In the three months since Nohi's private beta launched, a clear pattern has emerged: sellers who optimize for AI agents see dramatically different results than those who treat Nohi like another traditional marketplace.
We've analyzed data from our top 50 sellers — those generating 10x or more revenue compared to the median — and distilled their strategies into actionable guidance.
The fundamental shift: writing for machines, not eyeballs
On a traditional marketplace, your listing competes for human attention. You invest in lifestyle photography, clever copywriting, and emotional hooks. On Nohi, your listing competes for algorithmic trust. AI agents don't care about hero images or brand stories — they care about structured data, accurate specifications, and consistent pricing.
This doesn't mean your listing should be dry or robotic. It means the substance of your offering matters far more than the presentation.
Strategy 1: Maximize schema completeness
Every field in Nohi's product schema is an opportunity for an AI agent to match your product to a buyer's need. Our data shows a direct correlation between schema completeness and discovery rate:
- Listings with 90%+ schema completeness are discovered 4.2x more often
- Listings with detailed specification fields convert 2.8x higher
- Listings with machine-readable return policies see 60% fewer disputes
The most successful sellers fill out every field, even optional ones. They provide precise weight measurements, exact dimensions, detailed ingredient lists, and specific compatibility information. They don't round or approximate.
Strategy 2: Price transparency and consistency
AI agents are exceptional at price comparison. They'll check your pricing against every comparable product on the platform in milliseconds. Sellers who try to game pricing — with hidden fees, inflated MSRPs, or bait-and-switch tactics — are quickly deprioritized by agent algorithms.
Top sellers use transparent, consistent pricing. They set clear volume discounts and update prices promptly when costs change. Several top sellers have implemented dynamic pricing through our API, adjusting prices based on inventory levels and demand signals — but always within consistent, predictable ranges.
Strategy 3: Fulfillment speed and reliability
When an AI agent recommends a product, its reputation is on the line. Agents learn from outcomes: if a product arrives late or doesn't match the listing, that seller gets deprioritized in future recommendations.
Our top sellers maintain fulfillment rates above 98% and average delivery times under their listed estimates. Several have integrated their inventory management systems directly with Nohi's API, ensuring real-time accuracy of stock levels and delivery windows.
Strategy 4: Rich, structured reviews
Nohi's review system is designed for agent consumption. Instead of free-text reviews, buyers rate specific attributes — quality, accuracy of description, delivery speed, value for money. Top sellers actively encourage these structured reviews, which give agents granular quality signals.
Some sellers have implemented post-purchase feedback flows that guide buyers through attribute-specific ratings, resulting in review completion rates 3x higher than passive collection.
Strategy 5: API-first inventory management
The highest-volume sellers on Nohi don't manage listings through a dashboard — they manage them through our API. This allows real-time synchronization with their existing inventory systems, automatic price adjustments, and programmatic creation of new listings.
One SaaS seller in our top 10 has automated their entire Nohi presence: new features are automatically reflected in their listing specifications, pricing tiers update when their billing system changes, and usage-based pricing is calculated in real-time via webhooks.
The compounding effect
These strategies compound. A seller with complete schemas, transparent pricing, fast fulfillment, and rich reviews creates a virtuous cycle: agents recommend them more, which drives more sales, which generates more reviews, which increases agent confidence, which drives even more recommendations.
We're still in the early days of agent-mediated commerce. The sellers who invest now in optimizing for this new paradigm are building durable competitive advantages that will only strengthen as AI agent adoption accelerates.
