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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 product managers who wish to improve their products in meaningful ways.
In this article...
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 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 customer service 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?
CX analytics encompasses a large range of CX data points. These may include:
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 or the product manager. To be able to generate meaningful insights for their organization (and not go crazy), they need to have a robust strategy in place.
As a product manager, your main goal is to make sure the product or service answers its customers’ needs perfectly, gets adopted quickly, 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 product development and design process:
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 product (prompting marketing to focus on these areas), and what aspects they didn’t enjoy (urging you to come up with engineering improvements to reduce customer churn).
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 but is especially useful during the period after launch when adoption is of crucial importance. What you get at the end of this exercise is a map of the user journey with the weakest links in plain sight.
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 product is failing them, and how they expect the product to work for them to feel satisfied.
Iterating on an existing feature is always an event that causes trepidation in the product manager’s heart. Will the improvement drive better adoption of the feature? Will users 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 adoption, retention rate, and satisfaction before and after the changes so that you know how this round of improvements went.
As we already mentioned, CX analytics tools may vary greatly depending on the needs of every organizations. 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.
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.
Curious to learn more about a (free) platform that unifies aspects of all of these types of CX analytics? Come this way >>
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 and 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.
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).
If you’re looking for the part that says “Best Practices” – here it is:
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 >>
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.
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.
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.
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. For free.
You can get started in a few minutes – the installation is quick and easy and doesn’t involve complex manual tagging. The forever free plan includes 1500 sessions and can be upgraded at any time, no strings attached.
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 managers because it can help them improve the product development and design process, such as 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.
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