“Customer Experience is at a Crossroads”.
While it’s a compelling statement, I actually find myself disagreeing with the premise. I believe the relentless pursuit of “efficiency” too often overshadows the crucial experiences of both our customers and our agents. Many of the metrics we hold ourselves accountable to daily are, in my opinion, performative, often missing the true point, and sometimes, they simply don’t really matter.
The Flaws in Our Metrics
Let’s take Average Handling Time (AHT). Does this sound familiar? “I want us to build a rapport with our customers.” It’s a great sentiment; it places value on the customer experience. But then, almost immediately, comes the caveat: “But can you do it in 350 seconds or less, please?” Is that even possible? This creates an immediate conflict: what’s truly more important — quality or speed? Relationships or metrics?
And how about Abandon Rates? Is there anyone in the industry that doesn’t measure this? It’s often presented as a measure of customer experience. But if we’re honest, what kind of experience does it really promise? “When you do need to call us, we’ll probably answer”?
Imagine a typical day where 900 customers call you. At a 5% abandon rate, 45 of those calls simply go unanswered. Those could be 45 crucial renewals, 45 customers struggling financially who desperately need help, or 45 loyal customers who might now fall out of love with your organisation. We simply don’t know the impact of those missed calls.
Furthermore, tracking Abandon Rates by interval can be incredibly misleading. A busy 30-minute interval at 9 AM might see 200 calls, while at 7 PM, it might be just 10 calls. If we chase a 10% Abandon Rate for both intervals, we’re effectively abandoning 19 customers at 9 AM but only one at 7 PM. Yet, both intervals technically meet the metric.
It’s traditionally been considered inefficient to answer every call. But that’s an outdated notion. With multi-skilled agents and multiple channels, it’s no longer inefficient to schedule staff to answer every call, especially when you can truly create agility. If the desired experience for your teams and customers is genuine service, then by effectively mixing channels and contact types and serving them to your teams, you can foster flexibility and fungibility. This isn’t about commoditising your resources; it’s about creating the necessary flexibility to truly meet customer demand, meeting customers where and when they want to be met.
A significant danger I’ve observed is the perception that it’s more cost-effective to force customers through a particular channel or journey. In the short-term, this might appear true, but in the wider scope of customer experiences, loyalty, and advocacy, why not let them choose? They are the customer, after all.
During my time running the Amazon Connect Product Team, at a previous company, I was once challenged to “shift 80% of contact through to digital channels”. There was no data to justify this; it was just an idea based on the assumption that, “it’s probably cheaper”. As I pointed out then, “I could get to 100% digital if I just switch the phones off.” This, to me, is a perfect example of measuring the wrong things without truly considering the outcomes.
AI: Beyond the Buzzword
Fortunately, technology is finally starting to align with this forward-thinking approach, and AI can play a significant part by supplementing the agent’s experience, thereby improving the customer’s experience.
For example, at QStory we have a natural language generator, the Why Detector, that creates detailed reviews of past performance. This tool gives planning professionals and operations leaders an indicator of what analysis they might need to do, allowing them to focus on their core strengths rather than replacing them. We’ve also developed a metric that brings consistency and equality to decision-making for each interval, moving beyond sole reliance on coverage or service level, and instead identifying if a break move or a shift slide can genuinely reduce customer wait times.
In the role I mentioned previously, I had relatively free rein to experiment with different AWS technologies. One of the biggest successes involved a voice IVR where internal transfers between Operations Teams were a significant challenge, accounting for around 10% of calls. As part of an IVR review, I used Contact Lens to transcribe these transferred calls to understand the root cause. We discovered it was mostly customers mashing the 1 button to get through. By implementing a solution with Contact Lens and a robust database of utterances, we took internal transfers down from 10% to zero in a part of the business that receives over a million calls annually.
This single change had multiple positive impacts:
- Improved customer experience because they no longer had to be transferred.
- Improved efficiency, saving 20 seconds per transfer on almost 10,000 calls a month.
- Improved agent experience, as they weren’t immediately on the back foot with these types of calls.
QStory’s Why Detector, and AWS’ Contact Lens are just a couple of examples illustrating my point: technology, particularly AI, can be incredibly powerful in supporting your teams to better help your customers.
However, AI itself can be a very broad term. Are we too often simply shoe-horning natural language chat, voice IVRs, and generative AI help into every corner of customer contact? Are we guilty of just ticking the AI box or claiming an AI strategy without genuine innovation?
The Agile, AI-Enabled Contact Centre of Tomorrow
So, what does a truly agile, AI-enabled service centre look like, and how can leaders evolve beyond mere scheduling?
For me, it’s fundamentally about augmenting and enhancing your agents’ experiences through the smart use of technology. This can be achieved through schedule flexibility, greater autonomy, or simply by supporting and empowering them to do their jobs effectively. AI certainly plays a crucial part in this and should be embraced, but ultimately, it’s more about measuring what the right outcomes are for both your teams and your customers. And it’s vital to remember that these experiences will be personal, meaning no single solution is likely to fit everyone.
Barry Jones, Product Director at QStory, shares his thoughts on what a truly agile, AI-enabled service operation looks like – adapted from his presentation at CCA Leaders’ Summit on the 19th June 2025.
If you’d like to find out more about how QStory’s AI platform empowers your agents, enhances customer experiences and helps your organisation focus on the right outcomes beyond traditional efficiency metrics, get in touch with us at hello@qstory.ai