Turning Data into Decisions: Laura Fiacco on Value-Driven Analytics
We caught up with Laura Fiacco, Head of CS & CX Analytics at Kiwi.com, ahead of her session “Value-Driven Analytics: Making Data Work for Decision Makers” at the Data & AI Conference Europe 2025 (13–17 October, London). With a career spanning investment banking in New York to tech leadership roles in Dublin and Barcelona, Laura brings a truly global perspective on turning data into strategic influence. In this interview, she shares how shifting from traditional CX metrics to business impact transformed her team’s approach, why storytelling is the ultimate tool for analytics professionals, and how AI is shaping the future of decision intelligence.
1. From Metrics to Meaning
Your session focuses on shifting from traditional CX metrics to business impact. What was the tipping point that pushed your team to start “speaking the language of ROI”?
The team had been struggling with lack of engagement for our Voice of Customer report, a report where we report on customer experience and highlight the main customer pain points. Despite the report taking over a week to prepare, there were hardly any comments or momentum as a result.
True value is a pull, not a push. Instead of pushing people to respond and engage, I started by asking for feedback. I learned that teams did not like the format of the report – that it was impossible to compare “NPS impact” to the other revenue-driving initiatives.
It was instantly clear that we needed to adjust our language to make it easy for teams to compare experience initiatives with commercial developments. So, we built a simple calculator that translated customer sentiment into repeat revenue.
The result was incredible! After that shift, customer experience became a conversation, not a fight. There was still a trade-off between time spent on revenue-driving developments and fixing customer pain points, but now it was clear that fixing those pain points had a cost beyond just customer sentiment.
2. Cross-Functional Alignment
You mention the importance of adapting communication to different audiences. What’s your go-to strategy for tailoring analytics conversations to non-technical stakeholders?
There are two questions that I use to frame analytical conversations to non-technical audiences:
1) “How would I explain this if I were talking to my neighbour?”
2) “Why should this person care?”
The first question helps me to give enough context, assuming the other person has no idea what I do (as this is often the case). It also helps remind me to simplify concepts. It’s ironic – building good analysis requires having good attention to detail, but the opposite skills are needed to have a useful conversation about that work. Start with introducing the big picture, and see where the conversation evolves. You might end up including the analytical details as questions come up, but offering it all at once only overwhelms the other person.
The second question reframes the conversation to drive action. People want to know their role in a conversation – are you asking for their approval? Their feedback? Once you’ve made the role of that person clear, it’s inevitable that you’ll have a more productive conversation.
3. Storytelling with Data
What makes a data story resonate with executive decision-makers? Can you share an example where storytelling led to a breakthrough?
Every executive has that “top of mind” challenge that keeps them up at night. Once you figure out what that is, building a story around how to solve that problem is music to their ears.
An example of this was in a previous SaaS role where I was meeting with a client who was at risk of churn. Through data storytelling, I was able to show them that the licenses they purchased were not just an expense – they were driving revenue growth, and that by churning, they would actually be reducing profitability.
4. Breaking Down Silos
How do you build bridges between analytics teams and departments like product, finance, or operations to ensure alignment and action?
I find that the best way to break silos is to build analytics into the ways of working. Instead of creating additional meetings with analytics, bring analysts into the recurring meetings and have them give updates on metrics that highlight the successes or opportunities aligned with key initiatives.
5. Global Perspective
Having worked across the US and Europe, what differences have you noticed in how organisations value and apply analytics in decision-making?
Although data is often central to how decisions are made across both cultures, the biggest difference I’ve seen is in the presentation. From my experience in the US, business conversations quickly escalate into talking about numbers. Meetings are run swiftly and efficiently, and if you don’t get to the point quickly you risk losing attention. In Europe, it’s often considered rude to jump right into business talk. Meetings start with a pleasant conversation getting to know each other and ease into ROI conversations.
6. Culture Shift
What advice would you give to analytics professionals who want to shift their team from being “report producers” to strategic business partners?
The best way to demonstrate value is to solve a problem that someone didn’t ask you to solve. Analytics professionals who proactively deliver insights are brought into more conversations, and you’ll see that stakeholders start treating you like strategic business partners instead of “report producers”.
7. Biggest Lesson
Looking back on your transition from investment banking to tech and now travel, what’s the most valuable lesson you’ve learned about turning data into influence?
The most valuable lesson I’ve learned is that data amplifies intuition – it doesn’t replace it. I’ve seen senior finance executives lose faith in valuation analysis because the number “felt wrong”- and they were often right. Similarly, I’ve seen tech leaders invest in technology because it “felt right” despite having limited data to support a business case.
What separates good analysts from “great” analysts is the ability to use data to resonate emotionally with decision makers. Don’t just focus on what the numbers say, but on how it supports or challenges your audience’s intuition. Pairing great analysis with compelling storytelling is a magic bullet that works in any industry.
8. Looking Ahead
What are you most excited about in the evolving world of CX analytics and decision intelligence?
I would be a fool not to answer “AI” here! I feel like each day opens a new door of possibility – not just with the ability to support customers at even greater scale, but also transforming those conversations into a feedback loop to improve the product roadmap. The challenge has always been how to create a closed loop between customer experience, operational metrics, and business outcomes, and I think AI will play a massive role in how we make that happen.
Laura’s approach is a reminder that analytics is about more than just numbers — it’s about connecting data to decisions that matter. By speaking the language of business, breaking down silos, and embracing new AI capabilities, she’s helping to redefine what analytics teams can achieve. Don’t miss her session on Tuesday, 14 October 2025, 10:20–11:00 AM at the Data & AI Conference Europe 2025, where you’ll learn practical strategies to make data resonate with decision-makers and drive real organisational change.
