By Will Varney

Case Study: 91% CPA Reduction for Comfort-In

How Feisty Agency used AI-enhanced UGC video ads to reduce Comfort-In's cost-per-acquisition from $115 to $10 and achieve a 54.5x return on ad spend — a 1,059% improvement.

$115 → $10
CPA Reduction
91% lower
54.5x
Peak ROAS
Up from 4.7x
1,059%
ROAS Increase
4.7x → 54.5x
50+
Creatives Tested
Per month

Client Background

Comfort-In is a Melbourne-based product business operating in the 4x4 and outdoor accessories market. They sell premium aftermarket products to customers across Melbourne and regional Victoria, with an average order value (AOV) exceeding $300.

As a family-owned business, Comfort-In had built a loyal customer base through word-of-mouth and community engagement in the 4x4 scene. However, their digital advertising efforts were underperforming, and they needed a scalable way to reach new customers profitably through paid channels.

Industry
4x4 & Outdoor Accessories
Location
Melbourne, Australia
Average Order Value
$300+

The Challenge

Before engaging Feisty Agency, Comfort-In faced several interconnected advertising challenges:

  • High cost-per-acquisition (CPA): Comfort-In was spending $115 to acquire each new customer through Meta ads, making it difficult to scale profitably given their product margins.
  • Low ROAS: Their return on ad spend was 4.7x — acceptable for some industries, but below the threshold needed for profitable scaling in the accessories market.
  • Creative fatigue and limited volume: With only a handful of ad creatives in rotation, performance degraded as audiences saw the same ads repeatedly. Producing new content was expensive and slow.
  • Broad, untargeted campaigns: Comfort-In was advertising to broad audiences without systematic testing of specific segments, messaging angles, or creative formats.

The core problem was a common one for growing product businesses: they knew paid advertising could work, but couldn't produce enough quality creative at a cost that made scaling viable.

The Solution

Feisty Agency implemented a three-phase approach combining AI-enhanced UGC creative production with structured campaign testing:

Phase 1: Content Audit & AI Creative Production (Week 1–2)

We audited Comfort-In's existing content library — customer photos, unboxing videos, social media posts, and product reviews. From approximately 20 pieces of raw customer content, we used AI tools (including Veo3, Sora 2, and Kling 2.6) to produce the first batch of 50+ ad variations.

Each variation featured a different attention-grabbing hook — the critical first 1–3 seconds designed to stop users from scrolling. AI-generated hooks included visual effects, text overlays, and creative edits that transformed raw customer content into professional-quality ad creative.

Phase 2: Structured Campaign Testing (Week 2–4)

Rather than running a single campaign with broad targeting, we implemented a structured testing framework:

  • Audience segmentation: Separated campaigns by audience type — 4x4 enthusiasts, camping and outdoor interests, competitor brand followers, and lookalike audiences based on existing customers.
  • Creative rotation: Distributed the 50+ ad variations across segments, measuring which hook styles, content formats, and messaging angles resonated with each audience.
  • Rapid iteration: After the first 1,000 impressions per variation, we cut underperformers and doubled down on winning combinations.

Within 2–3 weeks, clear patterns emerged: customer testimonial-style UGC with AI-enhanced hooks consistently outperformed all other creative formats, particularly when targeting the 4x4 enthusiast segment.

Phase 3: Optimisation & Scale (Week 5–8+)

With winning creative and audience combinations identified, we focused on scaling:

  • Increased budget allocation to top-performing campaigns while maintaining profitable CPA thresholds.
  • Produced new rounds of AI-enhanced creative variations based on the winning hook styles, preventing fatigue as spend scaled.
  • Expanded audience targeting to include broader interest groups adjacent to the 4x4 community while maintaining ROAS targets.
  • Implemented retargeting campaigns using different UGC angles to nurture users who engaged but didn't purchase.

Results

The AI-enhanced UGC campaign delivered significant improvements across all key performance metrics:

MetricBeforeAfterChange
Cost per Acquisition (CPA)$115$1091% reduction
Return on Ad Spend (ROAS)4.7x54.5x1,059% increase
Monthly Creative Volume5–10 ads50+ ads5–10x increase
Creative Production Time2–4 weeks2–3 days~90% faster

Results represent peak performance metrics during the engagement period. ROAS of 54.5x reflects peak campaign performance; average ROAS across all campaigns was lower. Past performance does not guarantee future results.

Key Takeaways

Volume enables discovery

Testing 50+ ad variations rather than 5–10 was the single biggest factor in finding winning creative combinations. AI-enhanced production made this volume economically viable.

Authentic content outperforms polished content

Customer-filmed UGC with AI-enhanced hooks consistently beat studio-quality branded content in every A/B test. Audiences trusted real customer experiences over scripted ads.

Systematic testing beats intuition

Structured audience segmentation and creative testing revealed insights that would not have been apparent from running a single broad campaign. Data drove every decision.

AI enhances — it doesn't replace — authenticity

The AI tools enhanced the reach and impact of genuine customer content. The winning combination was real UGC (trust factor) + AI hooks (attention factor) + systematic testing (optimisation factor).

Timeline

Week 1
Onboarding & Content Audit

Strategy session, content library review, Meta Business Suite setup, tracking implementation.

Week 1–2
First Creative Batch

50+ AI-enhanced ad variations produced from existing customer content. First campaigns launched.

Week 2–4
Testing Phase

Structured A/B testing across audience segments and creative formats. Identified winning combinations.

Week 5–8
Optimisation & Scale

Scaled winning campaigns, produced new creative rounds, expanded audience targeting. Peak ROAS of 54.5x achieved.

Ongoing
Continuous Improvement

Monthly creative refreshes, ongoing optimisation, new audience testing, and performance reporting.

Frequently Asked Questions

What was Comfort-In's CPA before working with Feisty Agency?
Before working with Feisty Agency, Comfort-In's cost-per-acquisition (CPA) on Meta ads was $115 per customer. After implementing AI-enhanced UGC ad campaigns, their CPA dropped to $10 — a 91% reduction.
What ROAS did the Comfort-In campaign achieve?
The Comfort-In campaign achieved a peak return on ad spend (ROAS) of 54.5x, up from an initial ROAS of 4.7x. This represents a 1,059% increase in advertising efficiency.
How long did it take to see results?
Initial improvements were visible within the first 2–3 weeks as the first round of AI-enhanced UGC ads began outperforming existing creative. The peak ROAS of 54.5x was achieved during the optimisation phase (weeks 5–8) as winning creative combinations were identified and scaled.
What type of business is Comfort-In?
Comfort-In is a Melbourne-based product business in the 4x4 and outdoor accessories category. They sell premium products with an average order value above $300, targeting Melbourne and regional Victorian customers who are active in the outdoor and 4x4 community.

Want Results Like Comfort-In?

Every product business is different, but the approach is proven. Book a free strategy session and we'll show you how AI-enhanced UGC ads could work for your brand.

Or email will@feistyagency.com

Case Study: 91% CPA Reduction for Comfort-In | Feisty Agency Melbourne | FEISTY Agency - AI-Enhanced Meta Ads