The Hidden Cost
of Bad Product Discovery

Bad product discovery creates an invisible leak in ecommerce revenue: shoppers arrive with intent, search for something specific, fail to find it and leave before analytics clearly explain why.

However, the issue is not always a broken search bar. More often, the products exist in the catalogue, but the experience does not help shoppers reach them. For example, search may return irrelevant products, bury profitable items, misunderstand synonyms or lead shoppers to a dead-end zero-results page.

This is where searchandising matters. In short, searchandising gives ecommerce teams control over how products are found, ranked and presented, while keeping relevance at the centre of the experience.

What product discovery really means

The cost starts with high-intent shoppers

A shopper who uses site search is telling you what they want in their own words. As a result, search becomes one of the highest-intent surfaces on an ecommerce website.

In the benchmarks followed by ElasticSuite Solutions, shoppers who use search can convert up to three times more than shoppers who browse without using it. However, this is not a universal guarantee. Instead, it shows why poor ecommerce search can have an outsized commercial impact.

When the first results do not match the query, shoppers may not browse through several pages to correct the system. Instead, they may return to Google, visit a competitor or abandon the purchase altogether.

Four hidden costs of bad product discovery

1. Lost high-intent revenue

Search users have already done part of the buying work. They have identified a need and are trying to shorten the path to a product. Therefore, if search adds friction, you risk losing visitors who were already close to conversion.

2. Zero-results dead ends

A zero-results search does not always mean that the product is missing. For example, the shopper may have used a synonym, a different spelling, a product code, a plural form or a term that does not appear in your catalogue.

In practice, every no-results page is therefore a merchandising question: is the product genuinely unavailable, or did the search experience fail to connect the shopper with an available product?

3. Relevant products ranked too low

A product can be technically present in search results and still be commercially invisible. For example, if the best match appears on page three while a less relevant product appears first, the shopper experiences the ranking as a recommendation.

4. Margin left on the table

The first relevant product is not always the product that best supports your business. As a result, without merchant control, search may overexpose low-margin items, products with excess stock or products that do not support a current campaign.

Why ecommerce search underperforms

Traditional ecommerce search often matches words rather than shopping intent. It looks for a relationship between the query and catalogue fields. However, that relationship can be too rigid for the way customers actually search.

For example, customers may search by use case, material, audience, colour, technical specification, shorthand or internal product reference. In addition, they may make spelling mistakes or use language that is absent from your product data.

The operational problem is that merchants often have little visibility into why products appear in a certain order. As a result, when ranking behaves like a black box, the team cannot confidently explain, test or improve the customer experience.

Searchandising puts the merchant in control

Searchandising is the practice of applying merchandising decisions to search and product discovery so that shoppers see relevant products while the business can influence commercial priorities.

In other words, search is not just a technical feature. It is a customer-facing sales surface. Therefore, merchandisers should be able to decide what to promote, what to demote and how to respond when a query does not map cleanly to the catalogue.

In practice, ElasticSuite Solutions makes this approach workable for ecommerce teams by combining relevance with merchant control, clarity and measurable performance.

What good product discovery looks like

Good product discovery creates a clear path to relevant products and gives merchants understandable levers to improve that path.

Search results that reflect intent

Search should account for synonyms, spelling variations, product attributes and the language customers actually use. The goal is not to return more products. Instead, it is to return the right products in a useful order.

Facets that reduce decision effort

Filters should reflect how shoppers compare products. For example, clear facets for size, colour, brand, availability, price or technical characteristics help customers narrow a broad result set without starting a new search.

Boost and bury rules merchants can explain

Merchants should be able to boost products for a launch or campaign, and bury products that are unavailable, obsolete or commercially unsuitable. Importantly, these decisions should work with relevance, not replace it. Discover boost and bury merchandising.

Useful no-results handling

A no-results experience should offer a next step: corrected queries, related categories, popular products or alternative recommendations. For example, at Chomette, optimising search reduced zero-result searches by around 43%, showing that no-results performance can be managed as a measurable business outcome.

Insights your team can act on

Search reports should reveal the queries that generate no results, weak engagement or unexpected exits. As a result, marketing and merchandising teams can improve product data, add synonyms, adjust ranking rules and identify gaps in the assortment.

Search and product discovery are not the same

Search	Product discovery
Responds to a typed query.	Supports the full path from need to product.
Focuses mainly on matching words.	Connects intent, navigation, filters and merchandising.
Can be treated as a technical feature.	Is managed as a commercial experience.
Can end with zero results.	Creates a useful next step when the first query fails.

How to diagnose the problem

Start with the searches that matter most to revenue, not with a generic technical audit. First, review the queries used by customers, the products shown first, the rate of zero-results searches and what shoppers do next.

1. Identify your highest-volume and highest-value searches.
2. Find queries with no results, weak engagement or high exit rates.
3. Check whether the first results match the shopper’s likely intent.
4. Review where commercial priorities should influence ranking.
5. Test one change and measure its commercial impact.

This approach keeps ownership with the people who understand the assortment, the customer and the commercial calendar. In short, product discovery improves through continuous observation and controlled iteration.

Your search bar should not be a black box between shoppers and your catalogue.

ElasticSuite Solutions helps ecommerce teams turn product discovery into a controlled, measurable growth lever. See how it works in a demo.