Who is Noemergis Recommend for?

Ecommerce and merchandising teams using non-Shopify or custom commerce storefronts.

What is needed to begin?

A defined use case, approved representative inputs, a named reviewer, and agreed success measures.

Does Noemergis make the final decision?

No. Accountable people keep review, approval, and production authority.

Commerce Intelligence Pilot

Guide Shoppers Toward Relevant Products.

Noemergis Recommend uses approved catalog and storefront signals to present useful product choices while keeping merchandising decisions with your team.

Discuss a Pilot →View scope

What Recommend Is

Add a controlled recommendation layer to an existing commerce storefront. Teams can choose placements, control eligibility and merchandising rules, review why products were recommended, and measure directly attributed and assisted activity before expanding the integration.

Explore the Commerce Intelligence family →

Catalog-aware ranking

Rank eligible products from approved catalog and storefront signals within the placements your team selects.

Merchandising controls

Keep eligibility, exclusions, boosts, and placement rules under explicit merchant control.

Attribution reporting

Measure directly attributed and assisted recommendation activity without presenting estimates as proven revenue.

Commerce integration pilot

Launch through a bounded integration with agreed storefront surfaces, acceptance criteria, and review points.

Why It Matters

Improve measurable product discovery and cross-sell relevance.

Easier product discovery

Help shoppers reach useful products without forcing them through broad catalog navigation.

More useful cross-sell paths

Create relevant add-on and complementary-product paths within merchant-approved rules.

Clear merchandising control

Let merchandising teams decide what is eligible, promoted, excluded, and reviewed.

Measurable recommendation activity

Connect recommendation placements to reviewable activity and agreed commerce measures.

How It Works

A simple, human-in-the-loop process built for trust.

Learn more

Connect catalog data

The work stays inside the agreed scope and controls.

Apply merchandising rules

The work stays inside the agreed scope and controls.

Show relevant choices

A person checks uncertain or consequential results.

Review measured activity

The work stays inside the agreed scope and controls.

What You Receive

Configured recommendation placements for agreed storefront surfaces
Catalog, eligibility, and merchandising-rule integration
Merchant control setup for boosts, exclusions, and overrides
Attribution and recommendation-activity reporting
Quality review against agreed acceptance criteria
Pilot findings and prioritized implementation recommendations

Where It Works

Commerce Environments

Custom ecommerce storefronts
WooCommerce and supported retailers
Catalog and product-detail surfaces
Cart and cross-sell placements
Merchandising workflows

Business Use Cases

Product discovery
Complementary-product recommendations
Controlled cross-sell placements
Merchandising-rule evaluation
Recommendation pilot measurement

Merchant Control by Design

Recommend is built on Enterprise Trust. Intelligence supports discovery; merchants retain commercial control.

Recommendations propose. Merchants decide.Your team controls placements, eligibility, and overrides.
Reasoning stays reviewable.Inspect the catalog and storefront signals behind placements.
Rules remain enforceable.Exclusions, boosts, and inventory constraints stay explicit.
Performance stays accountable.Review attributed and assisted activity before expansion.

Learn about Enterprise Trust →

Pilot Scope & Safeguards

Bounded pilot with agreed placements and success measures
Approved catalog fields, eligibility rules, and exclusions
Representative storefront traffic and product activity
Merchant review for consequential configuration changes
Secure, role-based access to commerce information
No autonomous catalog, price, or merchandising changes

What It Does Not Do

Recommend boundaries. Responsible expectations.

⊗Does not guarantee sales.Accountable review and approved operating rules remain in place.

⊗Does not change the catalog without permission.Accountable review and approved operating rules remain in place.

⊗Does not present estimates as proven revenue.Accountable review and approved operating rules remain in place.

Expected Outcomes

Example pilot outcome focus areas.

Easier product discoveryMake relevant catalog options easier for shoppers to reach.More useful cross-sell pathsIncrease exposure to useful complementary products within approved placements.Clear merchandising controlPreserve merchant ownership of eligibility, ranking rules, and exceptions.Measurable recommendation activityReview attributed and assisted activity before expanding the integration.

Outcomes vary by organization and use case.

Ready to evaluate Recommend?

Let’s define your use case, agree on success measures,
and launch a focused pilot.

Discuss a Pilot →View Pilot Scope

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Commerce Intelligence Pilot

Guide Shoppers Toward Relevant Products.

Noemergis Recommend uses approved catalog and storefront signals to present useful product choices while keeping merchandising decisions with your team.

Discuss a Pilot →View scope