Those who sell products requiring explanation are not fighting against competitors. They are fighting against a lack of understanding. Why visual explanation formats are the most effective lever in selling complex offerings – and what role Artificial Intelligence plays in the production process.
Some products sell at a glance. A pair of shoes, a bottle of wine, a new smartphone – you see it, you understand it, you want it. And then there are the others: SaaS platforms, industrial components, financial products, technical services, medical devices. Products whose biggest enemy is not price, but complexity. If you don't understand what you're buying, you won't buy it. It's that simple.
The challenge faced by companies with products requiring explanation is fundamentally a communicative one. It's not about making the product better; it's about making it understandable. And this is precisely where an astonishing paradox emerges: the better and more powerful a product is, the harder it often is to convey its value immediately. One could even say: the best products often have the biggest explanation problem.
At the same time, information behaviour has changed radically. According to Forbes, 59 per cent of all senior managers prefer to watch a video than read text when given the choice. This means that even C-level decision-makers – precisely the people who control budgets for complex investments – prefer visual formats. Those who still rely on twenty-page whitepapers in this environment are failing to communicate with their target audience.
The Explanation Problem: When Good Products Fail in Sales
In consumer research, high-priced and complex offerings are referred to as extensive purchasing decisions. This means that customers invest considerable time in searching for information, comparing providers, reading test reports, and weighing risks before making a decision. Philip Kotler's classic 5-stage model of the purchasing decision process clearly shows that the information search and alternative evaluation phase is particularly long and prone to abandonment for complex products.
The problem: in precisely this phase, you are not only competing with other providers, but also with the inertia of not understanding. If you don't understand a technical product, you postpone the decision. If you still don't understand it after two minutes of reading, you click away. And if you generally understand it but feel unable to assess its full implications, you remain sceptical.
Text-based explanations quickly reach their limits with products requiring explanation. They describe functions, but they don't show connections. They list benefits, but they don't create an experience. And it is precisely this experience – the ability to imagine a product in one's own reality – that is the decisive lever for the purchasing decision.
Why Video is the Superior Explanation Format
A recent master's thesis from FH Wiener Neustadt, conducted in cooperation with the Austrian Federal Economic Chamber, investigated the influence of product videos on purchasing decisions in e-commerce. The central finding: product videos exert their effect not directly through the richness of the medium, but through mental imagery. The better customers can imagine how they would actually use a product, the higher the probability of purchase. Particularly noteworthy: perceived product complexity played no role – videos were effective regardless of whether a product was classified as simple or complex (cf. WKO/FH Wiener Neustadt, 2024).
This is a finding with far-reaching consequences: it means that even the most complicated B2B product can be sold with the right visual format if it succeeds in triggering mental images in the customer's mind. It is not the amount of information that matters, but the ability to bring the product to life in the viewer's mind.
Data from market research firm Wyzowl confirms this trend broadly: 91 per cent of consumers watch explainer videos to understand products or services. And 84 per cent of marketing managers surveyed report that videos have helped them generate leads. These figures are not theory; they reflect real campaigns in which explainer videos as a sales tool have measurably contributed to revenue.
The Trust Problem: Understanding Alone is Not Enough
However, it would be too simplistic to view explainer videos merely as an information format. Especially with complex and high-priced products, trust plays at least as significant a role as understanding. Customers must not only understand what they are buying; they must also trust the provider to deliver on their promises.
A recent Ipsos study, conducted in 30 countries, shows how sensitive this trust is: 79 per cent of Germans demand transparency about how content is created. In the comparison phase of the purchasing process, 60 per cent of consumers prefer content on B2C marketing websites that has been created by humans (cf. Ipsos, 2025). This means that authenticity and craftsmanship are not 'nice to haves', but direct trust factors.
Professionally designed explainer videos achieve precisely this. They not only show what a product can do, but also convey competence and diligence. A bespoke explainer video with a well-thought-out story, individual illustration, and clear tone sends a signal: someone here understands what they are doing, and they take the time to make it understandable. In a world where generic content rushes by every second, this diligence is a differentiator.
Where AI Changes the Production Process – and Where It Doesn't
Now it gets exciting, because Artificial Intelligence is currently reshuffling the cards in video production. Not as a replacement for creative work, but as a powerful tool that significantly accelerates certain phases of the production process.
In the conceptualisation phase, for example, AI language models can act as idea generators: they generate initial script drafts, suggest scene sequences, or help translate complex content into an understandable narrative. In post-production, AI tools automate time-consuming routine tasks such as rough cuts, colour correction, audio optimisation, or subtitle creation. This saves not days, but weeks, and gives creative teams the freedom to focus on what AI cannot do: strategy, emotional depth, and brand-appropriate storytelling.
At the same time, there is a clear limit here too. Fully AI-generated videos still consistently perform worse in tests with decision-makers than human-curated content. The reason is obvious: AI can recognise and reproduce patterns, but it cannot think along. It does not understand why a certain metaphor works for a specific target group, why a pause in the right place says more than three additional sentences, or why a particular illustration style creates trust and another distance. Especially with complex products, where precision and credibility are crucial, a generic-looking video can do more harm than none at all.
In the explainer video industry, an exciting trend is therefore emerging: the best results are achieved where AI tools are embedded in a professional production process, not where they are intended to replace it. Templates and automated solutions may work for simple social media clips, but anyone who wants to explain a complex B2B product in a way that actually influences purchasing decisions needs conceptual depth that no algorithm can provide.
Research confirms this finding. A study published in the journal Scientific Reports showed that the perceived explainability of a system influences all dimensions of user trust (cf. Nature/Scientific Reports, 2025). Applied to explainer videos, this means: the way something is explained is at least as important as what is explained. And this 'way' – tone, timing, visual metaphor – remains firmly in human hands for now.
The Intelligent Workflow: Human and AI in Interaction
The future of explainer video production lies not in the choice between human and machine, but in their intelligent interaction. The formula that is increasingly proving successful in practice is this: AI takes over everything that is fast, scalable, and rule-based. Humans take over everything that requires empathy, judgment, and creative decision-making.
Specifically, this means: AI-supported research and data analysis provide the content basis. AI tools accelerate the visualisation of drafts and help to efficiently produce variants for different target groups or platforms. And AI-based performance analysis shows after publication which content works and where optimisation is needed.
But the core – the strategic conceptualisation, the script and storyboard, the illustration, the emotional direction – remains human work. Not for nostalgic reasons, but because this is precisely where the difference arises between a video that informs and one that sells. A study by the Medienanstalten underscores this with an impressive finding: nine out of ten respondents demand binding transparency about when AI is involved, and clearly prefer content where human curation remains recognisable (cf. Medienanstalten, Transparency Check, 2024).
The Right Target Audience, the Right Format
Another aspect often underestimated in video production for complex products is target group differentiation. Not every recipient needs the same explanation. A technical buyer needs different information than a managing director, an end customer different from a sales partner.
AI can also make a valuable contribution here by helping to efficiently tailor content to different target groups: shorter social media versions for the awareness phase, detailed product explanations for the consideration phase, technical deep-dives for specialist decision-makers. Those who know their target audience preciselycan produce a whole arsenal of sales tools with a single video project – more efficiently than ever before.
The WKO study recommends using videos specifically in the comparison phase, precisely where customers are weighing up different options. Here, explainer videos most strongly influence the purchasing decision because they activate mental imagery and reduce uncertainties.
Conclusion: Those Who Explain Clearly, Sell Better
Complex products don't need simpler messages. They need better explanations. Explainer videos are not a pretty extra for the website, but a measurable sales tool that works at the crucial points of the customer journey: where understanding is created, where trust grows, and where purchasing decisions are made.
Research is clear: product videos enhance mental imagery, and this imagery is the strongest predictor of purchasing decisions – regardless of how complex the product is. At the same time, professionally produced videos send a signal of competence and diligence, which is invaluable in an era of growing scepticism towards generic content.
AI makes the production of these videos faster, more scalable, and in certain phases, cheaper. It accelerates research, facilitates variant production, and automates routine tasks in post-production. But it does not replace the conceptual depth that a professional explainer video provider brings. Because in the end, it is not technology that determines the success of a video, but whether it tells the right story in the right way.
If you want to sell complex products, you have to stop talking about features. And start making them visible.
