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Commerce

Commerce Search & Discovery

When product search, personalization, or visual discovery underperform, the issue is usually deeper than the UI or model.

Searchplex helps retail and e-commerce teams find what is limiting discovery and what to fix first.

Explore AI Search & Personalization
Outcomes

What Searchplex helps improve

Product search

Understand why shoppers exit search, hit zero results, or never see the products you want to sell — and build a path to stronger conversion and long-tail exposure.

Personalization and recommendations

Make recommendations and personalized ranking explainable to the business, aligned with search, and driven by intent, history, and commercial goals — not a black box beside the main journey.

Visual discovery

Turn image-led discovery into a production capability that respects your catalog, filters, and merchandising — not a demo that breaks on real SKUs, stock, and categories.
One foundation

Commerce discovery is becoming one system

Search, recommendations, personalization, visual search, and merchandising often fail separately because they are not designed together.

In production they still pull from the same product data, shopper signals, and rules about what gets shown — so fixing one surface without the foundation rarely holds.

When the foundation fragments

Shoppers see disconnected experiences: search misses intent, recommendations feel unrelated, personalization is hard to explain, visual discovery fails on real catalog constraints, and merchandising fights relevance.

Business impact

Discovery quality affects business performance

Weak product discovery shows up as:

  • Higher search exits and more zero-result journeys
  • Lower add-to-cart and conversion from search
  • Poor long-tail and assortment exposure
  • Weak recommendation and personalization engagement
  • Failed substitutions and promo underperformance
  • Less control over merchandising and campaign strategy

Searchplex helps teams identify which part of the experience is limiting performance, then agree on what to fix, build, migrate, or measure next — with product, growth, and engineering aligned.

Commerce models

Built for your commerce model

Online retail / e-commerce
Improve findability and conversion across large catalogs, seasonal assortments, and long-tail products without over-relying on bestsellers.
Grocery
Handle store availability, substitutions, promotions, and basket context so search and recs work for how people actually shop.
Marketplace
Balance relevance with seller quality, trust, duplicates, ads, and fairness so discovery supports marketplace economics.
B2B commerce
Support account-specific catalogs, contract pricing, permissions, and technical fit — not one-size-fits-all consumer search.
Omnichannel retail
Keep product context consistent across web, app, store, and service channels so shoppers and associates see the same truth.
Failure patterns

Where commerce discovery breaks

Symptoms product and growth teams recognize — and what they cost in production.

Shoppers cannot find the right product

Search exits and zero-result journeys rise; teams compensate with merchandising patches instead of fixing root cause.

Personalization is inconsistent

Experiences feel different by channel or session; stakeholders cannot explain why someone saw a given result.

Recommendations feel disconnected from search

Recs ignore what the shopper just looked for; search and recommendations feel like two products, not one journey.

Visual search fails on real catalogs

Pilots look good in demos but break on variants, stock, category rules, or merchandising in production.

Long-tail products disappear

Bestsellers and sponsored placements dominate; margin and assortment goals suffer.

Filters kill relevant results

Shoppers apply filters and lose obvious matches — a common driver of abandonment after search.

Merchandising fights relevance

Campaigns and manual rules override search in ways that hurt trust, conversion, or operational agility.

Teams cannot explain why products win

Product, growth, and engineering cannot align on what to change because wins and losses are not measurable or traceable.

Framework

What sits under discovery

The symptoms above usually trace back to the same layers: catalog truth, what can be retrieved, how results are ranked, and how you measure change.

The Retrieval Foundation

Searchplex uses one framework for diagnosing production discovery systems — source quality, retrieval, ranking, freshness, and evaluation — whether the surface is search, recommendations, visual discovery, or agents.

What you get

How Searchplex helps

For product, growth, and engineering leaders when discovery is hurting conversion, campaign performance, or control over the shopper experience.

Pinpoint why shoppers exit search or hit zero results

Recover revenue when the right products rank too low or never surface

Make search, recommendations, and personalization feel like one experience

Balance merchandising, campaigns, and relevance without constant firefighting

Prioritize fixes with metrics tied to conversion and discovery performance

Why Searchplex

Start with a Commerce Search Stack Audit

Searchplex helps teams see where the commerce discovery journey breaks: catalog and stock truth, what shoppers can find, how results are ordered, and whether merchandising and personalization work together.

Get a clear diagnosis of what is limiting product discovery today, which issues matter most for conversion and merchandising control, and a prioritized roadmap for what to fix, build, or measure next.

Explore AI Search & Personalization