What it takes to create “effortless” experiences

Effortless. Seamless. Easy. These are the customer experiences that brands of all types aspire to achieve. But as you know if you’ve ever tried something without preparation and practice, just because something looks effortless doesn’t mean it is.

A few years ago, I signed up for a 10K run before I realized it was the morning after my best friend’s 30^th birthday party. After riding the party bus and imbibing in the free-flowing food and drinks the previous night, I was woefully unprepared to manage the unexpected hills and the endurance needed for the race. I finished next to last, just besting an octogenarian. I was unprepared and exhausted, with little outcome to show for it.

The winners of that race made it look easy as they crossed the finish line. Effortless. Simple. They trained, prepared, and probably skipped a casino trip the night before. For customer experiences, it’s the same thing.

A good experience is explicitly designed to reduce effort on the part of customers, but so much goes on under the surface within a CX organization to make it happen. Technology integration. Well-trained employees. Ongoing data analysis for actionable insight. Clear processes.

This issue celebrates the detail, hard work, and minutiae companies work with to craft “seamless” experiences for their customers and employees.

Explore how to tackle the uphills within CX efforts – siloed information and action, unreliable or unavailable data, and untrained employees, just to name a few. Check out how Avelo Airlines competes against the big guys with simplified experiences. And get tips on how to outsmart failure points within CX innovation projects.

Let’s get moving.

Sincerely,
Liz Glagowski
Editor-in-Chief

Conversational AI vs. conversation AI: What’s the difference?

AI is evolving so quickly it can be hard to keep all the different types straight. That’s especially true when it comes to conversational AI and conversation AI. Not only do both use AI to enable natural-sounding conversations, but their names are so similar they’re often (mistakenly) used interchangeably, adding to the confusion.

But there are important differences when it comes to conversational AI vs. conversation AI, and understanding those distinctions is key to ensuring you’re getting the most out of each.

Conversational AI helps in the moment

Conversational AI is the set of technologies that enable machines to simulate conversations. At its core, it delivers real-time voice or text assistance to people.

Conversational AI powers tools that help customers (or associates) in the moment, by quickly delivering the answers or information they need. These include chatbots, speech-based assistants, voice bots, and other self-service options.

Not all conversational AI tools are the same. AI-powered chatbots, for instance, are automated software that simulate a chat conversation with a user in natural language. They’re very useful for automating simple tasks and enabling 24/7 access for customers, but limited because they’re primarily text-based and scripted to answer only specific questions.

Intelligent virtual assistants (IVAs), on the other hand, use conversational AI to learn from each interaction and get smarter over time. They’re chat assistants that can generate more personalized responses by combining analytics and cognitive computing. They consider – in real time – individual customer information, past conversations, and location, and are more advanced than simple chatbots.

Conversation AI improves the future

Unlike conversational AI that’s used to facilitate seamless interactions in the moment, conversation AI (also known as conversation intelligence) analyzes large volumes of data from conversations to cull insights and trends over time and improve future decision making and interactions.

Your contact center collects huge amounts of data; conversation AI harnesses its potential by making sense of it all. Technologies like speech and predictive analytics let you listen in on every interaction happening in the contact center.

In addition to helping identify what works and what doesn’t during interactions, these tools quickly comb through large quantities of data and identify trends, patterns, and anomalies. You’ll get to know your customers much better, enabling you to serve them faster.

Armed with those insights, you can eliminate guesswork and make data-backed decisions that improve customer experience (CX), employee experience (EX), and your bottom line going forward. Speech analytics, for instance, helped a global social media company grow customer conversions by 233% and call volume analysis helped a national energy company reduce call volume by 60%.

Simply put, conversation AI speeds up your ability to put insights to work.

Both are keys to CX success

While there are definite differences when it comes to conversational AI vs. conversation AI, both can play important roles in a successful CX operation.

Embrace conversational AI where automating simple tasks makes sense. Customers will appreciate the ability to resolve basic inquiries in their own time and in their preferred channels. And using chatbots and other tools frees your associates up to focus on tasks where they can add more value – improving CX, EX, customer satisfaction, and loyalty.

Use conversation AI tools on a deeper level, to get the most from your data. Your contact center is a treasure trove of insights, but you’ll never uncover them without the right tools. Conversation AI can help you to get know your customers (and your contact center) better and make more-informed decisions that drive the results you need.

But don’t implement either type of AI merely for technology’s sake. Neither will deliver the ROI or results you want if they aren’t part of a thoughtful AI strategy. A “set it and forget it” approach doesn’t work for AI.

Brands need to continually check on how tools are performing and making adjustments as needed. If you lack that know-how in house, working with a CX partner that specializes in conversational and conversation AI is a great way to tap into proven best practices and expertise.

Redefining Customer Feedback: Embracing Comprehensive Metrics for Accurate Sentiment Analysis

By Ricardo Saltz Gulko

This article is published through a partnership with the European CX Organisation (ECXO). Read the original here.

Introduction

The Net Promoter Score (NPS) has long been a widely used metric for assessing customer loyalty, satisfaction, and the potential for customer churn as a relationship and transactional metric. Despite its widespread use across various industries, NPS has come under scrutiny for not providing a holistic view of the customer experience. This article examines the critiques of NPS, its performance in different business contexts, and emerging global trends in customer feedback strategies. By adopting a multifaceted approach, organizations can gain a thorough understanding of customer sentiment, leading to better decision-making and enhanced customer satisfaction.

The Inadequacies of NPS

NPS is centered on a single question: “How likely are you to recommend us?” This provides a limited and momentary glimpse into customer sentiment. Gartner predicts that over 75% of organizations will move away from using NPS as a primary metric for customer service and support by 2025. The simplicity of NPS fails to capture the complexities of customer relationships and experiences, which are vital for improving satisfaction. Companies like Toyota and Samsung in Asian markets have found that while NPS gives a quick snapshot, it doesn’t delve deeply into changing customer expectations and perceptions. A more continuous and longitudinal approach is needed to truly understand customer behavior and preferences.

The Broader Critique of Singular Metrics

The issue with NPS is not unique. In various fields, relying on a single metric can lead to incomplete conclusions. In customer experience (CX), metrics like CSAT and CES face similar limitations. In accounting, metrics such as Net Operating Profit need additional context to be meaningful. In healthcare, a single heart rate measurement is insufficient without considering other factors like activity level. No single metric can provide a complete picture; a combination of metrics is necessary for a true understanding.

The Need for Comprehensive Metrics in B2B and B2C Contexts

In B2C environments, where interactions are more transactional, NPS can be a useful indicator of customer advocacy. Companies like Unilever and Siemens use NPS to assess consumer sentiment and identify product improvement areas. However, in B2B settings, characterized by complex decision-making and long-term relationships, NPS often falls short. Sony and LG in South Korea exemplify the difficulties of applying NPS in contexts that require sustained service excellence and relationship management. A comprehensive approach that integrates multiple feedback sources, including Voice of the Customer (VOC) metrics, data analytics, and AI, is essential for a complete understanding.

Global Adoption of NPS and Its Limitations

Despite its limitations, many global companies like Alibaba and SAP continue to use NPS within broader customer experience strategies. These companies complement NPS with qualitative insights and additional metrics to create a complete picture. Platforms like Medallia support NPS implementation across diverse markets, emphasizing the need for localized customer feedback approaches. Metrics such as CSAT, CES, and others are most valuable when integrated into broader strategies.

The Impact of Data Analytics, AI, and Real-Time Feedback

Advancements in data analytics and real-time feedback mechanisms are transforming how companies gather and use customer insights. Companies like Rakuten and L’Oréal leverage AI-driven analytics to monitor sentiment across digital platforms, enabling proactive responses. This approach challenges the retrospective nature of NPS surveys, offering immediate insights that inform strategic decisions and enhance satisfaction. AI can mitigate survey biases by covering all customers and using operational data to generate insights, facilitating communication within the company.

Diverse Metrics for Holistic Customer Insights

To achieve a comprehensive understanding of customer sentiment, organizations are adopting various metrics alongside NPS:

Customer Effort Score (CES): Measures the ease of interaction and issue resolution.
Customer Satisfaction (CSAT): Evaluates satisfaction with specific interactions.
Customer Lifetime Value (CLV): Estimates long-term revenue potential from a customer.
Revenue Growth: Tracks growth attributed to customer experience initiatives.
Customer Retention Rate (CRR): Measures the ability to retain customers over time.
Return on Investment (ROI): Calculates profitability from specific CX investments.

Proactive and Predictive Insights

Traditional NPS feedback often reflects past interactions, which may lose relevance over time. Real-time insights and predictive analytics allow businesses to shift from reactive to proactive strategies. Effective leadership requires leveraging real-time service data and AI to understand the customer journey and sentiment upfront. This data-driven approach moves beyond instinctual responses to dynamic customer sentiments, ensuring satisfaction before and after interactions.

Implementing Effective Customer Feedback Strategies

To utilize these metrics effectively, companies must define clear metrics, data sources, scorecards, and KPIs aligned with strategic goals. This ensures a comprehensive evaluation of customer experience efforts, fostering continuous improvement. Companies like Tencent and Nestlé exemplify the integration of diverse metrics to drive customer-centric strategies and enhance relationships.

Building a Customer-Centric Culture

Creating a 360-degree feedback system involves:

Multi-Channel Feedback Collection: Capturing diverse perspectives across touchpoints.
Segmentation and Personalization: Tailoring feedback mechanisms to different customer segments.
Continuous Feedback Loop: Establishing real-time responses to customer issues.
CRM Integration: Correlating feedback with customer profiles for deeper insights.
Advanced Analytics and AI: Analyzing large volumes of feedback data.
Cross-Functional Collaboration: Ensuring feedback insights drive strategic decisions.
Clear Metrics and KPIs: Aligning metrics with business objectives.
Cultural and Regional Sensitivity: Making feedback methods relevant across diverse bases.
Customer-Centric Culture: Valuing and acting on feedback at all levels.

Conclusion

While NPS remains valuable, its limitations are evident. The rise of advanced analytics and real-time feedback offers a transformative opportunity to move beyond NPS. By embracing a diverse range of metrics and technologies like AI, businesses can gain a nuanced understanding of customer sentiment. This holistic approach enables proactive decision-making, anticipates customer needs, and delivers personalized experiences. Integrating qualitative insights with quantitative metrics provides a deeper exploration of customer motivations and behaviours. Evolving NPS into a broader feedback strategy is essential for thriving in dynamic markets. By leveraging advanced technologies and diverse metrics, organizations can unlock deeper insights, foster meaningful relationships, and lead in customer experience excellence.

Is generative AI is making customer experience worse?

By Tom Lewis, Senior Vice President of Consulting, TTEC Digital

When ChatGPT burst onto the scene, it was so widely adopted – and so quickly, by so many – that consumers soon started to expect generative AI-level responses from customer service bots. As generative AI suddenly infiltrated so many aspects of daily life, consumers assumed brands would be using it to deliver relevant information and answers at a moment’s notice.

But there’s a major disconnect: customers are expecting generative AI-level responses from customer service chatbots, yet they’re often presented with very narrow-scoped bots that don’t know anything about them. The result? Bots often fail to deliver a satisfactory experience and customers have to be transferred to live associates.

The expectation gap

While chatbots and interactive voice response (IVR) technologies have advanced significantly in the past decade, they are still often chosen by brands not because they deliver a more seamless customer experience but because they are a “cheaper cost channel,” as highlighted in the book The Effortless Experience.

Chatbots are still useful since they often manage to bypass the need for human interaction, a scenario many consumers seek to avoid. But since many of these automated systems are so bad, many consumers just take the stance that they will circumvent the technology and go straight to the human. They believe that they will have to repeat everything they just communicated in the automated system anyway, so why go through the effort?

Many consumers are asking, “Why, if my kid can converse with ChatGPT on an iPad, can’t company chatbots handle basic prompts like ‘What is my balance?'” The typical chatbot experience really highlights the deficiencies with most of the current technology. And recent advances in generative AI just make traditional bots’ limitations more evident.

Traditional chatbots being used by many contact centers are falling short of customers’ expectations in the modern AI age. That’s why I feel generative AI is causing worse customer experiences with a technology that hasn’t changed, simply because of that expectation gap.

Bridging the gap

A major investment focus for private equity and venture capital firms of late has been around AI, specifically generative AI. Many of these firms are also looking at companies that focus on the customer experience SaaS (software as a service) industry, which creates a unique opportunity for investors and businesses.

But some companies remain hesitant. Many brands are still experimenting with this technology in customer service departments because they are concerned it will “hallucinate” or otherwise provide inaccurate answers. This happened recently to an Air Canada customer who was granted a refund via a bot and then told “no” by a human at the company.

For sophisticated voice and text bots to evolve, the next step will be the complete integration of generative AI. As software companies roll out these capabilities and brands experiment and gain comfort with the answers they give customers, consumers will see more and more of these technologies.

How they embrace generative AI will be a true differentiator for brands. Customers will choose those that make interactions effortless.
As they evolve, not only will these bots be able to handle a wider range of inquiries, but they’ll also be able to relate to consumers specifically based on their relationships with the brand. They won’t offer options that are irrelevant to customers, and they will tailor their responses and recommendations. This “mass personalization” will further reduce friction, differentiate brands, and endear consumers to those brands.

The current state may not be that pretty, but the near future looks bright. Brands should be experimenting now with this technology and pressing to roll it out quickly to grow customer loyalty and stand out from competitors.

A version of this article originally ran in Forbes.

A Comprehensive Analysis of AI’s Impact on the Employee Experience

By Ricardo Saltz Gulko

This article is published through a partnership with the European CX Organisation (ECXO). Read the original here.

As we have explored, AI is fundamentally transforming the employee experience, touching every aspect from recruitment and onboarding to learning, development, and day-to-day engagement. This transformation, driven by advanced data analytics, machine learning, and predictive technologies, is ushering in a new era of workplace efficiency and personalization. However, the path forward is not without its challenges. To fully harness the potential of AI, organizations must navigate a complex landscape of ethical, privacy, and change management considerations. This comprehensive conclusion examines these facets in greater depth and outlines a strategic approach to leveraging AI for enhanced employee experiences.

The Multi-Dimensional Impact of AI

AI’s impact on the employee experience is multi-faceted, providing significant benefits while also posing substantial challenges. By examining these dimensions closely, we can better understand how to maximize the advantages while mitigating the risks.

Enhancing Recruitment and Onboarding

AI’s role in recruitment and onboarding is transformative. Automated resume screening, AI-powered interviews, and predictive analytics streamline the hiring process, making it faster and more efficient. This not only improves the candidate experience but also ensures that organizations attract the best talent. However, the reliance on AI also necessitates stringent measures to avoid biases and ensure fairness, as AI systems can inadvertently perpetuate existing biases in hiring practices.

Personalized Learning and Development

AI-driven personalized learning paths and continuous feedback mechanisms are revolutionizing employee development. By tailoring learning experiences to individual needs and career aspirations, AI fosters a culture of continuous improvement and skill acquisition. This adaptability is crucial in an era where the pace of technological change demands ongoing learning. Yet, the success of these initiatives depends on the quality of data and the sophistication of AI algorithms. Organizations must invest in robust data infrastructure and continuously refine their AI models to ensure accuracy and relevance.

Employee Engagement and Well-being

AI’s ability to monitor employee sentiment and personalize well-being programs is a game-changer for maintaining high levels of engagement and satisfaction. Sentiment analysis tools that gauge employee morale through various communication channels enable HR to proactively address issues, thereby preventing potential burnout and disengagement. Personalized well-being programs tailored to individual preferences further enhance this engagement. However, organizations must ensure that these AI tools are used ethically, respecting employee privacy and obtaining explicit consent for data usage.

Performance Management

Image source DALL·E

AI enhances performance management by providing real-time insights and predictive analytics, allowing for timely interventions and support. This leads to more accurate performance evaluations and targeted development plans. The predictive capabilities of AI can identify trends and potential issues before they become significant problems, thereby enhancing overall productivity. Nevertheless, the implementation of AI in performance management requires transparency and fairness to ensure that employees trust the system and feel valued.

Collaboration and Communication

AI-powered communication tools facilitate better collaboration, especially in remote and hybrid work environments. Smart assistants and enhanced collaboration platforms streamline workflows and ensure that employees have the necessary information and resources at their fingertips. This not only boosts productivity but also fosters a more cohesive and collaborative work culture. The challenge lies in ensuring that these tools are user-friendly and seamlessly integrated into existing workflows to minimize disruption.

Navigating Challenges and Ethical Considerations

While the benefits of AI are substantial, the challenges and ethical considerations cannot be overlooked. Data privacy, ethical AI use, and effective change management are critical to the successful implementation of AI technologies.

Data Privacy and Security

The increasing use of AI necessitates stringent data privacy and security measures. Organizations must implement robust data governance frameworks to manage data access, usage, and protection. Ensuring transparency and obtaining employee consent for data usage are essential steps in building trust and compliance with regulations.

Ethical AI Use

The ethical use of AI is paramount. Organizations must regularly audit AI systems for biases and take corrective actions as needed. Maintaining clear documentation of AI decision-making processes and establishing mechanisms for accountability are critical to ensuring that AI decisions are fair and transparent.

Change Management

Integrating AI into the workplace requires careful change management. Organizations must provide comprehensive training programs to help employees understand and effectively use AI tools. Open communication about the benefits and challenges of AI adoption is essential to address employee concerns and foster a positive attitude toward technological change.

The Strategic Path Forward

To fully leverage the potential of AI, organizations must adopt a strategic approach that integrates AI responsibly and effectively into their operations. This involves several key steps:

Invest in Robust Data Infrastructure: Ensure that data used by AI systems is accurate, comprehensive, and up-to-date. Invest in data management technologies and practices that support the effective use of AI.
Develop Ethical AI Practices: Establish clear guidelines and practices for the ethical use of AI. Regularly audit AI systems for biases and ensure transparency in AI decision-making processes.
Foster a Culture of Continuous Learning: Encourage a culture of continuous learning and development. Provide employees with access to AI-driven learning tools and resources that support their career growth and development.
Engage Employees in the AI Journey: Involve employees in the AI adoption process. Communicate the benefits and challenges of AI, address concerns, and provide training and support to help employees adapt to new technologies.
Monitor and Evaluate AI Impact: Continuously monitor the impact of AI on the employee experience. Use feedback and performance data to refine AI systems and practices, ensuring they continue to meet organizational and employee needs.

Read the complete article for a strategic path forward and to learn how Samsung, Unilever, Siemens and IBM are using AI to enhance their employee experience.

Emerging technologies meet familiar challenges at CCW conference

During the dot com boom, I got my first real job at internetnews.com, reporting on new internet startups and how legacy brands tried to keep up with the new online world. There, I was introduced to trade shows by attending Internet World, a sprawling event where the enthusiasm and excitement was palpable for how the internet was changing the world in real time.

This year, I got a similar feeling at the recent Customer Contact Week conference, the popular annual gathering of contact center players in Las Vegas hosted by Customer Management Practice. The show — its largest to date — featured two expo halls full of AI and other tech vendors touting their digital wares. Meanwhile, nearly 5,000 attendees included many contact center practitioners looking to stay on top of the changing industry.

The yin and yang of people and technology was on full display. Conversations volleyed between AI and data analysis to mental health and employee burnout. Last year’s fear and skepticism about AI on the show floor was replaced with an urgency to understand which tools are best suited for a variety of contact center challenges.

The one question on everyone’s mind, as it was at Internet World decades ago: “How do I integrate technology to innovate without damaging my brand, customer, or employee experience?”

Nicole Kyle, managing director of CMP Research, said it’s a question of managing digital dexterity for brands and customers. Digital experiences have been normalized by consumers across all industries, and expectations are high for AI and other digital tools to support internal and external operations. Companies are still hesitant to take big steps, however.

“Inertia is in the industry generally,” Kyle said, but data shows companies can’t afford to wait. Only 7% of consumers feel experiences have gotten much better over the past year, while 55% say they have gotten worse, according to CCW Digital’s 2024 June Market Study.

Like in the internet’s nascent days, there’s no one proven path. “When everyone [in the vendor space] does everything, it’s hard to know where to start,” said James Bednar, head of product at TTEC, during a thought leadership session. Adaptability and flexibility are critical to the CX industry’s evolution, especially as the theory of AI outshines its current practical impact, he added.

“Experiences may not be human to human, but they have to feel human to human.”
Nick Cerise, Chief Marketing Officer, TTEC

For example, Kyle presented data from the new report, “2024-2025 Customer Contact Benchmarking Report,” which found that a majority of consumers are theoretically willing to use chatbots for self-service, but the current reality doesn’t match the vision. Only 17% are confident they can successfully address a service issue with a chatbot.

Balance humanity with technology

Low confidence levels in AI come from uncertainty when humans are not present in the interaction. Discussions at the show focused on balancing technology with humans and knowing when to lean into AI and when to lead with a human touch. Technology alone is not the answer.

“We don’t view automation as being bad,” said Bednar. “A lot matters in the quality of the implementation, with time and effort to get the most out of [the technology].” For customers, he said, use automation and AI tools to reduce friction and escalate to humans quicker with context.

This aligns with new CMP research that cited “creating a frictionless customer experience” as the top priority among global customer contact and CX leaders.

Frictionless doesn’t mean completely automated or completely human. Find the balance that works for unique customer journeys, said TTEC Chief Marketing Officer Nick Cerise.

“Experiences may not be human to human, but they have to feel human to human,” he said.

Leadership lessons from Las Vegas

Besides technology conversations, attendees were hungry for insight on how to engage employees and lead when employees don’t share the same space. Kyle and her colleagues shared research showing that only 11% of contact center employees work on site, compared to 76% before COVID. As a result, engaging and retraining associates is a top leadership priority.

“Even if people don’t say it, they yearn for connection,” added Mark Killick, senior vice president of experience operations for logistics company Shipt, in a conversation with Kyle.

Contact center employees are understandably uneasy about the industry’s uncertain future. They are dealing with more complex calls, unhappy customers, and adopting new tech. Mental health awareness and burnout are challenges that shouldn’t be ignored.

“Even if people don’t say it, they yearn for connection.”
Mark Killick, senior vice president of experience operations, Shipt

Today’s leaders must create deeper, more authentic, and supportive relationships with employees to manage AI’s disruption without jeopardizing their engagement, Kyle said during a leadership workshop. She shared seven competencies for effective CX leaders:

Stability
Autonomy
Emotional intelligence
360-degree coaching
Mindfulness
Leadership
Functional expertise

In a snap poll, most attendees said they felt most confident in their functional expertise, and least confident in their autonomy to trust themselves and their teams to produce good work without micro-managing. That’s backed by CMP research data — only 6% of contact centers grant associates freedom to go off-script and provide “above and beyond” care.

“Leaders need to create space for employees, to help them to see where AI and new technology changes work for the better,” Kyle said.

My overall takeaway from the show was that the CX industry is vibrant and energized about the shift taking place. CX leaders are beginning to show some digital dexterity and are taking steps to balance humans and technology with AI implementations to improve associate work and gain deeper customer insights.

There’s a lot to be optimistic about for the future, even if it’s not yet fully defined, according to Amber Scott, vice president of CX at Serta Simmons Bedding.

“I think there will be space in CX for anyone who wants to be in CX, it will just look different.”

4 golden tickets to capture CX ROI

This article was written as part of a partnership between 1to1 Media and the European Customer Experience Organization.

Talk to someone like Lynn Hunsaker and she’ll tell you there’s some 24 metrics to convey the value of the customer experience. She’s dissected and painstakingly diagrammed each one.

When all the Venns, funnels, PowerPoints, histograms, flowcharts, and scatter plots are set aside, however, something remarkable becomes evident: While there are two dozen CX ROI metrics to track, companies need only focus on four.

That’s music to the ears of those struggling to improve the experience. They already know focusing on too many goals at once means there’s no focus at all.

Hunsaker gets it. The chief customer officer of ClearAction Continuum reveals four — just four — CX ROI benchmarks to prioritize during the “Four Gold CX ROI Metrics LinkedIn webinar hosted by the European Customer Experience Organization (ECXO) earlier this month.

The “Four Gold CX ROI Metrics” webinar was the final episode in the three-part series hosted by ECXO. The previous webinars were “Fast-Track CX ROI with 3 Levels of Improvement” in May and the “Mastering the Maze of CX Metrics & Money” in April.

In the webinar, she labels these metrics “gold” because success with these four CX ROI metrics triggers a domino effect that fuels success with all 24 metrics to maximize return on CX investments.

“In the customer experience, we are looking to achieve quite a lot — higher reputation, greater ease of work and ease of business, more revenue, more market share, more lifetime value. If there were only four things to focus on in order to remove the revenue roadblocks for all of those, wouldn’t that be wonderful?” she asked.

Mirage or meaningful? You pick.

When it comes to the customer experience, chasing the mirage (and all its shiny objects) can be more enticing than doing the real work of finding the root cause of friction and eliminating it once and for all.

That’s why get-rich-quick schemes and weight loss fads will always be with us. It’s human nature to seek the short-term wins. Hunsaker draws parallels between short-sighted efforts to improve fitness with misguided efforts to improve CX.

“You might take miracle weight loss pills, weigh yourself every hour — such as we do with customer satisfaction surveys — to see if your fitness is any better every hour. Tummy tucks, body wraps … Spanx, fasting. All these things are temporary fitness mirages,” she says. “They are not real. They aren’t really ‘fitness.’ You may fit into your tuxedo or evening gown for the wedding or a party by doing these things, but it is unstable, unsustainable. It doesn’t have lasting effects.

“So much of what we do in CX is like that,” Hunsaker adds.

A better approach to fitness is to focus on the most meaningful metrics such as improved cardio/strength, healthy eating, restorative sleep, and good stress management. These four ingredients of genuine fitness have counterparts in CX.

4 gold CX ROI metrics

Adopt customer-centric thinking and customer-centric actions across the company, not solely in sales and marketing, but also human resources, security, product development, and finance, Hunsaker says.

“It’s how you collect, clarify, communicate, and champion CX insights” that matters most, she adds. The four gold CX ROI metrics are:

CX-inspired growth involves leveraging insights before designing a product, modifying incentives, pricing, warranties, and checking in with customers frequently to understand what they value, what they don’t, and adjusting accordingly.
CX-inspired performance involves managing company performance in all functional area to prevent friction in the customer journey.
CX-inspired strategies involve mining data to understand customer viewpoints collected across all channels and making new insights available to all operational areas, not just marketing, sales, and service.
CX-inspired efficiencies is about being more efficient and not just cutting staff to achieve cost reduction goals.

“You don’t need to hire a whole team of people,” she says. “You just need to think differently.”

A 9700% CX ROI? Not bad.

“No more layoffs. No more austerity,” Hunsaker says. “We should be aiming for [customer] lifetime value because we are looking to maximize revenue, minimize cost, and maximize customer retention.” Rather than creating one-off incentives to prompt a specific customer response, companies should instead “mistake-proof” the root causes that restrict revenue growth, cost reduction, and customer loyalty/retention — for a permanent win.

Hunsaker cites an example showing how a 9700% CX return on investment is achievable for a company taking the long view. Consider a product that retails for $2,000 that generates a modest 15 returns and 20 customer support escalations per month. Because the issue consumed a mere 20 manpower hours each month, the problem could be perceived as mere “noise.” Inconsequential. The cost of doing business.

Over the course of years, however, the cost of ignoring the product issue mushroomed to nearly $2 million, she says.

An alternative path forward, to commit nine months of engineering time and CX expertise (30 hours weekly) for remediation, would remedy the product issue once and for all, achieving that astounding ROI in its first year, and in all subsequent years, too. Factored into Hunsaker’s 9700% ROI equation is all the marketing and sales budget dollars no longer needed to offset lost sales and customer churn caused by the product issue. That’s funds freed up that can be allocated to high-value CX opportunities.

AI evolves from blueprint to tangible reality

Read the latest issue of the Customer Strategist Journal.

As a writer, one of my biggest challenges is facing a blank page (or screen) before I start writing. How should I start? What should I say?

That blank canvas anxiety was all but eliminated with the introduction of ChatGPT and other generative AI tools. I can ask them to summarize a theme or start an article about XYZ. It gives me a starting point to jump off from as I work on my projects.

I also use AI tools for interview transcription and summarization, as a supercharged thesaurus, or to punch up something I’ve already written so it doesn’t sound the same.

In the year or so since ChatGPT broke onto the scene for everyday use, generative AI has slowly started embedding into business. Like me, many organizations find it extremely useful as a way to improve worker productivity and spur creativity through collaboration, not replace humans and automate our lives.

A recent Harvard Business Review article cited top use cases for AI at the moment, and results are not surprising:

Technical assistance/troubleshooting (23%)
Content creation and editing (22%)
Personal and professional support (17%)
Learning and education (15%)
Creativity and recreation (13%)
Research, analysis, and decision making (10%)

We’re at an inflection point of the use of AI. The initial excitement is waning, replaced by practical questions about its usefulness and results. People are hungry for real-world examples with actual outcomes.

That’s why we focused this issue of the Customer Strategist Journal into answering some of these questions. What’s hype, what’s real, and what’s being done using AI for CX.

From in-store associate support at Tractor Supply to dynamic tech support knowledge updates and applications of conversation intelligence, the articles in this issue explore what’s happening now at the intersection of AI and customer experience. Enjoy!

Extract those vexing pebbles to ease negative word of mouth

This article was written as part of a partnership between 1to1 Media and the European Customer Experience Organization.

Criminy! Blast! Ouch! Barnacles!

That pebble in your shoe elicits a yelp and other colorful expletives. And yet, companies too often ignore this root friction point — all in pursuit of quick wins.

Stop that, said Lynn Hunsaker, chief customer officer of ClearAction Continuum, a Phoenix-based CX consulting and training company. As a former CX and QA executive at Fortune 250 companies, author, and professor, Hunsaker said she understands why it’s tempting to focus on building positive word of mouth instead of fixing negative word of mouth. Research backs up why that’s misguided.

Companies that reduce negative word of mouth 1% stand to increase revenue 3x more than those that improve positive word of mouth 1%, she said, citing findings from the London School of Economics “Advocacy Drives Growth” study.

“When you reduce negative word of mouth, you are taking pebbles out of your customers’ shoes, freeing them up to be more productive in their lives so they can engage with you more and can afford your premium products,” Hunsaker said last week during the “Fast-Track CX ROI with 3 Levels of Improvement” LinkedIn webinar hosted by the European Customer Experience Organization (ECXO).

This week’s Fast Track CX ROI webinar is the second episode in ECXO’s three-part series of short, practical sessions hosted by Ricardo Saltz Gulko, ECXO co-founder and managing director of Eglobalis, a global adviser in CX, design, and innovation. The first 20-minute webinar, “Mastering the Maze of CX Metrics & Money,” was presented in April. The final event in the series, “The Four Gold CX ROI Metrics,” will be June 5 at 10 a.m. ET.

Let go of friction to unlock revenue

“You are making a stronger 1:1 ratio between what customers expected and what they got,” Hunsaker continued. “Say what you do and do what you say.” Removing friction leads to lower costs, higher margins, market share, and sales velocity. “Customers will expand their purchases because you don’t put a pebble in their shoe — and everybody else does.”

Resist the lure of the quick win and go for an action plan that involves all teams that have impact, direct or not, on the customer experience.

Journey mapping is a valuable ongoing exercise but it’s not enough. A faster way to achieve ROI is to engage all stakeholders from customer support and product teams to engineers and other noncustomer-facing teams to get at the root source of friction. The ultimate goal is to discover the vital few CX issues in greatest need of resolution.

Hunsaker said spending at least 50% of your energy on reducing negative word of mouth will “bless you” in three ways that recapture value lost and create new value:

Resolve each incident after a CX failure. First call resolution (FCR) is important, she said, but it’s better to avoid an incident altogether.
Halt the root cause: “This is what I call ‘CX work’ rather than customer service or customer support,” she said. “CX work is stopping roadblocks to revenue and all the rigmarole of those pebbles.”
Prevent occurrence of CX failure: This is achieved by ensuring every functional area in the organization understands their role in CX so everyone can push toward that 1:1 ratio between what customers expect and what they actually get — rather than “throwing things over the fence for customer support to handle,” Hunsaker said.

With each functional team educated about its role and impact on the customer experience, their input is crucial to identify the root cause of friction. Once symptoms are identified (inconvenience? usability? timeliness?) — companies must probe deeper to identify the underlying source of CX failures. You won’t get the right answer the first time you ask, “Why is this problem happening?”

Why ask ‘Why?’ 5 times

The real, hidden “why” needs to be teased out through a series of deeper questions. Consider:

Why are customers unhappy? Slow delivery.
Why is delivery slow? The warehouse is understaffed.
Why is the warehouse understaffed? High turnover.
Why is there high turnover? Low wages.
Why are we not paying a competitive wage? Cost pressures. Competition is undercutting our prices through AI and other automation. They deliver our product faster, cheaper, and more efficiently.

This exercise uncovers strategic and investment opportunities leadership may be unwilling — or unable — to consider. A point solution won’t do the trick. A major strategic shift may be needed and that’s not a simple undertaking.

“This is the place almost every CX expert is giving you bad advice, to focus on the quick wins. But the quick wins won’t move the needle. The quick wins are not sufficient to remove the pebble in the customer’s shoe,” Hunsaker said.

Learn more about developing a CX action plan and delver deeper into Hunsaker’s insight. Watch the webinar on-demand.

ECXO, an open-access CX professional business network that continuously evolves with CX by empowering leaders, people, and organizations to collaborate, discuss, generate brand awareness, learn, and grow. Learn more at https://ecxo.org

1to1 Media and ECXO announce CX partnership

We’re thrilled to announce our new thought leadership partnership with the European Customer Experience Organization (ECXO), a leading CX business network that empowers leaders, people, and organizations in Europe and around the world to collaborate, discuss, generate brand awareness, learn, and grow.

Join us as we continue to explore exciting developments in customer experience, innovation, employee experience (EX), design, adoption, and more—all related to digital media and customer engagement!

As part of the partnership, we will be sharing content from ECXO members, as well as participating and promoting events to drive awareness and education about what’s new and what’s next in the world of customer experience globally.

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