Normalized claim
Quantified impact: 0.1-2% decrease
Reduced zero-result searches from 2% to 0.1%, significantly improving product findability.
GCPEvidence: Medium50/100
Toolstation Improves Product Search and Customer Experience with Vertex AI Search for Commerce
Use case typeProduct discoveryUpdated Jun 13, 2026
Toolstation, a UK-based retailer, improved product search accuracy across its website, app, contact center, and physical stores using Google Cloud's Vertex AI Search for Commerce. The challenge was customers struggling to find products due to synonyms, slang, and spelling errors, leading to lost sales and poor reviews. They migrated from a rule-based legacy search tool to an ML-driven Vertex AI Search that dynamically understands customer search terms and continuously learns from search behavior. Implemented search integration in contact centers and in-store tills to assist staff in finding products faster and more accurately. Results included reducing zero-result searches from 2% to 0.1%, a 10% higher click-through rate, 5% increase in search-based revenue, and improved customer loyalty.
- Organization
- Toolstation
- Industry
- Retail
- Location
- United Kingdom
- Published
- June 2024
Reported outcomes
−30%
quantified impactCustomer experience
0.1-2%quantified impact+10%quantified impact+5%revenue+2%quantified impact
Strategic outcomes
Customer experience & trustImproved product findability across channelsNew product / capabilityAdded smart product discovery featuresCustomer experience & trustReduced search-related customer complaintsCustomer experience & trustIncreased customer loyalty and repeat visits
Catalog median for customer experience deployments: −30% across 8 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Quantified impact: 10% increase
Increased daily click-through rate by over 10%, boosting engagement.
Normalized claim
Revenue: 5% increase
Grew search-based revenue by 5%.
Normalized claim
Quantified impact: 30% decrease
30% reduction in customer complaints about irrelevant search results.
Normalized claim
Quantified impact: 2% increase
Increased customer loyalty with 2% more returning customers.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Toolstation
- Provider
- GCP
- Maturity
- Unknown
- Linked source
- Google Cloud Customer Stories
No explicit deployment-stage evidence found.
Customer identity supportedSource describes one deploymentMaturity evidence evaluated
Primary read
Use case focus
Showing 2 of 2
- 1AI-powered product search
- 2Unified search across digital and physical retail channels
- Improving search accuracy for products amidst varied customer terminology and typos.
- Reducing manual effort of maintaining thousands of search rules.
- Enhancing customer satisfaction and reducing lost sales caused by poor search results.
- Migrated product search to Google Cloud Vertex AI Search for Commerce leveraging ML model that auto-learns from search data.
- Integrated search capabilities into website, mobile app, contact center, and in-store tills for unified experience.
- Enabled 'similar items' and other smart features to enhance product discovery and user experience.
Technologies
- Reduced zero-result searches from 2% to 0.1%, significantly improving product findability.
- Increased daily click-through rate by over 10%, boosting engagement.
- Grew search-based revenue by 5%.
- 30% reduction in customer complaints about irrelevant search results.
- Increased customer loyalty with 2% more returning customers.
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jun 1, 2024Publisher: Google Cloud Customer StoriesEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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