Case Study: Scaling a Apparel Brand
Before I dive into yet another whopping case study, I must give you a disclaimer…
I’ve managed advertising for 8-9 figure brands in the information and e-commerce industry for the last 5 years.
My team and I work closely with 25-30 clients annually and manage more than 3 million dollars in ad spend every month.
This case study examines the strategies and outcomes of a marketing campaign for a unisex t-shirt apparel brand. The brand, facing initial challenges with low Return on Ad Spend (ROAS) and limited advertising budget, aimed to increase spending while maintaining profitability. The breakeven for profitability was identified as a ROAS of 1.8x. We onboarded them in May, at a point where the brand was struggling to achieve these objectives. We scaled this brand from spending $2,000 per month to $96,000 per month.
The sales for the website were low. The primary challenge was increasing ad spend while maintaining or improving ROAS. Initially, the brand struggled with low ROAS and limited advertising budget, hindering its growth potential.
On Google, they weren’t spending a lot. The overall campaign spend was $700-800 per month.
Most of the traffic was branded and new prospecting customers were low.
Strategies Applied on Meta
The campaign was structured in four phases, each with specific strategies:
Phase 1 – Creative Testing and Catalog Development:
- Focus: Sales objective with emphasis on creative testing.
- Approach: Tested static images and video animations, followed by category-specific catalog creation.
Phase 2 – Audience Testing:
- Focus: Identifying the most effective audience mix.
- Approach: Tested various audiences, including Lookalike audiences based on purchases, initiateCheckout, addToCart, and viewContent events, along with stack interests and broad audiences.
Phase 3 – Retargeting Campaign:
- Focus: Engaging with past interactors on Facebook, Instagram, and the website.
- Approach: Retargeted FB, Insta, and web engagers with budget allocation at the Ad set level.
Phase 4 – Scaling Campaigns:
- Focus: Leveraging winning creatives and audiences for scaling.
- Approach: Ran three distinct campaigns optimized for different goals – highest volume & value, cost per result, and ROAS.
Scaling Campaigns The campaigns were diversified to cover various aspects of optimization:
Sales Campaigns with CBO Allocation:
- Aimed at optimizing for volume, value, cost per result, and ROAS.
- Tested various cost per result goals ($10-$15) and ROAS goals (5x to 2.75x).
Creative and Audience Optimization:
- By systematically testing and selecting winning creatives and audience segments, we improved campaign relevance and efficiency.
Strategic Budget Allocation:
- Allocating budgets based on campaign performance and optimization goals.
Retargeting and Engagement:
- Enhanced engagement with past interactors to improve conversion rates.
Strategies Applied on Google:
We have implemented the type-3 strategy for standard shopping campaigns along with performance max campaigns.
We launched the tier-3 standard shopping campaigns along with branded search campaigns and performance max campaigns.
We have also utilized the feed only performance max campaigns to support the performance of the overall account.
We restricted our performance max campaigns for branded traffic to increase the number of orders from new customers.
We implemented the above mentioned strategy and scaled up the Google Ads account to spend more than $1K per day while maintaining the positive ROAS above 300%.
We also increased the number of orders up to 181% in this Q4 as compared to the last Q4.
The overall sales were increased by 344% as compared to the previous Q4.
The goal is to optimize the Google Ads for new customer acquisition and increase the brand visibility across the internet. Regularly refine ad creatives and audience segments to maintain campaign effectiveness.
Sustainability and Consistency:
Ensure sustainable growth by balancing scale with profitability. Make the company more profitable than the previous year and increase the number of orders and lower the cost per customer acquisition.
Utilize a more sophisticated data analysis tool (Madgicx) to understand consumer behavior and campaign performance in greater depth.