The biggest challenge for marketers is to achieve sustainable business growth despite high customer churn rates.
While businesses are always interested in increasing the number of potential customers and converting them into paying customers to drive business growth, they also have to strengthen their relationships with existing customers to stay ahead of the competition.
The main objective of any business professional is to acquire and retain customers. For this, he has to keep an eye on customer churn because as more customers exit the marketing funnel, the slower the company’s growth will be.
In other words, a company that cannot retain its customers cannot hope to expand. Hence, business professionals need to understand and measure their churn rates.
Generally, Companies use traditional data analytics tools to measure profit and loss.
These tools provide insights into customer pain points, such as issues with your product or lack of engagement, but they cannot identify signs that a customer is likely to leave your funnel until they have already churned. That is where Behavioral analytics can step in for predictive retention.
What do you mean by Behavioral analytics?
Behavioral analytics, or behavioral data analytics, is the method of measuring and analyzing consumer behavior to enhance your products and processes.
Moreover, it is primarily used in product management to ensure that a company’s offerings meet users' expectations.
The goal of using analytics is to measure the user experience, enabling you to make product changes that satisfy users more frequently.
Use behavioral modeling to acquire new customers >>> Read more
Why is behavioral analytics important for UX?
SaaS-based companies use behavioral analytics tools to focus on the latest trends and find out what features customers are interested in so that they can work around them.
It also involves using cookies to track customers’ journeys across multiple websites.
Behavior analytics in the retail industry has infinite possibilities. It involves identifying potential user challenges and removing guesswork, resulting in better business decision-making.
The goal behind this is to create a good user experience and build a strong base of satisfied customers.
Understanding customer behavior analytics is vital for capturing UX sentiment and identifying issues in the user journey to achieve higher conversion rates and drive more sales.
Let’s discuss how to use behavioral analytics further to improve the customer experience:
Determine clear goals
It is vital to set a goal if you intend to fulfill it. Later, you can develop a strategy that yields the desired results.
To improve your UX, you need to have the following questions in mind:
- Why are our landing pages not generating more conversions?
- What do customers say about our product or brand?
- What types of challenges do our users face when they start using our product?
- Why is our product experiencing a high churn rate? How can I reduce it?
Once you’ve established your end goals, you can devise a powerful strategy to achieve them.
Monitor various steps of the user journey
The customer journey isn't a single-step process, so you shouldn’t miss any of the steps. This way, you can take the user journey to the next level.
Use different plans and approaches
Use tactics such as A/B testing, heatmaps, session recordings, and customer feedback to understand user behavior from multiple angles.
This will help you gain valuable insights, enabling you to create better products for users.
Track the effectiveness of your actions
After making changes and improvements, use the Analytics tool to measure their effectiveness.
If you find the user experience is improving as expected, then you can look at other problematic areas and improve them.
Repeat the entire process
Improving the user experience is not a one-time job; it’s a continuous process that involves finding ways to build and nurture a loyal customer base through your product.
So, aim for creating a good UX for customers who want to use the product.
Why should companies use behavioral analytics?
Companies use customer behavioral analytics to understand what customers want from their products and how they interact with them.
They use behavioral analytics to monitor different actions of users, including:
- websites they visit
- time spent on websites
- clicks on a particular product or website
Simultaneously, it helps monitor the actions users take with your product, such as how often they purchase or share content on social media.
With behavioral data, companies can develop marketing strategies and plans to achieve better results. They can then use this information to delve deeper into customers' buying patterns, interests, and purchases to understand their needs better.
Behavior data can help in creating the following business goals for B2B, B2C, or SaaS companies:
- new customer acquisition
- user retention
- minimizing churns
Behavior data highlights when customers drop off and provides valuable insights to retain them and achieve expected results with the product.
The customer behavioral analytics tools offered by Express Analytics are compatible with many systems, deliver easy-to-use results, and allow marketers to integrate internal services such as CRM systems.
Our tool performs an in-depth analysis of customer data and generates automated visual representations to detect outliers and trends.
The next step will be to evaluate the predictions and make recommendations to enhance the user experience.
Different Stages of Behavioral Analytics
The behavioral analytics process has three essential stages. Let’s discuss them in brief:
Data collection: You can find plenty of data from different sources, but it’s impossible to list them all.
Whenever a client browses the internet, data is stored in cookie files and may be analyzed after recording.
Segmentation: This step involves grouping data into smaller chunks, which are then assigned to a few categories based on predefined criteria.
Segmentation may produce multiple outputs, as a single dataset can be processed in different ways.
Implementation: This step involves adjusting the advertisement's content based on the consumer’s needs, interests, and views using data.
The goal is to target the client individually and send him the correct information.
What are examples of behavioral data?
Different examples of behavioral data include newsletter sign-ups, social media likes or comments, new account creations on your website, contact form completions, app downloads, cart additions, and website views.
Behavioral data provides the best opportunity to understand your clients and boost your business.
Combining data from websites, social media, CRM systems, devices, and apps with enterprise data can reshape your marketing plans and also provide personalized suggestions.
This will help you use this information to customize users’ experiences.
Behavioral data not only includes positive actions toward a brand, but also negative actions such as order cancellations, email unsubscribes, removing items from the cart, and negative comments on social media.
It goes beyond customer demographics —such as location, age, job title, and gender —to understand their needs.
What are the different types of behavioral data?
Listed below are a few types of behavioral data:
First-party data: Collected through various sources, including your apps, website, social media, etc.
The problem with this is that if the customer leaves the platform, it’s impossible to track their data.
Second-party data: collected by another organization, i.e., trusted partners who share their audience insights with you.
Third-party data: Data obtained from a third-party source that sells customer information.
What are user behavior analytics tools?
User behavior analytics tools are designed to track and record user behavior across apps, websites, and other digital platforms. They assist in user segmentation by analyzing data such as cursor tracking, app analytics, search data, website analytics, user feedback, scrolling, navigation, clicks, and user experience.
The following are the best customer behavior analytics tools:
- A/B testing tools
- Voice of the Customer (VoC) and Feedback Tools
- Heatmap and session replay tools
How do you choose the right user behavioral analytics vendors?
Behavioral analytics solutions are compatible with various systems and deliver rapid results.
They enable the integration of products from desktop and mobile apps into internal services and help teams rapidly find answers through friendly interfaces.
Swapping out customer behavior analytics platforms can be time-consuming, so teams should conduct thorough research and invest in a platform that adds value.
Always choose the behavioral analytics tools which can have special features:
- Automatically capture customer and event data points.
- Access real-time data and query it in multiple ways.
- Pre-defined reports, including funnels, retention, and cohorts
How do I track user activity on a website?
The website provides multiple options for analyzing user activity, such as how they navigate, where they click and scroll, and when they leave.
Monitor how different design elements look and cross-verify to ensure a seamless experience across devices.
Don’t forget to compare the behavior of returning and first-time visitors.
This observation is vital for evaluating visitor engagement and retention rates.
For SaaS and eCommerce websites, conversion rate optimization plays a key role.
How to track user activity on an app?
You have to monitor user interactions with mobile apps and check for misclicks. You can fix this by adjusting the size and placement of CTA buttons.
Here, you can track which features users like most and decide which to remove, but keep in mind that your app should load faster.
How do you track product user behavior?
Product analytics helps you track feature usage and analyze which designs are getting better engagement. As a result, you can ask the product team to prepare a marketing plan that solves users’ queries.
This analysis improves retention rates, user experience, and churn rates.
Use behavioral modeling to acquire new customers >>> Read more
What are the benefits of user behavior analytics?
- Trends prediction
- Rapid innovation and development
- Intelligent business decision-making and effective marketing campaigns
- Better utilization of company resources
- increase in customer loyalty, satisfaction, and lifetime value
- increase in conversion rates
- Enhanced fraud detection
Disadvantages of behavioral analytics
- Every single step online is monitored and tracked.
- Don’t expect privacy online.
- Customers must agree to the data collection policies.
- Data collection is a harmful task.
Business applications of Behavioral analytics
Organizations that provide financial services use this concept to identify suspicious behavioral patterns and strengthen anti-fraud measures.
Simultaneously, they link both traffic patterns and demographic data to customer profiles to identify where to find ATMs and branches.
Retail industries use it to track customer journeys across channels, identifying which channels customers use for different transactions and how they respond to television ads, mobile couponing, and email campaigns.
Health insurance service providers have begun using this technique to understand better and improve customer satisfaction scores.
Also, hospitals and healthcare providers use it to minimize negative feedback, improve patient engagement, and protect patient data.
To remain competitive and achieve higher retention rates, the telecommunications industry must improve the customer experience.
For that, they use behavioral analytics tools to offer relevant discounts, craft personalized data packages, and run targeted advertising campaigns to retain customers.
Conclusion:
With advances in machine learning algorithms, behavioral analytics has become more useful. It is a never-ending process as businesses move forward; they have to continue maintaining a grasp of rapidly changing consumer demands, market trends, and how consumers’ actions and beliefs are influenced by external factors.