The shopper wants
Gentle, long-lasting hydration for sensitive skinProduct discovery for both sides of commerce
Recommend what shoppers want—and what works for your business.
AgentGora first finds products that genuinely fit the shopper. Then it chooses the option that also creates the strongest business outcome.
- 1Protect shopper relevance
Only compare products that fit the shopper's needs.
- 2Add merchant context
Consider availability, economics, promotions, and priorities.
- 3Choose the best shared outcome
Recommend the product that works best for both sides.
Start with historical data. Test in a controlled pilot. Expand only when the results justify it.
Illustrative product decision
Why this product wins
The merchant needs
Healthy availability, an active offer, and sustainable contribution
1 Keep shopper-relevant products
→
2 Find the strongest shared result
Best shared outcome
Selected recommendation
Calm Barrier Cream
It is the strongest fit for the shopper's sensitive-skin need and the merchant's current business conditions.
Best for the shopper
- Designed for sensitive skin
- Supports the skin barrier
- Provides lasting hydration
Best for the merchant now
- Healthy inventory position
- Current promotion is ready
- Supports healthy contribution
Why the other relevant options rank lower
The winner has the best balance—not just the highest score on one side.
Aqua Gel
Strong stock position, but less barrier support for this shopper.
Daily Lotion
Good everyday value, but less tailored to sensitive skin.
Recovery Mask
Attractive basket value, but too rich for the shopper's daytime need.
The simple idea
Conversion matters. It is not the whole outcome.
A recommendation can be relevant and still miss a better commercial opportunity. AgentGora considers both sides while keeping shopper fit non-negotiable.
Start with shopper fit
Use intent, preferences, behavior, and journey context to identify genuinely relevant choices.
Add today's business reality
Bring in product economics, inventory, promotions, and the merchant's current priorities.
Choose a shared winner
Select the relevant option with the strongest combined shopper and merchant outcome.
What AgentGora is
A decision layer for product discovery.
AgentGora works alongside existing commerce systems. It improves the decision about what relevant product or commercial response to show next.
Shopper contextWhat will help this person?
+
Merchant contextWhat creates value now?
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AgentGora
→
RecommendationRelevant and commercially aligned
Where AgentGora works
Improve high-intent commerce surfaces.
See how the shopper and merchant rationale changes with the surface.
Campaign landing pageJointly optimized
Shopper contextSensitive-skin hydration
Need state and campaign intent
Merchant contextCampaign readiness
Healthy stock and a funded offer
Featured product
Calm Barrier Cream
Sensitive-skin hydration, ready to feature
Why shoppers benefitCalming barrier support
Why the merchant benefitsHealthy stock and funded offer
Campaign signal → what gets featured
Landing pages and campaigns
Feature products and offers that match visitor intent while reflecting current inventory and campaign economics.
RevenueContribution profitInventory healthPromotion efficiency
A low-risk starting point
Find the opportunity. Then prove it.
Start with historical evidence, test AgentGora on a controlled surface, and expand only if measured results justify it.
Discuss an opportunity audit- 1Identify
Find decisions with meaningful economic potential.
- 2Test
Run a controlled pilot alongside the current experience.
- 3Measure
Compare revenue, profit, conversion, and relevant KPIs.
- 4Expand
Scale only when the evidence supports it.
About AgentGora
Research depth. Commercial focus.
AgentGora was founded by Negin Golrezaei, an MIT professor whose work spans AI, optimization, marketplaces, and online decision-making.
Our mission is to help merchants make better decisions while creating more relevant and sustainable experiences for shoppers.
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