Industry: Food & Beverage / Restaurants
Tech Stack: Paid Ads (PPC), Google Ads, AI Optimization
Objective: Improve ROAS, increase conversions, and lower cost per conversion across Forage Kitchen’s online campaigns.

Executive Summary

Forage Kitchen, a multi-location restaurant brand, faced challenges in scaling online orders profitably. Before Cube’s engagement, campaigns delivered moderate impressions and clicks but low ROAS and high cost per conversion. Cube implemented a comprehensive paid media optimization strategy, combining data-driven campaign restructuring, audience targeting, and creative testing.

Results within 10 months (Jun 2025 – Mar 2026):

• ROAS: +158%
• Conversions: +113%
• Cost per Conversion: -48%
• Impressions: +438%
• Interactions/Clicks: +161%

The Challenge: Scaling Efficiently

• Campaigns were underperforming with rising ad spend but modest conversion growth.
• Certain locations and audiences were yielding higher costs per conversion.
• Lack of optimized creatives and audience segmentation was limiting campaign efficiency.

The Solution: Data-Driven Paid Media Optimization

Cube implemented a multi-faceted approach:

1) Campaign Restructuring

• Segmented campaigns by locations and high-value audiences.
• Optimized bids based on conversion likelihood and historical performance.
• Shifted budget to high-performing ad groups.

2) Audience Targeting & Demographics

• Focused on primary persona: 25–34-year-old females driving 58% of conversions.
• Tailored ads for high-converting locations: Whitefish Bay, Pewaukee, and Milwaukee.

3) Cost Efficiency

• Reduced cost per conversion by optimizing bids, placements, and ad scheduling.
• Focused spend on high-ROAS campaigns and paused low-performing segments.

Key Metrics (May 2025 vs Mar 2026)

Metric	Before Cube	With Cube	Improvement
Impressions	167,408	901,173	+438%
Clicks / Interactions	9,315	24,197	+161%
Conversions	7,257	15,447	+113%
Cost per Conversion	$0.66	$0.34	-48%
ROAS	1.40	3.61	+158%

Top Performing Locations:

• Whitefish Bay: 22,029 conv., ROAS 4.21
• Pewaukee: 20,781 conv., ROAS 3.94
• Milwaukee: 13,521 conv., ROAS 3.68

Key Takeaways

1. Data-Driven Segmentation Works: Campaigns structured by audience and location drove measurable ROAS and conversions.
2. Persona-Focused Targeting: Concentrating on the 25–34 female demographic yielded the majority of conversions.
3. Cost Efficiency: Strategic budget allocation and bid management lowered cost per conversion significantly.

Conclusion

Cube’s data-driven, performance-focused strategy revolutionized Forage Kitchen’s Google campaigns. The initiatives achieved a 3.6x average ROAS, 113% growth in conversions, and a 48% reduction in cost per conversion. By targeting high-value audiences, optimizing creatives, and allocating budget efficiently, Cube not only expanded reach on Google but also delivered measurable, sustainable profitability for the brand.

Industry: On-Demand Residential Services / Prop-Tech

Geography Focus: Austin & Dallas, Texas

Objective: Consolidate fragmented architecture and achieve geographic precision.

Executive Summary

A premium on-demand housekeeping brand faced a significant performance plateau. Despite a multi-year history of consistent Meta spend, the account suffered from extreme campaign fragmentation and “audience dilution,” leading to high acquisition costs and creative fatigue.

Cube was engaged to overhaul the account architecture. By pivoting to Geographic Micro-Market Targeting and Life-Stage Cohort Messaging, we achieved a 7.21x ROAS (a 264% improvement) and slashed the Cost Per Purchase by 62% within five months.

1. The Challenge: “The Broad-Reach Trap.”

Prior to Cube’s intervention, the brand’s Meta strategy relied on wide, city-level targeting that failed to distinguish high-propensity neighborhoods from lower-value areas. This resulted in:

• Campaign Fragmentation: Over 35 active campaigns split the conversion signal too thin, preventing Meta’s algorithm from exiting the “Learning Phase.”
• Creative-Audience Mismatch: Generic creative was served broadly, failing to resonate with the specific needs of different life stages (e.g., busy professionals vs. families).
• Ad Fatigue: An exceptionally high frequency (9.47) indicated that the same users were being over-saturated with the same message, driving up CPCs and diminishing returns.
• Funnel Leakage: A lack of structured retargeting meant high-intent users who visited the booking page but didn’t convert were rarely re-engaged.

2. The Solution: Precision Architecture & Micro-Market Strategy

Cube implemented a “Quality-over-Quantity” framework, concentrating spend on the highest-propensity ZIP codes and life-stage segments.

Key Strategic Pillars:

Strategy	Tactical Execution	Business Impact
Geographic Micro-Targeting	Replaced city-wide targeting with Premium Corridor ZIP-codes. Tailored creative to reference local neighborhood identities.	76% Increase in CTR; higher traffic quality at the start of the booking funnel.
Life-Stage Cohorts	Developed unique messaging for 3 pillars: Young Professionals (Convenience), Families (Non-toxic/Safety), and New Movers (Deep Cleans).	Improved creative resonance and conversion intent across diverse user groups.
Architectural Consolidation	Collapsed 35+ fragmented campaigns into a streamlined “Advantage+ Shopping” structure.	Accelerated algorithmic learning, allowing for stable, automated scaling.
Dynamic Retargeting	Deployed a full-funnel re-engagement strategy for “Add-to-Cart” and “Booking Abandonment” users with time-sensitive incentives.	133% increase in monthly purchase velocity.
Creative Refresh Cycle	Established a high-velocity rotation of seasonal and cohort-specific assets.	32% reduction in frequency, effectively solving the brand’s long-standing ad fatigue.

3. The Results: Unprecedented Efficiency

The transition from broad reach to geographic and demographic precision transformed the account from a cost-center into a highly profitable acquisition engine.

Key Performance Indicators (Pre-Cube vs. Post-Cube):

Key Metrics	Performance Delta
Purchase ROAS	+264% improvement (from 1.98x to 7.21x)
Cost Per Purchase	62% reduction
Monthly Purchase Volume	+133% growth
Click-Through Rate (CTR)	+76% improvement
Ad Fatigue (Frequency)	32% reduction
Traffic Quality	Significant decrease in Cost Per Landing Page View

Conclusion

Embracing a Micro-Market Precision model, the brand successfully more than tripled its ROAS while also significantly scaling volume. This case study proves that for premium service brands, who you reach is just as important as how many you reach. Cube’s data-driven consolidation turned a fragmented account into a streamlined, high-yield growth engine.