Customer Experience Analytics For Digital Products

Customer experience analytics has become a hot topic in recent years. Businesses are looking for new ways to understand their customer's needs and wants, and CX analytics is one way they can do that.

Why is it so difficult to build a great digital product?

It's not because digital products are hard to build. It's harder than ever to understand if customers are actually liking the product and if we're making improvements that matter.

The problem is that with hundreds of thousands of users, testing a new feature can be costly, risky, and time-consuming.

There's typically a small handful of metrics you can use to determine if something is working: bounce rate, engagement score, conversion rate, signups, etc. But what if you could measure how every customer was interacting with your product in real-time? What if you knew exactly how every customer was feeling about using your product?

Most products have endless opportunities for improvement and the challenge is figuring out where to start. One way to do this is by using Customer Experience Analytics (CEA). CEA gives you the insights needed to make decisions that will drive more value for your customers and help increase sales. 

Definition – Customer Experience Analytics

Analytics is the study of data. In the context of Customer Experience (CX), it is used to measure the impact of a company's products and services in order to identify opportunities for improvement. Taken together, the techniques add up to a more nuanced view of customer behavior than ever before. For example, companies track how many customers submitted an inquiry but didn't follow up with a purchase, or how many people browse a product page but don't buy anything at all. Customer experience analytics can also help teams determine what factors influence a customer's loyalty, how likely they are to buy additional products and services, and how likely they are to refer their friends. These insights can help you identify the best ways to improve metrics like sales conversion rate and customer satisfaction. That kind of information also gives businesses the power to tailor their interactions with customers to get them to take—and hopefully complete—the action they want them to take.

Customer Experience Analytics Types

The term “customer experience analytics" may evoke visions of a dark, foreboding room with mysterious machines analyzing data but there are actually several different types of analytics that can be used together to help your team improve the customer experience. Here are five types of analytics and how they can help you create better experiences for customers:

  1. Customer acquisition analytics: This tells you where your customers are coming from and how you're getting more of them. For example, if you're using search engine marketing (SEM), then it's important to understand what keywords people are using to find your business online. This will help you improve your SEM campaigns.
  2. Customer behavior analytics: Customer behavior tells you what customers do on your website once they land there. For example, if most of your customers convert on a particular page of your website, it could be a good idea to test variations of that page to see if any offer even better conversion rates.
  3. Customer journey analytics: This gives a broader overview of how users move through your website or app and what they do when they get there. Journey analytics use tools such as heatmaps and scroll maps to give insight into how users interact with individual pages or sections of the site. 
  4. Customer segmentation analytics: Segmentation analytics helps companies categorize customers into groups based on specific characteristics such as age, sex, income level, purchase history, etc. This type of analysis allows businesses to formulate marketing strategies based on the characteristics of different groups of customers. For example, if your company sells golf equipment, segmentation analytics can be used to identify potential clients such as young men in their 20s who earn high incomes for targeted marketing campaigns.
  5. Customer sentiment analytics: Customer sentiment analytics is a set of techniques and tools for analyzing what customers are saying about your brand online. It helps you identify online conversations about your brand that have an impact on your bottom line. Sentiment analysis can give you accurate insights into how people feel about your offers, products, services, and news. By listening to what customers are saying, you can improve and optimize your marketing campaigns and increase customer satisfaction.

Role of Customer Experience Analytics In Building Awesome Digital Products

Customer experience analytics is a relatively new field, but it's one that's gaining traction quickly. 

Truly understanding your customer experience and how it can be improved is invaluable to your business. With the right information, you'll be able to create a better product for your customers, make them happier with engaging experiences, and ultimately earn their loyalty.

Here are three ways that customer experience analytics can help you build a better digital product:

1. It measures how customers really interact with your product through the actions that they take. Not everyone uses your product the same way. So the only way to understand what's working and what isn't is through data collection. By monitoring where people are dropping off or leaving certain aspects of your product, you'll be able to make changes in order to boost your product usage.

2. It helps you identify problem areas. If a certain feature or process isn't working well, customer experience analytics can help identify exactly where the problem lies so that you can make adjustments accordingly. For example, if a button isn't converting well, customer experience analytics will be able to tell you what percentage of people who click on the button actually complete a transaction. This allows you to tweak the color, text, or placement of the button for maximum conversion efficiency.

3. It helps you personalize user experiences. Truly understanding your customers' needs, wants and desires are crucial to providing them with a personalized experience. Analytics help you understand what your users like, where they go and what they're looking for. You can use the insights to turn every single interaction into an opportunity to wow them and make them feel special.

How Can AI Help In Customer Experience Analytics

Customer Experience Analytics (CEA) is the process of collecting, storing, analyzing, and taking action on customer data. Dealing with big data can be a huge challenge, since there are many different types of data, such as web metrics, social media insights, software logs, and more. All these data have to be analyzed to provide a complete picture of what your customers want. AI has been proven to be very successful in helping businesses make the right decisions with ease. It can easily crunch and analyze the massive amounts of data that is generated daily in any business.

Using AI for collecting data has several advantages: It is quicker, more accurate, and more comprehensive than human-generated data. For example, chatbots can be used to collect feedback on social media platforms. The chatbot can then be programmed to ask specific questions in a precise manner that will generate better responses.

The next step is to use AI tools to create predictive models based on historical data. By implementing machine learning techniques like neural networks and deep learning, it is possible to predict future trends based on previous analysis.

With AI, machine learning, and predictive analytics, CEA has become more powerful. It provides more granular and actionable insights into what customers want and expect. This enables a business to build better products for their customers which eventually helps them to retain customers and gain new ones through repeat business and recommendations from existing customers.

Advanced Customer Experience Analytics Tool – Qualetics 

Qualetics is an advanced customer experience analytics tool that helps businesses increase revenue and loyalty through a deep understanding of what customers are thinking and doing. Qualetics provides an all-in-one platform that enables organizations to make informed decisions about their customer experience by providing the following analytics in one platform –

  • Software Quality Analytics
  • Performance Analytics
  • Product Analytics
  • API Analytics
  • Business Analytics
  • AI-Based Insights
  • Embedded AI Features 

By combining advanced analytics with the power of an artificial intelligence engine, Qualetics provides a wide range of insights from simple to complex. It is a fully-featured analytics tool that provides a 360º view of your customers, allowing you to see all their interactions with your site from a single screen. You can set up and use Qualetics immediately, and it's scalable so that as your business grows, you can easily add more users and data sources.

Qualetics will help you answer questions like:

  • How do I find my best customers? Who are they and what are their characteristics?
  • How do my customers behave after they've left my app or website? Will they come back? When? How often?
  • Where are my greatest opportunities for growth? 
  • Where should I spend my marketing dollars? 
  • What features should I add to my product?

Customer analytics software

To know more about the Qualetics Customer Experience Analytics platform or book a demo click here.