Insight-driven merchandising: Turning intelligence into action

Key Highlights

• Insight-driven merchandising transforms discovery data into actionable insights, helping merchandisers optimize search faster without manual analysis.

• Automatically identifies opportunities such as underperforming search queries, missing synonyms, and redirect suggestions.

• Surfaces actionable recommendations directly in the console, reducing time spent reviewing reports.

• Leverages Netcore Unbxd capabilities such as Measurement Search, Named Entity Recognition (NER), AI Redirect Suggestions, Synonyms, Transliteration, and Google Translator.

• Delivers measurable outcomes, including improved search conversion, better product discovery, and higher customer satisfaction.

Product discovery platforms today use AI to power search, personalization, and recommendations. But improving discovery performance still depends heavily on the merchandisers behind the console.

From reviewing reports to analyzing search trends, identifying broken queries, updating synonyms, adding redirects, and fixing catalog mappings, your team does manual & time-consuming work in the era of AI.

What if the discovery platform could surface these opportunities automatically? Introducing Netcore Unbxd Insight-driven Merchandising.

Improving ecommerce product discovery requires manual efforts

Every retail site collects a large amount of discovery data, and within this data are clear signals about how product discovery can improve for them, but turning those signals into action requires. Merchandisers often spend hours reviewing reports to answer questions such as:

• Which search queries fail to convert?
• Where are shoppers abandoning search?
• Which terms require synonyms or redirects?
• Are shoppers searching for product dimensions?
• Are language variations affecting results?

Even with advanced discovery tools, the process of analyzing this information can slow down optimizations. Retail teams want to focus on optimizing experiences, not digging through data.

Insight-driven merchandising helps retailers optimize search faster

Instead of asking merchandisers to search through reports, the Insight-driven Merchandising highlights opportunities directly inside the console.

It looks at how shoppers interact with discovery features and your products to surface clear suggestions on what can be improved. These insights connect with existing Netcore Unbxd capabilities. Each insight points to a specific opportunity to improve discovery.

Instead of identifying problems manually, merchandisers can see where action is needed and respond quickly.

Improving measurement-based search

Measurement queries are common across many categories.

A shopper looking for a TV may search for “65-inch Samsung TV.”
A customer shopping for furniture may search for a “72-inch dining table.”
Someone browsing appliances may search for “30-inch wall oven.”

Measurement Search helps interpret these queries accurately. Insight-driven Merchandising highlights where measurement queries appear frequently and where product matching may need improvement.

For example, it may show queries where the dimension appears in the search, but the catalog attributes are incomplete or inconsistent. This allows merchandisers to quickly identify gaps and improve search precision.

Supporting real-world search language

Shoppers do not always type product names perfectly. They may use phonetic spellings, brand variations, informal language, and even colloquial terms.

A shopper might search for “nikey running shoes.”
Another might type “samsng tv.”
A customer may search for “jean jacket” even if the catalog lists it differently.

These variations are common, especially in mobile search. Insight-driven Merchandising identifies queries where transliteration or synonym expansion could improve recall.

Merchandisers can then update language mappings so the discovery system recognizes these variations more effectively. Over time this improves search coverage and reduces missed results.

How to fix underperforming search queries in ecommerce

Not all queries fail because of language issues. Some are simply too broad or unclear.

A search for “laptop” may need stronger category associations.
A search for “winter jacket” may benefit from redirecting to a curated collection page.

Insight-driven Merchandising identifies queries where shoppers frequently search but do not engage with results. It suggests actions such as:

• adding better keyword associations
• creating redirects to relevant category pages
• expanding entity recognition
• improving synonym coverage

These improvements help guide shoppers toward results that better match their intent.

Making ecommerce search optimization continuous

Retail discovery optimization often follows a cycle.

Teams review reports.
They make updates.
They wait to see how the changes perform.

Insight-driven Merchandising makes this process more continuous. As new patterns appear in search behavior, the platform highlights them as opportunities for improvement.

Merchandisers can focus their efforts on the changes that have the most impact. This reduces manual analysis and allows teams to respond faster to changing shopper behavior.

Netcore Unbxd powering insight-driven merchandising

Insight-driven Merchandising builds on the discovery intelligence already available in Netcore Unbxd. It connects search behavior with the platform’s product discovery features and turns that data into actionable recommendations.

Measurement insights highlight opportunities in dimension-based queries. Redirect suggestions help guide vague searches to stronger product pages. Named Entity Recognition improves how product attributes are interpreted in queries. Synonyms and transliteration expand language coverage. Google Translator helps support multilingual search environments.

Together these capabilities create a system that not only powers product discovery but also helps improve it.

Better product discovery for shoppers

When discovery improves, the experience feels simple.

Shoppers find the products they expect to see.

• Search results feel accurate.
• Queries lead to relevant product pages.
• Language variations do not interrupt the journey.

For retailers, these improvements lead to measurable outcomes.

• Search conversion improves.
• Product discovery becomes easier.
• Customers leave with greater confidence in their purchase decisions.

Insight-driven Merchandising does not replace the merchandiser. It supports them with insights that make optimization faster and more effective. Because great product discovery happens when the right data and the right decisions work together.

FAQs

1. What is insight-driven merchandising in ecommerce?

Insight-driven merchandising uses analytics and AI to identify opportunities to improve product discovery, search relevance, and shopping experiences by turning shopper behavior data into actionable recommendations.

2. What challenges do merchandisers face in optimizing ecommerce search?

Merchandisers often spend hours reviewing search analytics reports to identify issues such as zero-result queries, poor product matches, missing synonyms, and ineffective redirects.

3. How does insight-driven merchandising improve ecommerce search optimization?

Insight-driven merchandising surfaces insights directly within the discovery platform, highlighting opportunities like underperforming queries, measurement-based search gaps, and language variations so merchandisers can take faster action.

4. How does Netcore Unbxd support insight-driven merchandising?

Netcore Unbxd combines search analytics with discovery features such as Measurement Search, Named Entity Recognition, AI redirect suggestions, synonyms, transliteration, and multilingual support to generate actionable merchandising insights.