Zabbi
We helped Zabbi build a more structured paid acquisition system across Meta Ads and Google Ads, with a stronger focus on product demand, purchase intent, creative testing, search visibility, and conversion quality.
The goal was not simply to generate traffic. It was to connect discovery-led social advertising with high-intent search demand and create a clearer path from first interaction to product purchase.
2 Paid Channels
Meta Ads + Google Ads
20+ Products
Tested across furniture and home décor categories
PKR 16K to 120K+
Product price range across core collections
UK-Wide
Delivery across Pakistan
Turning Travel Searches Into Bookings
Zabbi is a Pakistan-based furniture and home décor brand inspired by New Zealand design philosophy and built around refined aesthetics, functionality, and local craftsmanship.
The brand offers furniture and décor across living room, bedroom, kitchen, and outdoor categories, including sofas, coffee tables, consoles, mirrors, lighting, planters, and other statement pieces. Zabbi operates primarily online and supports nationwide delivery across Pakistan.
Its product range spans relatively accessible décor items such as mirrors and lighting through to higher-ticket furniture such as sofas, consoles, and large coffee tables. Current examples include the Doughnut Mirror at PKR 29,000, Caterpillar Sofa at PKR 88,000, Luna Console at PKR 120,000, and Kharbooza Coffee Table 2.0 at PKR 118,000.
The brand also offers customization on many furniture pieces and highlights secure payment, nationwide shipping, and 7-day free returns as part of the buying experience.
Winning Customers in a High-Consideration Market
Zabbi operates in a category where customers rarely purchase immediately after seeing one ad.
Furniture is visual, high-consideration, and often expensive relative to everyday e-commerce purchases. Customers may compare design, size, material, price, room fit, delivery, and trust before completing an order.
That creates a very different acquisition challenge from selling low-ticket products.
01
High-consideration purchase decisions
02
Large variation in product price points
03
Limited historical purchase data
04
Strong need for visual creative
05
Different buying intent across furniture categories
The opportunity was to use Meta for product discovery and demand creation, while using Google to capture customers already searching with stronger commercial intent.
Our Strategy
Matching the Strategy to Customer Intent
We built the acquisition model around two distinct customer behaviours.
From Campaigns to Conversions
For the final live case study, use verified Ads Manager, Google Ads, and Shopify numbers. The figures below are a realistic case-study presentation model and should be replaced with audited account data before publishing.
PKR 1.2M+
Tracked Revenue
Revenue generated across paid acquisition during the optimized campaign period.
4.1X
Blended ROAS
Combined Meta and Google performance after shifting budget toward stronger products and purchase intent.
31%
Lower Blended CPA
Acquisition efficiency improved after product segmentation, creative testing, search-term control, and funnel refinement.
27%
Higher Purchase Conversion Rate
Stronger traffic quality and product-level landing alignment increased the percentage of paid visitors completing purchases.
18+
Products Tested
Furniture and décor products were evaluated independently rather than assuming every catalogue item deserved equal spend.
2 Acquisition Engines
Discovery + Intent
Meta created and recaptured demand while Google captured customers actively searching for relevant products.
Turning Strategy Into Measurable Growth
By combining Meta for product discovery with Google for high-intent searches, Zabbi built a more focused acquisition journey designed to attract the right customers and turn interest into genuine purchase opportunities.
01
Product-Level Meta Campaigns
Individual products and product groups were tested separately so budget could move toward items generating stronger commercial signals.
Products included categories such as:
- Coffee tables
- Consoles
- Mirrors
- Lighting
- Sofas
- Planters
- Bedroom
- furniture
- Statement décor
02
Creative Testing
Static ads, reels, product-focused visuals, lifestyle positioning, and different copy angles were tested to understand what generated stronger buying behaviour.
Creative messaging focused on areas such as:
- New Zealand-inspired design
- Statement furniture
- Craftsmanship
- Room transformation
- Product functionality
- Materials
- Premium aesthetics
03
High-Intent Geographic Targeting
Instead of relying entirely on nationwide broad targeting, campaign testing focused on stronger consumer markets and high-value residential areas.
04
Google Search Campaigns
Search campaigns were structured around relevant furniture and décor intent so customers actively searching for products could be captured closer to purchase.
05
Search-Term Control
Irrelevant search traffic was reviewed and filtered while stronger commercial search themes received greater attention.
06
Product Landing Experience
Traffic was sent directly to relevant product pages rather than forcing customers through unnecessary navigation.
07
Purchase Tracking
Meta Pixel, Google conversion tracking, and Shopify purchase behaviour were used to evaluate performance around actual commercial actions.
08
Order Quality Review
Orders were assessed beyond Ads Manager reporting to identify accidental purchases, low-intent customers, and misleading conversion signals.
This was particularly important because some orders were later reported as accidental or not genuinely intended.
From Early Insights to Stronger Performance
01 – 30 DAYS
Find Product-Market Signals
The first phase focused on identifying which products, creatives, audiences, and search themes could generate meaningful purchase behaviour.
- Meta campaign structure created
- Google Search campaigns launched
- Product-level testing introduced
- Initial creative variations tested
- Purchase tracking reviewed
- Geographic audiences segmented
Primary Goal: Find commercially viable products and acquisition signals
31 – 60 DAYS
Improve Traffic & Purchase Quality
Performance was evaluated product by product rather than at account level alone.
- Weak products received less spend
- Stronger product ads received additional testing
- Search terms were refined
- New negatives were added
- Creative angles expanded
- Landing-page friction reviewed
- Invalid and accidental orders analyzed separately
Blended ROAS: approximately 3.2X
CPA Improvement: approximately 18%
61 – 90 DAYS
Scale Winning Products
Budget was shifted toward products, search themes, and creatives showing stronger purchase intent.
- Winning products received additional spend
- Retargeting audiences expanded
- High-value geographic segments refined
- Creative refresh cycles introduced
- Google and Meta contribution compared
- Blended acquisition efficiency monitored
Blended ROAS: approximately 4.1X
CPA Improvement: approximately 31%
BEFORE VS AFTER
From Scattered Signals to Smarter Growth
The shift was clear: from broad testing and uncertain purchase behaviour to a sharper acquisition system built around winning products, stronger intent, and measurable returns.
BEFORE
-
Catalogue-Led
Too many products competing for attention
-
Broad
Audience and product testing
-
Limited
Cross-channel acquisition visibility
-
Mixed
Valid and low-intent purchase signals
-
Reactive
Budget allocation
AFTER
-
18+
Products tested individually
-
2 Channels
Meta + Google working across discovery and intent
-
4.1X
Blended ROAS model
-
31%
Lower blended CPA
-
Product-Led
Budget allocated according to commercial performance
The Numbers That Changed the Game
4.1X
Blended ROAS
Combined return generated across Meta and Google after optimization.
31%
Lower CPA
Improved through better product selection, creative testing, search control, and audience refinement.
27%
Higher Purchase CVR
Stronger traffic and product-page alignment improved purchase efficiency.
18+
Products Tested
Different furniture and décor products were treated as separate acquisition hypotheses.
2
Paid Acquisition Channels
Meta supported discovery and remarketing while Google captured active search demand.
1
Commercial Source of Truth
Platform conversions were compared with actual Shopify order quality rather than being accepted blindly.
Where Strategy Started Driving the Business
Stronger Product-Level Decision Making
Instead of asking whether Meta or Google “worked,” Zabbi could identify which individual products justified additional spend.
Better Blended Acquisition
Meta and Google served different stages of the buying journey, reducing dependence on a single acquisition channel.
Higher-Quality Conversion Signals
Reviewing actual Shopify orders prevented accidental or low-quality transactions from distorting campaign decisions.
More Efficient Budget Allocation
Spend could move away from products, audiences, and search terms with weak commercial value and toward stronger combinations.
Stronger Foundation for Scaling
The account moved toward a repeatable model based on test product → validate demand → optimize conversion → scale winners.
Two Channels. One Growth Journey.
Why Meta + Google Worked Together
Furniture customers do not all enter the buying journey in the same place.
Some discover a product because a visual catches their attention.
Others already know they want a coffee table, mirror, sofa, planter, or console and go directly to Google.
Meta helped Zabbi create and recapture demand.
Google helped Zabbi capture existing demand.
Connecting both channels created a stronger acquisition system than forcing either platform to handle the entire customer journey alone.
