Search came back with nothing they can use.

Declared

The query, zero-result flag, and any filters they had on.

Example eligibility rule

Trigger after the search engine returns zero usable results following normal spelling correction and synonym expansion. Preserve the original query and filters. Treat service errors, unavailable indexes, and unsupported characters as technical failures rather than intent-recovery opportunities.

A specific query (SKU, size, job, misspelling) returns zero results or a junk page. High intent, no path. Most people leave rather than rewrite the query.

Avoid this assumption

A prettier empty state is not recovery. This case repairs a failed query. "They filtered until there was nothing left." repairs a filter combination that removed every result.

A null search is a clear signal that the current path failed. A close match, a synonym, or a "we don't have this, here's the nearest" is a different experience that is easy to test against the default.

Reach

How many eligible people can you reach in the chosen channel and time period?

Cost

What will content, delivery, QA and ongoing maintenance cost?

Return

What incremental outcome would cover that cost, and what is it worth?

Planning inputs, not measured results. Estimate reach × incremental outcome rate × value per outcome, then subtract cost. Use a range and a consistent time period.

Example format: Recommendations

Synonym and attribute recovery: show the nearest in-stock set, named as such.

Compare lighter and deeper responses

Choose the lightest response that solves the need.

Assist: Offer useful help

Keep the empty page. Add a close-match chip and a way to drop one filter.

Adapt: Change a meaningful part

Synonym and attribute recovery: show the nearest in-stock set, named as such.

Transform: Tailor the journey

A guided recovery: nearest products, a notify-me, and a related-need module.

What to watch out for

• Showing bestsellers that ignore the query.
• No holdout, so you never know if recovery paid.
• Hiding that you do not actually stock what they asked for.

Control

Default zero-result page.

Treatment

Intent-recovery results for the same query.

Success measure

Search-to-product after a null, then conversion.

Guardrail

Bounce on the results page. If they still leave, you recovered the wrong thing.

Win or lose, record what worked, for whom and why. What you learn becomes the next signal.

• Algolia Hosted search infrastructure with rule-based merchandising and an opt-in machine-learning personalization layer.
• Bloomreach Ecommerce Search AI-driven ecommerce search and discovery platform (Loomi AI) that personalizes ranking, recommendations, and merchandising from first-party shopper data.
• Coveo Enterprise AI search platform using deep-learning 'product affinities' to personalize ranking, suggestions, and recommendations in real time.
• Constructor Ecommerce search and recommendations platform that optimizes recs against a chosen business KPI using clickstream data and merchant rules.
• Athos Commerce Athos Commerce is the January 2025 holding brand created when Searchspring and Klevu combined under PSG ownership, alongside Intelligent Reach. Three separate products with separate contracts and pricing, not one merged platform.
• Algonomy Retail personalization suite (search, recs, dynamic listing pages, content/styling, social proof, shopping agent) built on the earlier RichRelevance/Manthan merger. Now operating under the ADA brand after ADA acquired Algonomy in July 2026.

They searched for something specific. You showed bestsellers. Put what they asked for first.

They want it. It's out of stock. Show something in stock that fits, and a waitlist that actually writes back.

They filtered until there was nothing left. Clear the filter that emptied the grid. Show what comes back.