Last week’s Walmart earnings call included several updates around Sparky, Walmart’s AI shopping assistant. Weekly active users doubled, automatic reordering functionality and Spanish language support were.
Walmart is investing in conversational commerce and AI assisted shopping experiences. More importantly, customers are adopting them. According to Walmart, customers using Sparky have an average order value 35% higher than non-Sparky users.
Historically, a customer searched for something broad like “dog treats,” reviewed pages of products, compared reviews, pricing, and shipping speed, then made a decision.
That process rewarded strong marketplace fundamentals and keyword optimization.
Today, AI is beginning to reshape the discovery layer.
Instead of searching for a broad product category, customers can provide context:
“I have two dogs with different food sensitivities and need healthy treats they can both eat.”
Instead of matching keywords, Sparky has to interpret a problem and identify products that solve it. To do that, it needs to understand what the product is, who it is for, when it should be used, and what problem it solves.
For pet brands, this shift creates and opportunity to reach new customers if you evolve with the new technology.
Complete Attributes Matter More Than Ever
Humans browse visually. We look at images, titles, pricing, and badges. AI behaves differently.
AI systems rely heavily on structured data and product attributes to understand products and determine relevance.
For pet products, that can include:
- Breed size
- Life stage
- Ingredients and flavors
- Weight range
- Allergy considerations
- Health benefits
- Package size
- Feeding or usage intent
If a listing simply says: “Salmon Dog Treat” there is very little context available for AI.
If a listing says “Freeze-dried salmon training treats designed for senior dogs with skin sensitivities”, AI has more information to understand the intended customer, use case, and problem the product solves.
The difference may determine whether a product is recommended or overlooked entirely.
Stop Writing Product Pages. Start Writing Use Cases.
Many product pages focus heavily on features. Fewer explain situations.
Pet parents generally are not purchasing ingredients or specifications. They are purchasing outcomes.
“Contains glucosamine” describes a product feature.
“For active or aging dogs needing joint support” describes a customer need.
Likewise:
“Grain free” describes a formulation.
“Designed for dogs with food sensitivities” explains why it matters.
The clearer the relationship between a product and the problem it solves, the easier it becomes for AI to understand and recommend it.
Design Around How Pet Parents Actually Shop
According to Walmart data, 63% of Walmart pet customers have multiple pets.
That creates increasingly complex shopping needs involving different breeds, life stages, dietary preferences, and health concerns.
AI assistants are uniquely positioned to help simplify those situations.
Instead of customers piecing together products one listing at a time, shopping can increasingly resemble a conversation:
“One dog likes chicken. Another likes salmon. Show me options they can both eat.”
That experience feels less like traditional search and more like speaking with a knowledgeable employee in a pet store.
For brands with multiple product variations, bundles and variety packs may become even more valuable in this environment. They create simple purchasing options for households with different needs and allow AI systems to recommend broader solutions instead of isolated products.
Align With Where Walmart Is Going
One observation we continue seeing on Walmart Marketplace is simple: sellers who align with the platform’s direction usually benefit.
Walmart is clearly investing in AI, personalization, and assisted shopping experiences.
The traditional marketplace fundamentals still matter. Inventory availability, competitive pricing, strong reviews, and fast delivery through Walmart Fulfillment Services remain critical.
But there is an additional layer emerging.
AI now needs to understand your product before it can recommend it.
For pet brands, the future of optimization may involve less emphasis on keyword matching and greater emphasis on product context.
Because in AI search, your products need to be understood.