Real estate markets behave differently metro by metro. What converts agents in Austin doesn't work in Boston. We build geo-calibrated performance campaigns that optimize for local market dynamics and manage dual-audience complexity.
The Problem
Geographic targeting complexity across metro areas
Real estate markets have different competitive dynamics, price points, and buyer behaviors in every metro area. National campaigns average out performance instead of optimizing for local opportunity. This directly impacts cost per qualified lead, making it harder to justify marketing spend to leadership. Long sales cycles (30-90 days for residential, 6-12 months for commercial) make attribution complex
High-value, low-frequency conversions break optimization
Real estate transactions are infrequent and high-value, which means small conversion sample sizes that make statistical optimization unreliable for standard performance marketing approaches. This directly impacts lead-to-close rate, making it harder to justify marketing spend to leadership. Local market dynamics require hyper-targeted strategies that national agencies struggle to execute
Agent and consumer campaigns fight for budget
PropTech companies often need to acquire both real estate professionals and consumers, creating dual-audience complexity where campaign strategies and budget allocation compete. This directly impacts average deal size, making it harder to justify marketing spend to leadership. Lead quality variance is extreme — most real estate leads never convert, wasting acquisition spend
How We Help
We build geo-specific performance campaigns calibrated to local real estate market dynamics. Each metro area gets its own targeting strategy, creative messaging, and budget allocation based on local competitive landscape, transaction volumes, and agent adoption patterns.
For high-value conversion optimization, we use proxy metrics and micro-conversion events that provide sufficient sample sizes for reliable optimization. Instead of optimizing solely on completed transactions, we build conversion models based on high-intent actions that statistically predict downstream revenue.
Dual-audience campaigns run through separate but coordinated architectures. Agent acquisition campaigns emphasize productivity gains and transaction efficiency. Consumer campaigns focus on search experience and property discovery. Budget allocation follows market-specific ROI analysis rather than top-down percentage splits.
Our approach starts with a thorough assessment of your current growth infrastructure. We review what is working, what is not, and where the highest-impact opportunities are. This diagnostic phase ensures we are solving the right problems before committing resources to execution.
What makes our approach different: attribution-first approach — fix measurement before optimizing spend, channel mix optimization based on incrementality, not platform metrics, systematic creative testing with 2-week sprint cycles. We operate as an extension of your team, not as outside advisors delivering slide decks. The fractional model means you get senior expertise without the overhead of a full-time hire, and the 90-day sprint structure ensures you see measurable progress at every phase.
We build measurement into every engagement from day one. Before we change anything, we establish baseline metrics so progress is tracked against real numbers. Monthly reporting shows what is working, what needs adjustment, and where to invest next. No vanity metrics — only indicators that connect to revenue.
What we deliver
- Geo-specific campaign architecture by metro area
- Proxy conversion optimization framework
- Dual-audience campaign structure
- Market-by-market budget allocation model
We build geo-calibrated performance campaigns that optimize for local market dynamics and manage dual-audience complexity.
Our Methodology
Our performance marketing methodology centers on three systems: attribution architecture, channel mix optimization, and systematic creative testing. We start by fixing your measurement foundation because you cannot optimize what you cannot accurately measure.
The first phase rebuilds your attribution model from the ground up. We implement server-side tracking, first-party data collection, and statistical modeling to recover conversion data lost to privacy changes. This gives you a reliable view of what's actually driving revenue, not just what platforms report.
With accurate attribution in place, we restructure your channel mix based on true incremental performance. Most brands over-invest in channels that look good in platform dashboards but underperform on incrementality. We run structured tests — holdout experiments, geo-lift studies — to prove which channels actually move the needle. The testing cadence runs on 2-week cycles with clear escalation criteria for scaling or killing creative.
How We Work
Performance marketing engagements start with a 2-week attribution audit. We review your tracking infrastructure, identify gaps in conversion data, and build a measurement plan that accounts for privacy changes. We also audit current channel performance using incrementality frameworks, not just platform-reported metrics.
Weeks 3-6 focus on rebuilding your performance infrastructure. We implement server-side tracking, restructure campaign architectures, and launch initial creative tests. Weekly performance reviews track spend, CAC, ROAS, and blended efficiency metrics.
From month 2 onward, we run systematic optimization cycles. Creative testing runs on 2-week sprints, channel allocation adjusts based on incrementality data, and we continuously expand into new acquisition channels to reduce platform dependency.
Typical engagements run 3-6 months with daily campaign monitoring, weekly strategy calls, and monthly executive reporting. We work alongside your internal team or manage agency relationships directly.
- Geo-optimized campaign performance
- Improved conversion optimization reliability
- Efficient dual-audience budget allocation
If your real estate / proptech company needs performance marketing leadership, we should talk.
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Frequently asked questions
How do you optimize campaigns with low conversion volumes in real estate?
We use proxy metrics — property search activity, agent tool engagement, lead form submissions — that have higher volume and statistically predict downstream transactions. This gives the optimization algorithm enough signal to work with.
Should PropTech companies prioritize agent or consumer acquisition?
Depends on your business model. Marketplace platforms often need supply-side (agent) acquisition first. Consumer-facing tools need demand-side growth. We analyze which side of your marketplace creates more leverage and allocate accordingly.
How granular should geo-targeting be for real estate performance marketing?
Metro-level at minimum, zip-code-level for high-value markets. Real estate dynamics change neighborhood by neighborhood, but campaign management complexity limits how granular you can go. We find the right balance between precision and operational feasibility.
How do you fix attribution after iOS 14.5?
We rebuild attribution from the ground up using server-side tracking, first-party data collection, and statistical modeling. This includes implementing conversion APIs for major platforms, building customer data infrastructure that captures the full journey, and creating modeled attribution that fills the gaps left by platform pixel loss. Most brands recover 50-70% of lost attribution visibility.
How much does performance marketing management cost?
Performance marketing engagements typically run $10K-$25K per month for strategy and management, separate from media spend. This includes attribution architecture, channel optimization, creative strategy, and reporting. Compare to hiring a performance marketing director ($180K-$250K fully loaded) — you get specialized expertise across channels without the overhead.
What makes your approach to performance marketing different?
We lead with attribution and measurement, not campaign tactics. Most agencies optimize within platforms based on platform-reported metrics. We build incrementality measurement first, then optimize based on true performance. This means some channels that look good in dashboards get cut, while undervalued channels get scaled. The result is better unit economics, not just better-looking reports.
