Compensating for the Drop in Organic Clicks: Strategies for Amazon Sellers

The online sales sector is undergoing a new transformation that many Amazon sellers have already noticed.

Click-based traditional search is gradually giving way to direct answers generated by artificial intelligence. In fact, what experts called just a few months ago the phenomenon of “zero-click searches” is already taking shape. A change that is not merely the result of ongoing technological innovation. Rather, it is something that is helping redefine how consumers discover and purchase products online.

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As of today, for example, over 27% of searches on Google in the United States end without any click.
Users are getting the answers they seek directly from the results pages or from AI-generated summaries. This figure, which grows by about 3% year over year, is a clear warning sign for all sellers relying solely on traditional organic visibility. For Amazon sellers, this means that the competition is no longer confined to the platform itself. It now begins much earlier—at the very moment a potential customer asks a question.

The new challenge is particularly complex. AI algorithms do not simply index content—they interpret, summarize, and present it in completely new formats.

Thus, citations are partly replacing clicks as the primary visibility metric, and as a result, they are rewriting the old rules for online selling. Amazon sellers who fail to adapt to this new reality risk becoming invisible just when demand for their products might be highest. But what can be done?

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Why Amazon sellers must rethink their visibility strategies

Amazon is undoubtedly one of the most important platforms for online sales. However, its effectiveness increasingly depends on sellers’ ability to engage customers before they arrive on the platform.

The main issue is that many sellers focus solely on Amazon’s internal optimization. They overlook the fact that product discovery often begins well before that—through voice searches, AI chatbots, and virtual assistants.

When a consumer asks ChatGPT, Gemini, or Alexa what the best product is for their needs, these systems pull from a broad ecosystem of information that extends well beyond Amazon product listings, including:

• independent reviews
• expert articles
• editorial comparisons
• social media mentions

These factors carry far more weight than most sellers realize in determining what products AI recommends.

Here lies the paradox: many Amazon sellers invest thousands of euros in on-platform pay-per-click ads but fail to allocate resources to building a digital presence that AI systems can recognize and cite. Being a top-selling product on Amazon means nothing if AI doesn’t know you exist—or worse, if it associates your brand with fragmented or contradictory information.

The battleground is now much broader. A context in which brand credibility, information consistency, and multichannel presence are critical for inclusion in automated recommendations.

Only those sellers who understand this dynamic have a chance to build a lasting competitive edge. Those who ignore it risk gradually losing market share.

Building authority outside of Amazon

Building online authority requires an approach that goes far beyond Amazon alone. AI systems evaluate brand credibility using signals from multiple sources, creating what we might call a “digital trust index” that directly influences automated recommendations.

The first pillar of this strategy is creating authoritative content that directly answers consumer questions. Not just SEO-optimized product descriptions—but in-depth guides, detailed comparisons, and educational resources that establish the brand as an expert. This content must be structured in a way that AI systems can easily extract and cite when users ask relevant questions.

Diversifying online presence is also essential for building this authority. A brand that appears only on Amazon looks one-dimensional to AI systems. On the other hand, a brand that’s active on expert websites, industry blogs, social media, and independent review platforms gains multi-dimensional credibility. This presence must be consistent in messaging but tailored to each channel.

In this context, collaborations with influencers and industry experts take on new strategic value. The goal is not merely short-term visibility—but long-lasting mentions that become part of AI knowledge bases. A detailed review from a recognized expert can generate AI citations for years, dramatically increasing ROI compared to traditional ads.

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The power of reviews and citations

Independent reviews are now one of the most valuable assets for Amazon sellers—probably far more than most realize. Traditionally seen as a conversion factor once a product is discovered, reviews now serve as a critical bridge between initial search and product discovery.

When AI systems need to answer a question like:

“What’s the best vacuum for pet hair?”

they don’t just pull from manufacturer descriptions, but primarily from detailed reviews, comparison tests, and real user opinions. A single in-depth review on a reputable site can generate more visibility than hundreds of superficial reviews on Amazon. It provides the rich, contextualized content that AI systems favor in their citations.

Amazon sellers must encourage the creation of such content without violating platform policies or compromising authenticity. This requires a sophisticated approach—a model that combines product excellence, flawless customer service, and targeted outreach to bloggers, journalists, and niche influencers.

Proactive reputation management is now a core skill for modern Amazon sellers. It’s no longer enough to just respond to negative reviews. Sellers must create a content ecosystem that consistently strengthens brand perception. One rich and diverse enough to offer multiple AI citation sources.

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Optimization techniques for AI

Sellers must now optimize for AI systems using a completely different technical approach than traditional SEO. While classic search engines rely mostly on keywords and links, AI systems analyze content semantically—they aim to understand meaning and context, not just keyword matches.

The first technical element is structuring data using advanced schema markup. Amazon sellers who manage external websites or collaborate with editorial partners must ensure that product information is coded with standards like Schema.org. This allows AI systems to immediately understand:

• product features
• pricing
• availability
• reviews

greatly increasing citation potential.

Creating Q&A content is another highly effective strategy to match voice assistant and chatbot queries. Rather than listing product features, content should anticipate common consumer questions and provide clear, complete answers. This turns every content block into a potential AI citation source.

Lastly, implement a content clustering strategy—creating interconnected content networks that strengthen each other in the eyes of AI. Instead of isolated articles, sellers should build content hubs where:

• general guides
• specific comparisons
• use cases
• FAQs

are organically linked, creating a knowledge map that AI systems can easily navigate and cite.

Better to diversify channels

Another crucial point is the strategic risk of relying solely on Amazon. Not only because platform policies can change suddenly, but also because it drastically limits discovery through AI-powered new channels.

An effective diversification strategy should combine Amazon presence with brand-owned channels. A well-structured company website should not compete with Amazon but complement it—providing in-depth content, brand storytelling, and educational resources that Amazon doesn’t allow in product listings. The website also becomes an authoritative source that AI systems can cite.

Presence on alternative marketplaces and niche platforms also boosts credibility for AI systems. A product available on Etsy, eBay, specialized verticals, and independent online stores appears more established and trustworthy than one found only on Amazon. Diversification requires more effort, but builds a safety net and amplifies visibility opportunities.

Finally, don’t overlook the value of strategic partnerships with physical and online retailers—a further source of valuable citations. Even if primary sales happen on Amazon, being listed:

• in authoritative retailer catalogs
• in physical showrooms
• in affiliate programs

generates trust signals that AI systems interpret positively.

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How to measure success in the post-click era?

Given all of this, one might ask: how can sellers measure success today?
Traditional ecommerce metrics are no longer enough to evaluate the effectiveness of strategies in the AI era. While CTR and conversions still matter, Amazon sellers must develop new KPIs that reflect their visibility in AI-generated responses.

First, monitor AI citations. This is the next frontier in competitive analysis. Tracking when and how your brand is mentioned by ChatGPT, Perplexity, and others offers valuable insights into how AI perceives your positioning. Naturally, this requires specialized tools and a systematic approach—but it can reveal hidden opportunities and emerging threats.

Sentiment analysis of citations is also key—not just how often you’re mentioned, but in what emotional context. A brand frequently cited in negative or problematic contexts must quickly intervene to correct the narrative before it’s embedded in AI databases.

Finally, focus on the correlation between distributed digital presence and Amazon performance. The most advanced sellers are already identifying clear patterns between:

• external content investments

• AI citation growth

• Amazon sales increases

allowing for optimized resource allocation across channels.

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What is the future of selling on Amazon?

So what does the future hold for Amazon sellers? And how should they prepare for what’s already unfolding?

It’s clear that online sales will continue evolving rapidly. And that Amazon sellers who want to remain competitive must adopt a mindset of continuous adaptation. What works today could be obsolete in months, as AI systems grow more sophisticated and consumer behaviors shift.

Investing in emerging technologies like:

• augmented reality
• advanced voice assistants
• conversational ecommerce platforms

will become increasingly important. Sellers who start experimenting now will gain a significant advantage when these tools become mainstream. This doesn’t mean abandoning proven strategies—but integrating them with innovative approaches that anticipate future trends.

AI-powered personalization is also a massive opportunity for sellers who can collect and analyze detailed behavioral data. Future AI systems will deliver increasingly precise recommendations based on individual preferences. Brands that invest in deep customer understanding will benefit most.

And finally, the need to build a resilient and diversified digital presence is already a strategic necessity. Sellers who combine operational excellence on Amazon with omnichannel visibility optimized for AI will not only survive the transition to zero-click searches—but thrive in an increasingly competitive, tech-driven market.