Today’s pace of life and how things actually work in the sphere of economics imposes the need to develop tools and techniques to analyze the market and customer experience. Companies of all types and sizes invest in identifying and tracking superior customer experience (CX), and the end goal certainly is to gain advantages.

Yet as leaders are constantly in the race for a precise and comprehensive picture of customer preferences and behaviors, they have no choice but to rely on senescent survey-based measurement systems, which are the foundation of CX efforts.

These systems efficiently track CX performance through various strategic surveys, and the resulting metrics can provide directions about employee bonuses, decision-making processes, and strategic investment decisions. Still, the survey-based measurement systems fail to meet the business’s CX needs entirely.

Several leading companies from different industries, like Tesla, Spotify, and DeepMind, are developing an improved approach to take full advantage of the available data. Businesses regularly and lawfully collect user interaction data from their customers, thus yielding detailed insights about financial and operations systems and customer preferences. The advanced data usage for analysis purposes can help businesses understand customer interactions and opportunities, anticipate behaviors, and identify CX issues in real-time.        

What Is Customer Experience Analytics?

Customer experience analytics (also known as CX analytics) is a method for gathering all data about customer engagement with a particular product to find and eliminate product friction and customer experience gaps.

This analysis measures whether the product or service meets or exceeds customer expectations, which helps companies to boost product growth and improve customer experience. Customer data includes all kinds of customer interactions: phone support, social media interaction, e-commerce, web chat, e-mails, and reviews of different platforms. When used appropriately, these insights help businesses develop a deep understanding of the customer journey.

CX analytics helps improve your products and services by relying on actual experiences rather than making assumptions and speculations. Data-driven actions have a significantly greater likelihood of positively impacting the ultimate business goal.  

Customer Experience: Turning Insights Into Action

Customer experience data is crucial to businesses. Still, according to Alchemer 2021 report, performed by Forrester Consulting to determine the effectiveness of Customer Experience (CX) and Voice of the Customer (VoC), there is a considerable gap between desired outcomes and reality. Namely, only 25% of respondents reported that their organizations effectively address customer feedback, meaning that lack of integration of CX experience in all organization’s aspects hinders performance.  

Daily, companies and their employees tend to align CX initiatives with business results, but not so rarely measuring customer experience, and interpreting CX data is arduous. Turning customer feedback channels into business insight and action generation is the real ‘sticky wicket.’  

Structured data is easy to use, but on the other side, lots of untapped business-critical insights are buried in unstructured data. According to an Accenture report, 80% of enterprise data is unstructured, including e-mails, résumés, images, recordings, videos, text files, PowerPoint presentations, and social media posts. Such type of data is exceptionally difficult to process and use. Companies and organizations aren’t failing to collect data; there is more than enough collected data. The issue is to draw actionable insights with a specific application.  

Most companies need help to improve the customer experience and generate revenues precisely because of this issue. Luckily, there is an operative and productive process to collect, analyze and use CX data to improve overall customer experience.

Why Should Businesses Care About CX Analytics?

Creating a business structure that puts CX at the leading edge in the company is the most effective way to understand current customers, bring in new customers and associates, and build loyalty. CX analysis is linked with customer engagement and purchasing. By analyzing collected data, businesses get actionable, measurable, and in the long term, profitable insights.

Customer experience analytics perforates every business segment, including marketing, sales, and customer retention. CX analysis shows beyond doubt the importance of marketing strategies and ensures that the company meets customers on the proper channels. CX analytics pinpoint customer satisfaction, engagement, and purchasing habits, and predictive analytics point in the direction of decisions that get results.   

How to collect CX analytics?

One of the key aspects of making successful customer experience analytics is gathering qualitative data. Instead of analyzing metrics and numbers, quantitative data can be explained as the quality of service or customer experience the company received. In other words, this type of data offers perspective about how customers feel about the brand.  

Set Goal for CX Analysis

In order to make data-driven decisions with the intention of performing CX analysis, it is of utmost importance to set a clear goal. This goal will navigate additional processes and help the company to determine and track metrics to achieve it.

Determining the type of CX data and insights the business needs will help further processes. For example, some businesses must successfully determine friction points in customer interactions, increase conversion rates, and forecast customer needs. The next step is creating a personalized and improved customer experience based on existing data.

Surveys and market research are effective but expensive methods of determining future steps. Instead of investing resources in preliminary research and filtering the results according to business needs, focusing on CX data collected from customer interactions across various channels is more efficacious. Gathering insights that are entirely related to the specific business is methodical, time-saving, and cost-effective, unlike new surveys and market research groups that are closely linked but not entirely. The difference is analyzing data from actual customers, test groups, and survey respondents.  

Identify All Channels Your Customers Use

The step that follows after setting the goal for CX analytics is identifying all channels where customers interact with the specific brand. It is essential to include both direct and indirect channels. The most common direct channels are:

• Calls
• chats 
• e-mails 
• SMS 
• surveys 
• web forms 
• reviews on-site.

The most popular indirect avenues that customers use to engage with brands include:

• social media 
• blogs 
• comment boards 
• employee feedback 
• third-party reviews.

Some companies have more, fewer or different channels, but regardless of where the data comes from, it is essential to focus on aggregating data from as many channels as possible. At this point, a comprehensive view of a single channel will provide a limited picture of the customer. Therefore, creating a holistic view of the customer and considering every channel is critical.

Generally speaking, phone, chat, and social media interactions offer a large amount of data but also are accessible and popular. However, that doesn’t mean other channels should be ignored. Different customers could use various channels differently and provide different insights. Differences between customer experiences and variety in customer journeys are the coalescence that takes CX to the next, higher level.

Sometimes the most important and influential customers are not necessarily noisy and might even interact with the business through an obscure channel that was previously not considered.

Aggregate Data From All Channels

After discussing the importance of gathering actionable data across all customer engagement channels, the next step is to explain how to collect and organize the CX data.

Manually pulling insights from each channel individually is ineffective and time-consuming. Also, it requires extensive experience in each channel. Even after collecting data, it is hard to analyze since there is a vast diversity of unstructured data from different channels. For instance, data collected from live chat will differ from the format of information from blogs, and the previous data format will differ from social media interaction data.   

How to Analyze CX Data

After collecting the data, the next step is to start analyzing it. When we talk about all the gathered data from all possible customer interactions and different channels, it should be considered that it is sizeable. Progress will be achieved only if the data is analyzed with an appropriate approach. The most important course of action is objectively and subjectively obtaining insights while keeping the ultimate business goal in mind.     

Prioritize the Most Commonly Used Channels

Looking at the mountain of data collected from all channels may be overwhelming, especially if the business is a newcomer to CX analytics. Therefore, it would be most effective to prioritize channels where the brand receives the most interactions. Whether it is social media, e-mails, or web chat, the area with the highest frequency of interactions should be the starting point. Ultimately, the idea is to analyze customer behavior from customer interactions with the brand.

Despite that, analysts should also pay attention to the rest of the channels. Choosing the most commonly used channel should be the only starting point, and, as mentioned before, tremendous success will be achieved solely if the other areas are examined. The CX analysis will be comprehensive and accurate when the brand collects more insights.     

Find Friction Points

CX friction points are obstacles that require consumers to make an unnecessary additional effort.

For example, the customer experience is the ease or difficulty with which it’s navigated. If there is any hurdle that stands between the customer and what they want, it might deter them from purchasing the product/ service. Steps that feel extra and unnecessary are just a few of the most common CX frictions, and the most common are:

• tiresome checkout process
• complicated phone menus
• bad inventor visibility
• minimal product content
• unclear delivery information
• lack of customer reviews
• poor site performance

Many companies create CX frictions without meaning to. Marketers offer a variety of on- and offline channels with the intention of providing digital and omnichannel environments. Still, it might be frustrating and confusing for customers to deal with different touchpoints.

Based on the interactions gathered from different channels, companies can identify what causes the friction points in the customer journey. A good approach for identifying as many friction points as possible is to analyze data by cohort. For example, looking for customer trends by channel, frequency of interaction, review scores, and a select group of customers with broken customer experience.

Spot Trends and Surface Insight With Metadata

For some businesses, friction points may not provide the desired results. Sometimes, the collected data must be analyzed from different angles and contexts.

Metadata or secondary data includes information about customer interactions that the primary analysis may not provide. This includes:

• purchase history
• clickstream data (web visits, engagement)
• CRM data (Customer Relationship Management)
• membership data
• marketing data.

Processing metadata will provide valuable insights even if it is analyzed in an unstructured form. From this type of data, companies can extract information about conservation, including keywords, topics, and sentiment, which is especially important for discovering current trends.

For example, if there are many mentions of the ‘return’ and ‘product name’ keywords in the conversations, the managing, product, and sales teams will be notified that certain items have quality issues, description or measurement inconsistencies, or improper warning labels. This will allow the company to take the affected products, create a script for customers, and improve overall effectiveness.   

Assemble Context for Issues

In the process of identifying areas of improvement in customer experience, it is critical to determine the root cause of each friction point. This step will enable the business to assemble context and determine the severity of the issue that needs a solution. By selecting the source and to what extent it impairs the business, companies can better understand how to approach and impact the problem.  

Not all friction points equally affect the business; therefore, it is crucial to make a stepwise selection of the points that reduce customer experience. It would be impossible to fix all problems at once. The best approach is to tackle the ‘quick wins’ before moving to the major obstacles.

Quantify the Impact of These Solutions

After implementing a solution for at least one issue, companies should take a step back and check the analytics used for identifying the issue. Questions that need answers are: has the situation improved? Is there a clear indication of why or why not?

The next step is to create solutions that directly address the friction points. The goal is to develop sustainable solutions with long-term impacts linked to business metrics. Also, it is crucial to produce measurable business outcomes and yield improvements in the Key Performance Indicator.

Direct feedback customer data (obtained from customers) include:

• Net Promoter Score (NPS): survey question that asks users to rate the likelihood that they would recommend a company/product/service to others on a scale of 1 to 10
• Customer Satisfaction (CSAT): measurement of how products/services supplied by a company meet or surpass customer expectations. CSAT is a key performance indicator for customer service and product quality in any business (100% fantastic – 0% terrible)
• Customer effort score (CES): a metric that measures the effort a customer needs to resolve a support issue, complete a transaction, or interact with the company on and offline
• Voice of the customer (VOC): a term that describes customers’ expectations, preferences, and aversions to products/services
• Customer Sentiment: a metric that refers to the overall sentiment of a customer toward a brand, including different emotions that customers go through while engaging with the brand (either positive or negative). This data is used to analyze interactions and represents where CX frictions happen   
• Customer responses on social media
• Text comments in customer feedback surveys.  

Indirect feedback customer data (collected from customer interactions but hasn’t been obtained directly from the customer) include:

• Average handle time (AHT): the amount of time it takes to help a customer in a call center. It is tracked by center software to measure efficiency
• Customer lifetime value: a metric that predicts the total amount of money a customer is expected to spend on products/services of the company during an average business relationship lifetime
• Average spend
• Customer churn rate: measurement for the rate at which customers stop doing business with the company over a certain period of time
• Customer renewal rate (also known as customer retention rate): percentage rate (%) at which customers extend their relationship with the company
• Voice and chat metadata, transcripts, and analysis
• Social listening
• Customer review monitoring.

Final solutions should be selected with the aim of impacting the KPIs directly. In other words, companies need improved customer satisfaction, higher net promoter scores, and reduced customer effort scores. Generally speaking, changes that tackle customer experience should improve the customer’s overall sentiment.

How to Use CX Analytics to Improve CX

Needless to say, the primary goal of customer experience analytics is the outcomes. When a business succeeds in improving customer experience, the company’s profit also increases. Several steps can be implemented for methodical and systematic customer journey improvement.   

Prioritize Issues Based on Revenue Impact

It is naïve to believe that all issues can be fixed simultaneously. In the process of improving customer experience, it is vital to prioritize problems and create a plan. Multiple weak points arranged by importance and urgency should be resolved, starting from the low-hanging fruits. Usually, issues that are fixed fast and easily have an immediate impact on revenue.

Additionally, implementing solutions that directly impact the company’s ultimate goal will give the CX program credibility. Sometimes, the brand needs modernizing and well-organized customer care, which will make the customer experience significantly better and may tackle more complex problems.      

Operate Transformation With Customer Behavior

Customers constantly interact with brands, and companies should pay close attention to their experience and value each opinion, whether it’s like or dislike. 

The success of any brand depends on customer preferences. Do they prefer communication via a particular channel (e-mails, live chat, social media)? Prioritize that channel. Do they prefer a specific website design? Use that particular design. Are they primarily interested in specific product/service types? Promote and extend the offer.

Not so rarely, customer needs and interests only partially align with the creator’s idea of that brand. Customer data helps companies better understand their customers and make them happy and satisfied. The power of CX solutions lies in the possibility of making changes without explicitly asking customers.

Create a Personalized Customer Experience

General customer preferences are essential for businesses of all sizes, but companies should also pay attention to understanding their particular unique tastes and preferences. Some customers expect to be treated as individuals and get personalized customer experiences rather than customer types or segments.

Small details, such as greeting customers by their name and dedicating time to understand what they want and need, customized content and relevant ads, show that the company cares about specific interests. The more customers feel welcomed and valued, the better the customer experience is.  

Forecast Customer Needs

A successful customer experience program is both proactive and reactive. Controlling the satiation with proactivity is equal to following what customers say about the company outside the brand interactions. The social listening solution combines CX insights with social listening to identify trends in conversations that occur across social media platforms. Any chatter about the product/service, the brand, the company or particular topic related to them, or even the competition, can provide crucial information about what customers like and dislike. This CX analysis can help predict what customers want and what to offer them.   

Customer Experience: Follow-up

Many companies devote effort and energy to achieving an ongoing relationship with their customers. It is essential to follow up and ensure that customers are still enjoying their experience, and through a customer journey, it is a good idea to ask for feedback through a survey. Indeed, it would be better to avoid annoying customers with too often requests for feedback and surveys. The key is to stay relevant without being burdensome.  

Differentiate Your Brand From Competitors

Customer experience analysis has one admittedly good quality of tracking competitor’s CX and the brand’s customer experience. This type of analysis can take a lot of time and effort to accomplish, so it would be feasible to perform it after developing a highly functioning customer experience program for the brand itself. Once the company has an effective CX program, tracking competition can yield additional valuable insights.

Perhaps competitors have creative inventions about something you still need to implement, and that detail might be what customers like. Or it might be something their customers would like to avoid, and you can also make improvements on your end. Sometimes the competitors may test products/ services, and you can see how customers like them without the need to try them yourself.

Regardless of the insights from the competitor analysis, you can make improvements or avoid mistakes. Staying on top of the competition means a better customer experience than theirs.   

The Most Significant Benefits of CX Analysis

Why analyze all that data? Undoubtedly for customer experience analysis purposes, companies need to collect a massive amount of data and analyze it to the smallest detail.

Some brands aim to reduce customer churn rate, while others want to improve online reviews for customer support. Regardless of the objective, analyzing CX data will help the company make decisions based on tangible information, including making staff schedules and new hires and selecting topics for further agent training. Some of the use case examples for customer experience analytics are:

Better Customer Insights

CX analytics provides sturdy and concrete facts about how customers perceive certain products/services and whether they like or dislike the brand. Making changes based on unadulterated opinions can help the company to improve the overall experience and distinguish itself from competitors.

Data analysis helps companies get into the core of problems. Even if there are minor issues, real-time customer insights will help the brand to provide a better customer experience.

Lower Customer Churn

Generally speaking, companies make CX analytics to get insights into where things aren’t going so well. When the brand has concrete information about what customers like and don’t like, managers can start the problem-solving process and better anticipate issues that might occur in the future.

Ultimately, CX analysis helps in preventing or minimizing customer churn, which occurs when customers repeatedly bump into the same issues. Frustration comes when they’re not getting the support they need.  

Effective and Efficient Agent Training

Training, constant improvement, and development of support agents’ teams are essential links to the chain of providing a good customer experience. Coaching and tutoring agents will lead to improved customer experience, and the virtuous cycle ends with achieving the ultimate business goal.

For example, analyzing the data for frequent keyword topics can help agent training. How? If the company employs many new agents without specific experience in a particular area, and customers lately ask the call agents to help them with repetitive keywords, the company can create an RTA (Real-time Assist) card. This customized sheet with notes will enable agents to help the customer with specific topics. Thus, there is no need to coach every call, and call agents will quickly get the information to answer customer questions promptly.

Increased Loyalty and Customer Retention

Regarding CX analysis, lower customer churn means higher retention and customer lifetime values. Customer loyalty, of course, is the end goal of any company.

Ups and downs are unavoidable, but good customer experience will help the company to patch up those problems and deliver excellent customer support.          

Who Benefits From Customer Experience Analytics? (Hint: Everyone!)

While customer experience analytics aims to provide better customer satisfaction and a more enjoyable experience, customer experience analytics solutions also boost the entire company’s performance, including employees working in the company.

Executives

Customer experience metrics, such as NPS and customer satisfaction, are great representations of what the brand offers. If analyzed properly, these metrics can pinpoint exact features, such as what types of products are missing and how the development roadmap should look. This enables high-level executives to make critical strategic decisions regarding marketing, sales, and product development based on CX analysis.

Chief Marketing Officers (CMOs)

CMOs, out of all C-suite executives, best understand how important it is to render a top-notch customer experience. Customer journey, especially customer experience, directly impacts marketing and business KPI.

CMOs are in charge of promoting comprehensive customer experience, including the company employees. Customer experience data is the main link in effectively managing customer satisfaction.

Contact Center Agents

CX analysis includes real-time reports, sentiment, and predictive analytics, which enables customer service call agents to make immediate decisions and recommendations based on concrete data reports.

How Does Analytics Improve Customer Experience? 

The best way to understand the current customers, bring new customers, and build loyalty is to create a culture that puts CX analytics at the forefront of the company. Customer experience has an unmediated connection with customer engagement and purchasing, and CX analytics provides actionable insights for creating strategies. With the help of customer experience analytics, companies can scan every aspect of their business, including sales, marketing, and customer retention. Moreover, CX analytics is critical for ensuring that the company meets customers on the proper channels. Unlike standard models based on broad metrics, CX analytics provides deep and valuable insights into customer satisfaction, engagement, and purchasing habits. 

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