Alexa+ new Amazons strengthen brands to rethink their marketing strategy

While Amazon prepares to support Alexa+, brands face an urgent need to adjust their digital strategy for aloud purchases. Recent patent findings suggest that Alexa’s integration with the intelligence of Amazon’s Rufus products will prioritize brands with comprehensive data attributes and daily, conversational in their lists. This shift creates both challenges and opportunities as traditional word optimization gives way to a more attribute -based approach, conversation to product content.

Optimization for that ‘SEO’ in Amazon

The recently discovered patent for Amazon’s Alexa-Rufus integration reveals a fundamental shift in how products will be discovered. While traditional research optimization focuses on matching specific keywords, Alexa+approach focuses on product attributes – structured features and specifications that the items determine.

“This patent is full of the word” attribute. “Itema content article may have an attribute set with an attribute, on the other hand, associated with an attribute value. For example, if given an item of content is a cell phone, its attributes may include color, operating system, memory size, type of storage capacity.”

As I mentioned in a previous post for stale Regarding the implications of this new technology, the purchase of shopping is set to roll out of “Find products, then research attributes” to “specify attributes, then discover qualifying products”.

For brands, this signals a critical change in content strategy. Success will increasingly depend on how completely the product attributes are documented and structured, rather than simply included the key words in titles and bullet points.

Structured data in a conversational world

Alexa’s ability to answer extensive questions by gathering information through numerous products presents a new dynamic -converter discovery. When consumers ask questions like “How much watt uses an RV microwave?” Or “Can I put plastic dishes on a container washing machine?”, the system will withdraw the corresponding attribute data from the entire catalog.

This creates some major imperatives for brands:

1. Complete all fields of attributes: Brands should fully populate all relevant areas of the product, including optional ones. Missing attributes may mean exception from Alexa+responses.
2. Use everyday language: Involvement of ordinary terms and natural language in product descriptions becomes essential, as the system extracts terms like “plastic dishes” from conversational questions.
3. Provide comprehensive technical specifications: Accurate measurements, capacities, materials and technical details must be included in the areas designated to answer specific attribute questions.

Morgan McAlenney, the lead of trade growth in the public label, advises brands to rethink how their content sounds in voice interactions: “Product data must be friendly and most importantly, aware. Have you heard, really heard, how Alexa speaks to your brand?

Recognition of brand in first voice purchases

Another critical dimension is brand recognition. In traditional visual interfaces, products can draw attention through images, signs or prominent placement. In sound interactions, brands must be specifically required to emerge.

Kara Babb, an e-commerce consultant and former Amazon employee, underlines the challenge: “The difference between a client who says’ Alexa buy electrolytes in Amazon ‘vs’ alexa, buy plink! Electrolytes in Amazon.” Amazon will buy the ‘Amazon selection’ for electrolytes, VS the specified brand. “

This dynamic creates a double imperative: optimizing the product content for Amazon systems, while at the same time constructing brand recognition outside the platform.

“Brands can choose or invest time/resources in building their brand through social, PR, creators or squeezing every last currency from the PDP in Amazon and operations to be a symbol of Amazon’s choice every time (loss of battle),” Babb notes.

Historical data factor

The patent also reveals that Alexa+recommendations will not only come from product attributes but also from user behavior data. According to Bell, the system considers “historical transactions, which will include purchasing plastic dishes, cases of plastic dishes that are added to the carriage, the carriage of virtual purchases … add the carriage rate, the purchase rate, and then the searches associated with plastic vessels”.

This suggests that strong historical performance products can have an advantage in Alexa+recommendations, potentially creating a challenge for newest lists. It also shows that driving traffic, chairs and conversions remain important in this new paradigm as well.

Importance Filtering: A new ranking factor

The patent describes a “importance filtering model” that determines whether a product is semantically important for a question. This machine learning model adds another layer to the detection process, beyond the matching of simple attributes.

For brands, this strengthens the need to ensure that the content of the product clearly communicates the cases of use, goals and relationships with wider categories. Content should create importance not only for specific research terms, but for the concept that is underlying a question.

Preparation for loud discovery

While Alexa+ begins to roll in the coming weeks, brands need to take some proactive steps:

1. Audit products lists for completing attribute

Perform a complete summary of your Amazon product lists to ensure that all possible areas of attributes are populated. Pay particular attention to the technical specifications, materials, use guidelines and often asked questions.

2. Optimize for conversational language

Review the content of your product with one eye towards the way it would sound in a voice interaction. Include daily phrases and questions that customers can ask orally, not just the terms they can write in a search box.

Lauren Morgenstein Schiavone, a former EXCELLANE OF P&G and AI’s business strategy consultant, notes: “Purchase will be formed from daily conversations, not just research. If you ask Alexa for dinner ideas, it will begin to learn your preferences. So later,” Alexa, ” oat milk. “

3. Test the presence of your brand voice

Actively test how your brands and products appear in sound interactions. Ask Alexa questions about the category of your products to understand what information it offers and if your products are mentioned.

4. Strengthen brand recognition

Invest in building awareness of brand and memory through marketing, PR and social media. When consumers specifically require your brand by name, you bypass the choice of algorithm as to which product to recommend.

Will the sponsored content evolve?

Sponsored placements have already been observed within the companion of Rufus purchases at Amazon.com and the Amazon shopping application.

While the patent does not clearly address the advertising or sponsored content, Alexa+ evolution raises questions about the future of promoting the product in the first loud environments.

Currently, Amazon advertising products require visual real estate to appear. How can promotional opportunities be developed in a first loud environment? Will brands eventually be able to sponsor answers to category questions, similar to how sponsored products appear in search results today?

These questions remain unanswered for now, but brands need to monitor developments closely as Amazon continues to evolve his voice shopping skills.

A fundamental change of detection

The integration of Alexa’s voice with Rufus’s product intelligence signals a potentially transformative shift in how consumers detect products online. For brands, this requires a strategic reassessment of how the product content is structured, how comprehensive are their attribute data and how they build recognition outside the Amazon ecosystem.

“We’re heading towards the lists of products that are even more conversations,” Bell suggests. “In that way, when all the information is extracted from the product detail pages, they must be simply full of conversational languages.”

While buying aloud evolves from a novelty on a general discovery route, brands that fit faster in this new paradigm are likely to gain competitive advantages in visibility and recommendation setting. Theelli is the understanding that optimization for Alexa+ is not just about adding some key words-it has to do with building a comprehensive product rich in attributes that can be understood by the systems and effectively delivered through the sound.

For a deeper understanding of how Alexa-Rufus Amazon’s integration works and its technological foundations, read my escort in a patent that reveals the Amazon product detection strategy.