Paul, you’ve worked across agencies, independents, and brand-side roles. What do you think is the biggest gap today between how marketing performance is measured and how growth actually happens?
This is a complex equation. There's no single "biggest gap" but a multitude of compounding challenges that prohibit growth. One I talk about often is an upstream failure to set objectives that are tethered to the realities of how people buy and how markets operate, which then has a significant downstream impact. For example, if a brand seeks to grow 10% year over year in a market that is flat, we must ask what we are doing to earn the right to outperform the category so significantly. If we're relying on advertising alone to do that, we're in trouble — and what this tends to do is force advertisers to focus on what's easy to measure, even if that measurement practice is flawed.
The second major challenge is in the distribution of incentives. Marketing and non-marketing executives are often incentivised to do things that inhibit growth and focus on efficiency. This is more likely to shrink a brand than grow it. Think: the best way to be more efficient and increase ROI is to spend less. Spend less and reduce your SOV. Reduce your SOV, and over time, you leave the market open for competitors to erode your SOM. These things are also compounded by vendors who have undue influence on marketers, particularly in the mid-market. We often forget that a vendor works in the interest of the vendor. The marketer must be orientated around the market.
You built Incubeta’s Marketing Intelligence function from scratch into a major growth driver. What critical market shifts made that evolution necessary?
No market shift really made this essential. It has always been essential. Plenty changed around it — signal loss, retail media, now AI rearranging how brands get discovered — but each of those became an excuse to get more technological and data-led, rather than a reason to ask whether the data was useful or the technology actually worked in our favour. It was important that we lead the way in fully demonstrating how advertising and marketing contribute to growth in a complete manner. That means understanding how the market, creative, media, data, and technology complement each other to drive better outcomes.
Candidly, we've become orientated around technology and data without really asking whether the data we have access to is useful, or whether the technology available really works in our favour. This has been a significant distraction from the important discipline of: how do markets move, how do customers choose, how do we set a budget that enables us to grow, how do we meet the market, how do we allocate that investment, how can I maximise my SOV within the constraints of that budget.
We, as an industry, have failed to recognise that advertising is a probabilistic practice, not a deterministic one. We cannot force buyers to buy, but we have to be mentally and physically present to maximise the probability we are chosen. Once we accept this, we can get on with the job of doing intelligent marketing. Not just anchoring decisions around what ad-tech vendor we favour, or flawed measurement practice that will provide us with the answers we want, not the truths we need.
Incubeta’s “Seamless Strategy” framework positions planning as continuous rather than campaign-based. What does modern planning look like when customer journeys are increasingly unpredictable?
You can't know the path any one buyer takes. But buying behaviour in aggregate is the opposite: predictable, lawful, boringly so. We have several decades of data showing how buyers choose brands and follow stable patterns. The concept that journeys are unpredictable is something vendors leverage to shape how they sell products, not a reflection of how markets operate and brands grow. Seamless Strategy, rather than merely being a framework, enables marketers to understand the complexity of the core "laws" that underpin buying patterns, applied to their unique circumstances.
For example, an advertiser who wants to extract more revenue from their existing customer base will find out that the volume they can extract from that base is tethered to category purchase frequency and their existing market. That's not to say it's an impossible task, but that they'll have to rely on things other than advertising, maybe, to achieve it. The tool effectively takes all the available evidence to guide better decisioning, set budgets, identify markets and audiences that are structurally favourable to the advertiser, and understand how the budget needs to be deployed to stimulate future and capture current demand, based on their category, their market, their brand size.
These principles are not a reaction to changes in the customer journey. They are the foundation of marketing intelligence and a rejection of the idea that any single tactic, or just the pushing of a few buttons, can achieve untethered growth.
Incubeta integrates AI-driven solutions through OutMeasure, OutSmart, and OutCreate. Beyond efficiency gains, where do you see AI genuinely improving strategic decision-making for marketers?
It's very easy to be enthusiastic about the advantages that AI brings. But equally important is not to get carried away with it and let it distract us from the core discipline of marketing. The efficiency gains from AI are obvious. We can do things faster, maybe cheaper (although AI, of course, comes at its own cost that I think is grossly underestimated today, and AI itself is under-commoditised).
But with OutSmart, OutMeasure, and OutCreate, what we're trying to do at Incubeta is put AI in the hands of excellent humans, to augment their work. Build at pace, but build with expert governance. You can build creative assets in minutes, but do they move the consumer? Are they anchored in your category entry points? Do we feel good about what we put into the market? We can build an MMM quicker than ever before. But is that model tethered to how marketing really influences choice?
If we, as humans, do not understand these things, there's an increasing risk that by allowing the model to do it for us, we follow the wrong path. Which is why we leverage AI to enhance our domain expertise in creative, media, and measurement. Not replace it.
Your experience spans TV, CTV, digital, search, and programmatic. How has the balance between brand-building and performance marketing evolved in the last few years?
The dichotomy of brand and performance is nonsensical. Performance marketing is a modern construct of something that has always existed: advertising that helps drive short-term outcomes, like a press ad with a price point and CTA, a price promotion in itself, or a DRTV infomercial. No one in their right mind believes we don't need to do both (although in practice, that's not always the case), but what really matters is understanding the weight we put behind stimulating future demand and harvesting immediate intent.
How advertisers budget for both streams has and always will vary on a number of factors: category growth rates, the purchase cycle, a buyer's decision-making or buying window, a brand's lifestage, the purchase method itself, among many others. It's no good anymore saying we need to do "both" — and no good reaching for "60:40" as if it were a rule rather than an average — what matters is that we anchor our budget in the realities of the market we face today.
In many respects, that's why I built Seamless Strategy: to provide that guidance to advertisers who simply do not know and struggle to defend that budget. This has created such a huge problem for advertisers who then become predisposed to measuring what's easy to measure, often under the undue influence of ad-tech and poor measurement practice, and thus end up underserving the things that make a brand "Quick to Mind" — seeding a little memory, a little neurological real estate — so that when they enter the market and are ready to buy, assuming the brand is also "Easy to Find", we increase the probability of being chosen.
You’ve written about “Search Before the Search” and evolving discovery behaviour. How do you see AI assistants, retail media, and platform-native discovery reshaping the future of media strategy?
If we assume these are changing the nature of media strategy, we risk entering a dangerous era where we believe that clever use of new tactics shifts the balance in our favour. Since the dawn of media, new channels have emerged, and some old ones have evolved. No new medium ever fully killed off an old one. Print still exists in 2026, and while it might be hanging on by a thread, those publishers are still alive and kicking — albeit behind the screen rather than on the page.
The search beyond the search is really about appreciating the number of touchpoints available to the media buyer where brands are discovered. People have always found and learned about products and brands in different ways. As media touchpoints proliferate, that continues. It means we may need more touchpoints to build the effective reach and frequency we once did with just a few. It means we may need to value attention — or rather, just enough attention to encode a memory — differently than we did before. It means our share of voice is constructed differently. But it doesn't change the core discipline of media planning: the principles that underpin how a brand survives and grows.
If you were rebuilding a modern marketing organization from scratch today, what’s one mindset you would never structure the old way again?
I'm a big believer that the marketing discipline has lost its way over the past ~15 years. We've created dichotomies that are false, narratives and choices that are too binary. We look for tactical solutions before asking the question, "what do buyers really want from us?" and "how can we best serve that?" — instead, we anchor our briefs in "how are we driving sales?" without looking at the map and finding the right path. It's for that reason that I'm a huge advocate for the "old way", which to me means anchoring strategies in the reality of the market, not believing we can click our way to success.
