Filmed in M+C Saatchi’s London office, this episode of The Undiscovered Metric explores what it takes to build marketing data you can actually trust, and why treating data quality as an ongoing product, not a one-off project, makes all the difference.
Host Mark Debenham, VP of Growth Marketing and Marketing Operations at Adverity, sits down with Amar Vyas, Chief Data and Technology Officer at M+C Saatchi Fluency, M+C Saatchi's award-winning data and technology consultancy, to discuss what it takes to build data systems that marketers can actually trust, and how to stop treating data quality as a one-time fix.
Amar describes his role as building the bridge between creativity and technology. Early in his career, that meant understanding audiences on a deeper level, where they are, what they want to see, and how to engage with them. Over time, his focus shifted toward creating decision-making engines that help marketers and commercial teams act with confidence.
When he co-founded Fluency, the mission was clear: to help ambitious leaders navigate complexity and turn data into something meaningful. “It’s a complex world, and this data and tech space is always changing,” he explains. “It’s about harnessing data better, building meaningful connections, and driving brand growth.”
That bridge between creative instinct and analytical precision only works when the foundations are strong. And that starts with trust.
For Amar, many data strategies fail for surprisingly simple reasons. “Strategies usually break down because there’s no common definition,” he says. “What's an impression? What's an engagement? And when do you use them? If everyone can agree on the definitions of metrics, you're halfway there.”
“Strategies usually break down because there’s no common definition."
Amar Vyas, Chief Data and Technology Officer at M+C Saatchi Fluency
Without shared language, every team speaks its own version of the truth. Add in neglected data pipelines and inconsistent maintenance, and marketers end up spending more time fixing data than using it. “If you’re a marketer, you feel it every day,” Amar adds. “Time wasted, duplicated work, misalignment around numbers and what they mean. We spend more time wrangling with the data than driving action from it.” The result is slow decisions and shrinking confidence in what the numbers really mean.
The core problem, Amar argues, is that marketing data decays fast. “It’s not once you have it, that’s it, you have to nurture it,” he says. “Taxonomies shift, platforms change the way that they measure data.” And those small changes create drift over time.
That drift is subtle at first. A tag is tweaked here, a file is fixed there. Over time, those small patches compound until the data decays. Once that happens, trust is hard to rebuild.
Fluency’s answer is to treat data quality as a living product, not a static project. “You have to treat it like a product,” Amar explains. “You need product managers and people regularly updating it so it gives you that consistency.” It’s a mindset shift from chasing quick fixes to building sustainable systems.
Artificial intelligence has brought data quality issues into sharper focus. “AI is a catalyst for inaccuracy,” Amar says. “It assumes the data going in is good quality, but if you feed in inconsistent data, you get poor attribution models. Errors are amplified at speed and scale.”
“AI is a catalyst for inaccuracy.”
Amar Vyas, Chief Data and Technology Officer at M+C Saatchi Fluency
That acceleration creates risk for marketing leaders under pressure to prove ROI. “You can’t build credible ROI stories if you don’t have strong data,” he notes. “Data quality has to shift from a nice-to-have to non-negotiable.”
In other words, the smarter your tools, the more dangerous bad data becomes. Without reliable inputs, even the most advanced models produce polished but misleading answers.
Many teams have learned to live with imperfect data simply to meet deadlines. Amar calls it a “survival instinct.” Over time, that acceptance becomes cultural. “If you normalize imperfect inputs,” he warns, “your models will confidently produce beautiful and incorrect answers. They look polished, people don't question them. But actually, fundamentally, there are errors, and the foundation is shaky.”
Fluency’s transformation projects focus on breaking that cycle. That means combining governance, adoption, and education. “It takes change management,” Amar says. “Making sure everyone in the business understands what the limitations of the data are, and when to use the right data.” That’s how you build real confidence behind the data.
Completeness and consistency remain the hardest problems to solve, largely because ownership is fragmented. CRM systems, social platforms, and eCommerce data all tell different stories. Amar argues that the solution lies in combining technology with human collaboration: automated data pipelines, yes, but also shared definitions and data councils that regularly evaluate how metrics are used.
Once the supply chain of data is healthy, Amar believes the next step is to humanize it. Analysts need to frame numbers with context, turning raw information into actionable insight. “Then you're much more proactive rather than being reactive,” he explains.
At Fluency, his team has developed synthetic metrics (data created from data) to tell richer stories. These include trust scores, cultural relevance measures, and touchpoint analysis. The goal is to help clients see the bigger picture instead of chasing vanity metrics.
“When you combine performance data with social analytics, sentiment data, and research, you can start using AI to create new kinds of metrics. It gives you a completely different lens on how to be more strategic.”
When asked which metric marketers overlook most, Amar doesn’t hesitate: cultural resonance. “I think cultural resonance is really important,” Amar says. “We get quite stuck into measuring awareness and consideration, and everyone’s doing that. So you’re not finding any real differentiation or advantage. Cultural relevance might seem a bit fluffy, but you can quantify it through signals like share of conversation, resonance with communities, and advocacy.”
It’s a fitting answer for a podcast built around the idea of uncovering what others miss. For Amar, cultural resonance is the ultimate expression of creativity meeting intelligence. It’s the point where data not only informs campaigns but also helps shape the culture around them.
And that brings the conversation full circle. Trust, governance, and quality may sound operational, but in the end, they enable what matters most in marketing: connection.
About Amar Vyas
Amar Vyas is Chief Data & Technology Officer and co-founder at M+C Saatchi Fluency, M+C Saatchi's award-winning data and technology consultancy. With over 15 years’ experience leading digital, data, and technology transformations for global brands including VW, Amazon, and the UK Government, he’s a recognised thought leader in building scalable, data-driven marketing solutions.
About Mark Debenham
Mark Debenham is VP of Growth Marketing and Marketing Operations at Adverity, where he leads the teams driving global demand, brand, and digital strategy. With over 15 years of experience spanning B2B SaaS, publishing, and edtech, Mark brings deep expertise in marketing automation, content strategy, and performance marketing. He’s spoken at HubSpot’s INBOUND and Grow London events, and currently sits on HubSpot’s 2025 Customer Advisory Board, shaping the future of its product strategy and customer experience.