable insights from user behavior. It’s called behavioral analytics. Let’s learn more.
Behavioral analytics is the collection and investigation of data from user actions on a digital product like a website, app, e-commerce store, game, social media platform, etc.
Tracking user actions as they navigate your site enables you to:
Determine whether they are engaged with your content
See if your interface is user-friendly
Understand what visuals grab the most attention
Normally, when two potential customers follow the same path and take drastically different actions at the point of purchase, you have little understanding of what went wrong.
That’s where behavioral analytics can help. It provides deeper insight into user actions to better understand what leads to their behavior.
Instead of guessing why a customer abandons a cart or makes a purchase, you can use hard data to understand specific behaviors.
Behavioral analytics requires you to use data to understand the actions of people who interact with your website, product, or other digital interface.
You'll need to use a platform or software designed to collect information about specific actions and segment the data.
You can analyze and monitor various behaviors, including:
Creating an account
Submitting a form
Adding an item to a shopping cart
Abandoning a shopping cart
Making a purchase
You can also track data from more subtle user actions, including:
Clicks and taps
Mouse movement
Scrolling
Sections where users spend the most and least time
The process begins with collecting user activity data based on your business goals and the information you hope to learn. You can use this data to divide users into groups based on their actions.
Once you've identified groups with specific behaviors, you can use various analytics techniques to extract deeper insights into different behaviors. The results can help you improve conversions, update your products, or otherwise meet your customers' needs.
Behavioral data documents what users do when they interact with your products. Performing specific tests to analyze the data helps you understand the why behind these actions.
For example, user actions just before they bounce or abandon a cart can reveal why they fail to convert.
Start by identifying the business goals you hope to achieve. This will help you use behavioral data effectively. You may want to increase conversions, define ways to upgrade your product, or reduce web page bounce rates.
These goals will inform what data you need to collect and how to segment users into groups based on their behavior.
Once you've established specific groups, you can run additional tests to identify the motivation behind their actions.
For example, you can see how far users scroll down a page to measure engagement. You can also see if they overlook important buttons that lead to completing a purchase.
Once you understand why users’ actions stray from your expectations, you can use the data to improve the user experience.
While behavioral analytics is a subset of business analytics, the terms are not interchangeable.
Business analytics uses statistical methods to analyze past data.
Example: Web analytics give you information about what types of customers visit your website at different times. It can even track the frequency of visits and time spent. However, it doesn't provide specific information about user actions during visits.
Behavioral analytics lets you draw more specific conclusions about user behavior by combining segmentation with event-tracking data.
Example: When Amazon suggests products you may like, these suggestions are based on your activity while on the site.
Just upload your customer research and ask your insights hub - like magic.
Try magic searchMeeting customer expectations means understanding what consumers want.
Behavioral analytics enables you to gather insight into what happens before users act unexpectedly during the customer journey.
With data supporting reasons behind behaviors, you can better understand customer preferences and properly address their pain points.
Behavioral analytics can help you make informed business decisions when you use it in targeted ways. These are just a few business benefits of behavioral analytics.
When users abandon a signup form or cart, they don’t complete the goal they set out to achieve. Behavioral analytics can help you identify barriers (such as unexpected shipping costs or a form with too many fields) that stop visitors from converting.
Behavioral analytics enables you to make business decisions based on how your customers are most likely to respond. You can use this data to inform page layouts, pricing, marketing efforts, product updates, and more.
Pinpointing customer pain points, areas of confusion, and bottlenecks during the customer journey allows you to make improvements to better meet the customer's needs.
Since companies can use behavioral analytics in many ways, multiple departments can work with the data to generate improvement.
These teams are most likely to benefit from behavioral analytics:
Behavioral analytics allows data analysts to compare user intent to actual results. Analysts can recommend actionable results by determining when and why customers act differently.
Over 70% of consumers expect businesses to provide personalized interactions. Segmenting target groups and tracking their behavior allows marketers to provide accurate personalized marketing, engaging more customers.
While browsing product pages may not signify intent to purchase, putting items in the cart typically does. With the right approach to behavioral analytics (such as user engagement and feedback), sales professionals can determine what's stopping users from taking action.
Behavioral analytics can help customer service teams learn more about customers' needs and pain points, helping them deliver personalized support.
Using data to run different tests and experiments provides deeper insight into what drives user activity. Depending on your business goals, you may use one or more of these methods:
Oversight of the entire customer journey can give you critical information about how you’re not meeting customer expectations.
A funnel analysis enables you to track and analyze each stage of the conversion process. It can identify hurdles and bottlenecks where users get stuck and are most likely to leave your site.
When the average e-commerce store loses over 75% of sales due to cart abandonment, identifying where dropoff occurs is essential for optimizing conversion rates.
As data creates a visual representation of the customer journey, you can also see positive aspects of the funnel that will most likely lead to a purchase.
The product pages that lead to the most purchases can help you optimize other pages or develop new products.
When you have an idea for a web page improvement or product upgrade, you can't peek into the future to see how your customers will respond. With split testing, you can do the next best thing.
A/B tests allow you to expose groups to different versions of the element you’re testing. The process can test hypotheses on various products with vastly different complexities.
To conduct A/B testing, create two versions of the element in question and randomly divide test subjects into groups that only see one version.
Collecting behavioral data to examine the actions of each group will provide insight into which version led to more conversions or higher satisfaction rates.
You can use A/B testing for something as simple as determining whether a different call-to-action (CTA) button leads to a higher conversion rate.
You could also use the method to determine whether an upgrade for a digital product is worth the cost of implementation.
Like A/B testing, audience segmentation requires you to divide your target audience into distinct groups. However, instead of dividing groups randomly, you'll use specific characteristics or behaviors to define each group.
You could divide shoppers into groups based on their purchase history: One group is repeat customers and another is shoppers who abandoned their carts.
Analyzing the different behaviors of these groups can uncover ways to reduce cart abandonment. Behavioral analysis can show you whether loyal customers are more engaged with the website or if they redeem coupons upon purchase.
If loyal shoppers frequently redeem discounts, welcoming new customers with an introductory offer might decrease cart abandonment rates.
Imagine if you could see the screen through users’ eyes while they interact with your products or web pages.
Session replay does just that. It shows you recordings of how the screen reacts to user behavior. You can see mouse movements, clicks, taps, and other actions to determine where users get stuck or frustrated.
For example, repeated clicking on a non-interactive element indicates that users can't find the active elements they need to get adequate information or make a purchase.
Activities like scrolling up and down or attempting and failing to open an interactive menu can provide insight into why pages have high levels of traffic but low conversion rates.
Customer feedback gives you the most specific information possible about customer behavior. Asking customers direct questions takes the guesswork out of the why behind specific actions.
Customer satisfaction surveys are a common business tool, but their data can be hard to use. Behavioral analytics can guide your use of surveys, providing more conclusive data targeted toward your business goals.
A two-question survey based on specific behaviors can be an excellent tool.
Example: A homepage survey that asks, "Did you find what you were looking for?" can have a second question based on the visitor's answer.
An answer of yes can have a follow-up like, "If you could change this page, what change(s) would you make?" An answer of no can simply ask, "What's missing?"
Similarly, a single-question survey based on user actions could launch when a visitor is about to leave your site without making a purchase.
Successful companies use behavioral analytics to anticipate customers' needs and adjust various elements to keep them happy.
Although you may not realize it, most companies you interact with use behavioral analytics to help you find products of interest and improve your customer experience.
Let’s look at a few examples.
Demographic data offers little information about viewer preferences. Netflix collects data regarding user actions on the platform to personalize each viewer’s experience.
When you click through an email to a store's sale page but fail to buy anything, the store notices. That’s why you get an email asking, "Didn't find what you were looking for?" and suggestions based on your past purchase behavior.
Amazon tracks user behavior through cookies to determine how often customers have viewed a particular product and if they browse related products together. They use this data to develop more attractive pricing strategies for potential buyers.
Behavioral analytics helps you collect and investigate data from users' actions, enabling you to determine their engagement with your offering. It’s a great way to see if your interface is user-friendly and understand what visuals grab the most attention.
Using hard data to understand behaviors takes the guesswork out of why a customer abandons a cart or makes a purchase. With behavioral analytics, you can extract deeper insights into different behaviors, improve conversions, and meet your customers' needs.
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