Amazon's latest AI advancements mean your success hinges on whether your Amazon listings align with buyer intent.
Amazon’s latest research is making one thing clear: if your listings don’t align with buyer intent, you’re leaving money on the table.
Understanding how customers search, and why, gives you a serious edge.
After all, 96% of B2B marketers say they hit their goals when using intent data.
It’s time Amazon sellers pay attention.
Cognism"Intent data provides insights into the online behaviours of a target audience."
Amazon's AI Closes the Search Gap
In today’s rapidly changing landscape, shoppers frequently use negation in their product searches to specify unwanted features. However, traditional search engines often struggle to comprehend these negative requests, leading to less-than-optimal shopping experiences.
The fundamental challenge lies in the vocabulary gap between a customer’s query keywords and the actual product descriptions. For instance, a shopper might search for “no fingerprints,” but relevant products are described with “anti-smudge” properties.
Amazon Science reported about its latest research on this challenge. They introduced a query rewriting approach designed to elevate the performance of product search engines when handling these complex negation queries.
This innovative approach leverages Large Language Models (LLMs) to extract valuable query rewrites directly from existing product text. A Seq2Seq model was then trained to generate accurate query rewrites for unseen queries, effectively bridging this communication gap.
Experiments with this new method demonstrated significant improvements in search precision. Specifically, query rewriting yielded a 3.17% precision@30 improvement for queries containing negations.
These promising results are a testament to Amazon’s commitment to enhancing the search experience for customers and sellers. They pave the way for further research aimed at continually elevating search performance for all types of complex search queries.
Dock"71% of B2B organizations collect buyer signals, but more than half of those organizations are not operationalizing the data."
Why your listing language matters more than ever for intent matching
Will Haire shared on LinkedIn his insights about the latest research, highlighting a long-standing problem in Amazon search. Customers often specify what they don’t want, yet traditional search engines frequently display exactly that, hurting both the customer experience and seller conversion rates.
The core issue stems from how traditional search engines handle negations and a persistent language gap between customer queries and product listings. For example, a shopper might search for “no fingerprints,” while a product features “anti-smudge” in its description, creating a missed connection.
Now, Amazon is actively addressing this challenge. They are leveraging Large Language Models (LLMs) to automatically rewrite negation-based queries into product-aligned language. This means a search for “no glare” can now be reinterpreted as “anti-glare,” enabling Amazon to surface the most relevant products if your listing speaks the same language.
This evolution brings significant implications for eCommerce sellers. Your listing language now matters more than ever, as Amazon’s rewrite model actively seeks clear, affirmative features rather than the absence of something. Sellers should focus on updating copy to reflect concrete benefits, such as “wireless” or “anti-odor,” instead of phrases like “no cords” or “doesn’t smell.”
Optimizing for this new system could elevate your product’s visibility. Listings may begin appearing for long-tail searches that previously failed to convert, boosting your overall impressions.
To create content with precision is also paramount; listings with vague or generic benefits risk being overlooked in this improved search alignment. To ensure your products are matched to negation-based queries, your titles and bullet points need to precisely mirror the phrases Amazon’s models are rewriting to.
Amazon’s internal testing has already shown compelling results from this approach. When the rewrite model was used correctly, relevant search results increased by up to 15%, translating directly to more qualified traffic for optimized sellers.
Ultimately, this is a clear signal that Amazon is strongly focusing on semantic relevance. If your Amazon listings don’t align with buyer intent and speak the same language as customer searches for products, you risk missing out on this dynamic opportunity.
A9’s smarter search demands intent-focused listings and content marketing
Amazon’s A9 algorithm is becoming more sophisticated, now prioritizing semantic understanding over traditional keyword matching. This means the platform is learning to interpret why a shopper is searching, not just what they’re typing.
Chris Jensen shared on LinkedIn that sellers should focus on user intent when optimizing listings. Amazon’s search engine is beginning to evaluate purchase-readiness and content relevance based on context, not just keyword inclusion.
Instead of simply matching “kids art set” to product titles, A9 now interprets whether the buyer is looking for a birthday gift, school supplies, or something educational. It also connects related ideas, like surfacing STEM toys when someone searches for “educational gifts.”
To keep up, sellers must rethink their content strategy and understanding search intent:
Maintain keyword usage, but avoid keyword stuffing.
Align product titles, bullets, A+ content, and reviews with customer motivations.
Ensure visuals (images, video) and FAQs reinforce the product’s use case and value.
Content that speaks directly to buyer goals will likely rank higher. Listings optimized around “what the customer wants to solve” stand a better chance in this evolving algorithmic landscape.
This shift is a clear signal: Amazon is rewarding listings that mirror real-world shopping behavior. Sellers who build listings around intent-driven content, not just technical SEO, are positioned for better visibility and stronger conversions.
Holistic listing optimization from back to front
To truly ensure your Amazon listings align with buyer intent, a comprehensive approach encompassing both front-end and back-end optimization is crucial. Overlooking discoverability attributes in the back-end of your listing can prevent your product from appearing in filtered results, regardless of how polished your title, bullets, or images may be.
This often proves especially critical for consumable and topical products, where customers constantly utilize filters to narrow down options by format, flavor, ingredients, and certifications. Despite this, many brands launch with half-complete flat files, mistakenly assuming their product is fully covered simply because the front end looks visually appealing.
To fully leverage Amazon’s evolving search capabilities, sellers must diligently fill these crucial discoverability attributes in the back-end. This effort should go hand-in-hand with optimizing your title, bullet points, and A+ content for maximum impact. An experienced Amazon agency can provide invaluable expertise in identifying and completing these vital back-end fields.
Here are some key back-end attributes to focus on for enhanced discoverability:
- Item Type Keywords (ITK) – Designated as
item_type_keyword, these automatically assign products to the correct browse nodes, primarily used within the US marketplace. - Style-specific Terms – Captured by
style_keywords, these are essential for describing apparel items, such as “ankle-boots” or “fur-lined,” enabling precise filtering. - Subject Keywords – Identified as
subject_keywords, these are specifically intended for describing Media products to enhance their search relevance. - Subject Matter – Using
thesaurus_subject_keywords, this field helps describe what is visually depicted on a product, for example, a poster depicting “horses.”
By diligently completing these back-end elements, sellers can significantly elevate their product’s chance of being discovered by customers with precise purchasing intent. This meticulous attention to detail ensures your listings are fully optimized for Amazon’s increasingly intelligent search algorithm.
