As AI continues to reshape the digital marketing landscape, new companies are emerging, harnessing AI, that promise not just incremental improvement, but genuine structural change.
NDA’s new interview series, AI Marketing Pioneers, talks to leaders in this space to discover what they are doing differently.
One of those is Neuralift, a business applying deep learning neural networks to customer segmentation in ways that challenge long-held assumptions about how marketers understand audiences. Leading its go-to-market strategy is Tim Norris-Wiles, a seasoned leader in data, advertising and martech who most recently served as Managing Director for EMEA at Habu and LiveRamp, where he helped drive the international expansion of clean room and data collaboration solutions before moving into his current role at Neuralift in 2026
In this Q&A, Justin Pearse, Editor-in-Chief of New Digital Age, speaks with Tim about why now feels like a defining moment for AI in marketing, how Neuralift aims to unlock growth by removing human bias from data-driven decision making, and what this means for the industry at large.
A career built on change
What made this move the right one, right now?
If you know anything about me, you will know that I have moved very early on a number of key marketing technology trends, and always with good reason. There has been a clear lineage to this, moving from ad serving to DMPs, then CDPs, into clean rooms, and now AI-nativesegmentation.
Each step reflected how the rules of marketing were changing, and how the tools needed to change with them.
What feels different now is that we are at a real inflection point. There are three structural shifts happening at the same time. GPU compute is no longer locked away in laboratories and is landing in marketing, performance marketing is expanding horizontally across businesses, and AI is finally allowing us to move from describing audiences to discovering them at scale.
That combination is incredibly powerful, and that is what drew me to Neuralift.
You mentioned discovering audiences rather than just describing them. Why is that such a big shift?
For years, marketers have relied on manual segmentation. Analysts write rules, define cohorts, and describe audiences based on what they already expect or want to find.
The problem is that data is now too large and too multi-dimensional for that to be effective at scale.
What excites me about Neuralift is that we apply deep learning neural networks to customer data segmentation. That sounds technical, but the principle is simple.
The platform uncovers latent patterns in customer data that no human analyst could realistically find. Data has become too big and too complex for rules-based segmentation. If you look at big platforms like Meta and Google, or entertainment platforms like Spotify or Netflix, they are not manually building cohorts.
They use neural networks to spot patterns across massive data sets and make recommendations that work. We are applying that same thinking to customer data, with a patented neural network at the core, but presenting it in a way that marketers can actually use.
How important is it to translate and simplify this technology for marketing teams?
It is absolutely critical.
There is a paradox at the moment. Marketing wants to be involved in the most advanced technology, but it is not necessarily their job to understand every technical detail behind it.
CMOs are being pushed to explore AI, but they do not have the time or resources to become data scientists. That is where independent AI vendors like us come in.
Our role is to take very complex technology and verticalise it for specific use cases. In our case, that is advertising, marketing, and business growth. AI needs to bring teams together to solve large cross-functional problems, be grounded in business needs, and be actionable not intimidating.
You mentioned processing extremely large data sets. Why does scale matter so much?
Scale is everything when you are trying to uncover hidden correlations.
Because we partner with NVIDIA and are part of its Inception Program, we can bring industrial scale GPU compute into marketing without the marketer having to worry about it.
That means we can run models across an entire customer universe, not just samples. Recently, we have even processed $8bn of historical purchase data for a single client. The more data you can process, the more meaningful patterns you can uncover, and that is where the real value lies.
What do clients actually get out of this approach in real world terms?
One of the biggest benefits is removing human bias from decision making.
Traditional segmentation is inherently human, which means it comes with cognitive bias, assumptions, and pre-defined hypotheses. Very often, teams end up finding exactly what they were looking for.
Neural networks work differently. They explore data in a non-linear, non-deterministic way, much closer to how the human brain actually learns. They look for patterns without being told what to find.
That can surface unexpected affinities, behaviours, and connections that would never have been identified through income bands or demographic groupings alone.
How does Neuralift fit into the wider organisation, not just marketing?
Historically, segmentation has existed at two extremes. You either had expensive, static, top down consultancy projects, or you had siloed segmentation built by individual teams like marketing, finance, or retention, each optimised for their own narrow view. It was either strategic without being actionable or very tactical without a strategy.
Neuralift can bring those worlds together. We allow customers to define the KPIs they want to move, whether that is loyalty, product adoption, NPS, or conversion. And it starts at a strategic level across your population but also allows you to zoom into prescriptive tactics to lift KPIs.
All segmentation is grounded in those objectives, which makes it usable across multiple teams, use cases and lines of business, not just media activation.
Which teams and sectors are you working with right now?
We are working client-direct at the moment, largely because clients own the data and we need access to it. Senior marketing & insights/analytics leaders are leaning in heavily.
We are not here to replace internal data science teams, but to help leaders get answers faster while freeing their teams up to focus on execution..
Sector wise, we have seen strong traction in media and entertainment, streaming, sports, consumer apparel, real-money gaming and restaurant chains focused on loyalty. Travel and financial services are likely next.
What ultimately excites you most about what Neuralift can change?
The biggest thing for me is removing blockers. I have seen so many teams ask perfectly valid business questions and be unable to answer them because of process, access, or resource constraints.
AI native discovery allows businesses to move with precision and speed, and that combination is transformative. This is not about speeding up old processes. It is about creating better ones.
We help organisations know more about their customer ahead of investment in time and resources. That unlocks better decisions, stronger loyalty, and real business impact. We are genuinely moving the industry forward.
