What does customer experience look like inside a company most people associate with switches, infrastructure, and engineering rather than surveys, empathy, and brand perception?

In this episode, recorded at the Qualtrics X4 event in Seattle, I sit down with Jerome Boissou, Head of Global Customer and Brand Experience at Legrand. Jerome has been with the company for 28 years and now leads a customer experience program designed to help Legrand better understand a customer base that is changing fast.

This matters because Legrand is no longer serving only its traditional markets. The company now operates across a huge product portfolio, serves commercial buildings as well as residential markets, and plays a significant role in areas such as data centers and hospitality.

At the heart of our conversation is Legrand's "Best Of Us" program, which was originally launched in 2018 and then revamped in 2021. Jerome explains that the original focus was on personas and journey mapping, but the company soon realized it needed a more quantitative approach too. What followed was a broader strategy built around three connected pillars: customer satisfaction, customer centricity, and brand equity. Rather than treating customer experience as a dashboard exercise, Legrand is using those pillars to improve business performance, spread customer knowledge internally, and help teams understand what different customer groups really want, expect, and struggle with.

One of the strongest themes in this conversation is that feedback without action creates frustration. Jerome is very clear on that point. He explains how Legrand built a "close the loop" process, then went further with what the company calls a "customer room" process. That means identifying pain points and weak signals, routing them to the right internal teams, tracking them with KPIs, and making sure action follows. He shares that 100 percent of detractors are meant to be handled through that closed-loop approach, and that around 80 percent of pain points can be solved as quick wins. That is a refreshing reminder that customer experience only matters when it changes something.

We also talk about the scale of measuring experience in a global B2B organization. Legrand runs yearly relational surveys for both direct and indirect customers, covering around 50 different personas, and supplements that with transactional surveys across 17 touchpoints. These include digital interactions, training, product launches, and post-case feedback from call centers.

Jerome explains how Qualtrics became a key part of making that global program work, helping Legrand roll out surveys worldwide and giving teams a way to analyze feedback more easily and consistently.

Of course, this being a tech podcast recorded at X4, we also get into AI. But what stood out to me is that Jerome does not talk about AI as a magic layer dropped on top of everything. He talks about context. In fact, context becomes one of the defining ideas in our conversation. Capturing feedback is useful, but understanding the environment around that feedback is what allows better decisions to happen. For Jerome, that is where AI becomes more useful, especially when it is trained within the reality of Legrand's complex markets rather than operating as a generic tool.

Another part of this episode I found especially interesting is how Legrand brings employees into the customer experience process. Jerome shares an example of sending the same surveys to employees and asking them to answer from the customer's point of view.

By comparing employee perception with actual customer feedback, Legrand can spot gaps, adjust training, and help teams build more empathy. In one case, factory teams thought customers were far less satisfied than they really were, simply because the internal metrics they saw every day focused only on pressure and output.

Reframing that with real customer satisfaction data, including a product quality satisfaction score of around 95 percent, helped restore pride and perspective.

This episode is really about something bigger than surveys or software. It is about how a global company can embed customer thinking into the culture, make people feel part of the process, and use data in a way that stays human. Jerome makes a strong case that customer experience in B2B is not separate from performance. It shapes brand perception, trust, internal alignment, and ultimately business outcomes.

I'd love to hear your thoughts. How is your organization making sure customer feedback leads to action rather than just another report?

What does it take to turn millions of customer interactions into meaningful relationships instead of missed opportunities?

In this episode, recorded live at the Qualtrics X4 Summit in Seattle, I sit down with James Bauman, Senior Director and Head of Experience, Analytics, and Insights at TruGreen. James leads customer experience, analytics, and retention strategy across a business that manages around 60 million customer touchpoints every year. And as he explains, that scale creates both opportunity and risk.

At the center of our conversation is a challenge he describes as the "leaky bucket." TruGreen was investing heavily in acquiring customers, but too many were slipping away due to inconsistent experiences and missed moments. The real question became how to understand what customers actually need, when they need it, and how to respond in a way that builds trust and long-term loyalty.

We explore how TruGreen built an omnichannel customer experience program designed to listen across every interaction, from digital channels to service calls, and connect that feedback with real customer behavior. But what stood out to me was how they moved beyond simply collecting feedback and into taking action in the moment.

That's where AI agents come in. Rather than relying solely on traditional follow-up processes, TruGreen is now embedding AI directly into customer check-ins and surveys. These agents respond in real time, using context from the customer's history and recent interactions to provide relevant, immediate support. It changes the experience from something reactive to something far more responsive.

The impact has been significant. James shares how AI agents are now addressing around 51% of customer concerns upfront and cutting escalations by more than 30%. At the same time, they are freeing up human teams to focus on the conversations that truly require empathy and relationship-building, rather than spending time on repetitive follow-ups that may never get a response.

We also talk about the reality behind making this work. There's no shortcut. The speed of implementation came from the groundwork TruGreen had already put in place, building a strong data foundation and connecting systems across the business. Without that, the AI would lack the context needed to be useful.

James also challenges some of the common narratives around AI. It's not something you can simply switch on and expect instant results. But it's also far from hype when applied thoughtfully. In his experience, AI agents can deliver real value, both in customer outcomes and business performance, when they are placed in the right moments and supported by the right data.

For me, this conversation is a reminder that customer experience is shifting. It's moving away from slow feedback loops and into something far more immediate, where businesses can listen, understand, and act in real time.

And I'd love to hear your perspective. Are you seeing AI agents genuinely improve customer experience in your organization, or are you still trying to figure out where they fit?

Useful Links

• Connect with James Bauman
• Learn more about TruGreen
• Qualtrics X4 Summit

What does it really take to move from AI hype to something that actually works inside a business?

In this episode, I sit down with Shibani Ahuja, SVP of Enterprise IT Strategy at Salesforce, to talk about why so many enterprise AI projects stall long before they deliver real value. While the market is full of noise around agents, copilots, and automation, Shibani makes the case that the real issue is often much simpler and much harder at the same time. Design. She explains why model capability alone will never rescue poor architecture, weak governance, or unclear data ownership.

Our conversation goes well beyond the usual agentic AI headlines. Shibani shares what she learned from speaking with hundreds of C-suite leaders over the past year, and why many early enterprise AI conversations were too focused on models instead of ecosystems. We unpack the difference between predictive, generative, and agentic AI, why trusted data means more than having lots of information, and how Salesforce's own internal journey revealed conflicting knowledge, governance gaps, and the importance of determinism in enterprise settings.

I also loved Shibani's perspective on the human side of this transformation. We talk about why successful organizations are framing agents as a capacity multiplier rather than a headcount story, how to bring employees along through visible wins and shared learning, and why the best starting point is often a simple, boring use case that removes pain for frontline teams. She also shares her thoughts on the eight design principles for the agentic enterprise, the myths that frustrate her most, and what will separate the leaders from the laggards over the next 18 to 24 months.

This is a conversation for anyone feeling pressure to do something with AI, but wanting a clearer view of what meaningful progress actually looks like. Are businesses building the right foundations for an agentic future, or are too many still mistaking experimentation for strategy? Have a listen and let me know your thoughts.

Useful Links

• Connect with Shibani Ahuja
• Agentic Enterprise Architecture