Location Performance Intelligence

Lyra’s Location Performance Intelligence provides geographic performance analysis across all campaigns, identifying underperforming regions, quantifying location-based budget waste, and surfacing split-campaign opportunities for targeted optimization.

Key Takeaways

• Regional performance visibility breaks down metrics by country, state, city, and metro area
• Waste quantification shows exactly how much budget underperforming locations consume
• Split-campaign recommendations identify when geographic segmentation justifies separate campaigns
• Bid modifier suggestions optimize location targeting within existing campaign structures

The Problem

Campaign performance varies significantly by geographic location. A campaign targeting the entire United States may perform well in aggregate but contain regions with drastically different cost and conversion dynamics:

• Urban vs. rural — CPCs, conversion rates, and competitive density differ between metropolitan areas and smaller markets
• Regional demand — Products and services have varying demand levels across regions that a single campaign treats uniformly
• Seasonal geography — Some regions show seasonal performance patterns (tourism, agriculture, weather-related services) that require location-specific strategy
• Competitive variation — Competitor presence and bidding intensity varies by market, affecting costs and position differently across locations

Google Ads provides geographic performance data, but analyzing it requires manual report creation, data export, and spreadsheet analysis. The native interface does not highlight underperforming regions proactively or suggest structural changes based on geographic performance gaps.

Without location-level analysis, campaigns overspend in low-performing regions and underfund high-performing ones. The aggregate metrics mask these imbalances, making them invisible during routine optimization.

How Lyra Solves It

Location Performance Intelligence automates geographic analysis and surfaces actionable insights:

The split-campaign analysis evaluates whether geographic segmentation would improve overall performance:

When the analysis indicates that splitting would provide significant improvement with manageable complexity, Lyra presents a recommendation with projected impact and a suggested campaign structure.

Location bid modifier recommendations work within existing campaign structures for situations where a full split is not justified:

• Increase modifiers for regions with above-average conversion rates and headroom for more volume
• Decrease modifiers for regions with below-average performance to reduce waste
• Exclude recommendations for regions with persistent zero conversion performance

Seasonal trend tracking adds a temporal dimension to geographic analysis. It identifies:

• Regions with recurring seasonal performance patterns
• The optimal timing for location bid modifier adjustments
• Year-over-year geographic performance trends

Use Cases

National campaign optimization. For campaigns targeting an entire country, Location Performance Intelligence identifies which states or metro areas drive most conversions versus which consume budget with poor returns. Use this data to apply bid modifiers or split into regional campaigns.

Multi-location business strategy. Businesses with multiple physical locations use geographic analysis to align ad spend with location performance. If one store’s region converts at half the rate of another, budget can be redistributed to match regional potential.

Market expansion decisions. When considering geographic expansion, review location performance data from existing campaigns to identify regions with untapped opportunity — high impressions but constrained by budget or low bids — that indicate latent demand worth pursuing.