AI workflows for smarter merchandising

The merchandising manager’s reality

If you manage a complex catalog, you already know the truth. Growth does not break first. Operations do.

Manual tasks to enter or update product data across platforms. Managing separate catalogs for different customer segments or sites. Converting units of measure manually for different buyers. No smart bundling or cross-sell suggestions based on buyer behavior.

When merchandising depends on manual effort, small inconsistencies compound into missed revenue, frustrated buyers, and slower growth.

The real challenge is not strategy. It is scale.

From manual maintenance to intelligent merchandising

AI does not replace merchandising teams. It removes the friction that slows them down.

With Opal, Optimizely’s agent orchestration platform, merchandising teams can deploy AI-powered workflows that continuously monitor, analyze, and optimize catalog data across the commerce lifecycle.

Some workflows are prebuilt. Others can be configured quickly using your existing commerce systems, analytics signals, and business rules.

Instead of periodic audits and reactive fixes, teams gain continuous intelligence that keeps the catalog accurate, relevant, and conversion ready.

Merchandising use cases

The following use cases represent AI-powered workflows that can be deployed using Opal and connected to your commerce data systems.

Product Restrictions Agent

Summarizes visitors, key events, and other web data into an easy-to-consume report.

This gives merchandising teams clearer visibility into product performance and buyer behavior, helping determine where products should be restricted, promoted, or adjusted to maintain relevance and reduce risk.

Inventory Low Stock Alert Agent

Predicts potential stock-outs based on current inventory levels, lead times, and sales velocity.

The workflow can draft an internal purchasing request for review or notify relevant stakeholders, helping prevent lost sales and protect buyer trust.

Product Data Enrichment Agent

Automatically generates SEO-optimized product descriptions and meta-tags based on a brief set of structured product attributes such as color, material, or size.

This improves product discoverability, ensures catalog consistency, and accelerates updates across large SKU sets.

Catalog Consistency Agent

Monitors product listings for inconsistencies such as missing images, mismatched prices between tiers, incomplete attributes, or descriptions that fall outside brand tone guidelines.

Issues are flagged for review or corrected based on predefined instructions to maintain brand integrity and data accuracy at scale.

The collective impact

Together, these AI workflows streamline the entire merchandising lifecycle. Product data stays accurate. Inventory risks surface earlier. Listings remain consistent across segments and tiers. Buyers find relevant products faster, reducing friction and improving conversion.

Beyond automation: real results

When merchandising teams spend less time correcting data, they gain more time to drive strategy.

Results include:

• Faster catalog updates
• Data-backed inventory decisions
• Improved search visibility
• Stronger brand consistency
• Higher conversion rates

AI workflows do not replace merchandisers. They amplify them, giving teams leverage no matter how complex the catalog becomes.

Ready to transform your merchandising?

Learn how Opal-powered AI workflows can streamline complex catalog management and help your team move from maintenance to momentum.