What is Customer Experience Analytics & How It Can Improve Your E-comm Strategy

What is Customer Experience Analytics & How It Can Improve Your E-comm Strategy

Elena Doynova

Apr 24, 2023 • 7 min read

What is Customer Experience Analytics & How It Can Improve Your Product Strategy

When was the last time you had a memorable customer experience? Chances are, quite recently. Many businesses are upping their game in this department by challenging the existing narratives and creating deeper and more meaningful interactions with their customers – both in stores and online. To do that, they need to know their customer base intimately without being creepy and know how to use that knowledge to craft customer experiences to write home about. In this article, we will discover the art of customer experience analytics and why it can be beneficial to e-commerce managers who wish to improve their stores in meaningful ways.

What is customer experience analytics?

Customer experience (CX) analytics is the process of collecting and analyzing data to better understand customers’ needs and experiences with your products or services. By gathering data from various touchpoints like social media, customer feedback, UX analysis, and contact centers, you can improve engagement, loyalty, and overall satisfaction, thus driving better adoption and retention. CX analytics as a process also helps you to identify issues that are impacting store or product performance, allowing you to take action and improve the entire customer journey.

Good data is key to providing an improved customer experience. With the right customer insights, you can make informed decisions to improve specific parts of the journey that you identify as weak links. For example, you might enhance your checkout experience by adding a new payment option or providing more detailed training materials for your support team. By using customer experience analytics (CX analytics) to guide your decisions, you can make improvements that will benefit both your customers and your bottom line in the long run.

How does it work?

What is customer experience analytics?

CX analytics encompasses a large range of CX data points. These may include:

  • Your customer support team: chats, calls, and emails
  • Customer surveys
  • Quantitative data from web, product, and UX analytics tools
  • Session recording visualizations
  • Social media analytics

The more data points you have – the better. But all the more difficult to process the data and uncover the trends. To assist you in this, digital analytics platforms like SessionStack combine quantitative and qualitative data. What this means is that you have all the right tools to conduct customer research in one package. 

One of the most important parts of the process is analyzing the results that the analytics tools give you. This means parsing through the data and unifying it in a meaningful way. To give you an example of how gargantuan this task may be, just imagine a conglomerate like LVMH trying to summarize its data points from offline and online channels for multiple brands in one segment at the same time. Sounds scary, right? 

While LVMH may have a whole department of data analysts, in smaller companies the task of analyzing customer interactions falls on the shoulders of a single team member – the customer success manager, the digital marketing manager, or the e-commerce manager. To be able to generate meaningful insights for their organization (and not go crazy), they need to have a robust strategy in place.

Why does customer experience analytics matter to e-comm managers?

As an e-comm manager, some of your main goals are to make sure the store answers its customers’ needs perfectly, gets visitors from browsing to purchasing, and generates value (and revenue) consistently. Customer experience analytics can be mapped onto all of these and beyond by telling you how you can actually achieve your goals. Here are four ways in which CX analysis can help you improve the e-store development and design process:

1. Identifying common areas of confusion in the user journey to prevent bottlenecks

Sifting through user reviews can give you a bird’s eye view of the common threads – what customers needed (real-life examples to back up your buyer persona), why they loved your store (prompting marketing to focus on these areas), and what aspects they didn’t enjoy (urging you to come up with engineering improvements to reduce drop-offs).

2. Understanding how users interact with different features and functionalities to bolster conversion rates

Using quantitative data, segmenting it wisely, and mapping it on funnels can paint a pretty good picture of how users interact with your product or a specific feature. This can be done at any point and it’s advisable to do it regularly. What you get at the end of this exercise is a map of the user journey with the weakest links in plain sight.

3. Gaining insights into user preferences and behaviors to inform feature prioritization

Carefully crafted customer surveys and takeaways from contact center communication are precious pieces of information that can drive your product improvement strategy. Unlike quantitative data, this type of qualitative data gives you an insight into what’s most important to your customers, what are the critical areas where your e-store design is failing them, and how they expect it to work for them to feel satisfied.

4. Measuring the impact of design changes or feature updates on user satisfaction and engagement

Iterating on an existing store module is always an event that causes trepidation in the e-comm manager’s heart. Will the improvement drive better conversion rates? Will visitors learn how to use it quickly enough? To answer these questions, the good ol’ combination of quantitative and qualitative data is necessary. This time, make sure to have a benchmark – measure traffic by channel, engagement rate, and conversion rate before and after the changes so that you know how this round of improvements went.

What are some examples of customer experience analytics tools?

As we already mentioned, CX analytics tools may vary greatly depending on the needs of every organization. While this classification is by no means definitive, it can give you a feel of the industry and what to expect when researching analytics tools. 

  • Digital Experience and UX analytics tools (like SessionStack)

UX analytics tools provide a comprehensive set of visual data you will need in your evaluation of the strategy you have created. This set records user sessions and includes visualizations like session replay, heatmaps and click maps, event logs, funnels, and more. With them, you can recreate customer experiences and literally see where they stumbled across a usability issue or a bug. A tell-tale sign of a user who is not happy with your product is also frustration signals such as rage clicks. 

  • Core web analytics tools (like Google Analytics)

Core web analytics tools give you a vast amount of quantitative data on the website or mobile app level organized into dashboards with the ability to segment users. This helps analyze data at scale and is the first step toward a data-driven assumption. Examples of the metrics you can get from these tools include session duration, bounce rate, geolocation, demographic data, etc.

Unlike core web analytics tools, product analytics tools provide quantitative data on the product level, thus getting you one level deeper into the problems your customers are facing. Examples of the data you can get from these tools include daily active users, churn rate, monthly recurring revenue, customer lifetime value, etc.

  • Customer survey tools (like Typeform)

This set of tools occupies a special place in every CX specialist’s heart. With the help of Likert-type questions, open-ended questions, and rating surveys CX teams can put a numerical value on something as subjective as how much their customers like their products, as well as capture user sentiments and define priorities for the improvement strategy. Examples of the quantitative metrics you can get from this type of tools include Net Promoter Score (NPS), Customer Satisfaction Score (CSAT), and Customer Effort Score (CES). 

How can product managers and e-comm managers use customer experience analytics?

What is customer experience analytics: PM's checklist

If you’re looking for the part that says “Best Practices” – here it is:

1. Define clear goals

What are you hoping to achieve with your analysis? What metrics are you tracking? Having a clear sense of what you’re trying to accomplish will help guide your analysis and ensure that you’re focusing on the right areas (hint: your North Star goal should always be the driving force). Learn more about setting goals here 👉

2. Collect data from multiple sources

In the section above, we described four of the most common analytics types you can use; there are even more. By collecting data from multiple touchpoints, you can gain a more complete picture of the customer experience.

3. Monitor customer feedback in real-time

Using analytics tools is essentially a retroactive approach to making assumptions about customer experiences. To complement it, consider using tools like chatbots or sentiment analysis software to automatically monitor customer feedback and respond to issues as they arise.

4. Act on insights

Nothing in this complex process of CX analysis will matter if it doesn’t lead to weaving your findings in the product development process. Make sure that your analysis leads to concrete action, whether that’s updating your product design, improving your customer service, or addressing specific pain points in the customer journey with new features.

Finding valuable insights is tough, though. This is why we built SessionStackAI to deliver them right to your desktop. In the next section we will discuss all the data that goes into the magic potion…

How to get started with CX analytics?

The fun part begins here! Let us introduce you to SessionStack – the all-in-one digital analytics platform that will help you gather (most of) the data you need to conduct your first customer experience analysis.

SessionStack Dashboards

What’s included:

  • Trends Dashboard: so you can see in real time an overview of your active users, spot arising problems with a breakdown of rage and dead clicks, and get a glimpse into the most clicked elements.
  • User Segmentation: segment by user, session, and event attributes to get a clearer picture of product usage and act on the findings to better cater to your users’ pain points.
  • Funnels: build funnels of varying complexity, even retroactively, to spot drop-offs and major conversion opportunities.
  • Session Replay: grab a cuppa and watch a few sessions to catch a glimpse of how bugs materialize. Assist customers with a better understanding of what really happened to them. Then send the problematic sessions to your engineering team for resolution. 
  • Machine Learning and generative AI: we are boosting our best-in-class session recording software with machine learning and artificial intelligence. The first vertical that we will cover is e-commerce – and if you’re interested in becoming an early adopter…

To put it in a nutshell…

Customer experience (CX) analytics involves the collection and analysis of data to understand customers’ needs and journeys with your products or services. By gathering data from various touchpoints, CX analytics helps to improve customer engagement, loyalty, and overall satisfaction. CX analytics matters to product and e-commerce managers because it can help them improve the development and design processes by identifying common pain points or areas of confusion in the user journey, understanding how users interact with different features and functionalities, and gaining insights into preferences and customer behavior to inform feature prioritization.

See what SessionStackAI can do for your business