Behavioural Science

Technology: The Comprehension Gap

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To stay abreast of technology and remain relevant in the sales and marketing industry I‘ve spent years mastering Web 3.0, the Metaverse, Cryptocurrency, and more recently Generative Engine Optimisation and AI Summary citations. The problem? These skills are useless if few people understand them. Businesses can’t adopt what they don’t grasp and in straightened times most won’t invest the time, money, or mental energy required to bridge that gap. The technology stalls and my consultancy stalls with it.

I’ve called it The Comprehension Gap. Given the title, I’ve attempted to be as concise as possible.

Every few years the internet reinvents itself.

Web3. The metaverse. Now AI. Each wave promises to change everything. Yet the same problem repeats: most people don’t really understand what it’s for.

That’s not a failing – it’s the point.

Mass adoption doesn’t happen because technology is clever. It happens when an average person can see the value without needing it explained. When the benefit is obvious, usage follows. When it’s not, adoption stalls.

Meta’s metaverse rebrand this decade is the sharpest example. Since 2020, it has burned more than seventy billion dollars building a future most couldn’t grasp. Not because the tech failed, but because the value wasn’t clear enough to justify the effort.

Most people didn’t reject it. They simply couldn’t answer a basic question: Why would I use this?

Web3 hit the same wall. Decentralisation, tokens, secure wallets, NFTs, blockchains. Technically clever, but hard to understand beyond enthusiasts. For most, the cost of understanding outweighed any benefit.

Here’s the uncomfortable truth:

  • If people need to learn new language before seeing value, adoption will be slow.
  • If using the tech feels like work, most will opt out.
  • If the benefit can’t be explained simply, it won’t spread.

This isn’t dumbing down. It’s how adoption works – remember Malcolm Gladwell’s description in The Tipping Point?.

The early internet succeeded because it didn’t ask people to change how they thought. Email felt like post. Search felt like asking a question. Social networks felt like a conversation. You didn’t need to understand the system. You just used it.

Web3 and the metaverse flipped this. They asked people to understand a fairly complicated premise first, then participate, then maybe benefit later. That order guarantees failure outside niches.

This gap between what technology can do and what average people grasp is expensive.

Big platforms pay for it. When users don’t “get it”, marketing becomes education, support becomes consultancy. Growth slows. Costs rise. Confidence evaporates.

Agencies pay too. Clients want to move forward but don’t understand what they’re signing up for. Strategy becomes explanation. Delivery becomes risk. Fees stop matching effort. Everyone feels busy; no one feels certain. An easy to confirm first page ranking becomes a ‘possible’ AI summary citation if the wind is in the right direction.

More truths:

  • When clients don’t understand the tech, they don’t trust outcomes.
  • When they don’t trust outcomes, they don’t commit long term.
  • When they don’t commit, adoption never scales.

Now AI and AI-driven search risk the same gap.

AI feels familiar. It fits on top of what we already do: write, search, research, plan. But the systems beneath are opaque. Rankings disappear. Attribution blurs. Decisions come from models that don’t explain themselves. The decision requires a leap of faith and businesses don’t run on faith.

For business leaders, that’s unsettling. Old rules vanish; new ones aren’t clear. Understanding lags behind capability.

When that happens, behaviour shifts. People hesitate. Budgets freeze. Vendors promising certainty gain power. Bad decisions follow.

This isn’t an innovation problem. It’s a comprehension problem.

Technology reshapes society only when it becomes boring enough to feel obvious. When people stop asking what it is and start asking how to use it. That moment won’t come if capability runs ahead of understanding.

The lesson from Web3 and the metaverse: the ideas weren’t wrong, but they weren’t simple enough for mass adoption.

AI won’t escape that fate unless it crosses the same line. The next internet phase won’t be won by the smartest systems. It will be won by the ones that make sense to non-experts.

Because mass adoption happens only when average comprehension is enough. Anything needing more will stay niche, no matter how much money pours in.

OPINION: Cars As iPhones

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On a recent trip to the cinema I was presented with two new car adverts, both glossy. My cynical joke about the Range Rover that the owner was driving into the dealer for warranty work was soon overshadowed by the normalisation of a homogenised MG ‘SUV’ being £35000 as the basic price. But of course nobody pays the cash price nowadays, they mentally justify the purchase as multiples of their iPhone monthly payment. Cars as iPhones is a masterclass in behavioural psychology. 

Sometime in the last decade I described modern car buying as the iPhonication of the forecourt and if anything the idea has aged better than most of the vehicles now sold under it.

There was a time when the first question was the price. The full price. A number large enough to demand a pause and some moral arithmetic. Today nobody asks that. They ask how much a month, and the rest is treated as background noise, like terms and conditions or the weather.

The trick is simple. We no longer evaluate cars as capital purchases but as subscriptions. The monthly payment is quietly reconciled against the iPhone in your pocket. Fifty quid a month for a phone feels normal. Three hundred quid a month for a car becomes six phones. You already live with one. Why not six sitting outside?

This is not financial logic so much as consumer conditioning.

PCP and PCH did not just change how cars are paid for, they changed how they are justified. Ownership became vague, temporary, almost impolite to mention. What mattered was whether the number could slip into the standing orders without causing an argument. Once it could, permission was granted.

Electric cars pushed this model to its logical conclusion. On paper many are startlingly expensive. In practice they arrive softened by language about efficiency, tax, sustainability and the future. The monthly figure does the heavy lifting. Nobody emotionally processes fifty or sixty thousand pounds. They process four hundred a month by comparing it to phones, streaming services and a gym membership they forgot to cancel.

The iPhone model also smuggles in another assumption, that upgrading is natural and permanence is old fashioned. You do not keep a phone for a decade. You refresh it, guilt free, because you were never meant to own it outright. PCP borrows that psychology wholesale. Three years, hand it back, move on, feel modern.

Electric cars lean into this harder than most. Big screens, software updates, range improvements promised just around the corner. They are sold less as machines and more as devices, which makes their disposability feel progressive rather than wasteful.

The danger is that when everything is framed as affordable monthly, nothing feels expensive anymore. Stretch the term, adjust the mileage, tweak the deposit and almost anything can be made to behave. The decision shifts from judgement to tolerance. Not can I afford this, but can I live with it?

That is a profound change. It moves cost out of focus and replaces it with habit. Comparison does the rest.

‘The electric transition is often presented as a clean break from the past, but it has been powered by the most contemporary consumer mechanism of all. Permanent payment and planned obsolescence, wrapped in virtue and delivered by direct debit.’

The propulsion may be changing, but the mindset is familiar. We have not made cars cheaper. We have just learned how to stop looking at the whole number, and how to measure our lives in iPhones instead.

AI: Search Summaries – Christmas 2025 Essay

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I’ve spent 2025 understanding Generative Engine Optimisation and AI Search Summary preeminence at an academic level. The complacency regarding this phenomenon in business is shocking, but from a behavioural psychology perspective not unexpected. Thankfully it’s not too late for your business to capitalise.


The Most Dangerous Assumption in Search Right Now

The most dangerous assumption business owners are making today is not that AI search will fail. It is that it will behave like search always has.

Those working closely with Generative Engine Optimisation already know the uncomfortable truth. Search is no longer primarily about ranking pages. It is about being recognised as a source of truth inside an answer that may never send a click at all. Yet across industries, business leaders remain curiously relaxed. Revenue still comes in. Rankings still look acceptable. Dashboards do not scream emergency.

This is precisely the problem.

AI summaries do not announce disruption with penalties or crashes. They erode relevance quietly. They absorb demand upstream. They reward authority before most organisations realise authority is being measured differently.

For years, visibility meant position. First page. Top three. Number one. The mental model was simple and it worked. Now the interface itself has changed.

‘The search engine no longer asks users to choose. It decides, synthesises and presents a conclusion. If your brand is not present in that synthesis, you are not competing. You are absent.’

Many business owners struggle to internalise this because absence is invisible. There is no warning light for being excluded from an AI-generated answer. Traffic does not collapse overnight. Leads taper slowly. Performance reviews become conversations about seasonality, budgets or market conditions. The real cause remains unseen.

Complacency is reinforced by past success. If traditional SEO, paid media and brand recognition have delivered growth for a decade, it feels reasonable to assume they will continue to do so. That assumption is understandable. It is also historically naïve. Every major platform shift has rewarded early adopters and punished those who waited for certainty.

There is also a deep misunderstanding about what AI systems value. Many businesses believe that being good at what they do is enough. Decades of experience. Strong client relationships. Industry reputation. None of this automatically translates into AI authority.

Generative systems privilege clarity, consistency and structure. They reward entities that are easy to understand, easy to verify and easy to cite. Expertise that lives only in people’s heads, sales conversations or poorly structured content might as well not exist.

This is confronting. It implies that real-world authority is not sufficient. That uncomfortable implication is often dismissed rather than addressed.

‘Another factor is fatigue. Business leaders have lived through years of algorithm updates, platform volatility and digital false dawns. Each new shift sounds like noise until it becomes unavoidable. AI summaries are therefore filed mentally alongside blockchain, voice search or the metaverse. Interesting, perhaps important one day, but not urgent.’

The flaw in that thinking is scale and intent. AI summaries are not an experiment at the edge of search. They are becoming the interface itself. They sit directly between demand and discovery. They collapse the journey from question to conclusion.

When experts raise the alarm, they are often ignored because they are early. Early warnings always sound theoretical. Yet AI systems do not wait for consensus. They learn continuously. They establish citation hierarchies long before markets agree they matter. In other words, they value early adoption.

So by the time AI summary inclusion is widely recognised as critical, the sources deemed authoritative will already be entrenched. Catching up will be far harder than acting now.

This is not about chasing another optimisation tactic. It is about ensuring your business is legible to machines that increasingly decide which voices are heard at all.

‘The real risk is not being outranked. It is being unrecognised.’

Unrecognised businesses do not fail dramatically. They fade quietly, wondering where the demand went, while answers are being given elsewhere.

Steve Coulter is a four decades Sales and Marketing professional and enthusiast who has embraced the Internet and e-Commerce since 1999.

DIGITAL MARKETING: The 2025 Creator Content Premium

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Why Creator Content is Outperforming Traditional Advertising

The marketing landscape has changed dramatically in recent years, with the rise of the creator economy at the heart of this transformation. New research confirms what many marketers have suspected: content made by creators doesn’t just match the impact of traditional advertising, it actually outperforms it. This is true for both long-term brand equity and short-term sales.

What the Research Tells Us

Several recent studies have compared creator content directly with standard industry advertising. The findings are compelling:

– Superior Performance: Creator content consistently beats traditional adverts on measures such as emotional resonance, memorability, and trustworthiness.
– Emotional Connection: Viewers are much more likely to feel an emotional response to content made by creators. In some cases, up to a third of people reported a genuine emotional reaction, which is invaluable for brands aiming to stay top of mind.
– Real Results: Brands aren’t just seeing warm feelings. Around 70% of brands say their most successful campaigns have involved creators, and most believe that creator-led content delivers a better return on investment than conventional adverts.
– Driving Action: Research shows that 80% of consumers have taken action after engaging with creator content, whether that’s looking up a brand, following them on social media, or making a purchase.

Why Are Creators So Effective?

There are a few key reasons why creators deliver such impressive results:

– Authenticity: People trust real voices more than polished adverts. Creators speak directly to their followers, often sharing personal stories and honest opinions. This authenticity is especially valued by younger audiences, who are increasingly sceptical of anything that feels too scripted.
– Emotional Engagement: Creators are skilled at building genuine connections with their communities. When a creator is enthusiastic about a product, that excitement rubs off on their audience, making a real difference to brand recall.
– Relevance: Creator content is often tailored to the interests and needs of a specific audience, making it far more relevant and effective than generic advertising.

The Power of Short-Form Video

Platforms like TikTok, Instagram Reels, and YouTube Shorts have amplified the impact of creator content. Short-form videos are quick, engaging, and perfectly suited to the way we consume media today. Nearly half of UK social shoppers say they’ve bought something after seeing it featured by a creator.

What Does This Mean for Brands?

The message is clear: if you want to make a real impact, it’s time to invest in creator partnerships. As the digital world becomes more crowded and AI-generated content becomes more common, the human touch offered by creators will only become more valuable.

Brands that embrace this shift and work with creators who genuinely align with their values are set to reap the rewards, both now and in the future.

–  “When creators grab and hold attention in social feeds, it generates an extended emotional reaction that fosters deep connections with the brand, driving brand memory and making it easier and faster for audiences to recall brands when making purchasing decisions.” Ben Jeffries, CEO of Influencer.

In summary, creator content isn’t just a passing trend. It’s the new gold standard for building brands and driving sales in the digital age.

MARKETING: The Michelin Brothers’ Lightbulb Moment

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How Michelin Used Behavioural Science to Sell Tyres (Before It Was Cool)

When we discuss successful applications of behavioural science in marketing, we often think of recent digital campaigns with sophisticated data analytics. Yet one of the most brilliant examples dates back to 1900, when the Michelin brothers created what would become one of the most prestigious culinary institutions in the world, originally as a clever ploy to sell more tyres.

A Problem of Demand

In 1900, the automobile industry was in its infancy. In France, where the Michelin tyre company was based, there were fewer than 3,000 cars on the road. For the Michelin brothers, André and Édouard, this presented an existential business challenge: how could they grow their tyre business when so few people owned cars?

The brothers identified the fundamental behavioural challenge underlying their business problem. Car ownership wouldn’t increase unless people had compelling reasons to drive – and drive often. Their tyres would only wear out (requiring replacement) if motorists felt motivated to embark on journeys.

The Behavioural Insight

Their solution was ingenious: create demand for driving itself. The brothers understood a key principle we now recognise in behavioural economics, i.e. if you want to change behaviour, reduce friction and increase motivation.

They published the first Michelin Guide – a free handbook for motorists that contained practical information including maps, instructions for changing tyres, listings of mechanics, and importantly, places where drivers could find petrol stations, accommodation and good food while travelling across France.

The brilliance of this approach was multifaceted:

1. Reduced uncertainty: The guide removed a significant psychological barrier to travel – the fear of the unknown and the anxiety of not knowing where to find essential services.

2. Created social proof: By documenting places others had visited, the guide normalised the idea of recreational motoring.

3. Leveraged the endowment effect: Once motorists received the free guide, they felt compelled to use it.

4. Applied loss aversion: The guide highlighted experiences motorists might miss if they didn’t venture out on the roads.

From Marketing Tool to Cultural Institution

What began as a marketing tactic evolved significantly. In 1920, the guide was no longer free, with André Michelin reportedly saying, “People only respect what they pay for.” By 1926, they introduced the now-famous star rating system for restaurants.

The Michelin brothers had tapped into something deeper than they initially intended (aka the Law of Unintended Consequences) the human desire for quality experiences and authoritative guidance. The restaurant ratings became so prestigious that chefs would dedicate their careers to achieving Michelin stars.

Lessons for Modern Marketers

The Michelin Guide case study offers several timeless lessons:

– Understand the ecosystem of your product: Michelin realised their success depended on the broader adoption of automobile culture.

– Address behavioural barriers: They identified and systematically removed reasons not to drive.

– Create value beyond your product: The guide offered genuine utility that extended far beyond tyres.

– Play the long game: What started as a marketing tool became a complementary business and brand-building exercise that has lasted over a century.

Long before the terms “content marketing” or “behavioural economics” entered our lexicon, the Michelin brothers were pioneering these concepts through intuition and business acumen. They understood that to sell tyres, they needed to sell the journey first.

In our current era of data-driven marketing, the Michelin story reminds us that understanding fundamental human behaviour and motivations remains the cornerstone of effective marketing. Sometimes the most powerful applications of behavioural science don’t come from complex algorithms but from simple insights about what makes people tick, or in this case, what makes them drive.

Next time you’re developing a marketing strategy, ask yourself: What’s your equivalent of the Michelin Guide? How might you create value that extends beyond your product while subtly driving demand for it? I say this looking at the EV manufacturers who are marketing ‘the performance’ of luxury EV brands when buyers already know that!

Steve Coulter is a 35+year career sales and marketing professional. Author and researcher of the digital transformation resource ‘The Definitive Guide To Digital Transformation For Legacy Businesses’ and ‘Audit-Fix-Maximise’ a – do the simple things well – strategy for all digital marketers.