How Boost Commerce helped Urban Sales improve the sitewide conversion rate by 14%

March 24, 2026

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3 min read

Urban Sales is a New Zealand furniture and homeware retailer with 1,900+ products across major home categories. Their business is digitally led, supported by a physical showroom in Auckland. With a growing catalog, they needed to improve product surfacing on search and collection pages and enable faster campaign execution without manual collection sorting.

This case study shows how Urban Sales used Boost Commerce for search, filtering, merchandising, and recommendations, and how Boost works alongside Klaviyo as they build retention flows over time.

Summary

What Urban Sales changed: Boost replaced manual sorting, automatically surfacing relevant products on search and collection pages based on shopper needs and business goals.
What you’ll learn: How to improve product discovery for a large furniture catalog using search, filters, merchandising rules, and recommendations that reduce friction for shoppers and workload for the team.
The practical shift: Campaign merchandising moved from manual updates to repeatable rules, so promotional products stay visible without constant re-sorting.
How Boost works alongside Klaviyo: Klaviyo can use shopper intent recorded by Boost to create email flows that bring customers back to the products and ranges they care about.
The outcome: A measurable lift in performance, including a 14% increase in conversion rate and a 20% increase in sales for handpicked products during promotional periods.

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The challenge: How to improve online discovery for a 1,900+ product furniture catalog

Urban Sales faced significant challenges in online product discovery before implementing Boost. The expanding product catalog made it difficult for online customers to navigate and locate the items they were looking for.

Product ranking and promotion were too manual.

The online store had limited ability to dynamically promote high-margin or priority products. Collection sorting required ongoing manual work, which did not scale during campaigns.

Search relevance was inconsistent for furniture shopping behavior.

Style-based queries, such as “Japandi” or “mid-century”, were harder to support with the default basic Shopify search. The search experience lacked contextual understanding.

Filtering was not strong enough for attribute-heavy products.

Furniture shoppers need filters for size, materials, finishes, and functional attributes. Their previous filtering structure made that difficult.

These issues affected measurable outcomes.

Jacky, Marketing Executive at Urban Sales, shared that the store reported lower conversion as a result of suboptimal ranking. They also missed revenue when high-performing or high-margin products were not surfaced. Furthermore, the average order value (AOV) declined, potentially due to insufficient prioritization of complementary and premium items.

Despite the online store experiencing negative growth, the Urban Sales team faced an increased operational burden during campaigns. This was due to their prior tool being primarily manual and lacking AI capabilities to automate tasks.

The solution: How Boost empowers and automates online discovery for Urban Sales

Urban Sales chose Boost because it combined AI-driven merchandising intelligence with practical control. They needed a solution that could rank products by performance and behavior, support advanced filtering, and scale with campaign activity without heavy manual input.

“Boost Commerce has fundamentally changed how we manage product discovery and merchandising. What was once a manual, reactive process is now intelligent, dynamic, and aligned with our commercial goals.” - Jacky, Marketing Executive at Urban Sales.

What they implemented and why it mattered

What Urban Sales used	The difference it made
Search Smart search with stronger relevance for style and attribute-based queries	Shoppers find relevant products faster, with less trial-and-error
Filtering Advanced filtering for size, material, finish, and storage type	Shoppers can narrow options using decision-making criteria that match furniture shopping
Merchandising Merchandising rules that support margin, inventory, tags, and performance	The team can run campaigns and maintain commercial priorities without constant manual resorting
Recommendations “Shop the Same Range” and “You May Also Like (Same Product Type)”	Shoppers explore complementary products more easily, increasing cross-sell opportunities
Boost × Klaviyo Boost runs alongside Klaviyo email automation (flows in progress)	Online discovery can inform retention when flows are ready, using real shopper intent

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Shoppers immediately see "Popular searches" and "Trending products" when they click the search bar.

Implementation and support

Urban Sales had core functionality live within a month. Initial setup covered search, filtering, and basic merchandising rules. Optimisation continued through weekly refinements as ranking was learned from behavioral data.

They also highlighted direct communication with the Boost team, fast turnaround on bug fixes and analytics questions, and weekly check-ins to review performance and adjust merchandising.

How Urban Sales uses Boost in the real world: Day-to-day merchandising and campaign support

Urban Sales uses Boost daily to manage search relevance, optimize sorting, and monitor merchandising performance.

To capture attention and increase the likelihood of purchase, bestsellers and on-sale items are prioritized at the beginning of each collection.

During campaigns, Boost helps them:

Prioritize promotional SKUs across collection pages
Surface high-margin and high-conversion products
Adjust ranking during flash sales and sitewide promotions
Refine filters to match campaign messaging, such as “solid wood,” “storage beds,” or specific sizes

This approach keeps the storefront consistent for shoppers. It also reduces the team's campaign workload.

The results: Higher campaign sales, stronger conversion, and less manual merchandising

Promotional products: ~20% sales increase

Sales of handpicked products increased by approximately 20% during promotional periods due to improved visibility and prioritized ranking.

Conversion rate: about +14% relative lift

Overall conversion rate improved by 14%. Urban Sales linked this to stronger product discoverability and better alignment between search intent and merchandising decisions.

Recommendations: incremental revenue from range-based discovery

The “Shop the Same Range” and “You May Also Like (Same Product Type)” widgets generated meaningful incremental revenue by encouraging cross-product exploration and increasing on-page engagement.

Urban Sales also described this as the biggest win. Product discovery became an active revenue driver by helping customers browse deeper and find complementary products more easily.

The "You may also like" carousel, positioned beneath the product description, naturally facilitates upselling and cross-selling by suggesting alternative and complementary products.

Team efficiency: less manual merchandising during campaigns

Boost significantly reduced manual merchandising workload, particularly during campaign periods.

“Boost Commerce has fundamentally changed how we manage product discovery and merchandising. What was once a manual, reactive process is now intelligent, dynamic, and aligned with our commercial goals.”

Lessons learned: Efficient growth strategies for Shopify stores with large product catalogs

“The platform (Boost Commerce) allows us to surface the right products at the right time, especially during key campaigns, while maintaining full strategic control. Beyond the technology itself, the responsiveness and proactive support from the Boost team have made a real difference. It feels less like using a tool and more like working with a growth partner.” - Jacky, Marketing Executive at Urban Sales.

Make discovery measurable.

When search and collection pages improve, performance across the site improves. Urban Sales saw this through higher engagement on collection pages and improved search-to-conversion performance.

Use merchandising rules to reduce campaign overhead.

Campaigns move quickly. Automated merchandising reduces manual work and keeps product visibility aligned with commercial goals.

Use recommendations that match how people shop.

Range-based and product-type recommendations help shoppers compare options and add complementary items without extra searching.

Connect onsite intent to retention when ready.

Boost works alongside Klaviyo. This gives teams a practical path from on-site behavior to more relevant email and SMS, as flows are developed.

If you manage a large catalog with complex attributes, Boost helps shoppers find the right products faster and helps your team run campaigns with less manual work.

Start a free trial of Boost Commerce and measure the impact on search, collections, and recommendations.

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Frequently asked questions

1) What results did Urban Sales see after implementing Boost Commerce?

Urban Sales reported a ~20% lift in handpicked promotional product sales and a 14% improvement in website conversion rate.

2) Which Boost capabilities were most important for a furniture store?

Urban Sales found that smart search, advanced filtering (for size and materials), merchandising rules, and AI-powered recommendation widgets were the most impactful and frequently used features. Beyond these, you can explore and use several other features, including pre-order and back-in-stock notifications, as well as integration with REVIEWS.io to build trust-based discovery on your online store.

3) How did Boost reduce manual merchandising work during campaigns?

Boost allowed the team to prioritize promotional SKUs, surface high-margin products, and adjust ranking during flash sales without manually re-sorting collections each time.

Ellie Ho

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Content Marketing Specialist

March 24, 2026

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3 min read

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How Boost Commerce helped Urban Sales improve the sitewide conversion rate by 14%

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