Piola Pizza USA

14.7x ROAS Across Two Restaurant Markets: How Geo-Targeted Google and Meta Ads Scaled Piola Pizza USA

Industry: Food and Beverage, Multi-Location Restaurant

Services Provided: Google Ads Management, Performance Max Campaigns, Meta Ads, Remarketing Automation, Conversion Tracking, Geo-Targeting Strategy

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Piola Pizza USA

The Challenge

Operating across multiple cities means every wasted ad impression carries a real cost. Piola Pizza USA needed to grow online orders and in-store visits across its Houston and Brickell locations simultaneously, without cannibalizing budget between markets or reaching audiences too far outside each restaurant’s delivery and walk-in radius. The brand required a fully segmented, location-aware paid media system that could drive measurable conversions in each market independently while building toward a unified, scalable structure across the restaurant network.
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Our Results

We built a dual-market paid media engine combining Google Search, Performance Max, and Meta Ads. Each campaign was architected around a single location’s geography, audience behaviors, and competitive landscape.

Location-Based Geo-Targeting

  • Defined custom delivery and walk-in radii around each restaurant so every ad dollar reached people who could actually order or visit.
  • Built individualized campaign structures per location, allowing for localized messaging, offers, and creative that reflected each neighborhood’s character.
  • Layered demographic and behavioral targeting on top of geography to reach pizza lovers, food delivery users, and high-intent local diners.

Google Ads for High- Intent Capture

  • Launched Search and Performance Max campaigns targeting high-intent keywords like “pizza near me,” “Italian restaurant delivery,” and branded location queries, generating 7,867 conversions at an average cost per conversion of $1.07.
  • Performance Max campaigns were the top performers: Houston PM delivered a 17.9x ROAS and Brickell PM hit a 31.5x ROAS, together accounting for over $84,000 in tracked conversion value.
  • Optimized bidding strategies per location based on order volume, time of day, and conversion patterns to maximize efficiency across both markets.

Meta Ads for Engagement and Discovery

  • Ran a Traffic campaign in the Brickell market delivering 2,822 landing page views at just $0.38 per visit, keeping qualified traffic flowing to the site at a highly efficient cost.
  • Deployed a Remarketing campaign to re-engage users who visited the website or interacted with the brand, adding 572 additional visits at $0.79 each to recover lost traffic.
  • Built lookalike audiences from existing customers to expand reach within each location’s geo-targeted radius without increasing cost per visit.

Performance Tracking & Optimization

  • Implemented conversion tracking for online orders, reservations, and in-store visits across both Houston and Brickell markets.
  • Analyzed performance by location weekly, reallocating budget toward the highest-performing campaigns and creative variations to protect ROAS.
  • Kept each location’s campaigns fully independent so that one market’s performance never masked or distorted results in the other, giving a clear picture of what was working where.
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Impact

The geo-targeted, multi-channel strategy generated $123,486 in tracked conversion value on $8,403 in total ad spend, a 14.7x blended ROAS, over a 5-month period across Houston and Brickell.
  • $123,486 in tracked conversion value generated across both markets in 5 months.
  • 14.7x blended ROAS on $8,403 in total Google Ads spend across all campaigns.
  • 7,867 conversions tracked across Search and Performance Max campaigns.
  • 2M+ impressions delivered within geo-targeted radii across Houston and Brickell.
  • $0.38 cost per landing page view on Meta Traffic campaigns in the Brickell market.
  • 31.5x ROAS on Brickell Performance Max, the highest-performing individual campaign.
This campaign proved that a restaurant chain does not need a massive budget to dominate its local markets. It needs a precisely structured, data-driven strategy built around where its customers actually are.

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