SEPTEMBER 2023 RELEASES
September 2023 Releases
Measuring Customer Experience: Proven Strategies to Assess and Enhance CX
Oh hey, there’s your old friend churn, knocking at the door again… And again. And again.
Maybe you’re not surprised that churn is there, but you’re not exactly sure why.
Chances are, there’s a gap in how you’re measuring customer experience. Somewhere, there’s a disconnect. But that’s okay.
We’re going to run through some pointers on how you can better connect your data, your systems, and testing—and in the process, drive better connections with your customers—in a way that drives real revenue impact.
We’ll break down what the best CX teams are doing to incorporate AI, track every interaction, A/B test, and centralize their analytics to prove customer experience ROI and gain deeper insights.
Why Measuring Customer Experience Matters
Your customer experience is the single most important driver of customer lifetime value. Plain and simple.
In high consideration industries like Healthcare, Insurance, Education, Legal, and Home Services, a single poor experience can mean a lost customer. Add these experiences up over time, and you’re left with millions in unrealized revenue.
“Unrealized” revenue is ultimately the point…
If you’re measuring your customer experience down to each and every interaction, you’ll be able to realize where revenue is being gained and lost. That insight will help you drive change to minimize poor experiences and make positive outcomes repeatable and scalable.
All of this is especially true as AI picks up more and more share of outreach across contact centers. If you’re using AI agents and not measuring every interaction, you’re wasting the value of AI.
Why’s that the case?
- The volume of your outreach will naturally increase, i.e. more opportunity for improvement.
- As AI agents handle more of your routine tasks, there are more measurable data points available, i.e. way more insights for you to build off of.
So, in short, customer experience is the biggest proof point and driver of revenue that you have. So why the hell would you not measure it as granularly as you could?
Key Metrics for Measuring Customer Experience
Not only does AI-driven outreach introduce more data points to measure, it makes real-time analytics more widely available, across all of your customer touchpoints.
So, while you’ll obviously continue tracking to traditional CX metrics, you’ll also want to make sure you layer in more micro-observations that signal whether or not your customers like you…
The Baseline Customer Experience Metrics
The goals you ultimately track to. The numbers that your CEO cares about.
- Net Promoter Score (NPS) – Measures loyalty and likelihood of referrals.
- Customer Satisfaction Score (CSAT) – Captures immediate satisfaction post-interaction.
- Customer Effort Score (CES) – Evaluates the ease of completing a customer action.
- Churn Rate – Tracks the percentage of customers who stop engaging over time.
- Customer Lifetime Value (CLV) – Predicts the long-term revenue impact of a customer.
AI-Powered Customer Experience Metrics
Where measurement gets smarter. Where you can spotlight the day-to-day in real-time and take the small steps that influence better baseline metric performance.
- Sentiment Analysis Scores – AI-driven sentiment tracking evaluates tone, emotion, and language in calls, chats, and emails, helping detect frustration before it escalates.
- Real-Time Call Analytics (Talk Time, Silence, Interruption Rate) – AI assesses talk-to-listen ratios, agent interruptions, and dead air time to identify if conversations are flowing naturally.
- First Contact Resolution (FCR) with AI Context Awareness – Measures how often issues are resolved on the first attempt, factoring in AI-assisted responses vs. human-only resolution rates.
- Intent Recognition Accuracy – Evaluates how effectively AI detects customer needs and next-best actions in conversations, helping refine automation accuracy.
- Proactive vs. Reactive Issue Resolution – Tracks how often AI or agents prevent issues (via predictive analytics) vs. how often customers must initiate contact.
- Personalization Score – Measures how tailored an interaction feels to the customer by analyzing past interactions, AI-driven personalization, and real-time contextual adjustments.
- Escalation Rate & AI-Human Handoff Efficiency – Tracks when and why AI agents escalate to human agents, ensuring handoffs are seamless and frustration-free.
- Response Latency (AI vs. Human Agents) – Measures the time it takes for AI vs. human agents to respond to customer inquiries, identifying delays that could impact satisfaction.
- Speech Emotion Detection & Frustration Markers – AI scans voice pitch, tone, and pacing to detect signs of anger, stress, or confusion—offering real-time coaching suggestions for agents.
How To Measure Customer Experience
Now, putting these metrics to use…
With the right systems, you’ll be able to centralize all of your data and monitor everything your agents do in real-time. That’s how you peel back the curtain on hidden friction points and opportunities for optimization when measuring customer experience. That’s what you should be after.
Here’s what you want to do:
1. Map AI-Powered Behavioral Tracking to Individual Journeys
How are your customers or patients interacting with—your website, your portals, your calls, emails, SMS, and other messages?
Drop-off points. Repeated, failed attempts at form fills or appointment scheduling. Where are your policyholders/patients/customers struggling to follow through?
Advice 👉 Marry all of your customer behavioral and interaction data, and map it to individual contacts and their associated journeys.
You should always have a trail of data, per contact, per interaction. A complete, chronological view like this will better inform each future interaction, and open up your ability to offer proactive support (at scale, no less).
2. Analyze Conversations for Sentiment, Emotion, and Efficiency
Advice 👉 Invest in AI-powered analytics that make it easy to connect and observe customer sentiment at scale.
Qualtrics and your CCaaS tool(s) will provide data on sentiment and other emotion-based metrics. But it can be hard to put to use.
AI-powered analytics recognize and surface sentiment and intent signals much faster (based on language, actions, etc.), and make it much easier to combine all of that data (along with anything from Qualtrics, your CCaaS, your CRM, or wherever) into customer data profiles.
You can detect frustration, confusion, and urgency in real-time, without much manual work… You can, and should be doing this at scale.
Within your AI-powered tools, you’ll also see conversation efficiency metrics—which signal a lot of helpful insights, too.
Talk ratio, interruption frequency, dead air time… These should all be part of your regular reporting, since they give general proof on whether conversations are running smoothly (especially important as you deploy more and more AI agents).
3. Predict Churn Before It Happens
Don’t let customers or patients walk away because you were too lazy with your analytics.
Advice 👉…
- Deploy machine learning models that detect disengagement patterns before customers leave.
- Compare AI vs. human-assisted interactions to identify where automation enhances or hinders CX.
- Track customer effort across touchpoints—if a resolution requires multiple steps, it’s already a problem.
Combine all of this with your sentiment and behavioral analysis, and you’ll be able to stop fires before they start, and identify likely churn candidates.
4. A/B Test Messaging, Channels, and AI Agents in Real Time
A/B testing is often the secret sauce to successful CX. It drives up the speed of iteration, and provides a way to proof outreach on a very granular level. AI-powered tools like Regal, make it possible to test on any level, in a way that doesn’t break the bank.
Advice 👉 Test down to every touchpoint. Cadences, scripts/AI guardrails, timing, tone of voice, AI vs. humans.
Understanding how each of these factors contribute to the customer experience will give you a major advantage against your competitors. By measuring these touchpoints in real-time, you’ll never not be improving.
5. Centralize, Centralize, Centralize
It is possible to bring all of this reporting into a few places, if not just a single platform (which will depend on the size of your contact center).
Advice 👉 The more you can centralize your data and testing workflows, the better.
It speeds up iteration. It speeds up improvement. It gives you an always-on pulse of how each and every one of your customers feel about you.
Customer Experience Measurement Tools
Your CRM, data lakes, and CCaaS/outreach tools are assumed in all of this. We know you’re using those. What else might your stack look like
What might your measurement stack look like outside of your CRM and data lakes?
Top CX Measurement Tools:
- CCaaS: Your CCaaS tool should provide in-depth insights on calls, email, and SMS.
- Customer/Patient Engagement Platform: Similar insights to that of a CCaaS, but more specific to Healthcare and other industries.
- Qualtrics: Advanced survey & sentiment analysis.
- Gainsight: Customer health scores & retention insights.
- Medallia: AI-driven experience analytics.
- Regal: AI powered CX platform infused with AI capabilities, designed to elevate customer experiences and streamline interactions. A combination of a lot of the tools mentioned above, if you will.
Proving Customer Experience ROI
Showing How CX Impacts Revenue
The link between better CX and business growth is undeniable:
- A 5% increase in customer retention can drive profits up by 25-95% (Bain & Company).
- Companies with high Net Promoter Scores (NPS) grow twice as fast as their competitors (Satmetrix).
- Brands that prioritize CX generate 5.7x more revenue than those that don’t (Harvard Business Review).
Retention, satisfaction, and loyalty aren’t vanity metrics—they are predictors of long-term profitability.
Making Your Business Case for CX Investments
Properly measuring customer experience is key in gaining future buy-in from your CEO.
To secure executive buy-in, tie CX metrics directly to financial outcomes. This is a story your CEO will understand.
- CSAT & NPS Improvements = More revenue, better retention
- Faster Resolution Times = Reduced operational costs
- AI-Powered Personalization = Higher Customer Lifetime Value (CLV)
- AI Agent Outreach = Lower cost per customer served, more calls made
Benchmark your CX performance against industry leaders, leverage AI-driven analytics, build your story with hard data, and always tie back to revenue.
Improving the customer experience takes investment. Proper measurement is your best proof-of-concept for each and every investment.
Improving Your Customer Experience Takes Investment
Regal has a range of customer stories that showcase how investing in better CX measurement translates to direct increases in CSAT scores, revenue, and retention rates.
Measuring customer experience is not just a matter of collecting data. It’s about how you connect that data to your systems, your agents, and use it to perfect every interaction you have with your customers—to drive loyalty, revenue, and better retention.
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