Giulia Panozzo’s neuroscientific approach challenges the dominant models in digital marketing, showing how cognitive biases and inconsistent design choices can sabotage even the most sophisticated strategies
Welcome to a new episode of SEO Confidential, the series where we listen to the most authoritative voices in fields such as search, SEO, marketing and user experience; professionals, journalists, analysts, scholars and researchers who work in the trenches every day and help us understand what is changing, why it is changing, and how to navigate with greater awareness this new era dominated by AI-powered answer engines.
The guest of this episode is Giulia Panozzo, one of the most interesting and thought-provoking voices you can find today at the intersection of neuroscience and applied marketing. A neuroscientist by training, with a degree in psychobiology and a master’s in neuroscience, she has years of advanced academic research behind her and works in London as a consultant, speaker and trainer for international brands.
She is a licensed psychologist in Italy, a guest lecturer at leading British universities and a speaker at top-tier events such as TEDx and BrightonSEO.
Her approach is rare because it is concrete and scientific: fewer slogans, more real understanding of human behavior.
Giulia, besides being a highly regarded researcher, is also a clear and expert communicator, able to make complex concepts such as those of neuroscience understandable even to non-specialists, without this compromising in the slightest the rigor and precision of her words. And that, in my opinion, is exactly what makes this conversation particularly valuable.
This interview goes straight to the point, talking about what really happens when you capture people’s attention and then fail to hold it, when the slightest friction ruins months of work, when negativity works in the short term but presents the bill over time.
If you work in marketing, search or UX, you will find yourself rethinking many certainties: because data matters, but the way you interpret it matters even more.
With these necessary premises out of the way, let’s get started!
“Negativity is a terrible trust builder. It works to catch the eye, but it can backfire”, Giulia Panozzo told us
In your article “Negativity Bias: Why Customers Don’t Want Anything To Do With You (And What To Do About It)” you write that people remember a negative experience far more vividly than many positive ones. Why, in your view, do so many companies keep using aggressive or ambiguous messaging to grab attention, even knowing they risk driving customers away instead of earning their loyalty?
Because they only see one part of the customer journey. We often hear that “attention is the new currency”, but the risk is forgetting that the consumer’s journey does not end there, at the moment of the click. In a context where we are literally bombarded by stimuli, digital and otherwise, capturing attention is certainly a fundamental requirement, but it is only the first micro-decision in a much broader process in which the user interacts with a website, a service or a product. Yet many companies keep relying on the “exploitation” of cognitive biases (negativity bias, for example) to capture attention, only to then fail to keep the promise made to the user at the moment of conversion.
A typical example: we see scarcity messages everywhere, but then the same offer reappears a thousand times and is no longer credible, a bit like those mattress commercials we used to see on TV in the ’90s; or we see aggressive, negative comparisons with a competitor, which reflects badly on the brand. It works to catch the eye, but not to build trust. The point is that users are not naive, and today they are far more competent and aware than many old sales strategies continue to assume.
On top of that, many teams still work in silos: they only handle the “acquisition” part, not what comes after. It is not a problem of missing data, it is a problem of an outdated mental model of what people really need. Grabbing attention is no longer enough: you have to hold it, deliver what you promised, and do it in a context where the user can walk away in a second for a dozen alternatives. If attention is the first requirement, user trust is what seals the contract.
At a biological level, negativity attracts attention almost automatically because it signals potential threats: we are more sensitive to what we might lose than to what we might gain (the principle of “loss aversion”), and professionals in our industry are well aware of it. However, even though it is an effective attention accelerator, negativity is a terrible trust builder.
How can this mechanism turn into a boomerang? Can I ask you for a practical example of how a strategy based on negativity ended up damaging a company’s experience or reputation?
Several brands exploit negativity, sometimes quite literally with hostile or aggressive messages to stand out from the crowd and attract attention, but other times also unintentionally, triggering negative reactions from users. And the old saying “there’s no such thing as bad publicity” works less and less in an omnichannel context, where every impression cascades onto other brand experiences and content the user comes into contact with. Negativity, in fact, does not act on attention alone, it also affects memorability. If the first impression is negative, it certainly makes the brand “stand out”, but it is very likely that that negative note will linger and contaminate subsequent recovery efforts as well. And this becomes a boomerang especially when the brand lives on trust or experience.
Examples that come to mind are Brewdog and Ryanair, which lean heavily on affronting the customer and on brashness in their marketing strategy to set themselves apart; the former suffered a major backlash the moment their ‘punk’, non-conformist image was joined, in the public eye, by toxic corporate practices and unorthodox behavior from one of the founders.
And Ryanair too, which makes a living out of its no-frills airline image, even bluntly and shrewdly attacking users who dare to complain on social media, had its share of customer losses the moment its deliberately negative image became associated with experiences of a non-existent customer service. This shows how, very often, a brand’s identity is inseparable from its internal dynamics and the people involved.
And then, in general, all the news media that exploit negativity for clickbait (local examples where I live include the Daily Mail and The Sun, which tend to be considered a league below other outlets precisely because of this tendency).
You argue that a single moment of frustration, even at the very end of the journey, is enough to ruin the perception of a brand. How underestimated, today, is the impact of very concrete problems such as a complicated checkout, unclear information or pages that simply don’t work?
In my experience, very much so. And this is a common problem especially in large companies, where UX, Customer Experience, SEO and Marketing often work separately and with no real opportunity to collaborate. The point is that we need the data from all of these areas to inform a better experience, one that translates not only into greater user satisfaction, but also into better search and performance results – especially now that a normal journey of discovery, evaluation and acquisition relies on several integrated channels.
That is also why I always try to act as a bridge between these teams. When they remain in silos, the impact of a sub-optimal experience is almost never fully understood, both because the information is fragmented and because each team uses different reporting systems and KPIs.
And here comes the “boomerang moment”: a single point of friction, even at the end of the journey, is enough to compromise the overall perception of the brand. The risk is taking for granted that the user is already convinced, when in reality trust is at stake at every point of the experience.
Baymard Institute, for example, has been showing for years how small frictions in the checkout can have huge impacts on abandonment rates, even when the rest of the experience is flawless. The same reasoning applies to dark patterns: they attract conversions in the short term, but erode trust in the long run.
The paradox is that we invest enormously in getting people to the bottom of the funnel, and then we lose them over one extra mandatory field or a button that can’t be seen.
In digital marketing there is a lot of talk about emotions and user centricity, and yet experiences full of obstacles keep being built. Why, from your point of view, do many companies invest so little in giving people a truly positive and coherent experience?
Because of a lack of data and a lack of real “prioritization” of the user experience. It is easy to call yourself “customer-centric”, but in the end it is always the numbers that drive decisions, especially in large companies. So user centricity risks remaining a slogan, without concretely translating into coherent initiatives, especially when you rely on traditional metrics that only reveal user behavior on the surface, without investigating what happens inside the user.
Traditional metrics measure the product of attention (time on page, CTR, etc.), but they do not measure how an emotional experience translates into loyalty. And since many companies struggle to translate emotions into operational metrics, this creates a prioritization problem “at the top”.
And if we cannot investigate emotions with traditional tools, we end up focusing only on metrics that are the result, not the cause, of a positive experience (clicks, transactions, retention) or a negative one. Some companies use NPS or proprietary surveys, although these are often a “nice to have” rather than a strategy driver. But still very few companies actually go and investigate what produces those results through more sophisticated methods such as measuring the pre-conscious response to certain messages or materials.
Sometimes the obstacles we see in the user journey also come down to a matter of internal alignment: what works for the team that works on the site is assumed to be universal (something we see a lot in localization or taxonomy, for example). And other times the lack of coherence is a deliberate choice: introducing friction or ambiguity to “push” the user toward a specific action, at the risk, however, of creating confusion and driving them to consider alternatives.
Giulia, we have seen how today many companies measure search success almost exclusively with quantitative data such as clicks, traffic and CTR. So, can you tell us which specific behavioral signals they should be watching instead, in your opinion, to understand where and why people really get stuck along the search journey, even before reaching the conversion?
I have an article dedicated to exactly this topic on Search Engine Journal. To really understand where the search journey breaks down, looking at clicks, traffic or CTR is not enough, because those numbers only describe the final outcome, not what determined that result.
What we need is to observe behavioral data, which is far more predictive and stable than algorithmic changes. Broadly speaking, I would group it into three big categories:
- Discovery channel indicators
They tell us where people start their search and why. We no longer start from Google in a linear way: the journey has become a loop of exploration and evaluation that runs through social, communities, UGC, forums, marketplaces, LLMs and search engines (what we now know as the ‘Messy Middle’).
Knowing which channels users come from helps us understand their motivations, expectations and information gaps, and gives us insight into what types of content and formats are best suited to capturing and holding attention for a given demographic group. This helps us align messages and content with our target audience across different channels, for cohesive and effective branding.
- Built-in mental shortcuts
These are biases and heuristics that guide decisions and attention in moments of cognitive load, and many times we can already identify some of them from the way a user phrases a search, through the words they use.
In the context of search and keywords we often see phrases that indicate confirmation bias, familiarity, loss aversion, social reinforcement, for example.
These patterns explain the quality of choices, the expectations behind the search, and where friction turns into abandonment. Besides informing us about what the user expects to get, common biases and heuristics also give us a window into the messaging and experience best suited to the user at that specific stage of the search.
- Underlying needs
These are the real reasons a search begins: reassurance, information, social reinforcement, convenience, risk reduction, and so on.
When these needs go unmet, the user does not abandon because they are “not interested”, but because they did not find the answer they were looking for.
Many of these can be grouped through social listening and analysis of online forums (especially in the pre-acquisition phase), post-purchase surveys, reviews and customer service chats.
In terms of specific behavioral signals, in addition to the engagement rate for key pages of interest and frequent drop-off points, I also recommend using heatmap data that shows us where the user clicks and scrolls (and above all where they don’t), and eye-tracking data that reveals the user’s eye movement patterns.
More and more businesses invest heavily in being visible everywhere, but then offer confusing or exhausting experiences. What are, in very practical terms, the most common mistakes that break the search journey today and cause even highly motivated users to be lost?
Very concretely, and often tied to the e-commerce world:
- lack of reviews;
- landing pages for offers from social media that redirect to the home page;
- filters that are confusing or not aligned with the user’s language;
- incomplete localization (not just in the language, but in the currency used, for example, which does not switch automatically from one country to another);
- perceived physical distance, especially in international markets; the absence of a physical location or local customer service tends to produce distrust;
- a journey that is too long, with too much information requested or unnecessary add-ons (like on every flight booking site, let’s be honest);
- on the same theme: no guest check-out;
- missing information that the company takes for granted (on return policies, shipping costs not calculated, the purchase process and FAQs);
- last but not least: no images/videos! Especially when it comes to a physical product, many people make decisions based on what they see, not on the product specs at the bottom of the page.
When users have to work too hard to resolve ambiguities, they tend to abandon, even if they are motivated.
As search increasingly shifts to different platforms and to AI-based systems, which user behaviors remain surprisingly stable and are still ignored by those designing search and content strategies?
The search for authentic content and opinions. This pattern is surprisingly stable even across digital “revolutions”. We used to trust word of mouth, and even though the purchasing platforms have changed, the fact remains that other people’s opinions and experiences are extremely important to validate our choice, which is why we go looking for social reinforcement through reviews.
A 2023 report highlighted how Gen-Z and millennials consider the presence of reviews and UGC on a site essential to completing a purchase – however, if these look too perfect or manipulated, they no longer trust them and turn to social media instead in search of authenticity. In fact, for some it is almost the first step.
And even there, when they recognize a paid partnership, they disengage completely because they do not perceive the product validation as authentic. So as brands we should let the quality of the product or service do the talking, instead of resorting to artificial validation strategies.
Your research shows that the nervous system distinguishes AI-generated content from human content at a preconscious level, but that this difference does not always drive the final choices. In concrete terms, why do people end up trusting or distrusting a piece of content anyway, even when they “feel” that something is off?
Because choices are rooted in past experiences and individual expectations. We talk a lot about emotions in universal terms, but in reality each of us lives within our own emotional spectrum, built over time.
This emerged clearly in a pilot study of mine where I measured nervous system activation in response to advertising videos that were either AI-generated or human-made: the participants’ pre-conscious response was very different and unpredictable, and looking at the post-experiment questionnaires I could see that it was linked not to the nature of the image or the message, but to the past experiences and personal conceptions they had of the brand.
For example, one participant showed a stronger emotional response to an ad that I had always found very moving, but the reason for their activation was different: it was, in fact, because they detested the brand. While another participant responded much more markedly to an artificially animated ad because they used to watch it at Christmas with their family, so the activation we saw on the sensor was due to nostalgia.
This is why it is always important to integrate qualitative measures with quantitative ones: they give us a much more complete spectrum of the human experience, which is diverse and very hard to translate into numbers. And above all, it is important to know the perception people have of our brand, the implicit associations they link to our identity, so that the experiences we offer do not come across as off-key.
You have written that AI works well when it informs and simplifies, but becomes dangerous when it fakes competence, authority or emotional involvement. In practice, which uses of AI should set off alarm bells for a company that does not want to lose credibility and trust in the eyes of its users?
The alarm bell rings when scaling comes at the expense of authenticity. At many moments of the acquisition journey, people look for reassurance, they trust other humans. If the first impression is built with AI, the feeling is that there is no one “putting their face on it”. We see this with artificially generated influencers or authors used to scale content: it works on volume, but not on trust.
The same goes for advertising campaigns: when AI simulates emotions or “humanity” in a way that is not aligned with the brand’s expectations (as in the case of the Coca-Cola Christmas campaign, or McDonald’s, Ed.) the result is a flop. Transparency about the use of AI should be a value, even though today there is still no strong regulatory incentive.
There is a lot of talk about “AI replacing humans”, but your work suggests a different scenario, based on collaboration. Which human skills remain genuinely non-automatable today, and why do they keep making the difference in marketing and in the relationship with users?
In my opinion, AI is not yet able to extract context from information in an effective and systematic way. That is why we see “regurgitated” content that we recognize almost immediately, beyond the infamous em dash! It has to be continuously fed and refined by us, by our experiences and our content, or it risks adding nothing new or useful to the user experience.
I would say that, for now, the ability to extract contextual cues, empathize and make inferences remains a human prerogative. These are skills built over time through lived experience, and they are fundamental in marketing when it comes to connecting with users and their needs.
To this I would add what we call “gut feeling”, our visceral reactions to certain situations: AI helps us rationalize, but many decisions require and give great weight to intuition, to first impressions and to what we, as humans, feel in response.
And finally there is diversity: different perspectives generate innovation and reveal blind spots that a statistical model cannot have. This is the reason why AI models, despite technical advances, still exhibit significant biases that risk anchoring user experiences to a single distorted perspective, one that perpetuates itself over time if it is not corrected with critical thinking.
Below you will find the video where I comment on the interview with Giulia Panozzo. I would love to know what you think, I’ll see you in the comments.
The difference between getting noticed and getting chosen
If you work in search or marketing and run a business that operates online, this conversation concerns you directly. Because the point is no longer managing to get noticed, but understanding what happens next.
Attention is won in an instant, lost just as quickly, and guarantees nothing unless it is sustained by a coherent experience. Continuing to read success only through clicks, impressions and traffic spikes means observing the final effect while ignoring the causes that produced it.
Search is changing its structure, answer engines are multiplying, AI accelerates and amplifies every choice. But people’s behavior remains surprisingly stable.
They abandon when they encounter friction, ambiguity, broken promises. Not because they are not motivated, but because they are more competent, more demanding and far less willing to “work” for clarity. This is where many strategies break down, precisely when they seem to be working.
Today the difference is not made by those who push harder, but by those who best align messages, content and experience.
Those who spot the signals before they turn into abandonment.
Those who accept that search is not an orderly funnel, but a complex system made of expectations, memory and context.
The question I want to ask you, at this point, is: are you working to capture fleeting attention, or to be chosen tomorrow too, with consistency and continuity?
