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SO, WHAT WERE THEY SELLING?

Graphic tees, hoodies and pop-culture apparel across different fandoms, genres and limited-edition drops.

The catalogue was not the problem. The challenge was knowing which products deserved attention right now.

WAY TOO MANY DESIGNS!

A catalogue this large can make an account look busy very quickly.

But busy is not the same as well managed.

The account had three things working against it:

WAY TOO MANY DESIGNS!

Strong designs and weak designs were often sharing the same budget, which made it harder for the real winners to break through.

NEEDED A MERCHANDISING SYSTEM

Limited drops needed to be tested quickly. Waiting too long for perfect data meant missing the moment when interest was highest.

THE ACCOUNT NEEDED A MERCHANDISING SYSTEM

The real question was not:

“Which campaign performed best?”

It was:

“Which design, collection and fandom is actually earning more budget?”

SO I BUILT A TEST, SCALE OR DROP SYSTEM.

Controlled
testing

Fresh products launched with enough budget to prove demand, without immediately being treated like guaranteed winners.

More spend to proven designs

Products with repeatable purchase volume earned more spend and a longer life inside catalogue and evergreen activity.

Treated Fandoms Sperately

Campaigns and creative were grouped around distinct themes instead of speaking to every pop-culture buyer in the same way.

Weak products were dropped

Designs that failed to earn clicks, carts or purchases were removed before they consumed too much budget

WAY TOO MANY DESIGNS!

A catalogue this large can make an account look busy very quickly. But busy is not the same as well managed.

Too many products competing for attention

👕

Design 01

🧢

Design 02

👕

Design 03

🧥

Design 04

🎨

Design 05

👕

Design 06

🧢

Design 07

👕

Design 08

Three things were working against the account

⚔️

Too many products
were competing

Strong designs and weak designs were often sharing the same budget, which made it harder for the real winners to break through.

🎭

Every fandom
behaved differently

Horror, gaming, anime, retro and sci-fi buyers did not respond to the same creative, message or offer.

⏱️

New launches had
a short window

Limited drops needed to be tested quickly. Waiting too long for perfect data meant missing the moment when interest was highest.

THE ACCOUNT NEEDED
A MERCHANDISING SYSTEM

The real question was not:

“Which campaign
performed best?”

→

“Which design,
collection & fandom
deserves budget?”

🎨

Design

Which individual products are earning attention and sales?

🗂️

Collection

Which groups of products are creating repeatable demand?

🎭

Fandom

Which audience themes are actually buying?

SO I BUILT A
TEST, SCALE OR DROP SYSTEM.

🧪

Test

Give new products enough room to prove demand.

→

📈

Scale

Give proven winners more budget and life.

→

Drop

Cut weak products before they consume more budget.

🧪

New designs entered
controlled testing

Fresh products launched with enough budget to prove demand, without immediately being treated like guaranteed winners.

New Product Controlled Budget Demand Test

📈

Proven designs moved
into stronger campaigns

Products with repeatable purchase volume earned more spend and a longer life inside catalogue and evergreen activity.

Proven Winner More Budget Evergreen

🎭

Fandoms were
treated separately

Campaigns and creative were grouped around distinct themes instead of speaking to every pop-culture buyer in the same way.

Horror Gaming Anime Retro

✂️

Weak products
were cut faster

Designs that failed to earn clicks, carts or purchases were removed before they consumed too much budget.

Low Clicks Low Carts No Purchases

HERE’S WHAT THE STRATEGY PRODUCED

MY KEY TAKEAWAYS

With a fast moving catalogue, the hardest part is not launching ads.

It is making product decisions quickly enough that good designs get room to grow and weak ones stop taking up budget.

The account worked better once paid media started behaving more like merchandising.

SO, WHAT WERE THEY OFFERING?

Premium coffee products for customers who cared about quality, taste and convenience. Getting consistent results was not the hard part, scaling it consistently was the real deal.

The actual problem

Some campaigns performed. Some didn’t. The bigger issue was that there wasn’t enough structure behind scaling with consistent returns.

The account had three things working against it:

THE ACTUAL PROBLEM

Some campaigns performed. Some didn’t. The bigger issue was that there wasn’t enough structure behind scaling with consistent returns.

THEY HAD DATA. HAD TO BE USED RIGHT

There were enough campaigns running to learn from. The problem was that the account wasn’t consistently using those learnings to decide what to kill, what to keep and what deserved more money.

THE ACCOUNT HAD THE DATA. IT ONLY HAD TO BE USED RIGHT

There were enough campaigns running to learn from.

The problem was that the account wasn’t consistently using those learnings to decide what to kill, what to keep and what deserved more money.

SO I MADE THE TESTING A LOT MORE BORING.

Segment audiences properly

Interest groups, lookalikes and warmer audiences were tested separately instead of being bundled into the same structure.

Built a repeatable system

New visuals, copy and offers were tested against clear controls so it was easier to see what was actually moving performance.

Improved path to purchase

Landing-page and checkout friction was reviewed so the ad was not doing all the work only to lose the customer afterwards.

Scaled
gradually

Winning campaigns earned more budget once they had enough data to prove they could handle it.

THE ACTUAL PROBLEM

Some campaigns performed. Some didn’t. The bigger issue was that there wasn’t enough structure behind scaling with consistent returns.

Campaign performance was moving in different directions

Campaign 01

Campaign 02

Campaign 03

Campaign 04

Campaign 05

Three things were working against the account

📉

ROAS was
inconsistent

Some campaigns were barely breaking even, which made it difficult to know where more budget should go.

🎯

The audience
was too narrow

The campaigns were missing potential buyers outside the most obvious coffee-interest segments.

📈

Scaling had
no real system

Increasing spend without knowing which audiences and messages were producing serious purchases only made the waste bigger.

The problem wasn’t a lack of data. It was a lack of structure for turning data into decisions.

THE ACCOUNT HAD THE DATA.
IT ONLY HAD TO BE USED RIGHT.

There were enough campaigns running to learn from. The problem was that the account wasn’t consistently using those learnings to decide what to kill, what to keep and what deserved more money.

📊

Data

Performance signals

→

❌

Kill

Remove weak performers

→

✓

Keep

Protect what works

→

📈

Scale

Give winners more room

The goal wasn’t to run more tests. It was to build a system where every test created a clearer next decision.

SO I MADE THE TESTING
A LOT MORE BORING.

🧪

Test

📊

Measure

🧠

Learn

📈

Scale

🎯

Separated the
audiences properly

Interest groups, lookalikes and warmer audiences were tested separately instead of being bundled into the same structure.

Interests Lookalikes Warm Audiences

🧪

Built a repeatable
creative-testing system

New visuals, copy and offers were tested against clear controls so it was easier to see what was actually moving performance.

Visuals Copy Offers

🛒

Improved the
path to purchase

Landing-page and checkout friction was reviewed so the ad wasn’t doing all the work only to lose the customer afterwards.

Landing Page Checkout Conversion

📈

Scaled
gradually

Winning campaigns earned more budget once they had enough data to prove they could handle the additional spend.

Proven Winners More Data Gradual Scale

HERE’S WHAT THE STRONGER CAMPAIGNS LOOKED LIKE

✦

GOOGLE PICKED UP THE PEOPLE ALREADY LOOKING

Meta helped create interest and bring the space into consideration. Google handled a different job: capturing people already searching for coffee, machinery and a potential partnership.

MY KEY TAKEAWAYS

Scaling gets a lot easier once the account stops guessing.

The biggest improvement here wasn’t one “winning ad”. It was building a system that made it obvious which campaigns deserved more budget and which ones didn’t.

SO, WHAT WERE THEY OFFERING?

Residential properties in the United States with a unique offer. Challenge wasn’t convincing people that homes are interesting. It was finding the people who were actually in a position to buy one.

The actual problem

Real-estate ads can attract a lot of curiosity. Unfortunately, curiosity and buying intent are not the same thing. The account had three things working against it:

THE ACTUAL PROBLEM

Real-estate ads can attract a lot of curiosity.

Unfortunately, curiosity and buying intent are not the same thing.

AN ENQUIRY CAN MEAN ANYTHING.

It might mean: “I’m ready to book a viewing.” Or: “I like this kitchen and wanted the brochure.” The campaigns needed a better way to tell those people apart before the sales team spent time following up.

A PROPERTY ENQUIRY CAN MEAN ALMOST ANYTHING.

It might mean:

“I’m ready to book a viewing.”

Or:

“I like this kitchen and wanted the brochure.”

The campaigns needed a better way to tell those people apart before the sales team spent time following up.

SO I MADE THE LEAD FORM DO MORE OF THE WORK.

Added qualification Qs

The instant forms asked for useful information such as preferred location, budget, purchase timeline and financing status.

Reworked the creative

Ads highlighted location benefits, property features, payment flexibility and lifestyle value instead of relying on generic listing visuals.

Improved follow-up flow

Lead details were structured so serious prospects could be identified and contacted faster.

Rephrased existing offer

I rephrased their existing offer to look more attractive and pull in serious buyers.

The actual problem

Real-estate ads can attract a lot of curiosity. Unfortunately, curiosity and buying intent are not the same thing.

The account had three things working against it:

👥

Too Many Low-Intent Leads

A large share of enquiries came from people browsing listings rather than actively planning a purchase.

🎯

The Audience Was Too Broad

Budget was being spread across people with very different levels of intent, affordability and readiness.

🏷️

A Weak Offer Was Presented

The offer was unique but not attractive enough to pull in serious buyers.

“`

A PROPERTY ENQUIRY CAN MEAN ALMOST ANYTHING

It might mean: “I’m ready to book a viewing.”

Or: “I like this kitchen and wanted the brochure.”

The campaigns needed a better way to tell those people apart before the sales team spent time following up.

SO I MADE THE LEAD FORM
DO MORE OF THE WORK

👤

Raw Lead

Someone shows interest

→

🔎

Qualify

Understand their situation

→

⚡

Prioritise

Find serious prospects

→

🤝

Buyer

Sales conversation

🔎

Added qualification
questions

The instant forms asked for useful information such as preferred location, budget, purchase timeline and financing status.

Location Budget Timeline Financing

🎨

Reworked
the creative

Ads highlighted location benefits, property features, payment flexibility and lifestyle value instead of relying on generic listing visuals.

Location Features Payments Lifestyle

⚡

Improved the
follow-up flow

Lead details were structured so serious prospects could be identified and contacted faster.

Lead Data Prioritisation Faster Contact

✨

Rephrased their
existing offer

I rephrased their existing offer to make it more attractive and compelling, helping pull in prospects who were more serious about buying.

Offer Value Buyer Intent

The form stopped being just a place to collect names. It became a qualification layer between the ad and the sales team.

HERE’S WHAT THE THREE MAIN CAMPAIGNS PRODUCED.

MY KEY TAKEAWAYS

Real estate campaigns can generate leads very quickly when the form is easynand the targeting is broad. That does not mean the sales team is gettingngood opportunities.

The real improvement came from asking better questions, making the ads more specific and being clearer about who the property was actually for.

The actual problem

Real-estate ads can attract a lot of curiosity. Unfortunately, curiosity and buying intent are not the same thing.

The account had three things working against it:

👥

Too Many Low-Intent Leads

A large share of enquiries came from people browsing listings rather than actively planning a purchase.

🎯

The Audience Was Too Broad

Budget was being spread across people with very different levels of intent, affordability and readiness.

🏷️

A Weak Offer Was Presented

The offer was unique but not attractive enough to pull in serious buyers.

“`

A PROPERTY ENQUIRY CAN MEAN ALMOST ANYTHING

It might mean: “I’m ready to book a viewing.”

Or: “I like this kitchen and wanted the brochure.”

The campaigns needed a better way to tell those people apart before the sales team spent time following up.

SO I MADE THE LEAD FORM
DO MORE OF THE WORK

👤

Raw Lead

Someone shows interest

→

🔎

Qualify

Understand their situation

→

⚡

Prioritise

Find serious prospects

→

🤝

Buyer

Sales conversation

🔎

Added qualification
questions

The instant forms asked for useful information such as preferred location, budget, purchase timeline and financing status.

Location Budget Timeline Financing

🎨

Reworked
the creative

Ads highlighted location benefits, property features, payment flexibility and lifestyle value instead of relying on generic listing visuals.

Location Features Payments Lifestyle

⚡

Improved the
follow-up flow

Lead details were structured so serious prospects could be identified and contacted faster.

Lead Data Prioritisation Faster Contact

✨

Rephrased their
existing offer

I rephrased their existing offer to make it more attractive and compelling, helping pull in prospects who were more serious about buying.

Offer Value Buyer Intent

The form stopped being just a place to collect names. It became a qualification layer between the ad and the sales team.

HERE’S WHAT THE THREE MAIN CAMPAIGNS PRODUCED

MY KEY TAKEAWAYS

Real estate campaigns can generate leads very quickly when the form is easy and the targeting is broad. That does not mean the sales team is getting good opportunities.

The real improvement came from asking better questions, making the ads more specific and being clearer about who the property was actually for.

SO WHAT WERE THEY SELLING?

A faith-based ecommerce brand selling apparel, rosaries, jewellery and accessories to a pretty specific audience. And that specificity was both thenadvantage and the problem.

THE ACTUAL PROBLEM

Religious content naturally gets likes, comments and shares. Great for community. Not automatically great for revenue.

WHAT I NOTICED…

I stopped treating everyone who interacted with the brand as one big audience. Some people were there for the content. Some were browsing. Some had shown actual purchase intent.

SO I REBUILT HOW THE ACCOUNT
THOUGHT ABOUT PEOPLE

📦

Separated
the products

Rosaries, apparel and accessories got their own campaigns, messaging and budgets instead of fighting inside one generic setup.

🎯

Separated interest
from intent

Engagement audiences were useful for building familiarity. Purchase-focused campaigns were reserved for people showing stronger buying signals.

👥

Expanded without
going completely broad

Past purchasers, email lists and engaged users helped build lookalikes, while adjacent interests gave the account room to grow beyond the obvious faith-based audiences.

📈

Made retargeting
actually sell

Product ads, testimonials, discounts and reminders went back to people who had already given us a reason to believe they might buy.

SO I REBUILT HOW THE ACCOUNT THOUGHT ABOUT PEOPLE

Separated the products

Rosaries, apparel and accessories got their own campaigns, messaging and budgets instead of fighting inside one generic setup.

Separated interest & intent

Engagement audiences were useful for building familiarity. Purchase-focused campaigns were reserved for people showing stronger buying signals

Expanded without broad

Past purchasers, email lists and engaged users helped build lookalikes, while adjacent interests gave the account room to grow beyond the obvious faith-based audiences.

Made retargeting sell

Product ads, testimonials, discounts and reminders went back to the people who had already given us a reason to believe they might buy.

AND THEN THE NUMBERS STARTED LOOKING LIKE THIS

BUT, META WASN’T WORKING ALONE!

Meta handled discovery, demand generation and retargeting. Google gave us another way to capture people already searching with intent.

MY KEY TAKEAWAYS

Niche audiences don’t always need more targeting. Sometimes they need better separation.

And high engagement is only impressive when you know what role it’s meant to play.

Contact Us

Let’s talk fragrance.

We would love to hear from you

Before you write

SO, WHAT WERE THEY SELLING?

WAY TOO MANY DESIGNS!

WAY TOO MANY DESIGNS!

NEEDED A MERCHANDISING SYSTEM

THE ACCOUNT NEEDED A MERCHANDISING SYSTEM

SO I BUILT A TEST, SCALE OR DROP SYSTEM.

Controlled testing

More spend to proven designs

Treated Fandoms Sperately

Weak products were dropped

WAY TOO MANY DESIGNS!

Too many products were competing

Every fandom behaved differently

New launches had a short window

THE ACCOUNT NEEDED A MERCHANDISING SYSTEM

SO I BUILT A TEST, SCALE OR DROP SYSTEM.

New designs entered controlled testing

Proven designs moved into stronger campaigns

Fandoms were treated separately

Weak products were cut faster

HERE’S WHAT THE STRATEGY PRODUCED

MY KEY TAKEAWAYS

SO, WHAT WERE THEY OFFERING?

The actual problem

THE ACTUAL PROBLEM

THEY HAD DATA. HAD TO BE USED RIGHT

THE ACCOUNT HAD THE DATA. IT ONLY HAD TO BE USED RIGHT

SO I MADE THE TESTING A LOT MORE BORING.

Segment audiences properly

Built a repeatable system

Improved path to purchase

Scaled gradually

THE ACTUAL PROBLEM

ROAS was inconsistent

The audience was too narrow

Scaling had no real system

THE ACCOUNT HAD THE DATA. IT ONLY HAD TO BE USED RIGHT.

SO I MADE THE TESTING A LOT MORE BORING.

Separated the audiences properly

Built a repeatable creative-testing system

Improved the path to purchase

Scaled gradually

HERE’S WHAT THE STRONGER CAMPAIGNS LOOKED LIKE

GOOGLE PICKED UP THE PEOPLE ALREADY LOOKING

MY KEY TAKEAWAYS

SO, WHAT WERE THEY OFFERING?

The actual problem

THE ACTUAL PROBLEM

AN ENQUIRY CAN MEAN ANYTHING.

A PROPERTY ENQUIRY CAN MEAN ALMOST ANYTHING.

SO I MADE THE LEAD FORM DO MORE OF THE WORK.

Added qualification Qs

Reworked the creative

Improved follow-up flow

Rephrased existing offer

The actual problem

The account had three things working against it:

Too Many Low-Intent Leads

The Audience Was Too Broad

A Weak Offer Was Presented

A PROPERTY ENQUIRY CAN MEAN ALMOST ANYTHING

SO I MADE THE LEAD FORM DO MORE OF THE WORK

Added qualification questions

Reworked the creative

Improved the follow-up flow

Rephrased their existing offer

HERE’S WHAT THE THREE MAIN CAMPAIGNS PRODUCED.

MY KEY TAKEAWAYS

The actual problem

The account had three things working against it:

Too Many Low-Intent Leads

The Audience Was Too Broad

A Weak Offer Was Presented

A PROPERTY ENQUIRY CAN MEAN ALMOST ANYTHING

SO I MADE THE LEAD FORM DO MORE OF THE WORK

Added qualification questions

Controlled
testing

Too many products
were competing

Every fandom
behaved differently

New launches had
a short window

THE ACCOUNT NEEDED
A MERCHANDISING SYSTEM

SO I BUILT A
TEST, SCALE OR DROP SYSTEM.

New designs entered
controlled testing

Proven designs moved
into stronger campaigns

Fandoms were
treated separately

Weak products
were cut faster

Scaled
gradually

ROAS was
inconsistent

The audience
was too narrow

Scaling had
no real system

THE ACCOUNT HAD THE DATA.
IT ONLY HAD TO BE USED RIGHT.

SO I MADE THE TESTING
A LOT MORE BORING.

Separated the
audiences properly

Built a repeatable
creative-testing system

Improved the
path to purchase

Scaled
gradually

SO I MADE THE LEAD FORM
DO MORE OF THE WORK

Added qualification
questions

Reworked
the creative

Improved the
follow-up flow

Rephrased their
existing offer

SO I MADE THE LEAD FORM
DO MORE OF THE WORK

Added qualification
questions

Reworked
the creative

Improved the
follow-up flow

Rephrased their
existing offer

SO I MADE THE TARGETING
A LOT LESS POLITE.

TOO MANY BRANDS WERE
SAYING THE SAME THING.

The positioning
was too generic

The creative
was getting tired

Cold audiences
were asked to buy too quickly

NOW THIS IS WHAT
I NOTICED……

FIRST-TIME
VISITOR

PRODUCT-AWARE
SHOPPER

SO I GAVE EACH PART OF THE
FUNNEL A DIFFERENT JOB.

Made the positioning
more specific

Built a proper
creative rotation strategy

Added more education
at the top

Matched the message
to intent

SO I MADE THE TARGETING
A LOT LESS POLITE.

The targeting
was too loose

The ads weren’t
giving people a reason to visit

Scaling had
no real system

A LEAD FORM WASN’T
THE REAL GOAL.

SO I BUILT THE CAMPAIGNS
AROUND BOOKING TOURS.