For decades CSAT and NPS have been the means for assessing customer experience delivery. Today, they are the benchmarks for measuring quality and consistency between direct competitors and across entire industry sectors.
But, in recent years, what these metrics track has evolved significantly. The elements that came together to define a positive customer experience even five years ago would no longer align with the average consumer’s expectations. And yet, NPS predates the arrival of social media, and CSAT is limited to assessing a single interaction, often in isolation.
This doesn’t mean organizations should shun these customer experience metrics — both are still solid indicators of contact center performance. CSAT, in particular, is a cheap and effective way of highlighting discrepancies between channels or team members.
But it does mean brands that haven’t already done so must start augmenting these CX metrics with modern approaches. The growing capabilities and accessibility of generative AI mean that, potentially, any organization is just a pilot project away from being able to draw insights directly from customer interactions and start seeing the big-picture view of their CX performance.
Metric misconceptions
While NPS and CSAT have specific limitations in assessing overall customer experience performance, all traditional metrics have strengths and weaknesses. More importantly, relying on these CX metrics without proper context poses significant risks.
A metric is only valuable if it reflects an organization’s current objectives or strategic aims. Any metric viewed in isolation lacks the necessary context. Focusing exclusively on traditional KPIs can lead to confirmation bias, stifle agility and hinder innovative thinking. Organizations might make decisions or implement changes that inflate metric values without genuinely improving service levels or building customer loyalty.
Adding AI to customer experience metrics
Artificial intelligence has been a key ingredient in the customer experience mix for many years. And it’s why, until recently, organizations with substantial budgets and robust partnerships with outsourcing and tech providers held a distinct edge in contextualizing CX success metrics and extracting actionable insights from customer interactions. They could leverage sophisticated tools to analyze data, enabling them to draw meaningful conclusions that inform strategic decisions.
But this is changing thanks to the availability of GenAI. This technology democratizes access to advanced analytical capabilities, leveling the playing field for businesses of all sizes. Now, organizations that were once constrained by limited resources can harness generative AI’s power to transcribe, summarize, and analyze textual and audio customer interactions, gaining a deeper understanding of customer sentiments and needs.
For example, imagine an organization that integrates generative AI to sift through call transcripts and customer feedback. This AI can identify patterns, highlight recurring issues and even predict customer behaviors. Suddenly, traditional customer experience metrics like CSAT or average handling time (AHT) acquire new dimensions of meaning. They no longer stand alone; instead, they are enriched by context that illustrates the underlying customer journeys.
Likewise, something as time-consuming and limited in scope as manually selecting and listening to calls for quality assurance can be automated and cover a large variety of contacts so that metrics focused on quality can be steered in the right direction with the right insights.
By interpreting data in a more holistic way, generative AI empowers companies to act proactively rather than reactively. Insights gathered from individual interactions can reveal broader trends, enabling organizations to pivot strategies, improve processes and enhance overall customer satisfaction. This shift can transform the narrative around customer experience, turning it from mere metrics into a vibrant story that accurately reflects customer needs and drives sustainable growth.
As such, we expect AI augmentation of existing metrics to become a trend among all organizations in the way it’s a standard operating practice among the biggest blue-chip brands.
Partnering with experts for enhanced insights
However, as with all forms of technology adoption and implementation, bolstering existing CX metrics in the contact center with AI can pose risks, especially if you attempt to go it alone.
To navigate this path to success effectively, the right partner is essential. Generative AI is most impactful when tailored to an organization’s unique tone of voice, business objectives and overarching strategy.
Engaging with experts ensures that any tool or technology aligns with your specific needs and delivers on expectations. Additionally, an informed implementation project will benefit from lessons learned, promoting efficiency. Most importantly, the right partnership will allow for a flexible and scalable solution that evolves with your business.
Generative AI is set to shake up how customer experience is delivered over the coming year and will be the catalyst for many enduring business trends. No one should underestimate the technology’s potential to democratize capabilities that until very recently were the preserve of the biggest brands — especially if an implementation is backed by a clear plan and equally clear objectives. So, to learn more about how the technology will influence the biggest customer experience trends of 2025, read the “Foundever® 2025 CX trends report: From buzzword to business case.”