Case study · Premium Furniture Ecommerce

Selling premium Italian design furniture on intent, not discounts

Calligaris is a benchmark name in considered, high-AOV design furniture — dining, seating and lighting bought slowly and rarely on a whim. We rebuilt its Paid Search and Shopping engine around true profitability, feeding Performance Max with a clean product catalogue and bidding to value, lifting blended ROAS to 4.2x while protecting the brand's premium price positioning.

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Client
Calligaris
Sector
Premium Furniture Ecommerce
Services
Paid Search (Google & Bing PPC), Performance Max, Shopping Feed Optimisation, Remarketing, Conversion Tracking & Value Bidding
Region
United Kingdom
Timeframe
12 months
0xBlended ROASfrom 2.0x baseline
+0%Online revenuepaid channels, 12 months
−0%Cost per acquisitionblended paid
+0%Average order valuepremium mix shift

The brand

Calligaris is one of Italy's most recognised design-furniture houses, crafting dining tables, chairs, sofas and lighting for the home since 1923. Its catalogue sits firmly at the premium end: pieces chosen deliberately, often saved for and configured to taste, with order values that dwarf everyday retail. The challenge with a brand like this is never demand — it is patience. The buyer researches for weeks across devices and showrooms before committing, and the wrong paid strategy simply pays to discount a product that should never compete on price.

Calligaris premium design furniture — lounge seating
FIG. 01

The challenge

High prices, long decisions and a feed that didn't tell the story

Premium furniture breaks most default paid-media playbooks. Order values are high but conversion rates are low, so any account optimised to last-click "purchases" quickly starves the very campaigns driving the considered, multi-week journeys that actually close. Calligaris also carries a vast configurable catalogue — finishes, materials and dimensions — which a generic Shopping feed flattens into noise, surfacing the wrong variants for the wrong searches. The brief was to grow online revenue without ever leaning on discount-led bidding: protect the premium positioning, get the right product in front of genuine intent, and bid to the real value of a long, high-AOV sale.

A £2,000 dining set and a £40 impulse buy are not the same problem. We rebuilt the account to bid for the customer, not the click.

After: value-led Calligaris Shopping & Performance Max
Before
BeforeAfter

The approach

Four moves to make every pound work harder.

01

Rebuild the product feed

We restructured the Shopping feed from the ground up — clean titles, finishes, materials and dimensions mapped to real search behaviour — so the right configurable variant surfaces for the right query instead of one flattened, generic listing.

Feed coverage +47%
02

Bid to value, not clicks

We moved the account off last-click "purchases" and onto a value-based model, feeding Performance Max and Search with conversion values weighted to AOV and margin so the algorithm chases profit on a high-price, low-frequency catalogue.

Blended ROAS 4.2x
03

Earn the considered buyer

Furniture is researched for weeks before it is bought, so we layered patient remarketing across Search and Shopping — staying present through showroom visits and cross-device comparison instead of forcing a first-session sale.

CPA -34%
04

Protect the premium

No race to the bottom: tightly themed asset groups and brand-led creative kept Calligaris positioned as design-led, not discount-led, lifting the share of revenue coming from higher-value collections.

AOV +61%

The results, in depth

The growth ledger.

Every channel, before and after — an audited view of where the value-led growth actually came from.

Shopping & Performance MaxRebuilt feed, value-based bidding1.8x
0x+156%
Paid Search (Google & Bing)Branded + high-intent category2.3x
0x+122%
RemarketingConsidered-purchase re-engagement3.1x
0x+119%
Online revenuePaid channels, 12 monthsBase
+0%YoY
Average order valuePremium collection mix shiftBase
+0%vs. start
TotalBlended ROAS 4.2xOnline revenue +118%Cost per acquisition -34%

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