CROs must take ownership of CX strategy. In this interview, boost.ai’s CRO Nick Mitchell explains how automation, self-service, and AI-led personalisation are directly moving the revenue needle.
How often do leaders associate customer experience with revenue or as a strategic driver of growth? The conversation of customer experience as a revenue lever needs to evolve as the lines between service and sales are blurring fast.
The connection between CX and revenue is not abstract. Every automated resolution, every intelligently routed query, every moment of frictionless support has the potential to drive sales, improve lifetime value, and unlock new growth channels. Yet many brands still treat CX performance in silos optimising for satisfaction without mapping it to business impact.
CXM Today talks to Nick Mitchell, Chief Revenue Officer (CRO) at boost.ai who puts the spotlight on the missing link: how to treat CX automation as a revenue strategy and more than a service upgrade.
According to him, revenue leaders must take ownership of CX automation strategy by demanding proof of impact from tech vendors. Trust and ROI go hand in hand—no buy-in happens without confidence in outcomes.
From self-service models that outperform humans in satisfaction to AI use cases that fuel upsell and conversion, Nick explores what it takes to future-proof CX and the bottom line.
Excerpts from the interview:
Do you believe most companies are underestimating the long-tail revenue potential of good support experiences?
No, the majority of companies recognise the value of good support experiences. Customer retention has always been driven largely by customer satisfaction. But companies are struggling to provide good service through efficient means, especially where the long tail is concerned and across the channels that the customer prefers.
Gartner predicts 30% of Fortune 500 companies will offer service through only a single, AI-enabled channel by 2028. So support experiences are increasingly a competitive differentiator, and therefore a long-term driver of revenue that businesses need to be laying the foundation for now.
What CX levers are actually moving the revenue needle today and how should brands measure that?
Self-service can now be delivered at CSAT higher rates than that of human equivalent transactions, Higher CSAT improves revenue generation and customer retention but also gives an opportunity for upsell, again in an automated fashion.. With clearer support queues, live agents are able to spend time relationship building and upselling, while growing in their roles too by providing more value.
Self-service today can match, and often enhance, the quality of human support, especially when it is designed to work hand in hand with live agents. At Telenor, Boost.ai’s virtual agent Telmi helped transform the customer service experience. By resolving over 630,000 inquiries across more than 2,000 topics and integrating with over 20 systems, Telmi streamlined service at scale and enabled the team to hit ROI targets in under a year. This freed up live agents to focus on revenue-generating interactions, while automation delivered the speed and satisfaction that drive long-term customer value.
Can conversational AI drive top-line growth? What are the revenue use cases people often overlook?
Absolutely, CAI can drive top-line growth both indirectly through improved CSAT/NPS but also through automated or semi-automated use cases. For example, gathering of key mortgage information prior to handing it to an appropriate agent to complete a mortgage agreement. Or by leveraging next best action and personalisation and offering a different product in a returns scenario in retail. There are many use cases where merging of different data sources can make the transaction richer and more seamless and the customer will then be comfortable to purchase.
McKinsey data reinforces this shift: CX-led organisations have seen more than 2X greater revenue growth compared to laggards since 2016, with leaders averaging a 44 net promoter score (NPS) versus laggards at 25. Their conclusion still rings true today: “Customer experience leaders across industries outperform peers on revenue growth.
If you had to build a revenue playbook powered by CX automation, what would be the first three metrics you’d track?
It’s all about the experience. You need to analyse the transactions themselves, automatically, and continue to iterate with improvements. Personalisation and persona understanding are also important.
To that end, I’d track:
- Transaction completion rates
- Transactional level NPS
- Sentiment analysis of both successful and unsuccessful transactions.
If at all possible, I recommend A/B testing all three and also comparing them to the revenue growth in other channels.
Where should revenue leadership sit in these new AI-powered CX initiatives?
In reality, every member of the C-suite must own a part of the business’ AI strategy. Scalable and trustworthy AI solutions cannot be achieved without input from every member. For revenue leadership, it’s important to bring their experience to the vetting process. If vendors or developers cannot point to specific examples of other implementations where ROI was delivered quickly, and a positive impact was made to revenue streams, it’s critical CROs own this space. People ultimately can’t put money on the line for an experience they don’t trust.
Where do you see the biggest gap between customer expectations and current CX capabilities?
A wave of “coming soon” AI features has led many customers to believe fully autonomous support is just a switch away and it is. However, like all technology projects it requires integration and access to the right data quickly and efficiently to enable the AI to do a great job. Expectations for faster service and smarter self-help tools are higher than ever. While CX capabilities have come a long way, the real gap lies in industry adoption.
For high trust brands, the risks tied to customer safety and data security impact implementation by creating more checkpoints. These industries face a higher bar to deploy the same tools others roll out more freely, creating experience gaps that, if left unaddressed, can hurt retention and long-term trust. Interestingly AI can be a help not a hindrance and can perform considerable advanced testing to ensure safety if deployed in the right way.
ALSO READ: Autonomous CX Is Coming. Are Brands Ready to Let Go?
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