Using Search recommendations to improve product discovery
How personalised suggestions help shoppers find relevant products faster and reduce zero‑result frustration
Overview
Search is one of the strongest signals of shopper intent. When a shopper uses your search bar, they are actively looking for something specific - but without support, they may struggle with broad queries, misspellings, or unclear product names.
Search recommendations help guide these shoppers by surfacing relevant products, categories, and alternatives that match their intent. This reduces zero-result pages, improves product discovery, and increases the likelihood that shoppers will continue exploring.
Why search needs personalisation
Even when shoppers know what they want, their search terms may not match your catalogue exactly. Personalised search recommendations help bridge this gap by interpreting intent and offering relevant options.
Common challenges in search
- Broad or vague search terms ('skincare', 'dress', 'gifts')
- Misspellings or incomplete queries
- Shoppers unsure of product names
- Zero-result pages that cause immediate drop-off
- Returning shoppers searching for items they viewed earlier
Search recommendations help guide shoppers toward relevant products before they lose momentum.
Zero-result pages are one of the fastest ways to lose high-intent shoppers.
How Liva 7 improves search discovery
Liva 7 uses behavioural signals and catalogue insights to personalise search recommendations in real time. This ensures that shoppers see relevant suggestions even before they finish typing.
What Liva 7 considers
- Recently viewed products
- Category-level browsing patterns
- Frequently searched or trending items
- Products related to the shopper's past behaviour
- High-performing items that match the query
- Alternatives when the search term is unclear
This helps shoppers find what they want faster - or discover something even better.
Search recommendations adapt instantly as the shopper types.
Where search recommendations perform best
Search recommendations can appear in multiple places to support different stages of the search journey.
Search bar (predictive suggestions)
- Show relevant products as the shopper types
- Surface categories or collections that match the query
Search results page
- Highlight personalised picks based on behaviour
- Offer alternatives when results are limited
Zero-result pages
- Provide fallback recommendations to prevent abandonment
- Suggest related categories or trending items
Predictive suggestions in the search bar deliver the strongest impact on discovery.
Effective strategies for search recommendations
Different strategies can be used depending on the shopper's behaviour and the type of search query.
- Personalised picks based on recent browsing
- Trending or high-performing products
- Category-level suggestions for broad searches
- Alternatives for misspellings or unclear terms
- Products frequently bought or viewed together
- Seasonal or campaign-aligned recommendations
These strategies help shoppers find relevant products even when their search is imperfect.
Combining personalised and trending suggestions often delivers the strongest results.
What results merchants typically see
Search recommendations often deliver strong improvements in product discovery because they support shoppers at the moment of highest intent.
Typical outcomes
- Higher click-through rates from search
- Fewer zero-result pages
- More product views per session
- Increased add-to-cart actions
- Reduced bounce rates
- Higher conversion rates from search traffic
Shoppers who engage with search recommendations are significantly more likely to find a product they want.
Search is one of the highest-intent behaviours - optimising it has outsized impact.
Quick checklist
- Search recommendations are enabled in the search bar and results page
- Strategies support both broad and specific queries
- Zero-result fallback content is set
- Recommendations feel relevant and fresh
- Performance is reviewed regularly for optimisation
Use this checklist to ensure your search recommendations support product discovery effectively.
