Hey friend!

At the beginning of 2024, we started working with an apparel brand that had built a loyal following and an expanding product catalogue. However, they struggled to scale beyond $150K per month while maintaining profitability.

In today’s edition of the Brick-By-Brick newsletter, we break down exactly what our team did over a 9-month timeframe to scale them to $1.1m per month… profitably.

IN TODAY’S EDITION

• How We Scaled an Apparel Brand from $150K to $1.19M Per Month Profitably

• AI Research Cheatsheet (Resource Giveaway)

Let’s dive in!

The Challenge

We were tasked with:

• Efficiently scaling their revenue through Meta & Google Ads

• Exploring previously untapped channels, such as YouTube

• Ensuring ad spend was managed effectively day-to-day

• Implementing a seamless creative testing process and feedback loop

• Building solid foundations (outside of the ad account) for consistent and scalable growth

• Maintaining the brand’s unique aesthetic and tone.

The Results

How We Did It

Consumer & Market Research: The Foundation of Success

Before making any major changes, we conducted in-depth research to ensure our decisions were data-driven rather than assumption-based. Our research focused on several key areas:

Customer & Competitor Review Analysis

• We analysed thousands of customer reviews, categorising feedback into common themes such as product quality, customer pain points, and reasons for repeat purchases.
  

• This process provided valuable insights into objections and motivations, helping us tailor ad copy and creative messaging that directly resonated with potential buyers.
  

  • We also reviewed competitor feedback to identify gaps in product offerings and customer service, which helped inform our positioning. We did this through analysing their product reviews and Facebook groups where people were discussing their products.

Data-Driven Persona Development

• Using Shopify, Google Analytics, previous customer interviews and post-purchase survey data, we segmented the brand’s customer base into distinct personas based on demographics, purchase behaviour, and interests.

• Each persona received customised ad creatives and messaging, ensuring we were speaking to their specific needs and preferences.

Ad Performance History Audit

• We conducted a retrospective analysis of all existing ad campaigns to identify patterns in creative performance, audience engagement, and best-performing products.

• This allowed us to double down on proven messaging angles while eliminating ineffective spend on underperforming assets.

• This also allowed us to identify areas that hadn't been tested and allowed us to spot low hanging fruit as to what to test first.

Website CRO & Optimisation

We conducted a deep CRO audit of their primary landing pages, identifying key areas for improvement:

• Improved product discovery: We analysed heatmaps to understand where users were dropping off, leading to improved product filtering and category structures that streamlined the browsing experience.
  

• Streamlined navigation: We removed jargon-heavy branding terms in favour of clearer, conversion-focused category names that new customers could easily understand.
  

• Free-shipping strategy: We tested multiple free shipping thresholds to identify the most profitable point where customers increased their basket size without negatively impacting conversion rates.
  

• AOV increase: Incremental price increases across key product lines led to higher average order values, which we tested against discount incentives to find the optimal balance between perceived value and conversion.
  

• Enhanced product pages: We added multiple additional image types to cater to different consumer decision-making styles:

  • Product shots (clear visuals of the item, up close and detailed)

  • Call-out images (highlighting key features and benefits)

  • Lifestyle images (helping customers visualise the product in real-life use)

  • UGC (providing social proof but also helping customers visualise the product in real-life use)

  • Product-in-use visuals (showing functionality and scale)
    

• Implemented upsells & cross-sells: We introduced personalised recommendations at checkout based on browsing and purchase behaviour, which increased units per transaction.
  

• Simplified the checkout process: We reduced cart abandonment rates by 12% by removing unnecessary fields and distractions.
  

• Site speed optimisation: A combination of lazy-loading images, compressing assets, and reducing third-party scripts significantly improved site load times.
  

• Tested into landing pages, including advertorials, ambassador, and collection landing pages to drive more targeted traffic and increase conversions. We A/B tested different storytelling approaches, with advertorial-style pages outperforming standard product pages by 18% in conversion rates.
  

• Introduced heatmapping tools to track customer interactions, identify friction points, and optimise key sections for better engagement. This data helped us remove bottlenecks in the checkout process and adjust content hierarchy on key pages.
  

• Used Knocommerce for post-purchase surveys to gain insights on customer experience and improve retention strategies. We specifically asked new customers about what nearly prevented them from purchasing, which informed our future ad creative and product positioning.

CRO Impact:

• Site speed improvements:

  • Desktop performance: 32 → 96

  • Mobile performance: 13 → 66

• Conversion rate increase: +23.88%

• AOV increase: +18%
  

• Offer Testing: We tested a variety of promotional structures to identify the highest-converting incentives, including:

  • Spend X, Get Y Gift: Encouraged higher basket values with minimal impact on margin.

  • Tiered Discounts: Increasing discount amounts based on cart value boosted AOV significantly.

  • Bundles vs. Individual Discounts: Testing showed that product bundles created more perceived value, leading to higher conversions.

All changes were tested incrementally to measure their impact before full implementation.

Omni-channel Synergy

We ensured all marketing efforts worked cohesively by aligning Meta, Google, YouTube, and email/SMS marketing into a unified strategy. This meant:

• Retargeting customers across multiple platforms with consistent messaging.

• Leveraging Google search intent data to inform Meta ad angles.

• Using email and SMS to reinforce ad messaging, increasing conversion rates by 10%.

We improved customer retention, engagement, and conversion rates by synchronising messaging across channels. This also allowed us to maximise cross-channel attribution and ensure no marketing effort operated in isolation.

Account Restructuring & Ad Optimisation

Meta & Google Ads: Initial Optimisation & Ongoing Management

When we first took over the brand’s Meta and Google Ads accounts, they were disorganised, inefficient, and lacked a structured testing framework. Here’s how we transformed them:

Initial Optimisation:

• Restructured Campaigns for Efficiency: The existing setup had multiple audience overlaps and fragmented campaigns, leading to wasted ad spend. We consolidated campaigns into a simplified, data-driven structure allowing better tracking and optimisation.
  

• Refined Targeting Strategy: We eliminated inefficient audience segments and replaced them with broad targeting, lookalike audiences, and high-intent custom audiences based on purchase data and engagement signals.
  

• Implemented Cost Controls: The previous campaigns were overspending on low-performing segments. We introduced bid caps, cost caps, and manual bidding strategies to ensure profitability while scaling aggressively.
  

• Creative & Offer Testing Integration: We launched controlled A/B tests across multiple creatives, ensuring that real data backed every ad variation before scaling. We tested variations in:

  • Hook angles (pain points vs. benefits-driven messaging)

  • Formats (static images, carousels, video ads, and UGC)

  • Headlines & CTAs (direct response vs. soft call-to-action approaches)
    

• Google Ads Performance Max Overhaul: The previous Google Ads structure relied too heavily on standard search campaigns. We transitioned to Performance Max campaigns, refining asset groups, negative keyword lists, and audience signals to drive more efficient spend allocation.

Ongoing Management & Optimisation:

• Daily Bid & Budget Adjustments: We monitored performance metrics such as CPA, ROAS, CTR, and CVR daily, making micro-adjustments to bids and budgets to maintain efficiency while pushing for scale.
  

• Automated Rules & Manual Oversight: We combined automation (e.g., rules for pausing low-performing ads) with manual checks to ensure the system adapted to real-time performance trends.
  

• Scaling Strategy: Rather than increasing spend across the board, we followed a structured incremental scaling approach where we identified top-performing campaigns and gradually increased budgets by 10-20% every 48 hours, preventing performance degradation.
  

• Keyword & Search Query Refinement: On Google, we conducted weekly search term audits, continuously refining negative keyword lists to eliminate irrelevant traffic.
  

• Creative Rotation & Fatigue Management: To prevent creative fatigue, we implemented a rolling creative refresh cycle, ensuring that winning ads were adapted and reintroduced with slight modifications in copy, angles, and visuals.

Seamless Feedback Loop Between Creative & Media Buying

One of the biggest challenges brands face is the disconnect between creative production and media buying. We ensured our creative strategists and media buyers worked in lockstep, resulting in faster iterations and data-backed creative decision-making. Here’s how:

• Creative Briefs Built from Real Data: Instead of guessing what might work, we built our creative briefs using insights from ad performance reports. If a certain messaging angle was resonating (e.g., “softest fabric ever” vs. “made for everyday wear”), we doubled down on it in future creatives.
  

• Weekly Creative Reviews: Our creative and media buying teams met weekly to review performance trends, allowing us to pivot quickly when certain creatives underperformed.
  

• Modular Creative Approach: We developed modular ad creatives, where different elements (hook, problem statement, CTA, product highlights) could be swapped in and out easily, allowing us to iterate rapidly without needing completely new assets each time.
  

• Real-Time Performance Feedback: If a new creative underperformed, media buyers could instantly provide feedback to the creative team, ensuring constant alignment and faster turnaround times on necessary adjustments.

The Final Results

• Scaled revenue from $147K/month → $1.19M/month in 9 months

• Achieved 3.5X ROAS while maintaining profitability

• Ongoing growth with scalable creative & ad strategies

With this partner's great products combined with our team's expertise, this brand has reached new heights—and is still growing!

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