Expert Mode: Reconciling the Customer Paradox of Price vs. Premium Experience
This article was based on the interview with Jenn Edwards, VP of Customer Experience at Five9 by Greg Kihlström, AI Adoption and Digital Experience keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
As enterprise marketing leaders, we’re navigating an interesting, if not slightly schizophrenic, consumer landscape. On one hand, economic pressures have sharpened our customers’ appetite for deals, with a significant majority making purchasing decisions based on discounts and raw value. On the other, the expectation for a seamless, personalized, and premium customer experience has not diminished in the slightest. If anything, it’s intensified. This creates a classic boardroom conundrum: do you invest in the bottom-line appeal of price, or the long-term value of a superior experience? It feels like a zero-sum game, forcing a choice between margin-eroding discounts and costly Customer Experience (CX) investments.
The reality, of course, is that this is a false choice. The modern consumer doesn’t operate in binaries; they want both. They expect the efficiency and savings of a digitally-native brand and the white-glove support of a luxury concierge, often within the same transaction. This is where the conversation pivots from a strategic dilemma to a technological imperative. The challenge isn’t about choosing one path over the other, but about building an operational model that can deliver both simultaneously. As Jen Edwards, VP of Customer Experience at Five9, suggests, the answer lies in a fundamental reframing of the problem, powered by the intelligent application of AI not as a back-office tool, but as a frontline differentiator.
Shifting from Competing Demands to Complementary Expectations
The first and most critical step for any leadership team is to move beyond the “price versus experience” mindset. The data from 5.9’s recent research is clear: while 45% of consumers are motivated by savings, a commanding 72% factor support quality into their decision-making. These aren’t mutually exclusive desires; they are intertwined facets of a single value equation in the customer’s mind. Treating them as such is the key to unlocking a more effective strategy.
Edwards proposes that leaders view these priorities as two sides of the same coin, working in concert to create brand loyalty. The strategic question then becomes less about “if” and more about “where” and “how” technology can serve both ends.
“We should really think about these priorities as complimentary expectations, because, you know, 45% of consumers in the research that we did are motivated by better savings or deals. But 72% of them factor in support quality and the experience that they’re going to have… Where do you place the AI in the experience so that it’s going to be a leverage point? You know, where we’ll deliver cost efficiency for them, and then obviously preserve the premium experiences… that are going to deliver the differentiation that you really need to create that brand loyalty.”
This reframe is empowering. It shifts the discussion from budget allocation battles between the CFO and CMO to a more collaborative exploration of operational efficiency. AI, in this context, becomes the bridge. It can automate routine inquiries, predict customer needs, and optimize backend processes to create the cost savings that fund competitive pricing. Simultaneously, a well-implemented AI can provide instant, 24/7 support, personalize recommendations, and free up human agents to handle the complex, empathy-driven interactions that truly define a premium experience. It’s not about replacing humans but augmenting them, allowing the entire support ecosystem to operate at a higher level of efficiency and quality.
The Imperative of Purposeful AI: Just Because You Can, Doesn’t Mean You Should
The current excitement around AI has created immense pressure on marketing and CX leaders to implement it—anywhere, everywhere, and immediately. This rush to adopt, however, often leads to technology being deployed for its own sake, rather than to solve a specific, tangible customer problem. This is a trap that can do more harm than good, eroding the very trust and loyalty that these initiatives are meant to build. A clunky chatbot that forces a user into a frustrating loop is worse than no chatbot at all.
Edwards emphasizes that the foundation of any successful AI-driven loyalty strategy is trust and transparency. Technology should be a facilitator of a better experience, not a barrier. If the AI doesn’t add clear value at a specific point in the journey, it shouldn’t be there.
“Trust and transparency is… really, really going to be quite important. And it is critical to actually adoption… do not let the technology be put in place for the sake of technology’s sake, because you will lose the trust, which will then mean that you are never going to get the loyalty… Look at the journey and really start to understand the points in which it’s going to make a great value to the customer. Otherwise, don’t put it in there… Just because you can doesn’t mean you should.”
This is a crucial piece of advice for leaders besieged by vendor pitches and internal mandates. The starting point for any AI project shouldn’t be the technology; it should be a rigorous mapping of the customer journey. Identify the moments of friction, the points of high-volume, low-complexity inquiries, and the opportunities for proactive assistance. Is a customer frequently asking “Where is my order?” That’s a prime candidate for an automated agent that provides instant, accurate information. Is a customer struggling with a complex product configuration? That’s a moment to seamlessly escalate to a human expert. The goal is to make the technology invisible and the outcome valuable. A bad experience with AI doesn’t just disappoint a customer; as Edwards notes, younger generations in particular will simply abandon the channel, and potentially the brand, altogether.
Measuring What Matters: Moving Beyond CSAT to Behavioral Metrics
As we invest in these advanced CX capabilities, our measurement frameworks must evolve as well. While traditional metrics like CSAT and NPS still have their place, they often provide a lagging, high-level view of customer sentiment. To truly understand the impact of AI on the customer journey, we need to dig deeper into behavioral data that reveals how customers are actually interacting with our systems.
The true test of a successful AI implementation isn’t a five-star rating on a post-interaction survey; it’s whether the customer willingly and repeatedly chooses to use that channel to solve their problems. This indicates that the experience was not just satisfactory, but efficient and effective.
“I would be looking at repeat purchases within the same channels coming back to the AI. You know, was it so good that you were like, ‘oh, I’m going to opt into doing it this way consistently?’… Do you stay within the channel you’re in? Are you having to switch because you’re not actually feeling that you have been able to accomplish what you set out to do?.. Are they completing and then are they coming back to it again where you can see repeat engagement through the same path is a good way to look at that.”
This is where the rubber meets the road. Leaders should be instrumenting their dashboards to track metrics like “channel stickiness” and “first-contact resolution within the automated channel.” A high rate of customers starting in a chatbot and immediately escalating to a phone call is a clear signal of friction and failure. Conversely, seeing a growing cohort of customers who consistently use your self-service tools for specific tasks is a powerful indicator of success. These behavioral metrics provide a real-time, objective measure of value. They show that you’ve not only solved a customer’s problem but have done so in a way that they find preferable to other available options, building a subtle but powerful habit of engagement with your brand.
Staying Grounded in a Fast-Moving World
Finally, in an era defined by rapid technological advancement and a deluge of data, one of the most powerful tools for staying agile is deceptively low-tech: empathy. Data dashboards and AI-driven insights are invaluable for understanding the “what,” but walking in the shoes of your customers and frontline employees is the only way to truly understand the “why.” This qualitative grounding is what separates brands that simply implement technology from those that build truly human-centric experiences.
Edwards champions the “day in the life” approach as a non-negotiable practice for any leader serious about customer experience. It’s about getting out of the boardroom and onto the front lines, whether that’s a retail floor or a virtual contact center.
“Day in the life. Best way to stay agile, get out in either my customers or my team’s shoes. Spend time listening and learning from them. Really asking good open-ended questions… at the end of the day, as a customer experience leader and a marketing leader… it’s walking in their shoes and really listening to them that I find the most beneficial. I always learn so much from them.”
This practice serves as the ultimate sanity check for any strategy. It’s where you discover that a theoretically elegant workflow is causing immense frustration for agents, or that a customer segment you thought was tech-averse is actually desperate for a better digital solution. It provides the context that data alone cannot. In a world moving at the speed of AI, this commitment to human connection ensures that our strategies remain grounded, relevant, and ultimately, effective. It’s the essential counterbalance to our technology stacks.
The path forward for enterprise brands is not about making a hard choice between price and experience. It’s about architecting an intelligent, agile system where technology creates the efficiencies that allow for both. It requires a strategic reframing of the problem, a disciplined and purposeful application of AI, an evolution in how we measure success, and an unwavering commitment to understanding the human beings at the center of it all.
Ultimately, as Edwards suggests, the conversation around AI will fade into the background. Like “the cloud” or “SaaS,” it will cease to be a novelty and will simply become part of the fundamental infrastructure of how business is done. The brands that will win in this next era are not those who talk about AI the most, but those who use it most thoughtfully to deliver on the complementary expectations of value and experience, building lasting loyalty one seamless interaction at a time.
