When On-Site Search Returns No Results

On-site search often serves shoppers who already know what they want. When a query returns no results, that high-intent journey can quickly stop.

A good zero-results page should help shoppers recover. It should explain what happened and give them another way to find relevant products.

For BigCommerce merchants, the issue can also go beyond page design. Product data and search settings may affect whether the right products appear at all.

Explore how Forix’s Design and Strategy services help eCommerce retailers improve search journeys and create clearer paths to product discovery.

Why Zero-Results Searches Matter

A shopper who uses search is trying to reach a specific product or category. Therefore, a failed search can interrupt an important part of the buying journey.

Common causes include:

• Misspellings

• Missing synonyms

• Unfamiliar product terms

• Missing search keywords

• Incomplete product data

• Model-number differences

• Unavailable products

• Search settings

However, shoppers rarely know why the search failed. They may simply assume the store does not carry what they need.

A clear recovery path gives them another option.

Understand What BigCommerce Search Can Find

Before redesigning the empty page, review the data behind search.

BigCommerce search can use product names, descriptions, and search keywords. Therefore, better product data can make products easier to find.

For example, shoppers may use a short term while the catalog uses a technical name. The correct product may exist, but search may still fail to show it.

Compare the words shoppers use with the terms in the catalog. This can reveal gaps that page design alone cannot fix.

Give Shoppers a Clear Recovery Path

First, explain the result in simple language.

Avoid technical messages such as “No records found.” Instead, tell shoppers that no exact match was found and offer useful next steps.

They may be able to:

• Check the spelling

• Try fewer words

• Remove extra model details

• Search by product type

• Try a related term

• Browse a relevant category

Also, keep the original query visible and editable. Shoppers should not have to start over.

Show Relevant Alternatives

Next, offer options that match the shopper’s intent.

An empty search page should not become a generic bestseller page.

In a BigCommerce store, useful options may include:

• Related categories

• Relevant brands

• Similar products

• Compatible products

• Recently viewed items

• Helpful content

• Customer support

For example, a shopper may search for an old product model. In that case, a replacement product is more useful than an unrelated bestseller.

The goal is to help the shopper continue from the original search.

Improve the Product Data Behind Search

A better zero-results page can help shoppers recover. However, repeated failures may point to a deeper product-data issue.

Review:

• Product names

• Descriptions

• Search keywords

• SKUs

• Brand names

• Categories

• Product attributes

• Abbreviations

• Model numbers

• Common customer terms

BigCommerce product search keywords can help connect shopper language with relevant products.

For example, shoppers may use an industry abbreviation while the catalog uses a longer name. Adding common customer terms can make the product easier to find.

As a result, zero-results data should also support regular catalog updates.

Account for the Search Technology in Use

Not every BigCommerce store uses the same search setup.

Some merchants use native search. Others use search tools with features such as autocomplete, synonyms, filters, merchandising, or recommendations.

Before designing the recovery page, check what the active search tool can do.

Review whether it can:

• Correct common misspellings

• Recognize synonyms

• Suggest related queries

• Show useful categories

• Recommend relevant products

Then design the recovery experience around those features.

Otherwise, the page may offer options that the search tool cannot support.

Make Mobile Recovery Easy

Mobile shoppers have less screen space. They may also make more typing errors.

As a result, recovery should require as little effort as possible.

Keep the search field easy to reach. In addition, make suggestions clear and easy to tap.

Product and category cards should use simple labels. Support should remain available, but it should not distract from the main recovery options.

Measure What Happens Next

A failed search is useful data.

Do not only count zero-results queries. Also review what shoppers do next.

Track:

• Failed queries

• Revised searches

• Suggestion clicks

• Category visits

• Product views

• Support contacts

• Exits

• Add-to-cart activity

• Purchases

These patterns can reveal problems with both UX and product data.

For example, a common failed term may show that a synonym is missing. Repeated model searches may point to weak or inconsistent product information.

In addition, searches for products the store does not carry may reveal unmet demand.

For BigCommerce retailers, this data can guide search updates, catalog work, and merchandising decisions.

Use Search Data to Improve Merchandising

Failed searches can show a gap between how a store organizes products and how customers think about them.

Those insights may improve:

• Search keywords

• Product names

• Categories

• Filters

• Product descriptions

• Compatibility content

• Merchandising

• Inventory decisions

Therefore, the solution may go beyond the zero-results page.

Search data can help retailers improve the full product discovery journey.

Conclusion

A zero-results search should guide shoppers forward, not end the journey.

Clear messages, editable queries, useful alternatives, and better product data can help shoppers recover. Search data can also reveal gaps in product terms, catalog content, and search settings.

Forix helps BigCommerce retailers find search friction and create clearer paths from high-intent searches to relevant products and categories.