How McPhails Furniture Lifted AOV by 35.7% with Boost Commerce and REVIEWS.io, After Switching from SearchSpring

December 30, 2025

January 22, 2026

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3 min read

All performance metrics and feature usage are based on McPhails Furniture’s Boost Analytics and implementation feedback.

McPhails Furniture is a family-owned furniture and homewares retailer that has operated from the same location since 1969. After major disruption during COVID, they accelerated their move to online selling and quickly scaled into a digital-first Shopify business, supported by their physical showroom.

As their online store grew, they needed two things that matter most in furniture eCommerce:

Product discovery that works at scale: shoppers must be able to find the right item fast, even when they search using different terms or misspellings.
Trust signals at the decision point: furniture purchases are high-consideration, so customers look for proof before they commit.

This case study will show you how McPhails Furniture combined Search, Recommendations, and Merchandising of Boost Commerce with the REVIEWS.io integration to improve discovery and buying confidence, resulting in to +35.7% AOV and standout performance from personalized recommendations and search engagement.

Summary

What McPhails Furniture changed: They paired Boost Commerce with REVIEWS.io, so product discovery became both smarter (via relevance, synonyms, and filtering) and more trusted (via review-led decision signals).
What you’ll learn: How to use AI search, recommendations, and merchandising together to reduce “can’t find it” friction and guide shoppers to the right products faster.
The big move: Turn reviews into an active discovery tool using filters by star rating and merchandising rules that boost well-reviewed items.
Why it matters for high-consideration categories: Furniture shoppers need confidence. This approach supports evaluation by combining relevance + social proof at key decision points.
The outcome: A measurable lift in revenue quality, including +35.7% AOV, plus strong engagement from personalized recommendations and AI-powered search.

The challenge: How to build better discovery for high-consideration products at the decision point

Furniture is not an “impulse add-to-cart” category. Shoppers need to compare sizes, materials, styles, and delivery timelines, then feel confident the product will live up to expectations.

McPhails Furniture had three compounding problems:

Their previous search tool stopped delivering the results they needed. After ~5 years with SearchSpring, it no longer supported the level of relevance and control required for their fast-growing catalog and customer expectations.
They weren’t consistently matching the right products to the right shoppers. The team put it plainly: if you are not feeding relevant products to the right people, conversions stall.
Trust signals were underused. Before REVIEWS.io, customer reviews were minimal and mostly ad hoc, which meant shoppers had fewer confidence cues during evaluation.

That friction matters in eCommerce overall: the average documented cart abandonment rate is 70.22%. Reducing “decision friction” earlier in the journey is one of the most controllable levers brands have.

Upgrade to trust-based discovery

Get started with Boost x REVIEWS.io integration

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The solution: A search + recommendations + merchandising engine powered by reviews

McPhails Furniture chose Boost because it was consistently recommended during their market review and stood out as the right fit. Then they paired Boost with REVIEWS.io to make product discovery more relevant and more trusted, at the same time.

What they implemented (and why it worked)

Boost capability	What McPhails Furniture used	Value for the store
AI Search	AI synonyms, spell correction, search suggestions, and product performance ranking	Shoppers find what they mean, even when they describe products differently (critical in furniture naming)
Navigation and filters	Review rating filters, custom filter trees by category	Lets shoppers narrow by what matters and use social proof as a decision shortcut
Merchandising	Search merchandising rules tied to inventory and review rating	Keeps high-intent searches conversion-ready by prioritizing in-stock, well-reviewed products
Bundles	A volume discount bundle on dining chairs, with tiers at 6, 8, and 10 items	Rewards shoppers for furnishing the whole table, not just one seat
REVIEWS.io integration	Star-rating filters, review display across discovery	Builds confidence where decisions happen, not just on the product detail pages

How McPhails Furniture used Boost + REVIEWS.io in the real world

AI synonyms that match how furniture shoppers talk

McPhails Furniture leaned into AI-generated synonym support so shoppers could search naturally:

Search: ‘chest of drawers’, also surface results containing: ‘dresser’.
Search: ‘Side table’, also surface results containing: ‘Lamp Table’ or ‘Coffee Table’.

This approach effectively reduces 'dead ends' in the customer journey, ensuring seamless, intuitive product discovery and a smoother shopping experience.

Furthermore, AI-powered search boosts operational efficiency by eliminating the need for manual configuration and maintenance of similar-meaning search terms.

Merchandising rules that prioritize in-stock, well-reviewed products

By leveraging Boost's automatic merchandising rules with REVIEWS.io data, McPhails Furniture consistently surfaces the products most likely to convert, right at the moment shoppers search.

Recommendation widgets with top-rated products.

For high-intent queries like “Buffet” and “Lounge,” they configured Search merchandising to:

Prioritize products that are in stock (inventory ≥ 1)
or have strong social proof, as indicated by REVIEWS.io ratings of 4 stars or higher.

For brand- or collection-specific searches, such as “Lockhart,” they boosted products primarily based on review quality (rating ≥ 4 stars). And for broader category terms like “Bedroom,” “Outdoor,” “Dining,” and “Living,” they ensured customers could see items available to buy now by boosting products with inventory ≥ 1.

The value is simple: customers get higher-rated results faster, reducing out-of-stock items, and wasted time on non-conversion-ready options.

McPhails Furniture benefits from reliable, scalable merchandising. Instead of manual weekly curation, always-on rules automatically keep search results aligned with revenue drivers: availability and proven customer satisfaction.

Volume discount bundles that price the whole dining set

Nobody buys one dining chair. McPhails Furniture made that the offer with a volume discount bundle in Boost's Predictive Bundles.

The bundle covers six chairs from two ranges: four colorways of the Wishbone Dining Chair and two of the Nile Dining Chair. The discount grows with quantity, and each tier matches a common table size.

How the volume discount bundle works on the Wishbone Dining Chair product page.

Here's why it works for furniture.

A shopper planning six chairs can see exactly what two more would cost. Because the tiers follow real table sizes, adding more feels like finishing the set rather than being upsold. And because the rule applies only to specific products, McPhails keeps control of its margin, with the deepest discount unlocking only at ten chairs.

The results: Higher AOV, better-performing discovery, and more sales from slow-moving products

“Boost and REVIEWS.io have been game-changers for our online store. Boost has significantly improved how customers discover products, while REVIEWS.io has helped us build trust and confidence at key decision points. Together, both platforms have become essential tools in scaling our ecommerce operations.” - Regan, Ecommerce and IT Manager at McPhails Furniture.

Since implementing Boost Commerce, McPhails Furniture increased AOV by approximately 35.7%. They attributed this lift to stronger merchandising and upselling, as well as better recommendations that help shoppers complete a set or add complementary items without extra effort.

Click-through rate of AI-powered search results peaked at 8.23% in November 2025.
For furniture, that matters because searchers often have high intent. When results are relevant, shoppers move faster from “looking” to “comparing” to “buying.”

McPhails Furniture also saw a meaningful operational win: products that were previously slow-moving started selling more frequently. That is what happens when merchandising stops being guesswork and becomes performance-led.

Lessons learned for other Shopify furniture and homewares brands

If you want shoppers to find products faster, trust your store sooner, and increase their AOV, follow McPhails Furniture's playbook:

Upgrade product discovery with Boost Commerce
Turn social proof into a conversion lever with REVIEWS.io
Connect them so your search, filters, recommendations, and merchandising can prioritize what shoppers trust most

It’s always free to get started.

Empower your online discovery with reviews

Learn how Boost x REVIEWS.io integration can help

Learn more

Frequently asked questions

1. How does Boost use REVIEWS.io data in product discovery?

Boost uses REVIEWS.io rating data throughout the discovery journey, enabling features such as rating- and attribute-based filters and merchandising rules (e.g., boosting products with a ≥ 4-star rating). This makes review quality an active signal for shoppers. Integrating REVIEWS.io reviews and sentiment data also enhances our AI search and recommendation models, ensuring prominence for high-trust products.

2. How long does it take to set up the Boost x REVIEWS.io integration?

You can connect the apps in the blink of an eye. McPhails Furniture shared that it took about five minutes to subscribe to and pair the platforms.

3. What recommendation and bundle widgets worked best for McPhails Furniture?

They used Personalized Recommendations on the Home and Product pages, Frequently Bought Together on the Cart page, Classic Bundles across instant search, search results, and product pages, and a Volume Discount Bundle on dining chair product pages. Together, these cover the full journey: browse, evaluate, and checkout.

4. Can I boost or demote products based on inventory and review rating?

Yes. McPhails Furniture set merchandising rules to boost products for specific search terms when Inventory ≥ 1 or when REVIEWS.io rating ≥ 4 stars, depending on the query. This keeps results conversion-ready, especially during high-intent searches.

Ellie Ho

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Content Marketing Specialist

January 22, 2026

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3 min read

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How McPhails Furniture Lifted AOV by 35.7% with Boost Commerce and REVIEWS.io, After Switching from SearchSpring

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