Why Top Companies Track Customer Experience Analytics

Customer Experience Analytics

It’s no secret that customer experience (CX) can significantly influence your brand image, customer loyalty, and bottom line.  

And with customer experience analytics, you can better understand how to improve the customer experience. You’ll gain insights into the customer’s point of view, experience, and what pain points they face with your offerings. 

In this article, we’ll discuss the top 3 benefits of customer journey analytics and how to analyze customer experience. We’ll also highlight nine important customer experience metrics that you should track today.

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What is Customer Experience Analytics?

Customer experience analytics involves collecting and assessing customer journey data like: 

  • Frequency of purchasing. 
  • Customer ratings and reviews.
  • Feedback on social media sites, etc.

These digital analytics help you make data-backed decisions about improving the customer journey — from the first contact to after-sales support. It also allows you to discover any roadblocks that may be hampering the customer’s experience.

You can easily collect this data using various analytics tools that measure customer metrics like satisfaction, cart abandonment rate, etc.

But why can’t you just conduct customer surveys to gather this data?

While surveys are good for gaining certain customer insights, they may not be a potent management tool. 

Traditional surveys have four flaws:

  • Surveys provide a limited view of the customer’s experience since they sample only about 7% of a company’s customers.
  • They offer hindsight but can’t help you make real-time decisions needed to resolve customer problems quickly.
  • Surveys may not always portray the exact customer sentiment. 
  • They may be unfocused, and basing business decisions solely on them may not resolve the root cause of the problem.

That’s why you can utilize modern analytics to comprehensively evaluate the entire customer journey and obtain a deeper insight into their experience. 

3 Key Benefits of Using Customer Experience Analytics

Once you have the required data, you can create a customer experience plan to:

  • Increase customer acquisition.
  • Boost customer engagement.
  • Reduce customer churn.
  • Offer a personalized experience.
  • Enhance the bottom line.

But to understand how well your plan is performing, you need to leverage CX analytics.

These detailed analytics allow you to:

1. Understand Customer Satisfaction Levels

Detailed customer analytics can help you understand whether the customers enjoy your brand’s user experience.

It can give you valuable insight into the kind of experience they expect and how you can modify your product, services, customer support, etc., to make that happen. 

You can analyze customer experience metrics like CSAT, NPS, etc., to understand the satisfaction level of your patrons. And if you introduce new services, you can comprehensively analyze whether the customers appreciate them and find them effective. 

You can then evaluate how you can offer better services to your existing and potential customers and stay ahead of your competitors. 

2. Discover Customer Roadblocks

Even if you have the best product or service, there are bound to be certain pain points or obstacles. Using customer analytics data, you can easily discover these roadblocks and develop solutions to resolve them quickly.

For example, NPS enables you to identify customers who aren’t keen on recommending your brand to others. You can reach out to them, find out what went wrong for them, and try to rectify that concern and enhance their satisfaction.

Predictive analytics and machine learning algorithms can help you better understand the customer struggle and resolve issues quickly.

3. Make Informed Decisions

To ensure that your brand caters to almost every customer, you can’t just rely on anecdotes or presumptions. 

Your chances of success may increase significantly if you base your decisions on actual data

CX analytics connects customer behavior with concrete metrics to help you make informed business decisions. CX data obtained using metrics lets you understand what your customers expect for an enhanced engagement and increased retention.

4 Simple Steps for Analyzing Customer Experience

Here are four steps for collecting and analyzing customer experience data.

1. Determine your Ideal Customer Profile

Ideal customers are those that’ll benefit the most from your product/service and would keep coming back to your brand. These customers can be your most valuable asset and form the backbone of your customer base.

You can identify ideal customers by tracking website traffic, surveying customers, studying the existing customer base, etc. You can also use Voice of Customer tools, user sentiment, and text analytics to understand customer needs and check if they fit your criteria.

Knowing your target customers can help you better analyze their experiences and modify your customer experience management (marketing strategy, sales, or customer support) accordingly.

2. Map your Customer Journey

To effectively collect and analyze your CX data, you need to identify all customer contact points and map their entire journey.

These are points of the customer-brand contact, right from the first ad they see to the post-purchase communications. These include:

  • First website visit.
  • Point of consideration.
  • Point of sale.
  • Customer onboarding.
  • Product return or subscription withdrawal (if any.)

For example, if they don’t reach the ‘purchase’ stage, you should identify the factors that prevented the progress.

A single touchpoint can make or break the customer experience and loyalty. That’s why it’s important to collect and analyze customer data around these points.

3. Track Important Metrics 

Once you finish the preliminary steps, it’s essential to track and analyze crucial business metrics like CSAT, Conversions, etc., using advanced analytics tools.

With an analytics platform, you can also collect customer feedback using metrics like Net Promoter Score (NPS) or Customer Effort Score (CES) to get quantified data.

Additionally, you can use social listening tools to monitor how your brand is perceived on social media sites like Facebook, LinkedIn, etc., and gain actionable insights about the customer data.

4. Evaluate the Data and Make a Plan

And finally, you should evaluate all the customer data you’ve collected to see if you have a comprehensive understanding of your customers’ experience. 

Ensure that you have data from various data sources and compare them with each other. It can help you identify the strengths and weaknesses of your brand. This information can help you create a plan of action to prioritize the customer experience and propel your business.

For example, if your analytics highlight a relatively high cart abandonment rate, you can dive deeper into its reasons. You can then formulate strategies like offering coupons, freebies, etc., to encourage customers to complete their purchases.

If your analytics represent only a section of your customer base, then try and extrapolate the findings to all customers.

So which metrics are essential for CX analytics?

Let’s find out.

9 Important Customer Experience Metrics You Should Track

CX analytics involves significant amounts of data. 

That’s why you should track and analyze the right metrics so that you don’t get lost in numbers.

Let’s look at the most critical CX metrics that you should consider:

1. Customer Effort Score

Customer Effort Score measures the effort made by the customer to purchase and use your product or get their issues resolved.

You can collect this data by asking customers to rank their experience on a scale of Very Difficult (1) to Very Easy (7). 

Here’s the equation:

CES

On average, a CES score of 5 or more is good.

2. Customer Satisfaction Score

The Customer Satisfaction (CSAT) score is a KPI (Key Performance Indicator) that indicates how content your customers are with your brand as a whole, from product to customer support.

They can rate their feedback as very satisfied, satisfied, not satisfied, very unsatisfied.

Based on this, you can calculate the CSAT score using the following formula:

CSAT Score

The CSAT score is directly related to the NPS because the better the customer satisfaction, the more likely they’re to promote your brand.

3. Net Promoter Score

Net Promoter Score measures your customers’ willingness to promote your product or service to others.

Customers are asked their likelihood to recommend the brand on a scale of 1-10. Based on their response, they’re categorized as promoters (9-10), passives (7-8), and detractors (0-6).

You can use this classification to calculate your NPS as follows:

nps

NPS is a powerful indicator of other metrics like customer retention rate, customer lifetime value, etc., that are crucial for boosting your revenue.

4. Website Visit Metrics

It measures the number of times a single user visits your website. Generally, the more times a prospect visits, the more likely they are to make a purchase.

Bounce rate and Pages per Session are important components of this metric.

Bounce rate is the number of visitors who leave your website after visiting just one page. And the Pages per session metric shows the average number of pages your users visit before leaving the site. 

When any potential customer lands on your e-commerce site, they’re either in the purchasing or consideration stage of their journey. If they’ve arrived on the site by mistake or don’t find what they’re looking for, this will be evident from a high bounce rate. 

All these metrics are great indicators of your brand’s customer interaction.

5. Conversions

Conversions indicate the number of targeted people who purchase from your brand or complete the desired goal, like filling out a form.

For example, if your landing page asks the visitors to sign up for your weekly newsletter, the visitors who actually sign up are considered ‘conversions.’

Additionally, if you have a physical store or a call center, the purchases made in-store or over the phone are also regarded as conversions.

6. Social Listening

Social listening is a metric that measures the number of times a customer mentions your brand on social media and what they’re saying. 

Some customers may share their opinions about your brand on your brand’s social media pages and their friends or family on their personal pages. 

This metric tracks the number of mentions on various channels and whether they’re positive or negative. It also allows you to jump into a conversation to redress any grievances.

7. Checkout Abandonment Rate

This metric shows the percentage of online shoppers who add your products to their virtual shopping cart but abandon it before completing the transaction.

Also known as Cart Abandonment Rate, it can indicate dissatisfaction in the customers’ online experience. 

Here’s the formula:

Cart Abandonment rate

Some of the reasons for dissatisfaction may include pricing surprises during checkout, lack of trust in the website’s security, etc. 

8. Support Rate

Support rate measures the percentage of patrons who require customer support because their concerns couldn’t be resolved through the self-service options. The metric lets you analyze the type of support requests and their reasons.

You can then make decisions about improving your product, services, website, etc., to reduce the support requests.

9. Upsell Rate

This metric tells you the number of customers who continue their purchases with your brand or upgrade their package.

It allows you to analyze customer satisfaction and their trust in your brand.

Learn about the other Customer Experience Metrics that you can track for more comprehensive analytics.

Now various digital tools can help you measure and analyze these metrics with ease. 

Let’s look at the three main features such tools should have.

3 Essential Features of a Customer Experience Analytics Tool

CX analytics tools often come with multiple features. 

However, the following three are the most important ones:

1. Executive Dashboards

A CX analytics dashboard allows you to analyze and visualize valuable customer metrics. 

It summarizes all metrics and KPIs so that executives can easily understand them and make business decisions accordingly.

Companies that wish to use the CX data to holistically improve their CX strategy should ensure that their data analytics tool offers an easily customizable dashboard.

It can offer a bird’s eye view of customer experience so that the decision-making authorities can always have the big picture in front of them.

2. Single Location for all Customer Data

Today’s customers expect and prefer at least some level of personalization from a business. 

That’s why a customer experience analytics solution should allow you to collect and store all customer journey data in one place for quick access.

It lets marketers provide personalized content and real-time responses to enhance the customer experience and engagement.

3. Employee Performance Analytics

Customer experience depends to a large extent on the performance of your sales and marketing teams. That’s why you should opt for an analytics solution that also measures your staff performance using selected KPIs.

Your managers can then use this data for gamification and to improve individual performance.

For example, you can use the tool to understand your contact center agent’s performance concerning their Average Handle Time (AHT), Average Call Duration (ACD), etc. It can help you understand the root cause of customer dissatisfaction and take corrective action.

Additionally, you can also use a performance management tool like Time Doctor to track the time spent by your agents on calls and other tasks.

Wrap Up

Efficient analysis of the customer experience and the overall customer journey can be valuable for making data-backed business decisions.

You can easily collect the customer experience data and improve your business outcome using the steps and metrics we covered here.

Once you’re armed with accurate data, you can take the right steps to boost your business’s customer experience. 

 
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