Amazon is gearing up to introduce Alexa+, prompting brands to rethink their digital strategies for voice-powered shopping. Recent patent discoveries hint at a fusion of Alexa with Amazon’s Rufus product intelligence, emphasizing the importance of detailed product attributes and conversational language in listings. This shift poses challenges and opportunities for brands as they navigate away from traditional keyword optimization towards a more attribute-focused and conversational approach to product content.
Optimizing for AI ‘SEO’ on Amazon
A newly unearthed patent concerning Amazon’s Alexa-Rufus integration signifies a significant change in how products will be found. While conventional search optimization centers on matching specific keywords, Alexa+ is set to prioritize product attributes—the structured characteristics and specifications that delineate items.
Ecommerce Manager Andrew Bell, analyzing the patent, notes the prevalence of the term ‘attributes’: “This patent is full of the word ‘attributes.’ That’s the number one word used.” Each content item will now boast a set of attributes, with each attribute linked to an attribute value. For instance, attributes of a mobile phone may include color, operating system, memory size, processor type, and storage capacity.
As highlighted in an earlier article for Forbes, this technological evolution will flip the shopping journey paradigm from “finding products, then researching attributes” to “specifying attributes, then discovering qualifying products.”
For brands, this paradigm shift mandates a fundamental transformation in content strategy. Success will increasingly hinge on comprehensive documentation and structuring of product attributes, rather than solely focusing on incorporating apt keywords in titles and bullet points.
Structured Data in a Conversational World
Alexa’s adeptness at addressing broad questions by amalgamating data across multiple products introduces a conversational twist to product discovery. When consumers pose queries like “How many watts does an RV microwave use?” or “Can I put plastic dishes in a dishwasher?”, the system will amalgamate relevant attribute data from the catalog.
This development drives key imperatives for brands:
Complete All Attribute Fields: Brands must meticulously populate all pertinent product fields, including optional ones. Omissions in attributes could result in exclusion from Alexa+’s responses.
Use Everyday Language: Injecting colloquial terms and natural language into product descriptions becomes pivotal, as the system extracts terms like “plastic dishes” from conversational queries.
Provide Comprehensive Technical Specifications: Precise measurements, capacities, materials, and technical specifics should be included in designated fields to answer attribute-specific queries.
Commerce Growth Lead at PUBLIC LABEL, Morgan McAlenney, advises brands to reevaluate how their content resonates in voice interactions: “Product data needs to be voice-friendly and more importantly context-aware. Have you listened, really listened, to how Alexa discusses your brand? What queries do consumers actually pose, not just how you put it?”
Brand Recognition in Voice-First Shopping
Another critical aspect is brand recognition. Whereas products can seize attention through images, badges, or prominent placement in traditional visual interfaces, brand differentiation in voice interactions necessitates a specific request for brands to stand out.
E-commerce consultant Kara Babb underscores this challenge: “It’s the difference between a customer saying ‘Alexa buy electrolytes on Amazon’ vs ‘Alexa, buy Plink! electrolytes on Amazon.’ Amazon will acquire the ‘Amazon’s choice’ for electrolytes rather than the specified brand.”
This interplay engenders a twofold imperative: honing product content for Amazon’s AI systems while concurrently bolstering brand recognition beyond the platform.
Babb further remarks, “Brands can opt to either invest resources in bolstering their brand via social, PR, creators OR extracting maximum value from their Amazon PDP’s and operations to secure the Amazon’s choice badge every time (an uphill struggle).”
The Historical Data Factor
The patent divulges that Alexa+’s recommendations won’t solely hinge on product attributes but will also incorporate user behavior data. According to Bell, the system will consider “historical transactions, including purchases of the plastic dishes, instances of plastic dishes being added to the cart, virtual shopping cart, add to cart rate, purchase rate, and searches related to plastic dishes.”
This hints that products boasting robust historical performance may enjoy an edge in Alexa+’s recommendations, potentially posing a challenge for newer listings. It further underscores the enduring significance of driving traffic, add-to-carts, and conversions even in this revamped landscape.
Relevance Filtering: A New Ranking Factor
The patent delineates a “relevance filtering model” dictating whether a product aligns semantically with a query. This machine learning model adds a new dimension to the discovery process, surpassing simple attribute matching.
For brands, this underscores the need for product content to eloquently elucidate use cases, purposes, and correlations to broader categories. Content must establish relevance not just to specific search terms but to the underlying concept behind a query.
As Alexa+ embarks on its rollout in the forthcoming weeks, brands should proactively undertake several measures:
Audit Product Listings for Attribute Completeness
Lauren Morgenstein Schiavone, a former P&G executive and AI business strategy consultant, advocates for a user-centric approach to content optimization: “Shopping will be shaped by daily conversations, not just searches. If you ask Alexa for dinner ideas, she’ll start to learn your preferences. So later, when you say, ‘Alexa, add milk to my cart,’ she’ll know you prefer oat milk.”
Test Your Brand’s Voice Presence
Actively evaluate how your brand and products manifest in voice interactions. Pose questions to Alexa pertaining to your product category to gauge the information provided and the visibility of your products.
Strengthen Brand Recognition
Invest in heightening brand awareness and recall through marketing, PR, and social media initiatives. When consumers specifically request your brand by name, you bypass the algorithm’s discretion in recommending products.
Will Sponsored Content Evolve?
While the patent remains mum on advertising or sponsored content, the evolution of Alexa+ raises queries regarding the future of product promotion in voice-first environments.
Presently, Amazon’s advertising products necessitate visual real estate for display. How might promotional opportunities evolve in a voice-centric environment? Could brands eventually sponsor answers to category queries akin to sponsored products in search results today?
These queries linger unanswered, prompting brands to vigilantly monitor developments as Amazon expands its voice shopping capabilities.
A Fundamental Shift in Discovery
The amalgamation of Alexa’s voice capabilities with Rufus’s product intelligence heralds a potentially transformative shift in how consumers unearth products online. Brands must strategically reevaluate how product content is structured, the depth of their attribute data, and how they cultivate recognition beyond the Amazon ecosystem.
Andrew Bell posits, “We’re progressing towards product listings being written even more conversationally. When all information is extrapolated from product detail pages, they should be rich in conversational language.”
As voice-powered shopping transitions from a novelty to a mainstream discovery pathway, brands swift to adapt to this paradigm shift stand to gain competitive advantages in visibility and recommendation placemen